R Under development (unstable) (2023-11-13 r85520 ucrt) -- "Unsuffered Consequences" Copyright (C) 2023 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > require("DoE.base") Loading required package: DoE.base Loading required package: grid Loading required package: conf.design Registered S3 method overwritten by 'DoE.base': method from factorize.factor conf.design Attaching package: 'DoE.base' The following objects are masked from 'package:stats': aov, lm The following object is masked from 'package:graphics': plot.design The following object is masked from 'package:base': lengths > ### test programs for crossing designs > ### and parameter designs > oa12 <- oa.design(nlevels=c(2,6,2), factor.names=c("first","second","third"),randomize=FALSE) > oa4 <- oa.design(nlevels=c(2,2,2), factor.names=Letters[4:6],randomize=FALSE) > oa4rep <- oa.design(nlevels=c(2,2,2), factor.names=Letters[7:9], repl=3,randomize=FALSE) > oa4reprepeat.only <-oa.design(nlevels=c(2,2,2), repl=3, factor.names=Letters[10:12], repeat.only=TRUE,randomize=FALSE) > cross1 <- cross.design(oa12,oa4,oa4rep,randomize=FALSE) > cross1 run.no run.no.std.rp first second third D E F G H J 1 1_1_1 1_1_1.1 1 1 1 1 1 1 1 1 1 2 1_1_2 1_1_2.1 1 1 1 1 1 1 1 2 2 3 1_1_3 1_1_3.1 1 1 1 1 1 1 2 1 2 4 1_1_4 1_1_4.1 1 1 1 1 1 1 2 2 1 5 1_1_5 1_1_1.2 1 1 1 1 1 1 1 1 1 6 1_1_6 1_1_2.2 1 1 1 1 1 1 1 2 2 7 1_1_7 1_1_3.2 1 1 1 1 1 1 2 1 2 8 1_1_8 1_1_4.2 1 1 1 1 1 1 2 2 1 9 1_1_9 1_1_1.3 1 1 1 1 1 1 1 1 1 10 1_1_10 1_1_2.3 1 1 1 1 1 1 1 2 2 11 1_1_11 1_1_3.3 1 1 1 1 1 1 2 1 2 12 1_1_12 1_1_4.3 1 1 1 1 1 1 2 2 1 13 1_2_1 1_2_1.1 1 1 1 1 2 2 1 1 1 14 1_2_2 1_2_2.1 1 1 1 1 2 2 1 2 2 15 1_2_3 1_2_3.1 1 1 1 1 2 2 2 1 2 16 1_2_4 1_2_4.1 1 1 1 1 2 2 2 2 1 17 1_2_5 1_2_1.2 1 1 1 1 2 2 1 1 1 18 1_2_6 1_2_2.2 1 1 1 1 2 2 1 2 2 19 1_2_7 1_2_3.2 1 1 1 1 2 2 2 1 2 20 1_2_8 1_2_4.2 1 1 1 1 2 2 2 2 1 21 1_2_9 1_2_1.3 1 1 1 1 2 2 1 1 1 22 1_2_10 1_2_2.3 1 1 1 1 2 2 1 2 2 23 1_2_11 1_2_3.3 1 1 1 1 2 2 2 1 2 24 1_2_12 1_2_4.3 1 1 1 1 2 2 2 2 1 25 1_3_1 1_3_1.1 1 1 1 2 1 2 1 1 1 26 1_3_2 1_3_2.1 1 1 1 2 1 2 1 2 2 27 1_3_3 1_3_3.1 1 1 1 2 1 2 2 1 2 28 1_3_4 1_3_4.1 1 1 1 2 1 2 2 2 1 29 1_3_5 1_3_1.2 1 1 1 2 1 2 1 1 1 30 1_3_6 1_3_2.2 1 1 1 2 1 2 1 2 2 31 1_3_7 1_3_3.2 1 1 1 2 1 2 2 1 2 32 1_3_8 1_3_4.2 1 1 1 2 1 2 2 2 1 33 1_3_9 1_3_1.3 1 1 1 2 1 2 1 1 1 34 1_3_10 1_3_2.3 1 1 1 2 1 2 1 2 2 35 1_3_11 1_3_3.3 1 1 1 2 1 2 2 1 2 36 1_3_12 1_3_4.3 1 1 1 2 1 2 2 2 1 37 1_4_1 1_4_1.1 1 1 1 2 2 1 1 1 1 38 1_4_2 1_4_2.1 1 1 1 2 2 1 1 2 2 39 1_4_3 1_4_3.1 1 1 1 2 2 1 2 1 2 40 1_4_4 1_4_4.1 1 1 1 2 2 1 2 2 1 41 1_4_5 1_4_1.2 1 1 1 2 2 1 1 1 1 42 1_4_6 1_4_2.2 1 1 1 2 2 1 1 2 2 43 1_4_7 1_4_3.2 1 1 1 2 2 1 2 1 2 44 1_4_8 1_4_4.2 1 1 1 2 2 1 2 2 1 45 1_4_9 1_4_1.3 1 1 1 2 2 1 1 1 1 46 1_4_10 1_4_2.3 1 1 1 2 2 1 1 2 2 47 1_4_11 1_4_3.3 1 1 1 2 2 1 2 1 2 48 1_4_12 1_4_4.3 1 1 1 2 2 1 2 2 1 49 2_1_1 2_1_1.1 1 3 1 1 1 1 1 1 1 50 2_1_2 2_1_2.1 1 3 1 1 1 1 1 2 2 51 2_1_3 2_1_3.1 1 3 1 1 1 1 2 1 2 52 2_1_4 2_1_4.1 1 3 1 1 1 1 2 2 1 53 2_1_5 2_1_1.2 1 3 1 1 1 1 1 1 1 54 2_1_6 2_1_2.2 1 3 1 1 1 1 1 2 2 55 2_1_7 2_1_3.2 1 3 1 1 1 1 2 1 2 56 2_1_8 2_1_4.2 1 3 1 1 1 1 2 2 1 57 2_1_9 2_1_1.3 1 3 1 1 1 1 1 1 1 58 2_1_10 2_1_2.3 1 3 1 1 1 1 1 2 2 59 2_1_11 2_1_3.3 1 3 1 1 1 1 2 1 2 60 2_1_12 2_1_4.3 1 3 1 1 1 1 2 2 1 61 2_2_1 2_2_1.1 1 3 1 1 2 2 1 1 1 62 2_2_2 2_2_2.1 1 3 1 1 2 2 1 2 2 63 2_2_3 2_2_3.1 1 3 1 1 2 2 2 1 2 64 2_2_4 2_2_4.1 1 3 1 1 2 2 2 2 1 65 2_2_5 2_2_1.2 1 3 1 1 2 2 1 1 1 66 2_2_6 2_2_2.2 1 3 1 1 2 2 1 2 2 67 2_2_7 2_2_3.2 1 3 1 1 2 2 2 1 2 68 2_2_8 2_2_4.2 1 3 1 1 2 2 2 2 1 69 2_2_9 2_2_1.3 1 3 1 1 2 2 1 1 1 70 2_2_10 2_2_2.3 1 3 1 1 2 2 1 2 2 71 2_2_11 2_2_3.3 1 3 1 1 2 2 2 1 2 72 2_2_12 2_2_4.3 1 3 1 1 2 2 2 2 1 73 2_3_1 2_3_1.1 1 3 1 2 1 2 1 1 1 74 2_3_2 2_3_2.1 1 3 1 2 1 2 1 2 2 75 2_3_3 2_3_3.1 1 3 1 2 1 2 2 1 2 76 2_3_4 2_3_4.1 1 3 1 2 1 2 2 2 1 77 2_3_5 2_3_1.2 1 3 1 2 1 2 1 1 1 78 2_3_6 2_3_2.2 1 3 1 2 1 2 1 2 2 79 2_3_7 2_3_3.2 1 3 1 2 1 2 2 1 2 80 2_3_8 2_3_4.2 1 3 1 2 1 2 2 2 1 81 2_3_9 2_3_1.3 1 3 1 2 1 2 1 1 1 82 2_3_10 2_3_2.3 1 3 1 2 1 2 1 2 2 83 2_3_11 2_3_3.3 1 3 1 2 1 2 2 1 2 84 2_3_12 2_3_4.3 1 3 1 2 1 2 2 2 1 85 2_4_1 2_4_1.1 1 3 1 2 2 1 1 1 1 86 2_4_2 2_4_2.1 1 3 1 2 2 1 1 2 2 87 2_4_3 2_4_3.1 1 3 1 2 2 1 2 1 2 88 2_4_4 2_4_4.1 1 3 1 2 2 1 2 2 1 89 2_4_5 2_4_1.2 1 3 1 2 2 1 1 1 1 90 2_4_6 2_4_2.2 1 3 1 2 2 1 1 2 2 91 2_4_7 2_4_3.2 1 3 1 2 2 1 2 1 2 92 2_4_8 2_4_4.2 1 3 1 2 2 1 2 2 1 93 2_4_9 2_4_1.3 1 3 1 2 2 1 1 1 1 94 2_4_10 2_4_2.3 1 3 1 2 2 1 1 2 2 95 2_4_11 2_4_3.3 1 3 1 2 2 1 2 1 2 96 2_4_12 2_4_4.3 1 3 1 2 2 1 2 2 1 97 3_1_1 3_1_1.1 1 5 1 1 1 1 1 1 1 98 3_1_2 3_1_2.1 1 5 1 1 1 1 1 2 2 99 3_1_3 3_1_3.1 1 5 1 1 1 1 2 1 2 100 3_1_4 3_1_4.1 1 5 1 1 1 1 2 2 1 101 3_1_5 3_1_1.2 1 5 1 1 1 1 1 1 1 102 3_1_6 3_1_2.2 1 5 1 1 1 1 1 2 2 103 3_1_7 3_1_3.2 1 5 1 1 1 1 2 1 2 104 3_1_8 3_1_4.2 1 5 1 1 1 1 2 2 1 105 3_1_9 3_1_1.3 1 5 1 1 1 1 1 1 1 106 3_1_10 3_1_2.3 1 5 1 1 1 1 1 2 2 107 3_1_11 3_1_3.3 1 5 1 1 1 1 2 1 2 108 3_1_12 3_1_4.3 1 5 1 1 1 1 2 2 1 109 3_2_1 3_2_1.1 1 5 1 1 2 2 1 1 1 110 3_2_2 3_2_2.1 1 5 1 1 2 2 1 2 2 111 3_2_3 3_2_3.1 1 5 1 1 2 2 2 1 2 112 3_2_4 3_2_4.1 1 5 1 1 2 2 2 2 1 113 3_2_5 3_2_1.2 1 5 1 1 2 2 1 1 1 114 3_2_6 3_2_2.2 1 5 1 1 2 2 1 2 2 115 3_2_7 3_2_3.2 1 5 1 1 2 2 2 1 2 116 3_2_8 3_2_4.2 1 5 1 1 2 2 2 2 1 117 3_2_9 3_2_1.3 1 5 1 1 2 2 1 1 1 118 3_2_10 3_2_2.3 1 5 1 1 2 2 1 2 2 119 3_2_11 3_2_3.3 1 5 1 1 2 2 2 1 2 120 3_2_12 3_2_4.3 1 5 1 1 2 2 2 2 1 121 3_3_1 3_3_1.1 1 5 1 2 1 2 1 1 1 122 3_3_2 3_3_2.1 1 5 1 2 1 2 1 2 2 123 3_3_3 3_3_3.1 1 5 1 2 1 2 2 1 2 124 3_3_4 3_3_4.1 1 5 1 2 1 2 2 2 1 125 3_3_5 3_3_1.2 1 5 1 2 1 2 1 1 1 126 3_3_6 3_3_2.2 1 5 1 2 1 2 1 2 2 127 3_3_7 3_3_3.2 1 5 1 2 1 2 2 1 2 128 3_3_8 3_3_4.2 1 5 1 2 1 2 2 2 1 129 3_3_9 3_3_1.3 1 5 1 2 1 2 1 1 1 130 3_3_10 3_3_2.3 1 5 1 2 1 2 1 2 2 131 3_3_11 3_3_3.3 1 5 1 2 1 2 2 1 2 132 3_3_12 3_3_4.3 1 5 1 2 1 2 2 2 1 133 3_4_1 3_4_1.1 1 5 1 2 2 1 1 1 1 134 3_4_2 3_4_2.1 1 5 1 2 2 1 1 2 2 135 3_4_3 3_4_3.1 1 5 1 2 2 1 2 1 2 136 3_4_4 3_4_4.1 1 5 1 2 2 1 2 2 1 137 3_4_5 3_4_1.2 1 5 1 2 2 1 1 1 1 138 3_4_6 3_4_2.2 1 5 1 2 2 1 1 2 2 139 3_4_7 3_4_3.2 1 5 1 2 2 1 2 1 2 140 3_4_8 3_4_4.2 1 5 1 2 2 1 2 2 1 141 3_4_9 3_4_1.3 1 5 1 2 2 1 1 1 1 142 3_4_10 3_4_2.3 1 5 1 2 2 1 1 2 2 143 3_4_11 3_4_3.3 1 5 1 2 2 1 2 1 2 144 3_4_12 3_4_4.3 1 5 1 2 2 1 2 2 1 145 4_1_1 4_1_1.1 1 2 2 1 1 1 1 1 1 146 4_1_2 4_1_2.1 1 2 2 1 1 1 1 2 2 147 4_1_3 4_1_3.1 1 2 2 1 1 1 2 1 2 148 4_1_4 4_1_4.1 1 2 2 1 1 1 2 2 1 149 4_1_5 4_1_1.2 1 2 2 1 1 1 1 1 1 150 4_1_6 4_1_2.2 1 2 2 1 1 1 1 2 2 151 4_1_7 4_1_3.2 1 2 2 1 1 1 2 1 2 152 4_1_8 4_1_4.2 1 2 2 1 1 1 2 2 1 153 4_1_9 4_1_1.3 1 2 2 1 1 1 1 1 1 154 4_1_10 4_1_2.3 1 2 2 1 1 1 1 2 2 155 4_1_11 4_1_3.3 1 2 2 1 1 1 2 1 2 156 4_1_12 4_1_4.3 1 2 2 1 1 1 2 2 1 157 4_2_1 4_2_1.1 1 2 2 1 2 2 1 1 1 158 4_2_2 4_2_2.1 1 2 2 1 2 2 1 2 2 159 4_2_3 4_2_3.1 1 2 2 1 2 2 2 1 2 160 4_2_4 4_2_4.1 1 2 2 1 2 2 2 2 1 161 4_2_5 4_2_1.2 1 2 2 1 2 2 1 1 1 162 4_2_6 4_2_2.2 1 2 2 1 2 2 1 2 2 163 4_2_7 4_2_3.2 1 2 2 1 2 2 2 1 2 164 4_2_8 4_2_4.2 1 2 2 1 2 2 2 2 1 165 4_2_9 4_2_1.3 1 2 2 1 2 2 1 1 1 166 4_2_10 4_2_2.3 1 2 2 1 2 2 1 2 2 167 4_2_11 4_2_3.3 1 2 2 1 2 2 2 1 2 168 4_2_12 4_2_4.3 1 2 2 1 2 2 2 2 1 169 4_3_1 4_3_1.1 1 2 2 2 1 2 1 1 1 170 4_3_2 4_3_2.1 1 2 2 2 1 2 1 2 2 171 4_3_3 4_3_3.1 1 2 2 2 1 2 2 1 2 172 4_3_4 4_3_4.1 1 2 2 2 1 2 2 2 1 173 4_3_5 4_3_1.2 1 2 2 2 1 2 1 1 1 174 4_3_6 4_3_2.2 1 2 2 2 1 2 1 2 2 175 4_3_7 4_3_3.2 1 2 2 2 1 2 2 1 2 176 4_3_8 4_3_4.2 1 2 2 2 1 2 2 2 1 177 4_3_9 4_3_1.3 1 2 2 2 1 2 1 1 1 178 4_3_10 4_3_2.3 1 2 2 2 1 2 1 2 2 179 4_3_11 4_3_3.3 1 2 2 2 1 2 2 1 2 180 4_3_12 4_3_4.3 1 2 2 2 1 2 2 2 1 181 4_4_1 4_4_1.1 1 2 2 2 2 1 1 1 1 182 4_4_2 4_4_2.1 1 2 2 2 2 1 1 2 2 183 4_4_3 4_4_3.1 1 2 2 2 2 1 2 1 2 184 4_4_4 4_4_4.1 1 2 2 2 2 1 2 2 1 185 4_4_5 4_4_1.2 1 2 2 2 2 1 1 1 1 186 4_4_6 4_4_2.2 1 2 2 2 2 1 1 2 2 187 4_4_7 4_4_3.2 1 2 2 2 2 1 2 1 2 188 4_4_8 4_4_4.2 1 2 2 2 2 1 2 2 1 189 4_4_9 4_4_1.3 1 2 2 2 2 1 1 1 1 190 4_4_10 4_4_2.3 1 2 2 2 2 1 1 2 2 191 4_4_11 4_4_3.3 1 2 2 2 2 1 2 1 2 192 4_4_12 4_4_4.3 1 2 2 2 2 1 2 2 1 193 5_1_1 5_1_1.1 1 4 2 1 1 1 1 1 1 194 5_1_2 5_1_2.1 1 4 2 1 1 1 1 2 2 195 5_1_3 5_1_3.1 1 4 2 1 1 1 2 1 2 196 5_1_4 5_1_4.1 1 4 2 1 1 1 2 2 1 197 5_1_5 5_1_1.2 1 4 2 1 1 1 1 1 1 198 5_1_6 5_1_2.2 1 4 2 1 1 1 1 2 2 199 5_1_7 5_1_3.2 1 4 2 1 1 1 2 1 2 200 5_1_8 5_1_4.2 1 4 2 1 1 1 2 2 1 201 5_1_9 5_1_1.3 1 4 2 1 1 1 1 1 1 202 5_1_10 5_1_2.3 1 4 2 1 1 1 1 2 2 203 5_1_11 5_1_3.3 1 4 2 1 1 1 2 1 2 204 5_1_12 5_1_4.3 1 4 2 1 1 1 2 2 1 205 5_2_1 5_2_1.1 1 4 2 1 2 2 1 1 1 206 5_2_2 5_2_2.1 1 4 2 1 2 2 1 2 2 207 5_2_3 5_2_3.1 1 4 2 1 2 2 2 1 2 208 5_2_4 5_2_4.1 1 4 2 1 2 2 2 2 1 209 5_2_5 5_2_1.2 1 4 2 1 2 2 1 1 1 210 5_2_6 5_2_2.2 1 4 2 1 2 2 1 2 2 211 5_2_7 5_2_3.2 1 4 2 1 2 2 2 1 2 212 5_2_8 5_2_4.2 1 4 2 1 2 2 2 2 1 213 5_2_9 5_2_1.3 1 4 2 1 2 2 1 1 1 214 5_2_10 5_2_2.3 1 4 2 1 2 2 1 2 2 215 5_2_11 5_2_3.3 1 4 2 1 2 2 2 1 2 216 5_2_12 5_2_4.3 1 4 2 1 2 2 2 2 1 217 5_3_1 5_3_1.1 1 4 2 2 1 2 1 1 1 218 5_3_2 5_3_2.1 1 4 2 2 1 2 1 2 2 219 5_3_3 5_3_3.1 1 4 2 2 1 2 2 1 2 220 5_3_4 5_3_4.1 1 4 2 2 1 2 2 2 1 221 5_3_5 5_3_1.2 1 4 2 2 1 2 1 1 1 222 5_3_6 5_3_2.2 1 4 2 2 1 2 1 2 2 223 5_3_7 5_3_3.2 1 4 2 2 1 2 2 1 2 224 5_3_8 5_3_4.2 1 4 2 2 1 2 2 2 1 225 5_3_9 5_3_1.3 1 4 2 2 1 2 1 1 1 226 5_3_10 5_3_2.3 1 4 2 2 1 2 1 2 2 227 5_3_11 5_3_3.3 1 4 2 2 1 2 2 1 2 228 5_3_12 5_3_4.3 1 4 2 2 1 2 2 2 1 229 5_4_1 5_4_1.1 1 4 2 2 2 1 1 1 1 230 5_4_2 5_4_2.1 1 4 2 2 2 1 1 2 2 231 5_4_3 5_4_3.1 1 4 2 2 2 1 2 1 2 232 5_4_4 5_4_4.1 1 4 2 2 2 1 2 2 1 233 5_4_5 5_4_1.2 1 4 2 2 2 1 1 1 1 234 5_4_6 5_4_2.2 1 4 2 2 2 1 1 2 2 235 5_4_7 5_4_3.2 1 4 2 2 2 1 2 1 2 236 5_4_8 5_4_4.2 1 4 2 2 2 1 2 2 1 237 5_4_9 5_4_1.3 1 4 2 2 2 1 1 1 1 238 5_4_10 5_4_2.3 1 4 2 2 2 1 1 2 2 239 5_4_11 5_4_3.3 1 4 2 2 2 1 2 1 2 240 5_4_12 5_4_4.3 1 4 2 2 2 1 2 2 1 241 6_1_1 6_1_1.1 1 6 2 1 1 1 1 1 1 242 6_1_2 6_1_2.1 1 6 2 1 1 1 1 2 2 243 6_1_3 6_1_3.1 1 6 2 1 1 1 2 1 2 244 6_1_4 6_1_4.1 1 6 2 1 1 1 2 2 1 245 6_1_5 6_1_1.2 1 6 2 1 1 1 1 1 1 246 6_1_6 6_1_2.2 1 6 2 1 1 1 1 2 2 247 6_1_7 6_1_3.2 1 6 2 1 1 1 2 1 2 248 6_1_8 6_1_4.2 1 6 2 1 1 1 2 2 1 249 6_1_9 6_1_1.3 1 6 2 1 1 1 1 1 1 250 6_1_10 6_1_2.3 1 6 2 1 1 1 1 2 2 251 6_1_11 6_1_3.3 1 6 2 1 1 1 2 1 2 252 6_1_12 6_1_4.3 1 6 2 1 1 1 2 2 1 253 6_2_1 6_2_1.1 1 6 2 1 2 2 1 1 1 254 6_2_2 6_2_2.1 1 6 2 1 2 2 1 2 2 255 6_2_3 6_2_3.1 1 6 2 1 2 2 2 1 2 256 6_2_4 6_2_4.1 1 6 2 1 2 2 2 2 1 257 6_2_5 6_2_1.2 1 6 2 1 2 2 1 1 1 258 6_2_6 6_2_2.2 1 6 2 1 2 2 1 2 2 259 6_2_7 6_2_3.2 1 6 2 1 2 2 2 1 2 260 6_2_8 6_2_4.2 1 6 2 1 2 2 2 2 1 261 6_2_9 6_2_1.3 1 6 2 1 2 2 1 1 1 262 6_2_10 6_2_2.3 1 6 2 1 2 2 1 2 2 263 6_2_11 6_2_3.3 1 6 2 1 2 2 2 1 2 264 6_2_12 6_2_4.3 1 6 2 1 2 2 2 2 1 265 6_3_1 6_3_1.1 1 6 2 2 1 2 1 1 1 266 6_3_2 6_3_2.1 1 6 2 2 1 2 1 2 2 267 6_3_3 6_3_3.1 1 6 2 2 1 2 2 1 2 268 6_3_4 6_3_4.1 1 6 2 2 1 2 2 2 1 269 6_3_5 6_3_1.2 1 6 2 2 1 2 1 1 1 270 6_3_6 6_3_2.2 1 6 2 2 1 2 1 2 2 271 6_3_7 6_3_3.2 1 6 2 2 1 2 2 1 2 272 6_3_8 6_3_4.2 1 6 2 2 1 2 2 2 1 273 6_3_9 6_3_1.3 1 6 2 2 1 2 1 1 1 274 6_3_10 6_3_2.3 1 6 2 2 1 2 1 2 2 275 6_3_11 6_3_3.3 1 6 2 2 1 2 2 1 2 276 6_3_12 6_3_4.3 1 6 2 2 1 2 2 2 1 277 6_4_1 6_4_1.1 1 6 2 2 2 1 1 1 1 278 6_4_2 6_4_2.1 1 6 2 2 2 1 1 2 2 279 6_4_3 6_4_3.1 1 6 2 2 2 1 2 1 2 280 6_4_4 6_4_4.1 1 6 2 2 2 1 2 2 1 281 6_4_5 6_4_1.2 1 6 2 2 2 1 1 1 1 282 6_4_6 6_4_2.2 1 6 2 2 2 1 1 2 2 283 6_4_7 6_4_3.2 1 6 2 2 2 1 2 1 2 284 6_4_8 6_4_4.2 1 6 2 2 2 1 2 2 1 285 6_4_9 6_4_1.3 1 6 2 2 2 1 1 1 1 286 6_4_10 6_4_2.3 1 6 2 2 2 1 1 2 2 287 6_4_11 6_4_3.3 1 6 2 2 2 1 2 1 2 288 6_4_12 6_4_4.3 1 6 2 2 2 1 2 2 1 289 7_1_1 7_1_1.1 2 2 1 1 1 1 1 1 1 290 7_1_2 7_1_2.1 2 2 1 1 1 1 1 2 2 291 7_1_3 7_1_3.1 2 2 1 1 1 1 2 1 2 292 7_1_4 7_1_4.1 2 2 1 1 1 1 2 2 1 293 7_1_5 7_1_1.2 2 2 1 1 1 1 1 1 1 294 7_1_6 7_1_2.2 2 2 1 1 1 1 1 2 2 295 7_1_7 7_1_3.2 2 2 1 1 1 1 2 1 2 296 7_1_8 7_1_4.2 2 2 1 1 1 1 2 2 1 297 7_1_9 7_1_1.3 2 2 1 1 1 1 1 1 1 298 7_1_10 7_1_2.3 2 2 1 1 1 1 1 2 2 299 7_1_11 7_1_3.3 2 2 1 1 1 1 2 1 2 300 7_1_12 7_1_4.3 2 2 1 1 1 1 2 2 1 301 7_2_1 7_2_1.1 2 2 1 1 2 2 1 1 1 302 7_2_2 7_2_2.1 2 2 1 1 2 2 1 2 2 303 7_2_3 7_2_3.1 2 2 1 1 2 2 2 1 2 304 7_2_4 7_2_4.1 2 2 1 1 2 2 2 2 1 305 7_2_5 7_2_1.2 2 2 1 1 2 2 1 1 1 306 7_2_6 7_2_2.2 2 2 1 1 2 2 1 2 2 307 7_2_7 7_2_3.2 2 2 1 1 2 2 2 1 2 308 7_2_8 7_2_4.2 2 2 1 1 2 2 2 2 1 309 7_2_9 7_2_1.3 2 2 1 1 2 2 1 1 1 310 7_2_10 7_2_2.3 2 2 1 1 2 2 1 2 2 311 7_2_11 7_2_3.3 2 2 1 1 2 2 2 1 2 312 7_2_12 7_2_4.3 2 2 1 1 2 2 2 2 1 313 7_3_1 7_3_1.1 2 2 1 2 1 2 1 1 1 314 7_3_2 7_3_2.1 2 2 1 2 1 2 1 2 2 315 7_3_3 7_3_3.1 2 2 1 2 1 2 2 1 2 316 7_3_4 7_3_4.1 2 2 1 2 1 2 2 2 1 317 7_3_5 7_3_1.2 2 2 1 2 1 2 1 1 1 318 7_3_6 7_3_2.2 2 2 1 2 1 2 1 2 2 319 7_3_7 7_3_3.2 2 2 1 2 1 2 2 1 2 320 7_3_8 7_3_4.2 2 2 1 2 1 2 2 2 1 321 7_3_9 7_3_1.3 2 2 1 2 1 2 1 1 1 322 7_3_10 7_3_2.3 2 2 1 2 1 2 1 2 2 323 7_3_11 7_3_3.3 2 2 1 2 1 2 2 1 2 324 7_3_12 7_3_4.3 2 2 1 2 1 2 2 2 1 325 7_4_1 7_4_1.1 2 2 1 2 2 1 1 1 1 326 7_4_2 7_4_2.1 2 2 1 2 2 1 1 2 2 327 7_4_3 7_4_3.1 2 2 1 2 2 1 2 1 2 328 7_4_4 7_4_4.1 2 2 1 2 2 1 2 2 1 329 7_4_5 7_4_1.2 2 2 1 2 2 1 1 1 1 330 7_4_6 7_4_2.2 2 2 1 2 2 1 1 2 2 331 7_4_7 7_4_3.2 2 2 1 2 2 1 2 1 2 332 7_4_8 7_4_4.2 2 2 1 2 2 1 2 2 1 333 7_4_9 7_4_1.3 2 2 1 2 2 1 1 1 1 334 7_4_10 7_4_2.3 2 2 1 2 2 1 1 2 2 335 7_4_11 7_4_3.3 2 2 1 2 2 1 2 1 2 336 7_4_12 7_4_4.3 2 2 1 2 2 1 2 2 1 337 8_1_1 8_1_1.1 2 4 1 1 1 1 1 1 1 338 8_1_2 8_1_2.1 2 4 1 1 1 1 1 2 2 339 8_1_3 8_1_3.1 2 4 1 1 1 1 2 1 2 340 8_1_4 8_1_4.1 2 4 1 1 1 1 2 2 1 341 8_1_5 8_1_1.2 2 4 1 1 1 1 1 1 1 342 8_1_6 8_1_2.2 2 4 1 1 1 1 1 2 2 343 8_1_7 8_1_3.2 2 4 1 1 1 1 2 1 2 344 8_1_8 8_1_4.2 2 4 1 1 1 1 2 2 1 345 8_1_9 8_1_1.3 2 4 1 1 1 1 1 1 1 346 8_1_10 8_1_2.3 2 4 1 1 1 1 1 2 2 347 8_1_11 8_1_3.3 2 4 1 1 1 1 2 1 2 348 8_1_12 8_1_4.3 2 4 1 1 1 1 2 2 1 349 8_2_1 8_2_1.1 2 4 1 1 2 2 1 1 1 350 8_2_2 8_2_2.1 2 4 1 1 2 2 1 2 2 351 8_2_3 8_2_3.1 2 4 1 1 2 2 2 1 2 352 8_2_4 8_2_4.1 2 4 1 1 2 2 2 2 1 353 8_2_5 8_2_1.2 2 4 1 1 2 2 1 1 1 354 8_2_6 8_2_2.2 2 4 1 1 2 2 1 2 2 355 8_2_7 8_2_3.2 2 4 1 1 2 2 2 1 2 356 8_2_8 8_2_4.2 2 4 1 1 2 2 2 2 1 357 8_2_9 8_2_1.3 2 4 1 1 2 2 1 1 1 358 8_2_10 8_2_2.3 2 4 1 1 2 2 1 2 2 359 8_2_11 8_2_3.3 2 4 1 1 2 2 2 1 2 360 8_2_12 8_2_4.3 2 4 1 1 2 2 2 2 1 361 8_3_1 8_3_1.1 2 4 1 2 1 2 1 1 1 362 8_3_2 8_3_2.1 2 4 1 2 1 2 1 2 2 363 8_3_3 8_3_3.1 2 4 1 2 1 2 2 1 2 364 8_3_4 8_3_4.1 2 4 1 2 1 2 2 2 1 365 8_3_5 8_3_1.2 2 4 1 2 1 2 1 1 1 366 8_3_6 8_3_2.2 2 4 1 2 1 2 1 2 2 367 8_3_7 8_3_3.2 2 4 1 2 1 2 2 1 2 368 8_3_8 8_3_4.2 2 4 1 2 1 2 2 2 1 369 8_3_9 8_3_1.3 2 4 1 2 1 2 1 1 1 370 8_3_10 8_3_2.3 2 4 1 2 1 2 1 2 2 371 8_3_11 8_3_3.3 2 4 1 2 1 2 2 1 2 372 8_3_12 8_3_4.3 2 4 1 2 1 2 2 2 1 373 8_4_1 8_4_1.1 2 4 1 2 2 1 1 1 1 374 8_4_2 8_4_2.1 2 4 1 2 2 1 1 2 2 375 8_4_3 8_4_3.1 2 4 1 2 2 1 2 1 2 376 8_4_4 8_4_4.1 2 4 1 2 2 1 2 2 1 377 8_4_5 8_4_1.2 2 4 1 2 2 1 1 1 1 378 8_4_6 8_4_2.2 2 4 1 2 2 1 1 2 2 379 8_4_7 8_4_3.2 2 4 1 2 2 1 2 1 2 380 8_4_8 8_4_4.2 2 4 1 2 2 1 2 2 1 381 8_4_9 8_4_1.3 2 4 1 2 2 1 1 1 1 382 8_4_10 8_4_2.3 2 4 1 2 2 1 1 2 2 383 8_4_11 8_4_3.3 2 4 1 2 2 1 2 1 2 384 8_4_12 8_4_4.3 2 4 1 2 2 1 2 2 1 385 9_1_1 9_1_1.1 2 6 1 1 1 1 1 1 1 386 9_1_2 9_1_2.1 2 6 1 1 1 1 1 2 2 387 9_1_3 9_1_3.1 2 6 1 1 1 1 2 1 2 388 9_1_4 9_1_4.1 2 6 1 1 1 1 2 2 1 389 9_1_5 9_1_1.2 2 6 1 1 1 1 1 1 1 390 9_1_6 9_1_2.2 2 6 1 1 1 1 1 2 2 391 9_1_7 9_1_3.2 2 6 1 1 1 1 2 1 2 392 9_1_8 9_1_4.2 2 6 1 1 1 1 2 2 1 393 9_1_9 9_1_1.3 2 6 1 1 1 1 1 1 1 394 9_1_10 9_1_2.3 2 6 1 1 1 1 1 2 2 395 9_1_11 9_1_3.3 2 6 1 1 1 1 2 1 2 396 9_1_12 9_1_4.3 2 6 1 1 1 1 2 2 1 397 9_2_1 9_2_1.1 2 6 1 1 2 2 1 1 1 398 9_2_2 9_2_2.1 2 6 1 1 2 2 1 2 2 399 9_2_3 9_2_3.1 2 6 1 1 2 2 2 1 2 400 9_2_4 9_2_4.1 2 6 1 1 2 2 2 2 1 401 9_2_5 9_2_1.2 2 6 1 1 2 2 1 1 1 402 9_2_6 9_2_2.2 2 6 1 1 2 2 1 2 2 403 9_2_7 9_2_3.2 2 6 1 1 2 2 2 1 2 404 9_2_8 9_2_4.2 2 6 1 1 2 2 2 2 1 405 9_2_9 9_2_1.3 2 6 1 1 2 2 1 1 1 406 9_2_10 9_2_2.3 2 6 1 1 2 2 1 2 2 407 9_2_11 9_2_3.3 2 6 1 1 2 2 2 1 2 408 9_2_12 9_2_4.3 2 6 1 1 2 2 2 2 1 409 9_3_1 9_3_1.1 2 6 1 2 1 2 1 1 1 410 9_3_2 9_3_2.1 2 6 1 2 1 2 1 2 2 411 9_3_3 9_3_3.1 2 6 1 2 1 2 2 1 2 412 9_3_4 9_3_4.1 2 6 1 2 1 2 2 2 1 413 9_3_5 9_3_1.2 2 6 1 2 1 2 1 1 1 414 9_3_6 9_3_2.2 2 6 1 2 1 2 1 2 2 415 9_3_7 9_3_3.2 2 6 1 2 1 2 2 1 2 416 9_3_8 9_3_4.2 2 6 1 2 1 2 2 2 1 417 9_3_9 9_3_1.3 2 6 1 2 1 2 1 1 1 418 9_3_10 9_3_2.3 2 6 1 2 1 2 1 2 2 419 9_3_11 9_3_3.3 2 6 1 2 1 2 2 1 2 420 9_3_12 9_3_4.3 2 6 1 2 1 2 2 2 1 421 9_4_1 9_4_1.1 2 6 1 2 2 1 1 1 1 422 9_4_2 9_4_2.1 2 6 1 2 2 1 1 2 2 423 9_4_3 9_4_3.1 2 6 1 2 2 1 2 1 2 424 9_4_4 9_4_4.1 2 6 1 2 2 1 2 2 1 425 9_4_5 9_4_1.2 2 6 1 2 2 1 1 1 1 426 9_4_6 9_4_2.2 2 6 1 2 2 1 1 2 2 427 9_4_7 9_4_3.2 2 6 1 2 2 1 2 1 2 428 9_4_8 9_4_4.2 2 6 1 2 2 1 2 2 1 429 9_4_9 9_4_1.3 2 6 1 2 2 1 1 1 1 430 9_4_10 9_4_2.3 2 6 1 2 2 1 1 2 2 431 9_4_11 9_4_3.3 2 6 1 2 2 1 2 1 2 432 9_4_12 9_4_4.3 2 6 1 2 2 1 2 2 1 433 10_1_1 10_1_1.1 2 1 2 1 1 1 1 1 1 434 10_1_2 10_1_2.1 2 1 2 1 1 1 1 2 2 435 10_1_3 10_1_3.1 2 1 2 1 1 1 2 1 2 436 10_1_4 10_1_4.1 2 1 2 1 1 1 2 2 1 437 10_1_5 10_1_1.2 2 1 2 1 1 1 1 1 1 438 10_1_6 10_1_2.2 2 1 2 1 1 1 1 2 2 439 10_1_7 10_1_3.2 2 1 2 1 1 1 2 1 2 440 10_1_8 10_1_4.2 2 1 2 1 1 1 2 2 1 441 10_1_9 10_1_1.3 2 1 2 1 1 1 1 1 1 442 10_1_10 10_1_2.3 2 1 2 1 1 1 1 2 2 443 10_1_11 10_1_3.3 2 1 2 1 1 1 2 1 2 444 10_1_12 10_1_4.3 2 1 2 1 1 1 2 2 1 445 10_2_1 10_2_1.1 2 1 2 1 2 2 1 1 1 446 10_2_2 10_2_2.1 2 1 2 1 2 2 1 2 2 447 10_2_3 10_2_3.1 2 1 2 1 2 2 2 1 2 448 10_2_4 10_2_4.1 2 1 2 1 2 2 2 2 1 449 10_2_5 10_2_1.2 2 1 2 1 2 2 1 1 1 450 10_2_6 10_2_2.2 2 1 2 1 2 2 1 2 2 451 10_2_7 10_2_3.2 2 1 2 1 2 2 2 1 2 452 10_2_8 10_2_4.2 2 1 2 1 2 2 2 2 1 453 10_2_9 10_2_1.3 2 1 2 1 2 2 1 1 1 454 10_2_10 10_2_2.3 2 1 2 1 2 2 1 2 2 455 10_2_11 10_2_3.3 2 1 2 1 2 2 2 1 2 456 10_2_12 10_2_4.3 2 1 2 1 2 2 2 2 1 457 10_3_1 10_3_1.1 2 1 2 2 1 2 1 1 1 458 10_3_2 10_3_2.1 2 1 2 2 1 2 1 2 2 459 10_3_3 10_3_3.1 2 1 2 2 1 2 2 1 2 460 10_3_4 10_3_4.1 2 1 2 2 1 2 2 2 1 461 10_3_5 10_3_1.2 2 1 2 2 1 2 1 1 1 462 10_3_6 10_3_2.2 2 1 2 2 1 2 1 2 2 463 10_3_7 10_3_3.2 2 1 2 2 1 2 2 1 2 464 10_3_8 10_3_4.2 2 1 2 2 1 2 2 2 1 465 10_3_9 10_3_1.3 2 1 2 2 1 2 1 1 1 466 10_3_10 10_3_2.3 2 1 2 2 1 2 1 2 2 467 10_3_11 10_3_3.3 2 1 2 2 1 2 2 1 2 468 10_3_12 10_3_4.3 2 1 2 2 1 2 2 2 1 469 10_4_1 10_4_1.1 2 1 2 2 2 1 1 1 1 470 10_4_2 10_4_2.1 2 1 2 2 2 1 1 2 2 471 10_4_3 10_4_3.1 2 1 2 2 2 1 2 1 2 472 10_4_4 10_4_4.1 2 1 2 2 2 1 2 2 1 473 10_4_5 10_4_1.2 2 1 2 2 2 1 1 1 1 474 10_4_6 10_4_2.2 2 1 2 2 2 1 1 2 2 475 10_4_7 10_4_3.2 2 1 2 2 2 1 2 1 2 476 10_4_8 10_4_4.2 2 1 2 2 2 1 2 2 1 477 10_4_9 10_4_1.3 2 1 2 2 2 1 1 1 1 478 10_4_10 10_4_2.3 2 1 2 2 2 1 1 2 2 479 10_4_11 10_4_3.3 2 1 2 2 2 1 2 1 2 480 10_4_12 10_4_4.3 2 1 2 2 2 1 2 2 1 481 11_1_1 11_1_1.1 2 3 2 1 1 1 1 1 1 482 11_1_2 11_1_2.1 2 3 2 1 1 1 1 2 2 483 11_1_3 11_1_3.1 2 3 2 1 1 1 2 1 2 484 11_1_4 11_1_4.1 2 3 2 1 1 1 2 2 1 485 11_1_5 11_1_1.2 2 3 2 1 1 1 1 1 1 486 11_1_6 11_1_2.2 2 3 2 1 1 1 1 2 2 487 11_1_7 11_1_3.2 2 3 2 1 1 1 2 1 2 488 11_1_8 11_1_4.2 2 3 2 1 1 1 2 2 1 489 11_1_9 11_1_1.3 2 3 2 1 1 1 1 1 1 490 11_1_10 11_1_2.3 2 3 2 1 1 1 1 2 2 491 11_1_11 11_1_3.3 2 3 2 1 1 1 2 1 2 492 11_1_12 11_1_4.3 2 3 2 1 1 1 2 2 1 493 11_2_1 11_2_1.1 2 3 2 1 2 2 1 1 1 494 11_2_2 11_2_2.1 2 3 2 1 2 2 1 2 2 495 11_2_3 11_2_3.1 2 3 2 1 2 2 2 1 2 496 11_2_4 11_2_4.1 2 3 2 1 2 2 2 2 1 497 11_2_5 11_2_1.2 2 3 2 1 2 2 1 1 1 498 11_2_6 11_2_2.2 2 3 2 1 2 2 1 2 2 499 11_2_7 11_2_3.2 2 3 2 1 2 2 2 1 2 500 11_2_8 11_2_4.2 2 3 2 1 2 2 2 2 1 501 11_2_9 11_2_1.3 2 3 2 1 2 2 1 1 1 502 11_2_10 11_2_2.3 2 3 2 1 2 2 1 2 2 503 11_2_11 11_2_3.3 2 3 2 1 2 2 2 1 2 504 11_2_12 11_2_4.3 2 3 2 1 2 2 2 2 1 505 11_3_1 11_3_1.1 2 3 2 2 1 2 1 1 1 506 11_3_2 11_3_2.1 2 3 2 2 1 2 1 2 2 507 11_3_3 11_3_3.1 2 3 2 2 1 2 2 1 2 508 11_3_4 11_3_4.1 2 3 2 2 1 2 2 2 1 509 11_3_5 11_3_1.2 2 3 2 2 1 2 1 1 1 510 11_3_6 11_3_2.2 2 3 2 2 1 2 1 2 2 511 11_3_7 11_3_3.2 2 3 2 2 1 2 2 1 2 512 11_3_8 11_3_4.2 2 3 2 2 1 2 2 2 1 513 11_3_9 11_3_1.3 2 3 2 2 1 2 1 1 1 514 11_3_10 11_3_2.3 2 3 2 2 1 2 1 2 2 515 11_3_11 11_3_3.3 2 3 2 2 1 2 2 1 2 516 11_3_12 11_3_4.3 2 3 2 2 1 2 2 2 1 517 11_4_1 11_4_1.1 2 3 2 2 2 1 1 1 1 518 11_4_2 11_4_2.1 2 3 2 2 2 1 1 2 2 519 11_4_3 11_4_3.1 2 3 2 2 2 1 2 1 2 520 11_4_4 11_4_4.1 2 3 2 2 2 1 2 2 1 521 11_4_5 11_4_1.2 2 3 2 2 2 1 1 1 1 522 11_4_6 11_4_2.2 2 3 2 2 2 1 1 2 2 523 11_4_7 11_4_3.2 2 3 2 2 2 1 2 1 2 524 11_4_8 11_4_4.2 2 3 2 2 2 1 2 2 1 525 11_4_9 11_4_1.3 2 3 2 2 2 1 1 1 1 526 11_4_10 11_4_2.3 2 3 2 2 2 1 1 2 2 527 11_4_11 11_4_3.3 2 3 2 2 2 1 2 1 2 528 11_4_12 11_4_4.3 2 3 2 2 2 1 2 2 1 529 12_1_1 12_1_1.1 2 5 2 1 1 1 1 1 1 530 12_1_2 12_1_2.1 2 5 2 1 1 1 1 2 2 531 12_1_3 12_1_3.1 2 5 2 1 1 1 2 1 2 532 12_1_4 12_1_4.1 2 5 2 1 1 1 2 2 1 533 12_1_5 12_1_1.2 2 5 2 1 1 1 1 1 1 534 12_1_6 12_1_2.2 2 5 2 1 1 1 1 2 2 535 12_1_7 12_1_3.2 2 5 2 1 1 1 2 1 2 536 12_1_8 12_1_4.2 2 5 2 1 1 1 2 2 1 537 12_1_9 12_1_1.3 2 5 2 1 1 1 1 1 1 538 12_1_10 12_1_2.3 2 5 2 1 1 1 1 2 2 539 12_1_11 12_1_3.3 2 5 2 1 1 1 2 1 2 540 12_1_12 12_1_4.3 2 5 2 1 1 1 2 2 1 541 12_2_1 12_2_1.1 2 5 2 1 2 2 1 1 1 542 12_2_2 12_2_2.1 2 5 2 1 2 2 1 2 2 543 12_2_3 12_2_3.1 2 5 2 1 2 2 2 1 2 544 12_2_4 12_2_4.1 2 5 2 1 2 2 2 2 1 545 12_2_5 12_2_1.2 2 5 2 1 2 2 1 1 1 546 12_2_6 12_2_2.2 2 5 2 1 2 2 1 2 2 547 12_2_7 12_2_3.2 2 5 2 1 2 2 2 1 2 548 12_2_8 12_2_4.2 2 5 2 1 2 2 2 2 1 549 12_2_9 12_2_1.3 2 5 2 1 2 2 1 1 1 550 12_2_10 12_2_2.3 2 5 2 1 2 2 1 2 2 551 12_2_11 12_2_3.3 2 5 2 1 2 2 2 1 2 552 12_2_12 12_2_4.3 2 5 2 1 2 2 2 2 1 553 12_3_1 12_3_1.1 2 5 2 2 1 2 1 1 1 554 12_3_2 12_3_2.1 2 5 2 2 1 2 1 2 2 555 12_3_3 12_3_3.1 2 5 2 2 1 2 2 1 2 556 12_3_4 12_3_4.1 2 5 2 2 1 2 2 2 1 557 12_3_5 12_3_1.2 2 5 2 2 1 2 1 1 1 558 12_3_6 12_3_2.2 2 5 2 2 1 2 1 2 2 559 12_3_7 12_3_3.2 2 5 2 2 1 2 2 1 2 560 12_3_8 12_3_4.2 2 5 2 2 1 2 2 2 1 561 12_3_9 12_3_1.3 2 5 2 2 1 2 1 1 1 562 12_3_10 12_3_2.3 2 5 2 2 1 2 1 2 2 563 12_3_11 12_3_3.3 2 5 2 2 1 2 2 1 2 564 12_3_12 12_3_4.3 2 5 2 2 1 2 2 2 1 565 12_4_1 12_4_1.1 2 5 2 2 2 1 1 1 1 566 12_4_2 12_4_2.1 2 5 2 2 2 1 1 2 2 567 12_4_3 12_4_3.1 2 5 2 2 2 1 2 1 2 568 12_4_4 12_4_4.1 2 5 2 2 2 1 2 2 1 569 12_4_5 12_4_1.2 2 5 2 2 2 1 1 1 1 570 12_4_6 12_4_2.2 2 5 2 2 2 1 1 2 2 571 12_4_7 12_4_3.2 2 5 2 2 2 1 2 1 2 572 12_4_8 12_4_4.2 2 5 2 2 2 1 2 2 1 573 12_4_9 12_4_1.3 2 5 2 2 2 1 1 1 1 574 12_4_10 12_4_2.3 2 5 2 2 2 1 1 2 2 575 12_4_11 12_4_3.3 2 5 2 2 2 1 2 1 2 576 12_4_12 12_4_4.3 2 5 2 2 2 1 2 2 1 class=design, type= crossed NOTE: columns run.no and run.no.std.rp are annotation, not part of the data frame > summary(cross1) Multi-step-call: $original $original[[1]] oa.design(nlevels = c(2, 6, 2), factor.names = c("first", "second", "third"), randomize = FALSE) $original[[2]] oa.design(nlevels = c(2, 2, 2), factor.names = Letters[4:6], randomize = FALSE) $original[[3]] oa.design(nlevels = c(2, 2, 2), factor.names = Letters[7:9], repl = 3, randomize = FALSE) $modify cross.design(oa12, oa4, oa4rep, randomize = FALSE) Experimental design of type crossed 192 runs each run independently conducted 3 times Factor settings (scale ends): first second third D E F G H J 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 4 4 5 5 6 6 > cross2 <- cross.design(oa12,oa4rep,oa4,randomize=FALSE) > cross2 run.no run.no.std.rp first second third G H J D E F 1 1_1_1 1_1.1_1 1 1 1 1 1 1 1 1 1 2 1_1_2 1_1.1_2 1 1 1 1 1 1 1 2 2 3 1_1_3 1_1.1_3 1 1 1 1 1 1 2 1 2 4 1_1_4 1_1.1_4 1 1 1 1 1 1 2 2 1 5 1_2_1 1_2.1_1 1 1 1 1 2 2 1 1 1 6 1_2_2 1_2.1_2 1 1 1 1 2 2 1 2 2 7 1_2_3 1_2.1_3 1 1 1 1 2 2 2 1 2 8 1_2_4 1_2.1_4 1 1 1 1 2 2 2 2 1 9 1_3_1 1_3.1_1 1 1 1 2 1 2 1 1 1 10 1_3_2 1_3.1_2 1 1 1 2 1 2 1 2 2 11 1_3_3 1_3.1_3 1 1 1 2 1 2 2 1 2 12 1_3_4 1_3.1_4 1 1 1 2 1 2 2 2 1 13 1_4_1 1_4.1_1 1 1 1 2 2 1 1 1 1 14 1_4_2 1_4.1_2 1 1 1 2 2 1 1 2 2 15 1_4_3 1_4.1_3 1 1 1 2 2 1 2 1 2 16 1_4_4 1_4.1_4 1 1 1 2 2 1 2 2 1 17 1_5_1 1_1.2_1 1 1 1 1 1 1 1 1 1 18 1_5_2 1_1.2_2 1 1 1 1 1 1 1 2 2 19 1_5_3 1_1.2_3 1 1 1 1 1 1 2 1 2 20 1_5_4 1_1.2_4 1 1 1 1 1 1 2 2 1 21 1_6_1 1_2.2_1 1 1 1 1 2 2 1 1 1 22 1_6_2 1_2.2_2 1 1 1 1 2 2 1 2 2 23 1_6_3 1_2.2_3 1 1 1 1 2 2 2 1 2 24 1_6_4 1_2.2_4 1 1 1 1 2 2 2 2 1 25 1_7_1 1_3.2_1 1 1 1 2 1 2 1 1 1 26 1_7_2 1_3.2_2 1 1 1 2 1 2 1 2 2 27 1_7_3 1_3.2_3 1 1 1 2 1 2 2 1 2 28 1_7_4 1_3.2_4 1 1 1 2 1 2 2 2 1 29 1_8_1 1_4.2_1 1 1 1 2 2 1 1 1 1 30 1_8_2 1_4.2_2 1 1 1 2 2 1 1 2 2 31 1_8_3 1_4.2_3 1 1 1 2 2 1 2 1 2 32 1_8_4 1_4.2_4 1 1 1 2 2 1 2 2 1 33 1_9_1 1_1.3_1 1 1 1 1 1 1 1 1 1 34 1_9_2 1_1.3_2 1 1 1 1 1 1 1 2 2 35 1_9_3 1_1.3_3 1 1 1 1 1 1 2 1 2 36 1_9_4 1_1.3_4 1 1 1 1 1 1 2 2 1 37 1_10_1 1_2.3_1 1 1 1 1 2 2 1 1 1 38 1_10_2 1_2.3_2 1 1 1 1 2 2 1 2 2 39 1_10_3 1_2.3_3 1 1 1 1 2 2 2 1 2 40 1_10_4 1_2.3_4 1 1 1 1 2 2 2 2 1 41 1_11_1 1_3.3_1 1 1 1 2 1 2 1 1 1 42 1_11_2 1_3.3_2 1 1 1 2 1 2 1 2 2 43 1_11_3 1_3.3_3 1 1 1 2 1 2 2 1 2 44 1_11_4 1_3.3_4 1 1 1 2 1 2 2 2 1 45 1_12_1 1_4.3_1 1 1 1 2 2 1 1 1 1 46 1_12_2 1_4.3_2 1 1 1 2 2 1 1 2 2 47 1_12_3 1_4.3_3 1 1 1 2 2 1 2 1 2 48 1_12_4 1_4.3_4 1 1 1 2 2 1 2 2 1 49 2_1_1 2_1.1_1 1 3 1 1 1 1 1 1 1 50 2_1_2 2_1.1_2 1 3 1 1 1 1 1 2 2 51 2_1_3 2_1.1_3 1 3 1 1 1 1 2 1 2 52 2_1_4 2_1.1_4 1 3 1 1 1 1 2 2 1 53 2_2_1 2_2.1_1 1 3 1 1 2 2 1 1 1 54 2_2_2 2_2.1_2 1 3 1 1 2 2 1 2 2 55 2_2_3 2_2.1_3 1 3 1 1 2 2 2 1 2 56 2_2_4 2_2.1_4 1 3 1 1 2 2 2 2 1 57 2_3_1 2_3.1_1 1 3 1 2 1 2 1 1 1 58 2_3_2 2_3.1_2 1 3 1 2 1 2 1 2 2 59 2_3_3 2_3.1_3 1 3 1 2 1 2 2 1 2 60 2_3_4 2_3.1_4 1 3 1 2 1 2 2 2 1 61 2_4_1 2_4.1_1 1 3 1 2 2 1 1 1 1 62 2_4_2 2_4.1_2 1 3 1 2 2 1 1 2 2 63 2_4_3 2_4.1_3 1 3 1 2 2 1 2 1 2 64 2_4_4 2_4.1_4 1 3 1 2 2 1 2 2 1 65 2_5_1 2_1.2_1 1 3 1 1 1 1 1 1 1 66 2_5_2 2_1.2_2 1 3 1 1 1 1 1 2 2 67 2_5_3 2_1.2_3 1 3 1 1 1 1 2 1 2 68 2_5_4 2_1.2_4 1 3 1 1 1 1 2 2 1 69 2_6_1 2_2.2_1 1 3 1 1 2 2 1 1 1 70 2_6_2 2_2.2_2 1 3 1 1 2 2 1 2 2 71 2_6_3 2_2.2_3 1 3 1 1 2 2 2 1 2 72 2_6_4 2_2.2_4 1 3 1 1 2 2 2 2 1 73 2_7_1 2_3.2_1 1 3 1 2 1 2 1 1 1 74 2_7_2 2_3.2_2 1 3 1 2 1 2 1 2 2 75 2_7_3 2_3.2_3 1 3 1 2 1 2 2 1 2 76 2_7_4 2_3.2_4 1 3 1 2 1 2 2 2 1 77 2_8_1 2_4.2_1 1 3 1 2 2 1 1 1 1 78 2_8_2 2_4.2_2 1 3 1 2 2 1 1 2 2 79 2_8_3 2_4.2_3 1 3 1 2 2 1 2 1 2 80 2_8_4 2_4.2_4 1 3 1 2 2 1 2 2 1 81 2_9_1 2_1.3_1 1 3 1 1 1 1 1 1 1 82 2_9_2 2_1.3_2 1 3 1 1 1 1 1 2 2 83 2_9_3 2_1.3_3 1 3 1 1 1 1 2 1 2 84 2_9_4 2_1.3_4 1 3 1 1 1 1 2 2 1 85 2_10_1 2_2.3_1 1 3 1 1 2 2 1 1 1 86 2_10_2 2_2.3_2 1 3 1 1 2 2 1 2 2 87 2_10_3 2_2.3_3 1 3 1 1 2 2 2 1 2 88 2_10_4 2_2.3_4 1 3 1 1 2 2 2 2 1 89 2_11_1 2_3.3_1 1 3 1 2 1 2 1 1 1 90 2_11_2 2_3.3_2 1 3 1 2 1 2 1 2 2 91 2_11_3 2_3.3_3 1 3 1 2 1 2 2 1 2 92 2_11_4 2_3.3_4 1 3 1 2 1 2 2 2 1 93 2_12_1 2_4.3_1 1 3 1 2 2 1 1 1 1 94 2_12_2 2_4.3_2 1 3 1 2 2 1 1 2 2 95 2_12_3 2_4.3_3 1 3 1 2 2 1 2 1 2 96 2_12_4 2_4.3_4 1 3 1 2 2 1 2 2 1 97 3_1_1 3_1.1_1 1 5 1 1 1 1 1 1 1 98 3_1_2 3_1.1_2 1 5 1 1 1 1 1 2 2 99 3_1_3 3_1.1_3 1 5 1 1 1 1 2 1 2 100 3_1_4 3_1.1_4 1 5 1 1 1 1 2 2 1 101 3_2_1 3_2.1_1 1 5 1 1 2 2 1 1 1 102 3_2_2 3_2.1_2 1 5 1 1 2 2 1 2 2 103 3_2_3 3_2.1_3 1 5 1 1 2 2 2 1 2 104 3_2_4 3_2.1_4 1 5 1 1 2 2 2 2 1 105 3_3_1 3_3.1_1 1 5 1 2 1 2 1 1 1 106 3_3_2 3_3.1_2 1 5 1 2 1 2 1 2 2 107 3_3_3 3_3.1_3 1 5 1 2 1 2 2 1 2 108 3_3_4 3_3.1_4 1 5 1 2 1 2 2 2 1 109 3_4_1 3_4.1_1 1 5 1 2 2 1 1 1 1 110 3_4_2 3_4.1_2 1 5 1 2 2 1 1 2 2 111 3_4_3 3_4.1_3 1 5 1 2 2 1 2 1 2 112 3_4_4 3_4.1_4 1 5 1 2 2 1 2 2 1 113 3_5_1 3_1.2_1 1 5 1 1 1 1 1 1 1 114 3_5_2 3_1.2_2 1 5 1 1 1 1 1 2 2 115 3_5_3 3_1.2_3 1 5 1 1 1 1 2 1 2 116 3_5_4 3_1.2_4 1 5 1 1 1 1 2 2 1 117 3_6_1 3_2.2_1 1 5 1 1 2 2 1 1 1 118 3_6_2 3_2.2_2 1 5 1 1 2 2 1 2 2 119 3_6_3 3_2.2_3 1 5 1 1 2 2 2 1 2 120 3_6_4 3_2.2_4 1 5 1 1 2 2 2 2 1 121 3_7_1 3_3.2_1 1 5 1 2 1 2 1 1 1 122 3_7_2 3_3.2_2 1 5 1 2 1 2 1 2 2 123 3_7_3 3_3.2_3 1 5 1 2 1 2 2 1 2 124 3_7_4 3_3.2_4 1 5 1 2 1 2 2 2 1 125 3_8_1 3_4.2_1 1 5 1 2 2 1 1 1 1 126 3_8_2 3_4.2_2 1 5 1 2 2 1 1 2 2 127 3_8_3 3_4.2_3 1 5 1 2 2 1 2 1 2 128 3_8_4 3_4.2_4 1 5 1 2 2 1 2 2 1 129 3_9_1 3_1.3_1 1 5 1 1 1 1 1 1 1 130 3_9_2 3_1.3_2 1 5 1 1 1 1 1 2 2 131 3_9_3 3_1.3_3 1 5 1 1 1 1 2 1 2 132 3_9_4 3_1.3_4 1 5 1 1 1 1 2 2 1 133 3_10_1 3_2.3_1 1 5 1 1 2 2 1 1 1 134 3_10_2 3_2.3_2 1 5 1 1 2 2 1 2 2 135 3_10_3 3_2.3_3 1 5 1 1 2 2 2 1 2 136 3_10_4 3_2.3_4 1 5 1 1 2 2 2 2 1 137 3_11_1 3_3.3_1 1 5 1 2 1 2 1 1 1 138 3_11_2 3_3.3_2 1 5 1 2 1 2 1 2 2 139 3_11_3 3_3.3_3 1 5 1 2 1 2 2 1 2 140 3_11_4 3_3.3_4 1 5 1 2 1 2 2 2 1 141 3_12_1 3_4.3_1 1 5 1 2 2 1 1 1 1 142 3_12_2 3_4.3_2 1 5 1 2 2 1 1 2 2 143 3_12_3 3_4.3_3 1 5 1 2 2 1 2 1 2 144 3_12_4 3_4.3_4 1 5 1 2 2 1 2 2 1 145 4_1_1 4_1.1_1 1 2 2 1 1 1 1 1 1 146 4_1_2 4_1.1_2 1 2 2 1 1 1 1 2 2 147 4_1_3 4_1.1_3 1 2 2 1 1 1 2 1 2 148 4_1_4 4_1.1_4 1 2 2 1 1 1 2 2 1 149 4_2_1 4_2.1_1 1 2 2 1 2 2 1 1 1 150 4_2_2 4_2.1_2 1 2 2 1 2 2 1 2 2 151 4_2_3 4_2.1_3 1 2 2 1 2 2 2 1 2 152 4_2_4 4_2.1_4 1 2 2 1 2 2 2 2 1 153 4_3_1 4_3.1_1 1 2 2 2 1 2 1 1 1 154 4_3_2 4_3.1_2 1 2 2 2 1 2 1 2 2 155 4_3_3 4_3.1_3 1 2 2 2 1 2 2 1 2 156 4_3_4 4_3.1_4 1 2 2 2 1 2 2 2 1 157 4_4_1 4_4.1_1 1 2 2 2 2 1 1 1 1 158 4_4_2 4_4.1_2 1 2 2 2 2 1 1 2 2 159 4_4_3 4_4.1_3 1 2 2 2 2 1 2 1 2 160 4_4_4 4_4.1_4 1 2 2 2 2 1 2 2 1 161 4_5_1 4_1.2_1 1 2 2 1 1 1 1 1 1 162 4_5_2 4_1.2_2 1 2 2 1 1 1 1 2 2 163 4_5_3 4_1.2_3 1 2 2 1 1 1 2 1 2 164 4_5_4 4_1.2_4 1 2 2 1 1 1 2 2 1 165 4_6_1 4_2.2_1 1 2 2 1 2 2 1 1 1 166 4_6_2 4_2.2_2 1 2 2 1 2 2 1 2 2 167 4_6_3 4_2.2_3 1 2 2 1 2 2 2 1 2 168 4_6_4 4_2.2_4 1 2 2 1 2 2 2 2 1 169 4_7_1 4_3.2_1 1 2 2 2 1 2 1 1 1 170 4_7_2 4_3.2_2 1 2 2 2 1 2 1 2 2 171 4_7_3 4_3.2_3 1 2 2 2 1 2 2 1 2 172 4_7_4 4_3.2_4 1 2 2 2 1 2 2 2 1 173 4_8_1 4_4.2_1 1 2 2 2 2 1 1 1 1 174 4_8_2 4_4.2_2 1 2 2 2 2 1 1 2 2 175 4_8_3 4_4.2_3 1 2 2 2 2 1 2 1 2 176 4_8_4 4_4.2_4 1 2 2 2 2 1 2 2 1 177 4_9_1 4_1.3_1 1 2 2 1 1 1 1 1 1 178 4_9_2 4_1.3_2 1 2 2 1 1 1 1 2 2 179 4_9_3 4_1.3_3 1 2 2 1 1 1 2 1 2 180 4_9_4 4_1.3_4 1 2 2 1 1 1 2 2 1 181 4_10_1 4_2.3_1 1 2 2 1 2 2 1 1 1 182 4_10_2 4_2.3_2 1 2 2 1 2 2 1 2 2 183 4_10_3 4_2.3_3 1 2 2 1 2 2 2 1 2 184 4_10_4 4_2.3_4 1 2 2 1 2 2 2 2 1 185 4_11_1 4_3.3_1 1 2 2 2 1 2 1 1 1 186 4_11_2 4_3.3_2 1 2 2 2 1 2 1 2 2 187 4_11_3 4_3.3_3 1 2 2 2 1 2 2 1 2 188 4_11_4 4_3.3_4 1 2 2 2 1 2 2 2 1 189 4_12_1 4_4.3_1 1 2 2 2 2 1 1 1 1 190 4_12_2 4_4.3_2 1 2 2 2 2 1 1 2 2 191 4_12_3 4_4.3_3 1 2 2 2 2 1 2 1 2 192 4_12_4 4_4.3_4 1 2 2 2 2 1 2 2 1 193 5_1_1 5_1.1_1 1 4 2 1 1 1 1 1 1 194 5_1_2 5_1.1_2 1 4 2 1 1 1 1 2 2 195 5_1_3 5_1.1_3 1 4 2 1 1 1 2 1 2 196 5_1_4 5_1.1_4 1 4 2 1 1 1 2 2 1 197 5_2_1 5_2.1_1 1 4 2 1 2 2 1 1 1 198 5_2_2 5_2.1_2 1 4 2 1 2 2 1 2 2 199 5_2_3 5_2.1_3 1 4 2 1 2 2 2 1 2 200 5_2_4 5_2.1_4 1 4 2 1 2 2 2 2 1 201 5_3_1 5_3.1_1 1 4 2 2 1 2 1 1 1 202 5_3_2 5_3.1_2 1 4 2 2 1 2 1 2 2 203 5_3_3 5_3.1_3 1 4 2 2 1 2 2 1 2 204 5_3_4 5_3.1_4 1 4 2 2 1 2 2 2 1 205 5_4_1 5_4.1_1 1 4 2 2 2 1 1 1 1 206 5_4_2 5_4.1_2 1 4 2 2 2 1 1 2 2 207 5_4_3 5_4.1_3 1 4 2 2 2 1 2 1 2 208 5_4_4 5_4.1_4 1 4 2 2 2 1 2 2 1 209 5_5_1 5_1.2_1 1 4 2 1 1 1 1 1 1 210 5_5_2 5_1.2_2 1 4 2 1 1 1 1 2 2 211 5_5_3 5_1.2_3 1 4 2 1 1 1 2 1 2 212 5_5_4 5_1.2_4 1 4 2 1 1 1 2 2 1 213 5_6_1 5_2.2_1 1 4 2 1 2 2 1 1 1 214 5_6_2 5_2.2_2 1 4 2 1 2 2 1 2 2 215 5_6_3 5_2.2_3 1 4 2 1 2 2 2 1 2 216 5_6_4 5_2.2_4 1 4 2 1 2 2 2 2 1 217 5_7_1 5_3.2_1 1 4 2 2 1 2 1 1 1 218 5_7_2 5_3.2_2 1 4 2 2 1 2 1 2 2 219 5_7_3 5_3.2_3 1 4 2 2 1 2 2 1 2 220 5_7_4 5_3.2_4 1 4 2 2 1 2 2 2 1 221 5_8_1 5_4.2_1 1 4 2 2 2 1 1 1 1 222 5_8_2 5_4.2_2 1 4 2 2 2 1 1 2 2 223 5_8_3 5_4.2_3 1 4 2 2 2 1 2 1 2 224 5_8_4 5_4.2_4 1 4 2 2 2 1 2 2 1 225 5_9_1 5_1.3_1 1 4 2 1 1 1 1 1 1 226 5_9_2 5_1.3_2 1 4 2 1 1 1 1 2 2 227 5_9_3 5_1.3_3 1 4 2 1 1 1 2 1 2 228 5_9_4 5_1.3_4 1 4 2 1 1 1 2 2 1 229 5_10_1 5_2.3_1 1 4 2 1 2 2 1 1 1 230 5_10_2 5_2.3_2 1 4 2 1 2 2 1 2 2 231 5_10_3 5_2.3_3 1 4 2 1 2 2 2 1 2 232 5_10_4 5_2.3_4 1 4 2 1 2 2 2 2 1 233 5_11_1 5_3.3_1 1 4 2 2 1 2 1 1 1 234 5_11_2 5_3.3_2 1 4 2 2 1 2 1 2 2 235 5_11_3 5_3.3_3 1 4 2 2 1 2 2 1 2 236 5_11_4 5_3.3_4 1 4 2 2 1 2 2 2 1 237 5_12_1 5_4.3_1 1 4 2 2 2 1 1 1 1 238 5_12_2 5_4.3_2 1 4 2 2 2 1 1 2 2 239 5_12_3 5_4.3_3 1 4 2 2 2 1 2 1 2 240 5_12_4 5_4.3_4 1 4 2 2 2 1 2 2 1 241 6_1_1 6_1.1_1 1 6 2 1 1 1 1 1 1 242 6_1_2 6_1.1_2 1 6 2 1 1 1 1 2 2 243 6_1_3 6_1.1_3 1 6 2 1 1 1 2 1 2 244 6_1_4 6_1.1_4 1 6 2 1 1 1 2 2 1 245 6_2_1 6_2.1_1 1 6 2 1 2 2 1 1 1 246 6_2_2 6_2.1_2 1 6 2 1 2 2 1 2 2 247 6_2_3 6_2.1_3 1 6 2 1 2 2 2 1 2 248 6_2_4 6_2.1_4 1 6 2 1 2 2 2 2 1 249 6_3_1 6_3.1_1 1 6 2 2 1 2 1 1 1 250 6_3_2 6_3.1_2 1 6 2 2 1 2 1 2 2 251 6_3_3 6_3.1_3 1 6 2 2 1 2 2 1 2 252 6_3_4 6_3.1_4 1 6 2 2 1 2 2 2 1 253 6_4_1 6_4.1_1 1 6 2 2 2 1 1 1 1 254 6_4_2 6_4.1_2 1 6 2 2 2 1 1 2 2 255 6_4_3 6_4.1_3 1 6 2 2 2 1 2 1 2 256 6_4_4 6_4.1_4 1 6 2 2 2 1 2 2 1 257 6_5_1 6_1.2_1 1 6 2 1 1 1 1 1 1 258 6_5_2 6_1.2_2 1 6 2 1 1 1 1 2 2 259 6_5_3 6_1.2_3 1 6 2 1 1 1 2 1 2 260 6_5_4 6_1.2_4 1 6 2 1 1 1 2 2 1 261 6_6_1 6_2.2_1 1 6 2 1 2 2 1 1 1 262 6_6_2 6_2.2_2 1 6 2 1 2 2 1 2 2 263 6_6_3 6_2.2_3 1 6 2 1 2 2 2 1 2 264 6_6_4 6_2.2_4 1 6 2 1 2 2 2 2 1 265 6_7_1 6_3.2_1 1 6 2 2 1 2 1 1 1 266 6_7_2 6_3.2_2 1 6 2 2 1 2 1 2 2 267 6_7_3 6_3.2_3 1 6 2 2 1 2 2 1 2 268 6_7_4 6_3.2_4 1 6 2 2 1 2 2 2 1 269 6_8_1 6_4.2_1 1 6 2 2 2 1 1 1 1 270 6_8_2 6_4.2_2 1 6 2 2 2 1 1 2 2 271 6_8_3 6_4.2_3 1 6 2 2 2 1 2 1 2 272 6_8_4 6_4.2_4 1 6 2 2 2 1 2 2 1 273 6_9_1 6_1.3_1 1 6 2 1 1 1 1 1 1 274 6_9_2 6_1.3_2 1 6 2 1 1 1 1 2 2 275 6_9_3 6_1.3_3 1 6 2 1 1 1 2 1 2 276 6_9_4 6_1.3_4 1 6 2 1 1 1 2 2 1 277 6_10_1 6_2.3_1 1 6 2 1 2 2 1 1 1 278 6_10_2 6_2.3_2 1 6 2 1 2 2 1 2 2 279 6_10_3 6_2.3_3 1 6 2 1 2 2 2 1 2 280 6_10_4 6_2.3_4 1 6 2 1 2 2 2 2 1 281 6_11_1 6_3.3_1 1 6 2 2 1 2 1 1 1 282 6_11_2 6_3.3_2 1 6 2 2 1 2 1 2 2 283 6_11_3 6_3.3_3 1 6 2 2 1 2 2 1 2 284 6_11_4 6_3.3_4 1 6 2 2 1 2 2 2 1 285 6_12_1 6_4.3_1 1 6 2 2 2 1 1 1 1 286 6_12_2 6_4.3_2 1 6 2 2 2 1 1 2 2 287 6_12_3 6_4.3_3 1 6 2 2 2 1 2 1 2 288 6_12_4 6_4.3_4 1 6 2 2 2 1 2 2 1 289 7_1_1 7_1.1_1 2 2 1 1 1 1 1 1 1 290 7_1_2 7_1.1_2 2 2 1 1 1 1 1 2 2 291 7_1_3 7_1.1_3 2 2 1 1 1 1 2 1 2 292 7_1_4 7_1.1_4 2 2 1 1 1 1 2 2 1 293 7_2_1 7_2.1_1 2 2 1 1 2 2 1 1 1 294 7_2_2 7_2.1_2 2 2 1 1 2 2 1 2 2 295 7_2_3 7_2.1_3 2 2 1 1 2 2 2 1 2 296 7_2_4 7_2.1_4 2 2 1 1 2 2 2 2 1 297 7_3_1 7_3.1_1 2 2 1 2 1 2 1 1 1 298 7_3_2 7_3.1_2 2 2 1 2 1 2 1 2 2 299 7_3_3 7_3.1_3 2 2 1 2 1 2 2 1 2 300 7_3_4 7_3.1_4 2 2 1 2 1 2 2 2 1 301 7_4_1 7_4.1_1 2 2 1 2 2 1 1 1 1 302 7_4_2 7_4.1_2 2 2 1 2 2 1 1 2 2 303 7_4_3 7_4.1_3 2 2 1 2 2 1 2 1 2 304 7_4_4 7_4.1_4 2 2 1 2 2 1 2 2 1 305 7_5_1 7_1.2_1 2 2 1 1 1 1 1 1 1 306 7_5_2 7_1.2_2 2 2 1 1 1 1 1 2 2 307 7_5_3 7_1.2_3 2 2 1 1 1 1 2 1 2 308 7_5_4 7_1.2_4 2 2 1 1 1 1 2 2 1 309 7_6_1 7_2.2_1 2 2 1 1 2 2 1 1 1 310 7_6_2 7_2.2_2 2 2 1 1 2 2 1 2 2 311 7_6_3 7_2.2_3 2 2 1 1 2 2 2 1 2 312 7_6_4 7_2.2_4 2 2 1 1 2 2 2 2 1 313 7_7_1 7_3.2_1 2 2 1 2 1 2 1 1 1 314 7_7_2 7_3.2_2 2 2 1 2 1 2 1 2 2 315 7_7_3 7_3.2_3 2 2 1 2 1 2 2 1 2 316 7_7_4 7_3.2_4 2 2 1 2 1 2 2 2 1 317 7_8_1 7_4.2_1 2 2 1 2 2 1 1 1 1 318 7_8_2 7_4.2_2 2 2 1 2 2 1 1 2 2 319 7_8_3 7_4.2_3 2 2 1 2 2 1 2 1 2 320 7_8_4 7_4.2_4 2 2 1 2 2 1 2 2 1 321 7_9_1 7_1.3_1 2 2 1 1 1 1 1 1 1 322 7_9_2 7_1.3_2 2 2 1 1 1 1 1 2 2 323 7_9_3 7_1.3_3 2 2 1 1 1 1 2 1 2 324 7_9_4 7_1.3_4 2 2 1 1 1 1 2 2 1 325 7_10_1 7_2.3_1 2 2 1 1 2 2 1 1 1 326 7_10_2 7_2.3_2 2 2 1 1 2 2 1 2 2 327 7_10_3 7_2.3_3 2 2 1 1 2 2 2 1 2 328 7_10_4 7_2.3_4 2 2 1 1 2 2 2 2 1 329 7_11_1 7_3.3_1 2 2 1 2 1 2 1 1 1 330 7_11_2 7_3.3_2 2 2 1 2 1 2 1 2 2 331 7_11_3 7_3.3_3 2 2 1 2 1 2 2 1 2 332 7_11_4 7_3.3_4 2 2 1 2 1 2 2 2 1 333 7_12_1 7_4.3_1 2 2 1 2 2 1 1 1 1 334 7_12_2 7_4.3_2 2 2 1 2 2 1 1 2 2 335 7_12_3 7_4.3_3 2 2 1 2 2 1 2 1 2 336 7_12_4 7_4.3_4 2 2 1 2 2 1 2 2 1 337 8_1_1 8_1.1_1 2 4 1 1 1 1 1 1 1 338 8_1_2 8_1.1_2 2 4 1 1 1 1 1 2 2 339 8_1_3 8_1.1_3 2 4 1 1 1 1 2 1 2 340 8_1_4 8_1.1_4 2 4 1 1 1 1 2 2 1 341 8_2_1 8_2.1_1 2 4 1 1 2 2 1 1 1 342 8_2_2 8_2.1_2 2 4 1 1 2 2 1 2 2 343 8_2_3 8_2.1_3 2 4 1 1 2 2 2 1 2 344 8_2_4 8_2.1_4 2 4 1 1 2 2 2 2 1 345 8_3_1 8_3.1_1 2 4 1 2 1 2 1 1 1 346 8_3_2 8_3.1_2 2 4 1 2 1 2 1 2 2 347 8_3_3 8_3.1_3 2 4 1 2 1 2 2 1 2 348 8_3_4 8_3.1_4 2 4 1 2 1 2 2 2 1 349 8_4_1 8_4.1_1 2 4 1 2 2 1 1 1 1 350 8_4_2 8_4.1_2 2 4 1 2 2 1 1 2 2 351 8_4_3 8_4.1_3 2 4 1 2 2 1 2 1 2 352 8_4_4 8_4.1_4 2 4 1 2 2 1 2 2 1 353 8_5_1 8_1.2_1 2 4 1 1 1 1 1 1 1 354 8_5_2 8_1.2_2 2 4 1 1 1 1 1 2 2 355 8_5_3 8_1.2_3 2 4 1 1 1 1 2 1 2 356 8_5_4 8_1.2_4 2 4 1 1 1 1 2 2 1 357 8_6_1 8_2.2_1 2 4 1 1 2 2 1 1 1 358 8_6_2 8_2.2_2 2 4 1 1 2 2 1 2 2 359 8_6_3 8_2.2_3 2 4 1 1 2 2 2 1 2 360 8_6_4 8_2.2_4 2 4 1 1 2 2 2 2 1 361 8_7_1 8_3.2_1 2 4 1 2 1 2 1 1 1 362 8_7_2 8_3.2_2 2 4 1 2 1 2 1 2 2 363 8_7_3 8_3.2_3 2 4 1 2 1 2 2 1 2 364 8_7_4 8_3.2_4 2 4 1 2 1 2 2 2 1 365 8_8_1 8_4.2_1 2 4 1 2 2 1 1 1 1 366 8_8_2 8_4.2_2 2 4 1 2 2 1 1 2 2 367 8_8_3 8_4.2_3 2 4 1 2 2 1 2 1 2 368 8_8_4 8_4.2_4 2 4 1 2 2 1 2 2 1 369 8_9_1 8_1.3_1 2 4 1 1 1 1 1 1 1 370 8_9_2 8_1.3_2 2 4 1 1 1 1 1 2 2 371 8_9_3 8_1.3_3 2 4 1 1 1 1 2 1 2 372 8_9_4 8_1.3_4 2 4 1 1 1 1 2 2 1 373 8_10_1 8_2.3_1 2 4 1 1 2 2 1 1 1 374 8_10_2 8_2.3_2 2 4 1 1 2 2 1 2 2 375 8_10_3 8_2.3_3 2 4 1 1 2 2 2 1 2 376 8_10_4 8_2.3_4 2 4 1 1 2 2 2 2 1 377 8_11_1 8_3.3_1 2 4 1 2 1 2 1 1 1 378 8_11_2 8_3.3_2 2 4 1 2 1 2 1 2 2 379 8_11_3 8_3.3_3 2 4 1 2 1 2 2 1 2 380 8_11_4 8_3.3_4 2 4 1 2 1 2 2 2 1 381 8_12_1 8_4.3_1 2 4 1 2 2 1 1 1 1 382 8_12_2 8_4.3_2 2 4 1 2 2 1 1 2 2 383 8_12_3 8_4.3_3 2 4 1 2 2 1 2 1 2 384 8_12_4 8_4.3_4 2 4 1 2 2 1 2 2 1 385 9_1_1 9_1.1_1 2 6 1 1 1 1 1 1 1 386 9_1_2 9_1.1_2 2 6 1 1 1 1 1 2 2 387 9_1_3 9_1.1_3 2 6 1 1 1 1 2 1 2 388 9_1_4 9_1.1_4 2 6 1 1 1 1 2 2 1 389 9_2_1 9_2.1_1 2 6 1 1 2 2 1 1 1 390 9_2_2 9_2.1_2 2 6 1 1 2 2 1 2 2 391 9_2_3 9_2.1_3 2 6 1 1 2 2 2 1 2 392 9_2_4 9_2.1_4 2 6 1 1 2 2 2 2 1 393 9_3_1 9_3.1_1 2 6 1 2 1 2 1 1 1 394 9_3_2 9_3.1_2 2 6 1 2 1 2 1 2 2 395 9_3_3 9_3.1_3 2 6 1 2 1 2 2 1 2 396 9_3_4 9_3.1_4 2 6 1 2 1 2 2 2 1 397 9_4_1 9_4.1_1 2 6 1 2 2 1 1 1 1 398 9_4_2 9_4.1_2 2 6 1 2 2 1 1 2 2 399 9_4_3 9_4.1_3 2 6 1 2 2 1 2 1 2 400 9_4_4 9_4.1_4 2 6 1 2 2 1 2 2 1 401 9_5_1 9_1.2_1 2 6 1 1 1 1 1 1 1 402 9_5_2 9_1.2_2 2 6 1 1 1 1 1 2 2 403 9_5_3 9_1.2_3 2 6 1 1 1 1 2 1 2 404 9_5_4 9_1.2_4 2 6 1 1 1 1 2 2 1 405 9_6_1 9_2.2_1 2 6 1 1 2 2 1 1 1 406 9_6_2 9_2.2_2 2 6 1 1 2 2 1 2 2 407 9_6_3 9_2.2_3 2 6 1 1 2 2 2 1 2 408 9_6_4 9_2.2_4 2 6 1 1 2 2 2 2 1 409 9_7_1 9_3.2_1 2 6 1 2 1 2 1 1 1 410 9_7_2 9_3.2_2 2 6 1 2 1 2 1 2 2 411 9_7_3 9_3.2_3 2 6 1 2 1 2 2 1 2 412 9_7_4 9_3.2_4 2 6 1 2 1 2 2 2 1 413 9_8_1 9_4.2_1 2 6 1 2 2 1 1 1 1 414 9_8_2 9_4.2_2 2 6 1 2 2 1 1 2 2 415 9_8_3 9_4.2_3 2 6 1 2 2 1 2 1 2 416 9_8_4 9_4.2_4 2 6 1 2 2 1 2 2 1 417 9_9_1 9_1.3_1 2 6 1 1 1 1 1 1 1 418 9_9_2 9_1.3_2 2 6 1 1 1 1 1 2 2 419 9_9_3 9_1.3_3 2 6 1 1 1 1 2 1 2 420 9_9_4 9_1.3_4 2 6 1 1 1 1 2 2 1 421 9_10_1 9_2.3_1 2 6 1 1 2 2 1 1 1 422 9_10_2 9_2.3_2 2 6 1 1 2 2 1 2 2 423 9_10_3 9_2.3_3 2 6 1 1 2 2 2 1 2 424 9_10_4 9_2.3_4 2 6 1 1 2 2 2 2 1 425 9_11_1 9_3.3_1 2 6 1 2 1 2 1 1 1 426 9_11_2 9_3.3_2 2 6 1 2 1 2 1 2 2 427 9_11_3 9_3.3_3 2 6 1 2 1 2 2 1 2 428 9_11_4 9_3.3_4 2 6 1 2 1 2 2 2 1 429 9_12_1 9_4.3_1 2 6 1 2 2 1 1 1 1 430 9_12_2 9_4.3_2 2 6 1 2 2 1 1 2 2 431 9_12_3 9_4.3_3 2 6 1 2 2 1 2 1 2 432 9_12_4 9_4.3_4 2 6 1 2 2 1 2 2 1 433 10_1_1 10_1.1_1 2 1 2 1 1 1 1 1 1 434 10_1_2 10_1.1_2 2 1 2 1 1 1 1 2 2 435 10_1_3 10_1.1_3 2 1 2 1 1 1 2 1 2 436 10_1_4 10_1.1_4 2 1 2 1 1 1 2 2 1 437 10_2_1 10_2.1_1 2 1 2 1 2 2 1 1 1 438 10_2_2 10_2.1_2 2 1 2 1 2 2 1 2 2 439 10_2_3 10_2.1_3 2 1 2 1 2 2 2 1 2 440 10_2_4 10_2.1_4 2 1 2 1 2 2 2 2 1 441 10_3_1 10_3.1_1 2 1 2 2 1 2 1 1 1 442 10_3_2 10_3.1_2 2 1 2 2 1 2 1 2 2 443 10_3_3 10_3.1_3 2 1 2 2 1 2 2 1 2 444 10_3_4 10_3.1_4 2 1 2 2 1 2 2 2 1 445 10_4_1 10_4.1_1 2 1 2 2 2 1 1 1 1 446 10_4_2 10_4.1_2 2 1 2 2 2 1 1 2 2 447 10_4_3 10_4.1_3 2 1 2 2 2 1 2 1 2 448 10_4_4 10_4.1_4 2 1 2 2 2 1 2 2 1 449 10_5_1 10_1.2_1 2 1 2 1 1 1 1 1 1 450 10_5_2 10_1.2_2 2 1 2 1 1 1 1 2 2 451 10_5_3 10_1.2_3 2 1 2 1 1 1 2 1 2 452 10_5_4 10_1.2_4 2 1 2 1 1 1 2 2 1 453 10_6_1 10_2.2_1 2 1 2 1 2 2 1 1 1 454 10_6_2 10_2.2_2 2 1 2 1 2 2 1 2 2 455 10_6_3 10_2.2_3 2 1 2 1 2 2 2 1 2 456 10_6_4 10_2.2_4 2 1 2 1 2 2 2 2 1 457 10_7_1 10_3.2_1 2 1 2 2 1 2 1 1 1 458 10_7_2 10_3.2_2 2 1 2 2 1 2 1 2 2 459 10_7_3 10_3.2_3 2 1 2 2 1 2 2 1 2 460 10_7_4 10_3.2_4 2 1 2 2 1 2 2 2 1 461 10_8_1 10_4.2_1 2 1 2 2 2 1 1 1 1 462 10_8_2 10_4.2_2 2 1 2 2 2 1 1 2 2 463 10_8_3 10_4.2_3 2 1 2 2 2 1 2 1 2 464 10_8_4 10_4.2_4 2 1 2 2 2 1 2 2 1 465 10_9_1 10_1.3_1 2 1 2 1 1 1 1 1 1 466 10_9_2 10_1.3_2 2 1 2 1 1 1 1 2 2 467 10_9_3 10_1.3_3 2 1 2 1 1 1 2 1 2 468 10_9_4 10_1.3_4 2 1 2 1 1 1 2 2 1 469 10_10_1 10_2.3_1 2 1 2 1 2 2 1 1 1 470 10_10_2 10_2.3_2 2 1 2 1 2 2 1 2 2 471 10_10_3 10_2.3_3 2 1 2 1 2 2 2 1 2 472 10_10_4 10_2.3_4 2 1 2 1 2 2 2 2 1 473 10_11_1 10_3.3_1 2 1 2 2 1 2 1 1 1 474 10_11_2 10_3.3_2 2 1 2 2 1 2 1 2 2 475 10_11_3 10_3.3_3 2 1 2 2 1 2 2 1 2 476 10_11_4 10_3.3_4 2 1 2 2 1 2 2 2 1 477 10_12_1 10_4.3_1 2 1 2 2 2 1 1 1 1 478 10_12_2 10_4.3_2 2 1 2 2 2 1 1 2 2 479 10_12_3 10_4.3_3 2 1 2 2 2 1 2 1 2 480 10_12_4 10_4.3_4 2 1 2 2 2 1 2 2 1 481 11_1_1 11_1.1_1 2 3 2 1 1 1 1 1 1 482 11_1_2 11_1.1_2 2 3 2 1 1 1 1 2 2 483 11_1_3 11_1.1_3 2 3 2 1 1 1 2 1 2 484 11_1_4 11_1.1_4 2 3 2 1 1 1 2 2 1 485 11_2_1 11_2.1_1 2 3 2 1 2 2 1 1 1 486 11_2_2 11_2.1_2 2 3 2 1 2 2 1 2 2 487 11_2_3 11_2.1_3 2 3 2 1 2 2 2 1 2 488 11_2_4 11_2.1_4 2 3 2 1 2 2 2 2 1 489 11_3_1 11_3.1_1 2 3 2 2 1 2 1 1 1 490 11_3_2 11_3.1_2 2 3 2 2 1 2 1 2 2 491 11_3_3 11_3.1_3 2 3 2 2 1 2 2 1 2 492 11_3_4 11_3.1_4 2 3 2 2 1 2 2 2 1 493 11_4_1 11_4.1_1 2 3 2 2 2 1 1 1 1 494 11_4_2 11_4.1_2 2 3 2 2 2 1 1 2 2 495 11_4_3 11_4.1_3 2 3 2 2 2 1 2 1 2 496 11_4_4 11_4.1_4 2 3 2 2 2 1 2 2 1 497 11_5_1 11_1.2_1 2 3 2 1 1 1 1 1 1 498 11_5_2 11_1.2_2 2 3 2 1 1 1 1 2 2 499 11_5_3 11_1.2_3 2 3 2 1 1 1 2 1 2 500 11_5_4 11_1.2_4 2 3 2 1 1 1 2 2 1 501 11_6_1 11_2.2_1 2 3 2 1 2 2 1 1 1 502 11_6_2 11_2.2_2 2 3 2 1 2 2 1 2 2 503 11_6_3 11_2.2_3 2 3 2 1 2 2 2 1 2 504 11_6_4 11_2.2_4 2 3 2 1 2 2 2 2 1 505 11_7_1 11_3.2_1 2 3 2 2 1 2 1 1 1 506 11_7_2 11_3.2_2 2 3 2 2 1 2 1 2 2 507 11_7_3 11_3.2_3 2 3 2 2 1 2 2 1 2 508 11_7_4 11_3.2_4 2 3 2 2 1 2 2 2 1 509 11_8_1 11_4.2_1 2 3 2 2 2 1 1 1 1 510 11_8_2 11_4.2_2 2 3 2 2 2 1 1 2 2 511 11_8_3 11_4.2_3 2 3 2 2 2 1 2 1 2 512 11_8_4 11_4.2_4 2 3 2 2 2 1 2 2 1 513 11_9_1 11_1.3_1 2 3 2 1 1 1 1 1 1 514 11_9_2 11_1.3_2 2 3 2 1 1 1 1 2 2 515 11_9_3 11_1.3_3 2 3 2 1 1 1 2 1 2 516 11_9_4 11_1.3_4 2 3 2 1 1 1 2 2 1 517 11_10_1 11_2.3_1 2 3 2 1 2 2 1 1 1 518 11_10_2 11_2.3_2 2 3 2 1 2 2 1 2 2 519 11_10_3 11_2.3_3 2 3 2 1 2 2 2 1 2 520 11_10_4 11_2.3_4 2 3 2 1 2 2 2 2 1 521 11_11_1 11_3.3_1 2 3 2 2 1 2 1 1 1 522 11_11_2 11_3.3_2 2 3 2 2 1 2 1 2 2 523 11_11_3 11_3.3_3 2 3 2 2 1 2 2 1 2 524 11_11_4 11_3.3_4 2 3 2 2 1 2 2 2 1 525 11_12_1 11_4.3_1 2 3 2 2 2 1 1 1 1 526 11_12_2 11_4.3_2 2 3 2 2 2 1 1 2 2 527 11_12_3 11_4.3_3 2 3 2 2 2 1 2 1 2 528 11_12_4 11_4.3_4 2 3 2 2 2 1 2 2 1 529 12_1_1 12_1.1_1 2 5 2 1 1 1 1 1 1 530 12_1_2 12_1.1_2 2 5 2 1 1 1 1 2 2 531 12_1_3 12_1.1_3 2 5 2 1 1 1 2 1 2 532 12_1_4 12_1.1_4 2 5 2 1 1 1 2 2 1 533 12_2_1 12_2.1_1 2 5 2 1 2 2 1 1 1 534 12_2_2 12_2.1_2 2 5 2 1 2 2 1 2 2 535 12_2_3 12_2.1_3 2 5 2 1 2 2 2 1 2 536 12_2_4 12_2.1_4 2 5 2 1 2 2 2 2 1 537 12_3_1 12_3.1_1 2 5 2 2 1 2 1 1 1 538 12_3_2 12_3.1_2 2 5 2 2 1 2 1 2 2 539 12_3_3 12_3.1_3 2 5 2 2 1 2 2 1 2 540 12_3_4 12_3.1_4 2 5 2 2 1 2 2 2 1 541 12_4_1 12_4.1_1 2 5 2 2 2 1 1 1 1 542 12_4_2 12_4.1_2 2 5 2 2 2 1 1 2 2 543 12_4_3 12_4.1_3 2 5 2 2 2 1 2 1 2 544 12_4_4 12_4.1_4 2 5 2 2 2 1 2 2 1 545 12_5_1 12_1.2_1 2 5 2 1 1 1 1 1 1 546 12_5_2 12_1.2_2 2 5 2 1 1 1 1 2 2 547 12_5_3 12_1.2_3 2 5 2 1 1 1 2 1 2 548 12_5_4 12_1.2_4 2 5 2 1 1 1 2 2 1 549 12_6_1 12_2.2_1 2 5 2 1 2 2 1 1 1 550 12_6_2 12_2.2_2 2 5 2 1 2 2 1 2 2 551 12_6_3 12_2.2_3 2 5 2 1 2 2 2 1 2 552 12_6_4 12_2.2_4 2 5 2 1 2 2 2 2 1 553 12_7_1 12_3.2_1 2 5 2 2 1 2 1 1 1 554 12_7_2 12_3.2_2 2 5 2 2 1 2 1 2 2 555 12_7_3 12_3.2_3 2 5 2 2 1 2 2 1 2 556 12_7_4 12_3.2_4 2 5 2 2 1 2 2 2 1 557 12_8_1 12_4.2_1 2 5 2 2 2 1 1 1 1 558 12_8_2 12_4.2_2 2 5 2 2 2 1 1 2 2 559 12_8_3 12_4.2_3 2 5 2 2 2 1 2 1 2 560 12_8_4 12_4.2_4 2 5 2 2 2 1 2 2 1 561 12_9_1 12_1.3_1 2 5 2 1 1 1 1 1 1 562 12_9_2 12_1.3_2 2 5 2 1 1 1 1 2 2 563 12_9_3 12_1.3_3 2 5 2 1 1 1 2 1 2 564 12_9_4 12_1.3_4 2 5 2 1 1 1 2 2 1 565 12_10_1 12_2.3_1 2 5 2 1 2 2 1 1 1 566 12_10_2 12_2.3_2 2 5 2 1 2 2 1 2 2 567 12_10_3 12_2.3_3 2 5 2 1 2 2 2 1 2 568 12_10_4 12_2.3_4 2 5 2 1 2 2 2 2 1 569 12_11_1 12_3.3_1 2 5 2 2 1 2 1 1 1 570 12_11_2 12_3.3_2 2 5 2 2 1 2 1 2 2 571 12_11_3 12_3.3_3 2 5 2 2 1 2 2 1 2 572 12_11_4 12_3.3_4 2 5 2 2 1 2 2 2 1 573 12_12_1 12_4.3_1 2 5 2 2 2 1 1 1 1 574 12_12_2 12_4.3_2 2 5 2 2 2 1 1 2 2 575 12_12_3 12_4.3_3 2 5 2 2 2 1 2 1 2 576 12_12_4 12_4.3_4 2 5 2 2 2 1 2 2 1 class=design, type= crossed NOTE: columns run.no and run.no.std.rp are annotation, not part of the data frame > summary(cross2) Multi-step-call: $original $original[[1]] oa.design(nlevels = c(2, 6, 2), factor.names = c("first", "second", "third"), randomize = FALSE) $original[[2]] oa.design(nlevels = c(2, 2, 2), factor.names = Letters[7:9], repl = 3, randomize = FALSE) $original[[3]] oa.design(nlevels = c(2, 2, 2), factor.names = Letters[4:6], randomize = FALSE) $modify cross.design(oa12, oa4rep, oa4, randomize = FALSE) Experimental design of type crossed 192 runs each run independently conducted 3 times Factor settings (scale ends): first second third G H J D E F 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 4 4 5 5 6 6 > altern <- c(35,55,80) > #alter <- factor(alter,levels=alter) > cross3 <- cross.design(oa12,oa4,altern,randomize=FALSE) > cross3 run.no run.no.std.rp first second third D E F altern 1 1_1_1 1_1_1 1 1 1 1 1 1 35 2 1_1_2 1_1_2 1 1 1 1 1 1 55 3 1_1_3 1_1_3 1 1 1 1 1 1 80 4 1_2_1 1_2_1 1 1 1 1 2 2 35 5 1_2_2 1_2_2 1 1 1 1 2 2 55 6 1_2_3 1_2_3 1 1 1 1 2 2 80 7 1_3_1 1_3_1 1 1 1 2 1 2 35 8 1_3_2 1_3_2 1 1 1 2 1 2 55 9 1_3_3 1_3_3 1 1 1 2 1 2 80 10 1_4_1 1_4_1 1 1 1 2 2 1 35 11 1_4_2 1_4_2 1 1 1 2 2 1 55 12 1_4_3 1_4_3 1 1 1 2 2 1 80 13 2_1_1 2_1_1 1 3 1 1 1 1 35 14 2_1_2 2_1_2 1 3 1 1 1 1 55 15 2_1_3 2_1_3 1 3 1 1 1 1 80 16 2_2_1 2_2_1 1 3 1 1 2 2 35 17 2_2_2 2_2_2 1 3 1 1 2 2 55 18 2_2_3 2_2_3 1 3 1 1 2 2 80 19 2_3_1 2_3_1 1 3 1 2 1 2 35 20 2_3_2 2_3_2 1 3 1 2 1 2 55 21 2_3_3 2_3_3 1 3 1 2 1 2 80 22 2_4_1 2_4_1 1 3 1 2 2 1 35 23 2_4_2 2_4_2 1 3 1 2 2 1 55 24 2_4_3 2_4_3 1 3 1 2 2 1 80 25 3_1_1 3_1_1 1 5 1 1 1 1 35 26 3_1_2 3_1_2 1 5 1 1 1 1 55 27 3_1_3 3_1_3 1 5 1 1 1 1 80 28 3_2_1 3_2_1 1 5 1 1 2 2 35 29 3_2_2 3_2_2 1 5 1 1 2 2 55 30 3_2_3 3_2_3 1 5 1 1 2 2 80 31 3_3_1 3_3_1 1 5 1 2 1 2 35 32 3_3_2 3_3_2 1 5 1 2 1 2 55 33 3_3_3 3_3_3 1 5 1 2 1 2 80 34 3_4_1 3_4_1 1 5 1 2 2 1 35 35 3_4_2 3_4_2 1 5 1 2 2 1 55 36 3_4_3 3_4_3 1 5 1 2 2 1 80 37 4_1_1 4_1_1 1 2 2 1 1 1 35 38 4_1_2 4_1_2 1 2 2 1 1 1 55 39 4_1_3 4_1_3 1 2 2 1 1 1 80 40 4_2_1 4_2_1 1 2 2 1 2 2 35 41 4_2_2 4_2_2 1 2 2 1 2 2 55 42 4_2_3 4_2_3 1 2 2 1 2 2 80 43 4_3_1 4_3_1 1 2 2 2 1 2 35 44 4_3_2 4_3_2 1 2 2 2 1 2 55 45 4_3_3 4_3_3 1 2 2 2 1 2 80 46 4_4_1 4_4_1 1 2 2 2 2 1 35 47 4_4_2 4_4_2 1 2 2 2 2 1 55 48 4_4_3 4_4_3 1 2 2 2 2 1 80 49 5_1_1 5_1_1 1 4 2 1 1 1 35 50 5_1_2 5_1_2 1 4 2 1 1 1 55 51 5_1_3 5_1_3 1 4 2 1 1 1 80 52 5_2_1 5_2_1 1 4 2 1 2 2 35 53 5_2_2 5_2_2 1 4 2 1 2 2 55 54 5_2_3 5_2_3 1 4 2 1 2 2 80 55 5_3_1 5_3_1 1 4 2 2 1 2 35 56 5_3_2 5_3_2 1 4 2 2 1 2 55 57 5_3_3 5_3_3 1 4 2 2 1 2 80 58 5_4_1 5_4_1 1 4 2 2 2 1 35 59 5_4_2 5_4_2 1 4 2 2 2 1 55 60 5_4_3 5_4_3 1 4 2 2 2 1 80 61 6_1_1 6_1_1 1 6 2 1 1 1 35 62 6_1_2 6_1_2 1 6 2 1 1 1 55 63 6_1_3 6_1_3 1 6 2 1 1 1 80 64 6_2_1 6_2_1 1 6 2 1 2 2 35 65 6_2_2 6_2_2 1 6 2 1 2 2 55 66 6_2_3 6_2_3 1 6 2 1 2 2 80 67 6_3_1 6_3_1 1 6 2 2 1 2 35 68 6_3_2 6_3_2 1 6 2 2 1 2 55 69 6_3_3 6_3_3 1 6 2 2 1 2 80 70 6_4_1 6_4_1 1 6 2 2 2 1 35 71 6_4_2 6_4_2 1 6 2 2 2 1 55 72 6_4_3 6_4_3 1 6 2 2 2 1 80 73 7_1_1 7_1_1 2 2 1 1 1 1 35 74 7_1_2 7_1_2 2 2 1 1 1 1 55 75 7_1_3 7_1_3 2 2 1 1 1 1 80 76 7_2_1 7_2_1 2 2 1 1 2 2 35 77 7_2_2 7_2_2 2 2 1 1 2 2 55 78 7_2_3 7_2_3 2 2 1 1 2 2 80 79 7_3_1 7_3_1 2 2 1 2 1 2 35 80 7_3_2 7_3_2 2 2 1 2 1 2 55 81 7_3_3 7_3_3 2 2 1 2 1 2 80 82 7_4_1 7_4_1 2 2 1 2 2 1 35 83 7_4_2 7_4_2 2 2 1 2 2 1 55 84 7_4_3 7_4_3 2 2 1 2 2 1 80 85 8_1_1 8_1_1 2 4 1 1 1 1 35 86 8_1_2 8_1_2 2 4 1 1 1 1 55 87 8_1_3 8_1_3 2 4 1 1 1 1 80 88 8_2_1 8_2_1 2 4 1 1 2 2 35 89 8_2_2 8_2_2 2 4 1 1 2 2 55 90 8_2_3 8_2_3 2 4 1 1 2 2 80 91 8_3_1 8_3_1 2 4 1 2 1 2 35 92 8_3_2 8_3_2 2 4 1 2 1 2 55 93 8_3_3 8_3_3 2 4 1 2 1 2 80 94 8_4_1 8_4_1 2 4 1 2 2 1 35 95 8_4_2 8_4_2 2 4 1 2 2 1 55 96 8_4_3 8_4_3 2 4 1 2 2 1 80 97 9_1_1 9_1_1 2 6 1 1 1 1 35 98 9_1_2 9_1_2 2 6 1 1 1 1 55 99 9_1_3 9_1_3 2 6 1 1 1 1 80 100 9_2_1 9_2_1 2 6 1 1 2 2 35 101 9_2_2 9_2_2 2 6 1 1 2 2 55 102 9_2_3 9_2_3 2 6 1 1 2 2 80 103 9_3_1 9_3_1 2 6 1 2 1 2 35 104 9_3_2 9_3_2 2 6 1 2 1 2 55 105 9_3_3 9_3_3 2 6 1 2 1 2 80 106 9_4_1 9_4_1 2 6 1 2 2 1 35 107 9_4_2 9_4_2 2 6 1 2 2 1 55 108 9_4_3 9_4_3 2 6 1 2 2 1 80 109 10_1_1 10_1_1 2 1 2 1 1 1 35 110 10_1_2 10_1_2 2 1 2 1 1 1 55 111 10_1_3 10_1_3 2 1 2 1 1 1 80 112 10_2_1 10_2_1 2 1 2 1 2 2 35 113 10_2_2 10_2_2 2 1 2 1 2 2 55 114 10_2_3 10_2_3 2 1 2 1 2 2 80 115 10_3_1 10_3_1 2 1 2 2 1 2 35 116 10_3_2 10_3_2 2 1 2 2 1 2 55 117 10_3_3 10_3_3 2 1 2 2 1 2 80 118 10_4_1 10_4_1 2 1 2 2 2 1 35 119 10_4_2 10_4_2 2 1 2 2 2 1 55 120 10_4_3 10_4_3 2 1 2 2 2 1 80 121 11_1_1 11_1_1 2 3 2 1 1 1 35 122 11_1_2 11_1_2 2 3 2 1 1 1 55 123 11_1_3 11_1_3 2 3 2 1 1 1 80 124 11_2_1 11_2_1 2 3 2 1 2 2 35 125 11_2_2 11_2_2 2 3 2 1 2 2 55 126 11_2_3 11_2_3 2 3 2 1 2 2 80 127 11_3_1 11_3_1 2 3 2 2 1 2 35 128 11_3_2 11_3_2 2 3 2 2 1 2 55 129 11_3_3 11_3_3 2 3 2 2 1 2 80 130 11_4_1 11_4_1 2 3 2 2 2 1 35 131 11_4_2 11_4_2 2 3 2 2 2 1 55 132 11_4_3 11_4_3 2 3 2 2 2 1 80 133 12_1_1 12_1_1 2 5 2 1 1 1 35 134 12_1_2 12_1_2 2 5 2 1 1 1 55 135 12_1_3 12_1_3 2 5 2 1 1 1 80 136 12_2_1 12_2_1 2 5 2 1 2 2 35 137 12_2_2 12_2_2 2 5 2 1 2 2 55 138 12_2_3 12_2_3 2 5 2 1 2 2 80 139 12_3_1 12_3_1 2 5 2 2 1 2 35 140 12_3_2 12_3_2 2 5 2 2 1 2 55 141 12_3_3 12_3_3 2 5 2 2 1 2 80 142 12_4_1 12_4_1 2 5 2 2 2 1 35 143 12_4_2 12_4_2 2 5 2 2 2 1 55 144 12_4_3 12_4_3 2 5 2 2 2 1 80 class=design, type= crossed NOTE: columns run.no and run.no.std.rp are annotation, not part of the data frame > summary(cross3) Multi-step-call: $original $original[[1]] oa.design(nlevels = c(2, 6, 2), factor.names = c("first", "second", "third"), randomize = FALSE) $original[[2]] oa.design(nlevels = c(2, 2, 2), factor.names = Letters[4:6], randomize = FALSE) $original[[3]] [1] altern $modify cross.design(oa12, oa4, altern, randomize = FALSE) Experimental design of type crossed 144 runs Factor settings (scale ends): first second third D E F altern 1 1 1 1 1 1 1 35 2 2 2 2 2 2 2 55 3 3 80 4 4 5 5 6 6 > alterc <- c("jung","mittel","alt") > #alter <- factor(alter,levels=alter) > cross4 <- cross.design(oa12,oa4,alterc,randomize=FALSE) > cross4 run.no run.no.std.rp first second third D E F alterc 1 1_1_1 1_1_2 1 1 1 1 1 1 jung 2 1_1_2 1_1_3 1 1 1 1 1 1 mittel 3 1_1_3 1_1_1 1 1 1 1 1 1 alt 4 1_2_1 1_2_2 1 1 1 1 2 2 jung 5 1_2_2 1_2_3 1 1 1 1 2 2 mittel 6 1_2_3 1_2_1 1 1 1 1 2 2 alt 7 1_3_1 1_3_2 1 1 1 2 1 2 jung 8 1_3_2 1_3_3 1 1 1 2 1 2 mittel 9 1_3_3 1_3_1 1 1 1 2 1 2 alt 10 1_4_1 1_4_2 1 1 1 2 2 1 jung 11 1_4_2 1_4_3 1 1 1 2 2 1 mittel 12 1_4_3 1_4_1 1 1 1 2 2 1 alt 13 2_1_1 2_1_2 1 3 1 1 1 1 jung 14 2_1_2 2_1_3 1 3 1 1 1 1 mittel 15 2_1_3 2_1_1 1 3 1 1 1 1 alt 16 2_2_1 2_2_2 1 3 1 1 2 2 jung 17 2_2_2 2_2_3 1 3 1 1 2 2 mittel 18 2_2_3 2_2_1 1 3 1 1 2 2 alt 19 2_3_1 2_3_2 1 3 1 2 1 2 jung 20 2_3_2 2_3_3 1 3 1 2 1 2 mittel 21 2_3_3 2_3_1 1 3 1 2 1 2 alt 22 2_4_1 2_4_2 1 3 1 2 2 1 jung 23 2_4_2 2_4_3 1 3 1 2 2 1 mittel 24 2_4_3 2_4_1 1 3 1 2 2 1 alt 25 3_1_1 3_1_2 1 5 1 1 1 1 jung 26 3_1_2 3_1_3 1 5 1 1 1 1 mittel 27 3_1_3 3_1_1 1 5 1 1 1 1 alt 28 3_2_1 3_2_2 1 5 1 1 2 2 jung 29 3_2_2 3_2_3 1 5 1 1 2 2 mittel 30 3_2_3 3_2_1 1 5 1 1 2 2 alt 31 3_3_1 3_3_2 1 5 1 2 1 2 jung 32 3_3_2 3_3_3 1 5 1 2 1 2 mittel 33 3_3_3 3_3_1 1 5 1 2 1 2 alt 34 3_4_1 3_4_2 1 5 1 2 2 1 jung 35 3_4_2 3_4_3 1 5 1 2 2 1 mittel 36 3_4_3 3_4_1 1 5 1 2 2 1 alt 37 4_1_1 4_1_2 1 2 2 1 1 1 jung 38 4_1_2 4_1_3 1 2 2 1 1 1 mittel 39 4_1_3 4_1_1 1 2 2 1 1 1 alt 40 4_2_1 4_2_2 1 2 2 1 2 2 jung 41 4_2_2 4_2_3 1 2 2 1 2 2 mittel 42 4_2_3 4_2_1 1 2 2 1 2 2 alt 43 4_3_1 4_3_2 1 2 2 2 1 2 jung 44 4_3_2 4_3_3 1 2 2 2 1 2 mittel 45 4_3_3 4_3_1 1 2 2 2 1 2 alt 46 4_4_1 4_4_2 1 2 2 2 2 1 jung 47 4_4_2 4_4_3 1 2 2 2 2 1 mittel 48 4_4_3 4_4_1 1 2 2 2 2 1 alt 49 5_1_1 5_1_2 1 4 2 1 1 1 jung 50 5_1_2 5_1_3 1 4 2 1 1 1 mittel 51 5_1_3 5_1_1 1 4 2 1 1 1 alt 52 5_2_1 5_2_2 1 4 2 1 2 2 jung 53 5_2_2 5_2_3 1 4 2 1 2 2 mittel 54 5_2_3 5_2_1 1 4 2 1 2 2 alt 55 5_3_1 5_3_2 1 4 2 2 1 2 jung 56 5_3_2 5_3_3 1 4 2 2 1 2 mittel 57 5_3_3 5_3_1 1 4 2 2 1 2 alt 58 5_4_1 5_4_2 1 4 2 2 2 1 jung 59 5_4_2 5_4_3 1 4 2 2 2 1 mittel 60 5_4_3 5_4_1 1 4 2 2 2 1 alt 61 6_1_1 6_1_2 1 6 2 1 1 1 jung 62 6_1_2 6_1_3 1 6 2 1 1 1 mittel 63 6_1_3 6_1_1 1 6 2 1 1 1 alt 64 6_2_1 6_2_2 1 6 2 1 2 2 jung 65 6_2_2 6_2_3 1 6 2 1 2 2 mittel 66 6_2_3 6_2_1 1 6 2 1 2 2 alt 67 6_3_1 6_3_2 1 6 2 2 1 2 jung 68 6_3_2 6_3_3 1 6 2 2 1 2 mittel 69 6_3_3 6_3_1 1 6 2 2 1 2 alt 70 6_4_1 6_4_2 1 6 2 2 2 1 jung 71 6_4_2 6_4_3 1 6 2 2 2 1 mittel 72 6_4_3 6_4_1 1 6 2 2 2 1 alt 73 7_1_1 7_1_2 2 2 1 1 1 1 jung 74 7_1_2 7_1_3 2 2 1 1 1 1 mittel 75 7_1_3 7_1_1 2 2 1 1 1 1 alt 76 7_2_1 7_2_2 2 2 1 1 2 2 jung 77 7_2_2 7_2_3 2 2 1 1 2 2 mittel 78 7_2_3 7_2_1 2 2 1 1 2 2 alt 79 7_3_1 7_3_2 2 2 1 2 1 2 jung 80 7_3_2 7_3_3 2 2 1 2 1 2 mittel 81 7_3_3 7_3_1 2 2 1 2 1 2 alt 82 7_4_1 7_4_2 2 2 1 2 2 1 jung 83 7_4_2 7_4_3 2 2 1 2 2 1 mittel 84 7_4_3 7_4_1 2 2 1 2 2 1 alt 85 8_1_1 8_1_2 2 4 1 1 1 1 jung 86 8_1_2 8_1_3 2 4 1 1 1 1 mittel 87 8_1_3 8_1_1 2 4 1 1 1 1 alt 88 8_2_1 8_2_2 2 4 1 1 2 2 jung 89 8_2_2 8_2_3 2 4 1 1 2 2 mittel 90 8_2_3 8_2_1 2 4 1 1 2 2 alt 91 8_3_1 8_3_2 2 4 1 2 1 2 jung 92 8_3_2 8_3_3 2 4 1 2 1 2 mittel 93 8_3_3 8_3_1 2 4 1 2 1 2 alt 94 8_4_1 8_4_2 2 4 1 2 2 1 jung 95 8_4_2 8_4_3 2 4 1 2 2 1 mittel 96 8_4_3 8_4_1 2 4 1 2 2 1 alt 97 9_1_1 9_1_2 2 6 1 1 1 1 jung 98 9_1_2 9_1_3 2 6 1 1 1 1 mittel 99 9_1_3 9_1_1 2 6 1 1 1 1 alt 100 9_2_1 9_2_2 2 6 1 1 2 2 jung 101 9_2_2 9_2_3 2 6 1 1 2 2 mittel 102 9_2_3 9_2_1 2 6 1 1 2 2 alt 103 9_3_1 9_3_2 2 6 1 2 1 2 jung 104 9_3_2 9_3_3 2 6 1 2 1 2 mittel 105 9_3_3 9_3_1 2 6 1 2 1 2 alt 106 9_4_1 9_4_2 2 6 1 2 2 1 jung 107 9_4_2 9_4_3 2 6 1 2 2 1 mittel 108 9_4_3 9_4_1 2 6 1 2 2 1 alt 109 10_1_1 10_1_2 2 1 2 1 1 1 jung 110 10_1_2 10_1_3 2 1 2 1 1 1 mittel 111 10_1_3 10_1_1 2 1 2 1 1 1 alt 112 10_2_1 10_2_2 2 1 2 1 2 2 jung 113 10_2_2 10_2_3 2 1 2 1 2 2 mittel 114 10_2_3 10_2_1 2 1 2 1 2 2 alt 115 10_3_1 10_3_2 2 1 2 2 1 2 jung 116 10_3_2 10_3_3 2 1 2 2 1 2 mittel 117 10_3_3 10_3_1 2 1 2 2 1 2 alt 118 10_4_1 10_4_2 2 1 2 2 2 1 jung 119 10_4_2 10_4_3 2 1 2 2 2 1 mittel 120 10_4_3 10_4_1 2 1 2 2 2 1 alt 121 11_1_1 11_1_2 2 3 2 1 1 1 jung 122 11_1_2 11_1_3 2 3 2 1 1 1 mittel 123 11_1_3 11_1_1 2 3 2 1 1 1 alt 124 11_2_1 11_2_2 2 3 2 1 2 2 jung 125 11_2_2 11_2_3 2 3 2 1 2 2 mittel 126 11_2_3 11_2_1 2 3 2 1 2 2 alt 127 11_3_1 11_3_2 2 3 2 2 1 2 jung 128 11_3_2 11_3_3 2 3 2 2 1 2 mittel 129 11_3_3 11_3_1 2 3 2 2 1 2 alt 130 11_4_1 11_4_2 2 3 2 2 2 1 jung 131 11_4_2 11_4_3 2 3 2 2 2 1 mittel 132 11_4_3 11_4_1 2 3 2 2 2 1 alt 133 12_1_1 12_1_2 2 5 2 1 1 1 jung 134 12_1_2 12_1_3 2 5 2 1 1 1 mittel 135 12_1_3 12_1_1 2 5 2 1 1 1 alt 136 12_2_1 12_2_2 2 5 2 1 2 2 jung 137 12_2_2 12_2_3 2 5 2 1 2 2 mittel 138 12_2_3 12_2_1 2 5 2 1 2 2 alt 139 12_3_1 12_3_2 2 5 2 2 1 2 jung 140 12_3_2 12_3_3 2 5 2 2 1 2 mittel 141 12_3_3 12_3_1 2 5 2 2 1 2 alt 142 12_4_1 12_4_2 2 5 2 2 2 1 jung 143 12_4_2 12_4_3 2 5 2 2 2 1 mittel 144 12_4_3 12_4_1 2 5 2 2 2 1 alt class=design, type= crossed NOTE: columns run.no and run.no.std.rp are annotation, not part of the data frame > summary(cross4) Multi-step-call: $original $original[[1]] oa.design(nlevels = c(2, 6, 2), factor.names = c("first", "second", "third"), randomize = FALSE) $original[[2]] oa.design(nlevels = c(2, 2, 2), factor.names = Letters[4:6], randomize = FALSE) $original[[3]] [1] alterc $modify cross.design(oa12, oa4, alterc, randomize = FALSE) Experimental design of type crossed 144 runs Factor settings (scale ends): first second third D E F alterc 1 1 1 1 1 1 1 alt 2 2 2 2 2 2 2 jung 3 3 mittel 4 4 5 5 6 6 > > cross5 <- cross.design(oa12,oa4,oa4reprepeat.only,randomize=FALSE) > cross5 run.no run.no.std.rp first second third D E F K L M 1 1_1_1 1_1_1.1 1 1 1 1 1 1 1 1 1 2 1_1_2 1_1_1.2 1 1 1 1 1 1 1 1 1 3 1_1_3 1_1_1.3 1 1 1 1 1 1 1 1 1 4 1_1_4 1_1_2.1 1 1 1 1 1 1 1 2 2 5 1_1_5 1_1_2.2 1 1 1 1 1 1 1 2 2 6 1_1_6 1_1_2.3 1 1 1 1 1 1 1 2 2 7 1_1_7 1_1_3.1 1 1 1 1 1 1 2 1 2 8 1_1_8 1_1_3.2 1 1 1 1 1 1 2 1 2 9 1_1_9 1_1_3.3 1 1 1 1 1 1 2 1 2 10 1_1_10 1_1_4.1 1 1 1 1 1 1 2 2 1 11 1_1_11 1_1_4.2 1 1 1 1 1 1 2 2 1 12 1_1_12 1_1_4.3 1 1 1 1 1 1 2 2 1 13 1_2_1 1_2_1.1 1 1 1 1 2 2 1 1 1 14 1_2_2 1_2_1.2 1 1 1 1 2 2 1 1 1 15 1_2_3 1_2_1.3 1 1 1 1 2 2 1 1 1 16 1_2_4 1_2_2.1 1 1 1 1 2 2 1 2 2 17 1_2_5 1_2_2.2 1 1 1 1 2 2 1 2 2 18 1_2_6 1_2_2.3 1 1 1 1 2 2 1 2 2 19 1_2_7 1_2_3.1 1 1 1 1 2 2 2 1 2 20 1_2_8 1_2_3.2 1 1 1 1 2 2 2 1 2 21 1_2_9 1_2_3.3 1 1 1 1 2 2 2 1 2 22 1_2_10 1_2_4.1 1 1 1 1 2 2 2 2 1 23 1_2_11 1_2_4.2 1 1 1 1 2 2 2 2 1 24 1_2_12 1_2_4.3 1 1 1 1 2 2 2 2 1 25 1_3_1 1_3_1.1 1 1 1 2 1 2 1 1 1 26 1_3_2 1_3_1.2 1 1 1 2 1 2 1 1 1 27 1_3_3 1_3_1.3 1 1 1 2 1 2 1 1 1 28 1_3_4 1_3_2.1 1 1 1 2 1 2 1 2 2 29 1_3_5 1_3_2.2 1 1 1 2 1 2 1 2 2 30 1_3_6 1_3_2.3 1 1 1 2 1 2 1 2 2 31 1_3_7 1_3_3.1 1 1 1 2 1 2 2 1 2 32 1_3_8 1_3_3.2 1 1 1 2 1 2 2 1 2 33 1_3_9 1_3_3.3 1 1 1 2 1 2 2 1 2 34 1_3_10 1_3_4.1 1 1 1 2 1 2 2 2 1 35 1_3_11 1_3_4.2 1 1 1 2 1 2 2 2 1 36 1_3_12 1_3_4.3 1 1 1 2 1 2 2 2 1 37 1_4_1 1_4_1.1 1 1 1 2 2 1 1 1 1 38 1_4_2 1_4_1.2 1 1 1 2 2 1 1 1 1 39 1_4_3 1_4_1.3 1 1 1 2 2 1 1 1 1 40 1_4_4 1_4_2.1 1 1 1 2 2 1 1 2 2 41 1_4_5 1_4_2.2 1 1 1 2 2 1 1 2 2 42 1_4_6 1_4_2.3 1 1 1 2 2 1 1 2 2 43 1_4_7 1_4_3.1 1 1 1 2 2 1 2 1 2 44 1_4_8 1_4_3.2 1 1 1 2 2 1 2 1 2 45 1_4_9 1_4_3.3 1 1 1 2 2 1 2 1 2 46 1_4_10 1_4_4.1 1 1 1 2 2 1 2 2 1 47 1_4_11 1_4_4.2 1 1 1 2 2 1 2 2 1 48 1_4_12 1_4_4.3 1 1 1 2 2 1 2 2 1 49 2_1_1 2_1_1.1 1 3 1 1 1 1 1 1 1 50 2_1_2 2_1_1.2 1 3 1 1 1 1 1 1 1 51 2_1_3 2_1_1.3 1 3 1 1 1 1 1 1 1 52 2_1_4 2_1_2.1 1 3 1 1 1 1 1 2 2 53 2_1_5 2_1_2.2 1 3 1 1 1 1 1 2 2 54 2_1_6 2_1_2.3 1 3 1 1 1 1 1 2 2 55 2_1_7 2_1_3.1 1 3 1 1 1 1 2 1 2 56 2_1_8 2_1_3.2 1 3 1 1 1 1 2 1 2 57 2_1_9 2_1_3.3 1 3 1 1 1 1 2 1 2 58 2_1_10 2_1_4.1 1 3 1 1 1 1 2 2 1 59 2_1_11 2_1_4.2 1 3 1 1 1 1 2 2 1 60 2_1_12 2_1_4.3 1 3 1 1 1 1 2 2 1 61 2_2_1 2_2_1.1 1 3 1 1 2 2 1 1 1 62 2_2_2 2_2_1.2 1 3 1 1 2 2 1 1 1 63 2_2_3 2_2_1.3 1 3 1 1 2 2 1 1 1 64 2_2_4 2_2_2.1 1 3 1 1 2 2 1 2 2 65 2_2_5 2_2_2.2 1 3 1 1 2 2 1 2 2 66 2_2_6 2_2_2.3 1 3 1 1 2 2 1 2 2 67 2_2_7 2_2_3.1 1 3 1 1 2 2 2 1 2 68 2_2_8 2_2_3.2 1 3 1 1 2 2 2 1 2 69 2_2_9 2_2_3.3 1 3 1 1 2 2 2 1 2 70 2_2_10 2_2_4.1 1 3 1 1 2 2 2 2 1 71 2_2_11 2_2_4.2 1 3 1 1 2 2 2 2 1 72 2_2_12 2_2_4.3 1 3 1 1 2 2 2 2 1 73 2_3_1 2_3_1.1 1 3 1 2 1 2 1 1 1 74 2_3_2 2_3_1.2 1 3 1 2 1 2 1 1 1 75 2_3_3 2_3_1.3 1 3 1 2 1 2 1 1 1 76 2_3_4 2_3_2.1 1 3 1 2 1 2 1 2 2 77 2_3_5 2_3_2.2 1 3 1 2 1 2 1 2 2 78 2_3_6 2_3_2.3 1 3 1 2 1 2 1 2 2 79 2_3_7 2_3_3.1 1 3 1 2 1 2 2 1 2 80 2_3_8 2_3_3.2 1 3 1 2 1 2 2 1 2 81 2_3_9 2_3_3.3 1 3 1 2 1 2 2 1 2 82 2_3_10 2_3_4.1 1 3 1 2 1 2 2 2 1 83 2_3_11 2_3_4.2 1 3 1 2 1 2 2 2 1 84 2_3_12 2_3_4.3 1 3 1 2 1 2 2 2 1 85 2_4_1 2_4_1.1 1 3 1 2 2 1 1 1 1 86 2_4_2 2_4_1.2 1 3 1 2 2 1 1 1 1 87 2_4_3 2_4_1.3 1 3 1 2 2 1 1 1 1 88 2_4_4 2_4_2.1 1 3 1 2 2 1 1 2 2 89 2_4_5 2_4_2.2 1 3 1 2 2 1 1 2 2 90 2_4_6 2_4_2.3 1 3 1 2 2 1 1 2 2 91 2_4_7 2_4_3.1 1 3 1 2 2 1 2 1 2 92 2_4_8 2_4_3.2 1 3 1 2 2 1 2 1 2 93 2_4_9 2_4_3.3 1 3 1 2 2 1 2 1 2 94 2_4_10 2_4_4.1 1 3 1 2 2 1 2 2 1 95 2_4_11 2_4_4.2 1 3 1 2 2 1 2 2 1 96 2_4_12 2_4_4.3 1 3 1 2 2 1 2 2 1 97 3_1_1 3_1_1.1 1 5 1 1 1 1 1 1 1 98 3_1_2 3_1_1.2 1 5 1 1 1 1 1 1 1 99 3_1_3 3_1_1.3 1 5 1 1 1 1 1 1 1 100 3_1_4 3_1_2.1 1 5 1 1 1 1 1 2 2 101 3_1_5 3_1_2.2 1 5 1 1 1 1 1 2 2 102 3_1_6 3_1_2.3 1 5 1 1 1 1 1 2 2 103 3_1_7 3_1_3.1 1 5 1 1 1 1 2 1 2 104 3_1_8 3_1_3.2 1 5 1 1 1 1 2 1 2 105 3_1_9 3_1_3.3 1 5 1 1 1 1 2 1 2 106 3_1_10 3_1_4.1 1 5 1 1 1 1 2 2 1 107 3_1_11 3_1_4.2 1 5 1 1 1 1 2 2 1 108 3_1_12 3_1_4.3 1 5 1 1 1 1 2 2 1 109 3_2_1 3_2_1.1 1 5 1 1 2 2 1 1 1 110 3_2_2 3_2_1.2 1 5 1 1 2 2 1 1 1 111 3_2_3 3_2_1.3 1 5 1 1 2 2 1 1 1 112 3_2_4 3_2_2.1 1 5 1 1 2 2 1 2 2 113 3_2_5 3_2_2.2 1 5 1 1 2 2 1 2 2 114 3_2_6 3_2_2.3 1 5 1 1 2 2 1 2 2 115 3_2_7 3_2_3.1 1 5 1 1 2 2 2 1 2 116 3_2_8 3_2_3.2 1 5 1 1 2 2 2 1 2 117 3_2_9 3_2_3.3 1 5 1 1 2 2 2 1 2 118 3_2_10 3_2_4.1 1 5 1 1 2 2 2 2 1 119 3_2_11 3_2_4.2 1 5 1 1 2 2 2 2 1 120 3_2_12 3_2_4.3 1 5 1 1 2 2 2 2 1 121 3_3_1 3_3_1.1 1 5 1 2 1 2 1 1 1 122 3_3_2 3_3_1.2 1 5 1 2 1 2 1 1 1 123 3_3_3 3_3_1.3 1 5 1 2 1 2 1 1 1 124 3_3_4 3_3_2.1 1 5 1 2 1 2 1 2 2 125 3_3_5 3_3_2.2 1 5 1 2 1 2 1 2 2 126 3_3_6 3_3_2.3 1 5 1 2 1 2 1 2 2 127 3_3_7 3_3_3.1 1 5 1 2 1 2 2 1 2 128 3_3_8 3_3_3.2 1 5 1 2 1 2 2 1 2 129 3_3_9 3_3_3.3 1 5 1 2 1 2 2 1 2 130 3_3_10 3_3_4.1 1 5 1 2 1 2 2 2 1 131 3_3_11 3_3_4.2 1 5 1 2 1 2 2 2 1 132 3_3_12 3_3_4.3 1 5 1 2 1 2 2 2 1 133 3_4_1 3_4_1.1 1 5 1 2 2 1 1 1 1 134 3_4_2 3_4_1.2 1 5 1 2 2 1 1 1 1 135 3_4_3 3_4_1.3 1 5 1 2 2 1 1 1 1 136 3_4_4 3_4_2.1 1 5 1 2 2 1 1 2 2 137 3_4_5 3_4_2.2 1 5 1 2 2 1 1 2 2 138 3_4_6 3_4_2.3 1 5 1 2 2 1 1 2 2 139 3_4_7 3_4_3.1 1 5 1 2 2 1 2 1 2 140 3_4_8 3_4_3.2 1 5 1 2 2 1 2 1 2 141 3_4_9 3_4_3.3 1 5 1 2 2 1 2 1 2 142 3_4_10 3_4_4.1 1 5 1 2 2 1 2 2 1 143 3_4_11 3_4_4.2 1 5 1 2 2 1 2 2 1 144 3_4_12 3_4_4.3 1 5 1 2 2 1 2 2 1 145 4_1_1 4_1_1.1 1 2 2 1 1 1 1 1 1 146 4_1_2 4_1_1.2 1 2 2 1 1 1 1 1 1 147 4_1_3 4_1_1.3 1 2 2 1 1 1 1 1 1 148 4_1_4 4_1_2.1 1 2 2 1 1 1 1 2 2 149 4_1_5 4_1_2.2 1 2 2 1 1 1 1 2 2 150 4_1_6 4_1_2.3 1 2 2 1 1 1 1 2 2 151 4_1_7 4_1_3.1 1 2 2 1 1 1 2 1 2 152 4_1_8 4_1_3.2 1 2 2 1 1 1 2 1 2 153 4_1_9 4_1_3.3 1 2 2 1 1 1 2 1 2 154 4_1_10 4_1_4.1 1 2 2 1 1 1 2 2 1 155 4_1_11 4_1_4.2 1 2 2 1 1 1 2 2 1 156 4_1_12 4_1_4.3 1 2 2 1 1 1 2 2 1 157 4_2_1 4_2_1.1 1 2 2 1 2 2 1 1 1 158 4_2_2 4_2_1.2 1 2 2 1 2 2 1 1 1 159 4_2_3 4_2_1.3 1 2 2 1 2 2 1 1 1 160 4_2_4 4_2_2.1 1 2 2 1 2 2 1 2 2 161 4_2_5 4_2_2.2 1 2 2 1 2 2 1 2 2 162 4_2_6 4_2_2.3 1 2 2 1 2 2 1 2 2 163 4_2_7 4_2_3.1 1 2 2 1 2 2 2 1 2 164 4_2_8 4_2_3.2 1 2 2 1 2 2 2 1 2 165 4_2_9 4_2_3.3 1 2 2 1 2 2 2 1 2 166 4_2_10 4_2_4.1 1 2 2 1 2 2 2 2 1 167 4_2_11 4_2_4.2 1 2 2 1 2 2 2 2 1 168 4_2_12 4_2_4.3 1 2 2 1 2 2 2 2 1 169 4_3_1 4_3_1.1 1 2 2 2 1 2 1 1 1 170 4_3_2 4_3_1.2 1 2 2 2 1 2 1 1 1 171 4_3_3 4_3_1.3 1 2 2 2 1 2 1 1 1 172 4_3_4 4_3_2.1 1 2 2 2 1 2 1 2 2 173 4_3_5 4_3_2.2 1 2 2 2 1 2 1 2 2 174 4_3_6 4_3_2.3 1 2 2 2 1 2 1 2 2 175 4_3_7 4_3_3.1 1 2 2 2 1 2 2 1 2 176 4_3_8 4_3_3.2 1 2 2 2 1 2 2 1 2 177 4_3_9 4_3_3.3 1 2 2 2 1 2 2 1 2 178 4_3_10 4_3_4.1 1 2 2 2 1 2 2 2 1 179 4_3_11 4_3_4.2 1 2 2 2 1 2 2 2 1 180 4_3_12 4_3_4.3 1 2 2 2 1 2 2 2 1 181 4_4_1 4_4_1.1 1 2 2 2 2 1 1 1 1 182 4_4_2 4_4_1.2 1 2 2 2 2 1 1 1 1 183 4_4_3 4_4_1.3 1 2 2 2 2 1 1 1 1 184 4_4_4 4_4_2.1 1 2 2 2 2 1 1 2 2 185 4_4_5 4_4_2.2 1 2 2 2 2 1 1 2 2 186 4_4_6 4_4_2.3 1 2 2 2 2 1 1 2 2 187 4_4_7 4_4_3.1 1 2 2 2 2 1 2 1 2 188 4_4_8 4_4_3.2 1 2 2 2 2 1 2 1 2 189 4_4_9 4_4_3.3 1 2 2 2 2 1 2 1 2 190 4_4_10 4_4_4.1 1 2 2 2 2 1 2 2 1 191 4_4_11 4_4_4.2 1 2 2 2 2 1 2 2 1 192 4_4_12 4_4_4.3 1 2 2 2 2 1 2 2 1 193 5_1_1 5_1_1.1 1 4 2 1 1 1 1 1 1 194 5_1_2 5_1_1.2 1 4 2 1 1 1 1 1 1 195 5_1_3 5_1_1.3 1 4 2 1 1 1 1 1 1 196 5_1_4 5_1_2.1 1 4 2 1 1 1 1 2 2 197 5_1_5 5_1_2.2 1 4 2 1 1 1 1 2 2 198 5_1_6 5_1_2.3 1 4 2 1 1 1 1 2 2 199 5_1_7 5_1_3.1 1 4 2 1 1 1 2 1 2 200 5_1_8 5_1_3.2 1 4 2 1 1 1 2 1 2 201 5_1_9 5_1_3.3 1 4 2 1 1 1 2 1 2 202 5_1_10 5_1_4.1 1 4 2 1 1 1 2 2 1 203 5_1_11 5_1_4.2 1 4 2 1 1 1 2 2 1 204 5_1_12 5_1_4.3 1 4 2 1 1 1 2 2 1 205 5_2_1 5_2_1.1 1 4 2 1 2 2 1 1 1 206 5_2_2 5_2_1.2 1 4 2 1 2 2 1 1 1 207 5_2_3 5_2_1.3 1 4 2 1 2 2 1 1 1 208 5_2_4 5_2_2.1 1 4 2 1 2 2 1 2 2 209 5_2_5 5_2_2.2 1 4 2 1 2 2 1 2 2 210 5_2_6 5_2_2.3 1 4 2 1 2 2 1 2 2 211 5_2_7 5_2_3.1 1 4 2 1 2 2 2 1 2 212 5_2_8 5_2_3.2 1 4 2 1 2 2 2 1 2 213 5_2_9 5_2_3.3 1 4 2 1 2 2 2 1 2 214 5_2_10 5_2_4.1 1 4 2 1 2 2 2 2 1 215 5_2_11 5_2_4.2 1 4 2 1 2 2 2 2 1 216 5_2_12 5_2_4.3 1 4 2 1 2 2 2 2 1 217 5_3_1 5_3_1.1 1 4 2 2 1 2 1 1 1 218 5_3_2 5_3_1.2 1 4 2 2 1 2 1 1 1 219 5_3_3 5_3_1.3 1 4 2 2 1 2 1 1 1 220 5_3_4 5_3_2.1 1 4 2 2 1 2 1 2 2 221 5_3_5 5_3_2.2 1 4 2 2 1 2 1 2 2 222 5_3_6 5_3_2.3 1 4 2 2 1 2 1 2 2 223 5_3_7 5_3_3.1 1 4 2 2 1 2 2 1 2 224 5_3_8 5_3_3.2 1 4 2 2 1 2 2 1 2 225 5_3_9 5_3_3.3 1 4 2 2 1 2 2 1 2 226 5_3_10 5_3_4.1 1 4 2 2 1 2 2 2 1 227 5_3_11 5_3_4.2 1 4 2 2 1 2 2 2 1 228 5_3_12 5_3_4.3 1 4 2 2 1 2 2 2 1 229 5_4_1 5_4_1.1 1 4 2 2 2 1 1 1 1 230 5_4_2 5_4_1.2 1 4 2 2 2 1 1 1 1 231 5_4_3 5_4_1.3 1 4 2 2 2 1 1 1 1 232 5_4_4 5_4_2.1 1 4 2 2 2 1 1 2 2 233 5_4_5 5_4_2.2 1 4 2 2 2 1 1 2 2 234 5_4_6 5_4_2.3 1 4 2 2 2 1 1 2 2 235 5_4_7 5_4_3.1 1 4 2 2 2 1 2 1 2 236 5_4_8 5_4_3.2 1 4 2 2 2 1 2 1 2 237 5_4_9 5_4_3.3 1 4 2 2 2 1 2 1 2 238 5_4_10 5_4_4.1 1 4 2 2 2 1 2 2 1 239 5_4_11 5_4_4.2 1 4 2 2 2 1 2 2 1 240 5_4_12 5_4_4.3 1 4 2 2 2 1 2 2 1 241 6_1_1 6_1_1.1 1 6 2 1 1 1 1 1 1 242 6_1_2 6_1_1.2 1 6 2 1 1 1 1 1 1 243 6_1_3 6_1_1.3 1 6 2 1 1 1 1 1 1 244 6_1_4 6_1_2.1 1 6 2 1 1 1 1 2 2 245 6_1_5 6_1_2.2 1 6 2 1 1 1 1 2 2 246 6_1_6 6_1_2.3 1 6 2 1 1 1 1 2 2 247 6_1_7 6_1_3.1 1 6 2 1 1 1 2 1 2 248 6_1_8 6_1_3.2 1 6 2 1 1 1 2 1 2 249 6_1_9 6_1_3.3 1 6 2 1 1 1 2 1 2 250 6_1_10 6_1_4.1 1 6 2 1 1 1 2 2 1 251 6_1_11 6_1_4.2 1 6 2 1 1 1 2 2 1 252 6_1_12 6_1_4.3 1 6 2 1 1 1 2 2 1 253 6_2_1 6_2_1.1 1 6 2 1 2 2 1 1 1 254 6_2_2 6_2_1.2 1 6 2 1 2 2 1 1 1 255 6_2_3 6_2_1.3 1 6 2 1 2 2 1 1 1 256 6_2_4 6_2_2.1 1 6 2 1 2 2 1 2 2 257 6_2_5 6_2_2.2 1 6 2 1 2 2 1 2 2 258 6_2_6 6_2_2.3 1 6 2 1 2 2 1 2 2 259 6_2_7 6_2_3.1 1 6 2 1 2 2 2 1 2 260 6_2_8 6_2_3.2 1 6 2 1 2 2 2 1 2 261 6_2_9 6_2_3.3 1 6 2 1 2 2 2 1 2 262 6_2_10 6_2_4.1 1 6 2 1 2 2 2 2 1 263 6_2_11 6_2_4.2 1 6 2 1 2 2 2 2 1 264 6_2_12 6_2_4.3 1 6 2 1 2 2 2 2 1 265 6_3_1 6_3_1.1 1 6 2 2 1 2 1 1 1 266 6_3_2 6_3_1.2 1 6 2 2 1 2 1 1 1 267 6_3_3 6_3_1.3 1 6 2 2 1 2 1 1 1 268 6_3_4 6_3_2.1 1 6 2 2 1 2 1 2 2 269 6_3_5 6_3_2.2 1 6 2 2 1 2 1 2 2 270 6_3_6 6_3_2.3 1 6 2 2 1 2 1 2 2 271 6_3_7 6_3_3.1 1 6 2 2 1 2 2 1 2 272 6_3_8 6_3_3.2 1 6 2 2 1 2 2 1 2 273 6_3_9 6_3_3.3 1 6 2 2 1 2 2 1 2 274 6_3_10 6_3_4.1 1 6 2 2 1 2 2 2 1 275 6_3_11 6_3_4.2 1 6 2 2 1 2 2 2 1 276 6_3_12 6_3_4.3 1 6 2 2 1 2 2 2 1 277 6_4_1 6_4_1.1 1 6 2 2 2 1 1 1 1 278 6_4_2 6_4_1.2 1 6 2 2 2 1 1 1 1 279 6_4_3 6_4_1.3 1 6 2 2 2 1 1 1 1 280 6_4_4 6_4_2.1 1 6 2 2 2 1 1 2 2 281 6_4_5 6_4_2.2 1 6 2 2 2 1 1 2 2 282 6_4_6 6_4_2.3 1 6 2 2 2 1 1 2 2 283 6_4_7 6_4_3.1 1 6 2 2 2 1 2 1 2 284 6_4_8 6_4_3.2 1 6 2 2 2 1 2 1 2 285 6_4_9 6_4_3.3 1 6 2 2 2 1 2 1 2 286 6_4_10 6_4_4.1 1 6 2 2 2 1 2 2 1 287 6_4_11 6_4_4.2 1 6 2 2 2 1 2 2 1 288 6_4_12 6_4_4.3 1 6 2 2 2 1 2 2 1 289 7_1_1 7_1_1.1 2 2 1 1 1 1 1 1 1 290 7_1_2 7_1_1.2 2 2 1 1 1 1 1 1 1 291 7_1_3 7_1_1.3 2 2 1 1 1 1 1 1 1 292 7_1_4 7_1_2.1 2 2 1 1 1 1 1 2 2 293 7_1_5 7_1_2.2 2 2 1 1 1 1 1 2 2 294 7_1_6 7_1_2.3 2 2 1 1 1 1 1 2 2 295 7_1_7 7_1_3.1 2 2 1 1 1 1 2 1 2 296 7_1_8 7_1_3.2 2 2 1 1 1 1 2 1 2 297 7_1_9 7_1_3.3 2 2 1 1 1 1 2 1 2 298 7_1_10 7_1_4.1 2 2 1 1 1 1 2 2 1 299 7_1_11 7_1_4.2 2 2 1 1 1 1 2 2 1 300 7_1_12 7_1_4.3 2 2 1 1 1 1 2 2 1 301 7_2_1 7_2_1.1 2 2 1 1 2 2 1 1 1 302 7_2_2 7_2_1.2 2 2 1 1 2 2 1 1 1 303 7_2_3 7_2_1.3 2 2 1 1 2 2 1 1 1 304 7_2_4 7_2_2.1 2 2 1 1 2 2 1 2 2 305 7_2_5 7_2_2.2 2 2 1 1 2 2 1 2 2 306 7_2_6 7_2_2.3 2 2 1 1 2 2 1 2 2 307 7_2_7 7_2_3.1 2 2 1 1 2 2 2 1 2 308 7_2_8 7_2_3.2 2 2 1 1 2 2 2 1 2 309 7_2_9 7_2_3.3 2 2 1 1 2 2 2 1 2 310 7_2_10 7_2_4.1 2 2 1 1 2 2 2 2 1 311 7_2_11 7_2_4.2 2 2 1 1 2 2 2 2 1 312 7_2_12 7_2_4.3 2 2 1 1 2 2 2 2 1 313 7_3_1 7_3_1.1 2 2 1 2 1 2 1 1 1 314 7_3_2 7_3_1.2 2 2 1 2 1 2 1 1 1 315 7_3_3 7_3_1.3 2 2 1 2 1 2 1 1 1 316 7_3_4 7_3_2.1 2 2 1 2 1 2 1 2 2 317 7_3_5 7_3_2.2 2 2 1 2 1 2 1 2 2 318 7_3_6 7_3_2.3 2 2 1 2 1 2 1 2 2 319 7_3_7 7_3_3.1 2 2 1 2 1 2 2 1 2 320 7_3_8 7_3_3.2 2 2 1 2 1 2 2 1 2 321 7_3_9 7_3_3.3 2 2 1 2 1 2 2 1 2 322 7_3_10 7_3_4.1 2 2 1 2 1 2 2 2 1 323 7_3_11 7_3_4.2 2 2 1 2 1 2 2 2 1 324 7_3_12 7_3_4.3 2 2 1 2 1 2 2 2 1 325 7_4_1 7_4_1.1 2 2 1 2 2 1 1 1 1 326 7_4_2 7_4_1.2 2 2 1 2 2 1 1 1 1 327 7_4_3 7_4_1.3 2 2 1 2 2 1 1 1 1 328 7_4_4 7_4_2.1 2 2 1 2 2 1 1 2 2 329 7_4_5 7_4_2.2 2 2 1 2 2 1 1 2 2 330 7_4_6 7_4_2.3 2 2 1 2 2 1 1 2 2 331 7_4_7 7_4_3.1 2 2 1 2 2 1 2 1 2 332 7_4_8 7_4_3.2 2 2 1 2 2 1 2 1 2 333 7_4_9 7_4_3.3 2 2 1 2 2 1 2 1 2 334 7_4_10 7_4_4.1 2 2 1 2 2 1 2 2 1 335 7_4_11 7_4_4.2 2 2 1 2 2 1 2 2 1 336 7_4_12 7_4_4.3 2 2 1 2 2 1 2 2 1 337 8_1_1 8_1_1.1 2 4 1 1 1 1 1 1 1 338 8_1_2 8_1_1.2 2 4 1 1 1 1 1 1 1 339 8_1_3 8_1_1.3 2 4 1 1 1 1 1 1 1 340 8_1_4 8_1_2.1 2 4 1 1 1 1 1 2 2 341 8_1_5 8_1_2.2 2 4 1 1 1 1 1 2 2 342 8_1_6 8_1_2.3 2 4 1 1 1 1 1 2 2 343 8_1_7 8_1_3.1 2 4 1 1 1 1 2 1 2 344 8_1_8 8_1_3.2 2 4 1 1 1 1 2 1 2 345 8_1_9 8_1_3.3 2 4 1 1 1 1 2 1 2 346 8_1_10 8_1_4.1 2 4 1 1 1 1 2 2 1 347 8_1_11 8_1_4.2 2 4 1 1 1 1 2 2 1 348 8_1_12 8_1_4.3 2 4 1 1 1 1 2 2 1 349 8_2_1 8_2_1.1 2 4 1 1 2 2 1 1 1 350 8_2_2 8_2_1.2 2 4 1 1 2 2 1 1 1 351 8_2_3 8_2_1.3 2 4 1 1 2 2 1 1 1 352 8_2_4 8_2_2.1 2 4 1 1 2 2 1 2 2 353 8_2_5 8_2_2.2 2 4 1 1 2 2 1 2 2 354 8_2_6 8_2_2.3 2 4 1 1 2 2 1 2 2 355 8_2_7 8_2_3.1 2 4 1 1 2 2 2 1 2 356 8_2_8 8_2_3.2 2 4 1 1 2 2 2 1 2 357 8_2_9 8_2_3.3 2 4 1 1 2 2 2 1 2 358 8_2_10 8_2_4.1 2 4 1 1 2 2 2 2 1 359 8_2_11 8_2_4.2 2 4 1 1 2 2 2 2 1 360 8_2_12 8_2_4.3 2 4 1 1 2 2 2 2 1 361 8_3_1 8_3_1.1 2 4 1 2 1 2 1 1 1 362 8_3_2 8_3_1.2 2 4 1 2 1 2 1 1 1 363 8_3_3 8_3_1.3 2 4 1 2 1 2 1 1 1 364 8_3_4 8_3_2.1 2 4 1 2 1 2 1 2 2 365 8_3_5 8_3_2.2 2 4 1 2 1 2 1 2 2 366 8_3_6 8_3_2.3 2 4 1 2 1 2 1 2 2 367 8_3_7 8_3_3.1 2 4 1 2 1 2 2 1 2 368 8_3_8 8_3_3.2 2 4 1 2 1 2 2 1 2 369 8_3_9 8_3_3.3 2 4 1 2 1 2 2 1 2 370 8_3_10 8_3_4.1 2 4 1 2 1 2 2 2 1 371 8_3_11 8_3_4.2 2 4 1 2 1 2 2 2 1 372 8_3_12 8_3_4.3 2 4 1 2 1 2 2 2 1 373 8_4_1 8_4_1.1 2 4 1 2 2 1 1 1 1 374 8_4_2 8_4_1.2 2 4 1 2 2 1 1 1 1 375 8_4_3 8_4_1.3 2 4 1 2 2 1 1 1 1 376 8_4_4 8_4_2.1 2 4 1 2 2 1 1 2 2 377 8_4_5 8_4_2.2 2 4 1 2 2 1 1 2 2 378 8_4_6 8_4_2.3 2 4 1 2 2 1 1 2 2 379 8_4_7 8_4_3.1 2 4 1 2 2 1 2 1 2 380 8_4_8 8_4_3.2 2 4 1 2 2 1 2 1 2 381 8_4_9 8_4_3.3 2 4 1 2 2 1 2 1 2 382 8_4_10 8_4_4.1 2 4 1 2 2 1 2 2 1 383 8_4_11 8_4_4.2 2 4 1 2 2 1 2 2 1 384 8_4_12 8_4_4.3 2 4 1 2 2 1 2 2 1 385 9_1_1 9_1_1.1 2 6 1 1 1 1 1 1 1 386 9_1_2 9_1_1.2 2 6 1 1 1 1 1 1 1 387 9_1_3 9_1_1.3 2 6 1 1 1 1 1 1 1 388 9_1_4 9_1_2.1 2 6 1 1 1 1 1 2 2 389 9_1_5 9_1_2.2 2 6 1 1 1 1 1 2 2 390 9_1_6 9_1_2.3 2 6 1 1 1 1 1 2 2 391 9_1_7 9_1_3.1 2 6 1 1 1 1 2 1 2 392 9_1_8 9_1_3.2 2 6 1 1 1 1 2 1 2 393 9_1_9 9_1_3.3 2 6 1 1 1 1 2 1 2 394 9_1_10 9_1_4.1 2 6 1 1 1 1 2 2 1 395 9_1_11 9_1_4.2 2 6 1 1 1 1 2 2 1 396 9_1_12 9_1_4.3 2 6 1 1 1 1 2 2 1 397 9_2_1 9_2_1.1 2 6 1 1 2 2 1 1 1 398 9_2_2 9_2_1.2 2 6 1 1 2 2 1 1 1 399 9_2_3 9_2_1.3 2 6 1 1 2 2 1 1 1 400 9_2_4 9_2_2.1 2 6 1 1 2 2 1 2 2 401 9_2_5 9_2_2.2 2 6 1 1 2 2 1 2 2 402 9_2_6 9_2_2.3 2 6 1 1 2 2 1 2 2 403 9_2_7 9_2_3.1 2 6 1 1 2 2 2 1 2 404 9_2_8 9_2_3.2 2 6 1 1 2 2 2 1 2 405 9_2_9 9_2_3.3 2 6 1 1 2 2 2 1 2 406 9_2_10 9_2_4.1 2 6 1 1 2 2 2 2 1 407 9_2_11 9_2_4.2 2 6 1 1 2 2 2 2 1 408 9_2_12 9_2_4.3 2 6 1 1 2 2 2 2 1 409 9_3_1 9_3_1.1 2 6 1 2 1 2 1 1 1 410 9_3_2 9_3_1.2 2 6 1 2 1 2 1 1 1 411 9_3_3 9_3_1.3 2 6 1 2 1 2 1 1 1 412 9_3_4 9_3_2.1 2 6 1 2 1 2 1 2 2 413 9_3_5 9_3_2.2 2 6 1 2 1 2 1 2 2 414 9_3_6 9_3_2.3 2 6 1 2 1 2 1 2 2 415 9_3_7 9_3_3.1 2 6 1 2 1 2 2 1 2 416 9_3_8 9_3_3.2 2 6 1 2 1 2 2 1 2 417 9_3_9 9_3_3.3 2 6 1 2 1 2 2 1 2 418 9_3_10 9_3_4.1 2 6 1 2 1 2 2 2 1 419 9_3_11 9_3_4.2 2 6 1 2 1 2 2 2 1 420 9_3_12 9_3_4.3 2 6 1 2 1 2 2 2 1 421 9_4_1 9_4_1.1 2 6 1 2 2 1 1 1 1 422 9_4_2 9_4_1.2 2 6 1 2 2 1 1 1 1 423 9_4_3 9_4_1.3 2 6 1 2 2 1 1 1 1 424 9_4_4 9_4_2.1 2 6 1 2 2 1 1 2 2 425 9_4_5 9_4_2.2 2 6 1 2 2 1 1 2 2 426 9_4_6 9_4_2.3 2 6 1 2 2 1 1 2 2 427 9_4_7 9_4_3.1 2 6 1 2 2 1 2 1 2 428 9_4_8 9_4_3.2 2 6 1 2 2 1 2 1 2 429 9_4_9 9_4_3.3 2 6 1 2 2 1 2 1 2 430 9_4_10 9_4_4.1 2 6 1 2 2 1 2 2 1 431 9_4_11 9_4_4.2 2 6 1 2 2 1 2 2 1 432 9_4_12 9_4_4.3 2 6 1 2 2 1 2 2 1 433 10_1_1 10_1_1.1 2 1 2 1 1 1 1 1 1 434 10_1_2 10_1_1.2 2 1 2 1 1 1 1 1 1 435 10_1_3 10_1_1.3 2 1 2 1 1 1 1 1 1 436 10_1_4 10_1_2.1 2 1 2 1 1 1 1 2 2 437 10_1_5 10_1_2.2 2 1 2 1 1 1 1 2 2 438 10_1_6 10_1_2.3 2 1 2 1 1 1 1 2 2 439 10_1_7 10_1_3.1 2 1 2 1 1 1 2 1 2 440 10_1_8 10_1_3.2 2 1 2 1 1 1 2 1 2 441 10_1_9 10_1_3.3 2 1 2 1 1 1 2 1 2 442 10_1_10 10_1_4.1 2 1 2 1 1 1 2 2 1 443 10_1_11 10_1_4.2 2 1 2 1 1 1 2 2 1 444 10_1_12 10_1_4.3 2 1 2 1 1 1 2 2 1 445 10_2_1 10_2_1.1 2 1 2 1 2 2 1 1 1 446 10_2_2 10_2_1.2 2 1 2 1 2 2 1 1 1 447 10_2_3 10_2_1.3 2 1 2 1 2 2 1 1 1 448 10_2_4 10_2_2.1 2 1 2 1 2 2 1 2 2 449 10_2_5 10_2_2.2 2 1 2 1 2 2 1 2 2 450 10_2_6 10_2_2.3 2 1 2 1 2 2 1 2 2 451 10_2_7 10_2_3.1 2 1 2 1 2 2 2 1 2 452 10_2_8 10_2_3.2 2 1 2 1 2 2 2 1 2 453 10_2_9 10_2_3.3 2 1 2 1 2 2 2 1 2 454 10_2_10 10_2_4.1 2 1 2 1 2 2 2 2 1 455 10_2_11 10_2_4.2 2 1 2 1 2 2 2 2 1 456 10_2_12 10_2_4.3 2 1 2 1 2 2 2 2 1 457 10_3_1 10_3_1.1 2 1 2 2 1 2 1 1 1 458 10_3_2 10_3_1.2 2 1 2 2 1 2 1 1 1 459 10_3_3 10_3_1.3 2 1 2 2 1 2 1 1 1 460 10_3_4 10_3_2.1 2 1 2 2 1 2 1 2 2 461 10_3_5 10_3_2.2 2 1 2 2 1 2 1 2 2 462 10_3_6 10_3_2.3 2 1 2 2 1 2 1 2 2 463 10_3_7 10_3_3.1 2 1 2 2 1 2 2 1 2 464 10_3_8 10_3_3.2 2 1 2 2 1 2 2 1 2 465 10_3_9 10_3_3.3 2 1 2 2 1 2 2 1 2 466 10_3_10 10_3_4.1 2 1 2 2 1 2 2 2 1 467 10_3_11 10_3_4.2 2 1 2 2 1 2 2 2 1 468 10_3_12 10_3_4.3 2 1 2 2 1 2 2 2 1 469 10_4_1 10_4_1.1 2 1 2 2 2 1 1 1 1 470 10_4_2 10_4_1.2 2 1 2 2 2 1 1 1 1 471 10_4_3 10_4_1.3 2 1 2 2 2 1 1 1 1 472 10_4_4 10_4_2.1 2 1 2 2 2 1 1 2 2 473 10_4_5 10_4_2.2 2 1 2 2 2 1 1 2 2 474 10_4_6 10_4_2.3 2 1 2 2 2 1 1 2 2 475 10_4_7 10_4_3.1 2 1 2 2 2 1 2 1 2 476 10_4_8 10_4_3.2 2 1 2 2 2 1 2 1 2 477 10_4_9 10_4_3.3 2 1 2 2 2 1 2 1 2 478 10_4_10 10_4_4.1 2 1 2 2 2 1 2 2 1 479 10_4_11 10_4_4.2 2 1 2 2 2 1 2 2 1 480 10_4_12 10_4_4.3 2 1 2 2 2 1 2 2 1 481 11_1_1 11_1_1.1 2 3 2 1 1 1 1 1 1 482 11_1_2 11_1_1.2 2 3 2 1 1 1 1 1 1 483 11_1_3 11_1_1.3 2 3 2 1 1 1 1 1 1 484 11_1_4 11_1_2.1 2 3 2 1 1 1 1 2 2 485 11_1_5 11_1_2.2 2 3 2 1 1 1 1 2 2 486 11_1_6 11_1_2.3 2 3 2 1 1 1 1 2 2 487 11_1_7 11_1_3.1 2 3 2 1 1 1 2 1 2 488 11_1_8 11_1_3.2 2 3 2 1 1 1 2 1 2 489 11_1_9 11_1_3.3 2 3 2 1 1 1 2 1 2 490 11_1_10 11_1_4.1 2 3 2 1 1 1 2 2 1 491 11_1_11 11_1_4.2 2 3 2 1 1 1 2 2 1 492 11_1_12 11_1_4.3 2 3 2 1 1 1 2 2 1 493 11_2_1 11_2_1.1 2 3 2 1 2 2 1 1 1 494 11_2_2 11_2_1.2 2 3 2 1 2 2 1 1 1 495 11_2_3 11_2_1.3 2 3 2 1 2 2 1 1 1 496 11_2_4 11_2_2.1 2 3 2 1 2 2 1 2 2 497 11_2_5 11_2_2.2 2 3 2 1 2 2 1 2 2 498 11_2_6 11_2_2.3 2 3 2 1 2 2 1 2 2 499 11_2_7 11_2_3.1 2 3 2 1 2 2 2 1 2 500 11_2_8 11_2_3.2 2 3 2 1 2 2 2 1 2 501 11_2_9 11_2_3.3 2 3 2 1 2 2 2 1 2 502 11_2_10 11_2_4.1 2 3 2 1 2 2 2 2 1 503 11_2_11 11_2_4.2 2 3 2 1 2 2 2 2 1 504 11_2_12 11_2_4.3 2 3 2 1 2 2 2 2 1 505 11_3_1 11_3_1.1 2 3 2 2 1 2 1 1 1 506 11_3_2 11_3_1.2 2 3 2 2 1 2 1 1 1 507 11_3_3 11_3_1.3 2 3 2 2 1 2 1 1 1 508 11_3_4 11_3_2.1 2 3 2 2 1 2 1 2 2 509 11_3_5 11_3_2.2 2 3 2 2 1 2 1 2 2 510 11_3_6 11_3_2.3 2 3 2 2 1 2 1 2 2 511 11_3_7 11_3_3.1 2 3 2 2 1 2 2 1 2 512 11_3_8 11_3_3.2 2 3 2 2 1 2 2 1 2 513 11_3_9 11_3_3.3 2 3 2 2 1 2 2 1 2 514 11_3_10 11_3_4.1 2 3 2 2 1 2 2 2 1 515 11_3_11 11_3_4.2 2 3 2 2 1 2 2 2 1 516 11_3_12 11_3_4.3 2 3 2 2 1 2 2 2 1 517 11_4_1 11_4_1.1 2 3 2 2 2 1 1 1 1 518 11_4_2 11_4_1.2 2 3 2 2 2 1 1 1 1 519 11_4_3 11_4_1.3 2 3 2 2 2 1 1 1 1 520 11_4_4 11_4_2.1 2 3 2 2 2 1 1 2 2 521 11_4_5 11_4_2.2 2 3 2 2 2 1 1 2 2 522 11_4_6 11_4_2.3 2 3 2 2 2 1 1 2 2 523 11_4_7 11_4_3.1 2 3 2 2 2 1 2 1 2 524 11_4_8 11_4_3.2 2 3 2 2 2 1 2 1 2 525 11_4_9 11_4_3.3 2 3 2 2 2 1 2 1 2 526 11_4_10 11_4_4.1 2 3 2 2 2 1 2 2 1 527 11_4_11 11_4_4.2 2 3 2 2 2 1 2 2 1 528 11_4_12 11_4_4.3 2 3 2 2 2 1 2 2 1 529 12_1_1 12_1_1.1 2 5 2 1 1 1 1 1 1 530 12_1_2 12_1_1.2 2 5 2 1 1 1 1 1 1 531 12_1_3 12_1_1.3 2 5 2 1 1 1 1 1 1 532 12_1_4 12_1_2.1 2 5 2 1 1 1 1 2 2 533 12_1_5 12_1_2.2 2 5 2 1 1 1 1 2 2 534 12_1_6 12_1_2.3 2 5 2 1 1 1 1 2 2 535 12_1_7 12_1_3.1 2 5 2 1 1 1 2 1 2 536 12_1_8 12_1_3.2 2 5 2 1 1 1 2 1 2 537 12_1_9 12_1_3.3 2 5 2 1 1 1 2 1 2 538 12_1_10 12_1_4.1 2 5 2 1 1 1 2 2 1 539 12_1_11 12_1_4.2 2 5 2 1 1 1 2 2 1 540 12_1_12 12_1_4.3 2 5 2 1 1 1 2 2 1 541 12_2_1 12_2_1.1 2 5 2 1 2 2 1 1 1 542 12_2_2 12_2_1.2 2 5 2 1 2 2 1 1 1 543 12_2_3 12_2_1.3 2 5 2 1 2 2 1 1 1 544 12_2_4 12_2_2.1 2 5 2 1 2 2 1 2 2 545 12_2_5 12_2_2.2 2 5 2 1 2 2 1 2 2 546 12_2_6 12_2_2.3 2 5 2 1 2 2 1 2 2 547 12_2_7 12_2_3.1 2 5 2 1 2 2 2 1 2 548 12_2_8 12_2_3.2 2 5 2 1 2 2 2 1 2 549 12_2_9 12_2_3.3 2 5 2 1 2 2 2 1 2 550 12_2_10 12_2_4.1 2 5 2 1 2 2 2 2 1 551 12_2_11 12_2_4.2 2 5 2 1 2 2 2 2 1 552 12_2_12 12_2_4.3 2 5 2 1 2 2 2 2 1 553 12_3_1 12_3_1.1 2 5 2 2 1 2 1 1 1 554 12_3_2 12_3_1.2 2 5 2 2 1 2 1 1 1 555 12_3_3 12_3_1.3 2 5 2 2 1 2 1 1 1 556 12_3_4 12_3_2.1 2 5 2 2 1 2 1 2 2 557 12_3_5 12_3_2.2 2 5 2 2 1 2 1 2 2 558 12_3_6 12_3_2.3 2 5 2 2 1 2 1 2 2 559 12_3_7 12_3_3.1 2 5 2 2 1 2 2 1 2 560 12_3_8 12_3_3.2 2 5 2 2 1 2 2 1 2 561 12_3_9 12_3_3.3 2 5 2 2 1 2 2 1 2 562 12_3_10 12_3_4.1 2 5 2 2 1 2 2 2 1 563 12_3_11 12_3_4.2 2 5 2 2 1 2 2 2 1 564 12_3_12 12_3_4.3 2 5 2 2 1 2 2 2 1 565 12_4_1 12_4_1.1 2 5 2 2 2 1 1 1 1 566 12_4_2 12_4_1.2 2 5 2 2 2 1 1 1 1 567 12_4_3 12_4_1.3 2 5 2 2 2 1 1 1 1 568 12_4_4 12_4_2.1 2 5 2 2 2 1 1 2 2 569 12_4_5 12_4_2.2 2 5 2 2 2 1 1 2 2 570 12_4_6 12_4_2.3 2 5 2 2 2 1 1 2 2 571 12_4_7 12_4_3.1 2 5 2 2 2 1 2 1 2 572 12_4_8 12_4_3.2 2 5 2 2 2 1 2 1 2 573 12_4_9 12_4_3.3 2 5 2 2 2 1 2 1 2 574 12_4_10 12_4_4.1 2 5 2 2 2 1 2 2 1 575 12_4_11 12_4_4.2 2 5 2 2 2 1 2 2 1 576 12_4_12 12_4_4.3 2 5 2 2 2 1 2 2 1 class=design, type= crossed NOTE: columns run.no and run.no.std.rp are annotation, not part of the data frame > summary(cross5) Multi-step-call: $original $original[[1]] oa.design(nlevels = c(2, 6, 2), factor.names = c("first", "second", "third"), randomize = FALSE) $original[[2]] oa.design(nlevels = c(2, 2, 2), factor.names = Letters[4:6], randomize = FALSE) $original[[3]] oa.design(nlevels = c(2, 2, 2), repl = 3, factor.names = Letters[10:12], repeat.only = TRUE, randomize = FALSE) $modify cross.design(oa12, oa4, oa4reprepeat.only, randomize = FALSE) Experimental design of type crossed 192 runs 3 measurements per run (not proper replications) Factor settings (scale ends): first second third D E F K L M 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 4 4 5 5 6 6 > cross6 <- cross.design(oa4rep,oa4reprepeat.only,randomize=FALSE) Warning message: In workhorse(design1, design2, ...) : repeat.only replications and proper replications mixed in one crossed design, this does not work with any post-processing! > cross6 run.no run.no.std.rp G H J K L M 1 1_1 1.1_1.1 1 1 1 1 1 1 2 1_2 1.1_1.2 1 1 1 1 1 1 3 1_3 1.1_1.3 1 1 1 1 1 1 4 1_4 1.1_2.1 1 1 1 1 2 2 5 1_5 1.1_2.2 1 1 1 1 2 2 6 1_6 1.1_2.3 1 1 1 1 2 2 7 1_7 1.1_3.1 1 1 1 2 1 2 8 1_8 1.1_3.2 1 1 1 2 1 2 9 1_9 1.1_3.3 1 1 1 2 1 2 10 1_10 1.1_4.1 1 1 1 2 2 1 11 1_11 1.1_4.2 1 1 1 2 2 1 12 1_12 1.1_4.3 1 1 1 2 2 1 13 2_1 2.1_1.1 1 2 2 1 1 1 14 2_2 2.1_1.2 1 2 2 1 1 1 15 2_3 2.1_1.3 1 2 2 1 1 1 16 2_4 2.1_2.1 1 2 2 1 2 2 17 2_5 2.1_2.2 1 2 2 1 2 2 18 2_6 2.1_2.3 1 2 2 1 2 2 19 2_7 2.1_3.1 1 2 2 2 1 2 20 2_8 2.1_3.2 1 2 2 2 1 2 21 2_9 2.1_3.3 1 2 2 2 1 2 22 2_10 2.1_4.1 1 2 2 2 2 1 23 2_11 2.1_4.2 1 2 2 2 2 1 24 2_12 2.1_4.3 1 2 2 2 2 1 25 3_1 3.1_1.1 2 1 2 1 1 1 26 3_2 3.1_1.2 2 1 2 1 1 1 27 3_3 3.1_1.3 2 1 2 1 1 1 28 3_4 3.1_2.1 2 1 2 1 2 2 29 3_5 3.1_2.2 2 1 2 1 2 2 30 3_6 3.1_2.3 2 1 2 1 2 2 31 3_7 3.1_3.1 2 1 2 2 1 2 32 3_8 3.1_3.2 2 1 2 2 1 2 33 3_9 3.1_3.3 2 1 2 2 1 2 34 3_10 3.1_4.1 2 1 2 2 2 1 35 3_11 3.1_4.2 2 1 2 2 2 1 36 3_12 3.1_4.3 2 1 2 2 2 1 37 4_1 4.1_1.1 2 2 1 1 1 1 38 4_2 4.1_1.2 2 2 1 1 1 1 39 4_3 4.1_1.3 2 2 1 1 1 1 40 4_4 4.1_2.1 2 2 1 1 2 2 41 4_5 4.1_2.2 2 2 1 1 2 2 42 4_6 4.1_2.3 2 2 1 1 2 2 43 4_7 4.1_3.1 2 2 1 2 1 2 44 4_8 4.1_3.2 2 2 1 2 1 2 45 4_9 4.1_3.3 2 2 1 2 1 2 46 4_10 4.1_4.1 2 2 1 2 2 1 47 4_11 4.1_4.2 2 2 1 2 2 1 48 4_12 4.1_4.3 2 2 1 2 2 1 49 5_1 1.2_1.1 1 1 1 1 1 1 50 5_2 1.2_1.2 1 1 1 1 1 1 51 5_3 1.2_1.3 1 1 1 1 1 1 52 5_4 1.2_2.1 1 1 1 1 2 2 53 5_5 1.2_2.2 1 1 1 1 2 2 54 5_6 1.2_2.3 1 1 1 1 2 2 55 5_7 1.2_3.1 1 1 1 2 1 2 56 5_8 1.2_3.2 1 1 1 2 1 2 57 5_9 1.2_3.3 1 1 1 2 1 2 58 5_10 1.2_4.1 1 1 1 2 2 1 59 5_11 1.2_4.2 1 1 1 2 2 1 60 5_12 1.2_4.3 1 1 1 2 2 1 61 6_1 2.2_1.1 1 2 2 1 1 1 62 6_2 2.2_1.2 1 2 2 1 1 1 63 6_3 2.2_1.3 1 2 2 1 1 1 64 6_4 2.2_2.1 1 2 2 1 2 2 65 6_5 2.2_2.2 1 2 2 1 2 2 66 6_6 2.2_2.3 1 2 2 1 2 2 67 6_7 2.2_3.1 1 2 2 2 1 2 68 6_8 2.2_3.2 1 2 2 2 1 2 69 6_9 2.2_3.3 1 2 2 2 1 2 70 6_10 2.2_4.1 1 2 2 2 2 1 71 6_11 2.2_4.2 1 2 2 2 2 1 72 6_12 2.2_4.3 1 2 2 2 2 1 73 7_1 3.2_1.1 2 1 2 1 1 1 74 7_2 3.2_1.2 2 1 2 1 1 1 75 7_3 3.2_1.3 2 1 2 1 1 1 76 7_4 3.2_2.1 2 1 2 1 2 2 77 7_5 3.2_2.2 2 1 2 1 2 2 78 7_6 3.2_2.3 2 1 2 1 2 2 79 7_7 3.2_3.1 2 1 2 2 1 2 80 7_8 3.2_3.2 2 1 2 2 1 2 81 7_9 3.2_3.3 2 1 2 2 1 2 82 7_10 3.2_4.1 2 1 2 2 2 1 83 7_11 3.2_4.2 2 1 2 2 2 1 84 7_12 3.2_4.3 2 1 2 2 2 1 85 8_1 4.2_1.1 2 2 1 1 1 1 86 8_2 4.2_1.2 2 2 1 1 1 1 87 8_3 4.2_1.3 2 2 1 1 1 1 88 8_4 4.2_2.1 2 2 1 1 2 2 89 8_5 4.2_2.2 2 2 1 1 2 2 90 8_6 4.2_2.3 2 2 1 1 2 2 91 8_7 4.2_3.1 2 2 1 2 1 2 92 8_8 4.2_3.2 2 2 1 2 1 2 93 8_9 4.2_3.3 2 2 1 2 1 2 94 8_10 4.2_4.1 2 2 1 2 2 1 95 8_11 4.2_4.2 2 2 1 2 2 1 96 8_12 4.2_4.3 2 2 1 2 2 1 97 9_1 1.3_1.1 1 1 1 1 1 1 98 9_2 1.3_1.2 1 1 1 1 1 1 99 9_3 1.3_1.3 1 1 1 1 1 1 100 9_4 1.3_2.1 1 1 1 1 2 2 101 9_5 1.3_2.2 1 1 1 1 2 2 102 9_6 1.3_2.3 1 1 1 1 2 2 103 9_7 1.3_3.1 1 1 1 2 1 2 104 9_8 1.3_3.2 1 1 1 2 1 2 105 9_9 1.3_3.3 1 1 1 2 1 2 106 9_10 1.3_4.1 1 1 1 2 2 1 107 9_11 1.3_4.2 1 1 1 2 2 1 108 9_12 1.3_4.3 1 1 1 2 2 1 109 10_1 2.3_1.1 1 2 2 1 1 1 110 10_2 2.3_1.2 1 2 2 1 1 1 111 10_3 2.3_1.3 1 2 2 1 1 1 112 10_4 2.3_2.1 1 2 2 1 2 2 113 10_5 2.3_2.2 1 2 2 1 2 2 114 10_6 2.3_2.3 1 2 2 1 2 2 115 10_7 2.3_3.1 1 2 2 2 1 2 116 10_8 2.3_3.2 1 2 2 2 1 2 117 10_9 2.3_3.3 1 2 2 2 1 2 118 10_10 2.3_4.1 1 2 2 2 2 1 119 10_11 2.3_4.2 1 2 2 2 2 1 120 10_12 2.3_4.3 1 2 2 2 2 1 121 11_1 3.3_1.1 2 1 2 1 1 1 122 11_2 3.3_1.2 2 1 2 1 1 1 123 11_3 3.3_1.3 2 1 2 1 1 1 124 11_4 3.3_2.1 2 1 2 1 2 2 125 11_5 3.3_2.2 2 1 2 1 2 2 126 11_6 3.3_2.3 2 1 2 1 2 2 127 11_7 3.3_3.1 2 1 2 2 1 2 128 11_8 3.3_3.2 2 1 2 2 1 2 129 11_9 3.3_3.3 2 1 2 2 1 2 130 11_10 3.3_4.1 2 1 2 2 2 1 131 11_11 3.3_4.2 2 1 2 2 2 1 132 11_12 3.3_4.3 2 1 2 2 2 1 133 12_1 4.3_1.1 2 2 1 1 1 1 134 12_2 4.3_1.2 2 2 1 1 1 1 135 12_3 4.3_1.3 2 2 1 1 1 1 136 12_4 4.3_2.1 2 2 1 1 2 2 137 12_5 4.3_2.2 2 2 1 1 2 2 138 12_6 4.3_2.3 2 2 1 1 2 2 139 12_7 4.3_3.1 2 2 1 2 1 2 140 12_8 4.3_3.2 2 2 1 2 1 2 141 12_9 4.3_3.3 2 2 1 2 1 2 142 12_10 4.3_4.1 2 2 1 2 2 1 143 12_11 4.3_4.2 2 2 1 2 2 1 144 12_12 4.3_4.3 2 2 1 2 2 1 class=design, type= crossed NOTE: columns run.no and run.no.std.rp are annotation, not part of the data frame > summary(cross6) Multi-step-call: $original $original[[1]] oa.design(nlevels = c(2, 2, 2), factor.names = Letters[7:9], repl = 3, randomize = FALSE) $original[[2]] oa.design(nlevels = c(2, 2, 2), repl = 3, factor.names = Letters[10:12], repeat.only = TRUE, randomize = FALSE) $modify cross.design(oa4rep, oa4reprepeat.only, randomize = FALSE) Experimental design of type crossed 16 runs 9 measurements per run (not proper replications) Factor settings (scale ends): G H J K L M 1 1 1 1 1 1 1 2 2 2 2 2 2 2 > design.info(cross2) $type [1] "crossed" $nruns [1] 192 $nfactors [1] 9 $nlevels [1] 2 6 2 2 2 2 2 2 2 $generating.oa [1] "L12.2.2.6.1" "L4.2.3" "L4.2.3" $origin [1] "Kuhfeld collection" "Kuhfeld collection" "Kuhfeld collection" $residual.df [1] 4 0 0 $factor.names $factor.names$first [1] 1 2 $factor.names$second [1] 1 2 3 4 5 6 $factor.names$third [1] 1 2 $factor.names$G [1] 1 2 $factor.names$H [1] 1 2 $factor.names$J [1] 1 2 $factor.names$D [1] 1 2 $factor.names$E [1] 1 2 $factor.names$F [1] 1 2 $replications [1] 3 $repeat.only [1] FALSE $randomize [1] FALSE $creator $creator$original $creator$original[[1]] oa.design(nlevels = c(2, 6, 2), factor.names = c("first", "second", "third"), randomize = FALSE) $creator$original[[2]] oa.design(nlevels = c(2, 2, 2), factor.names = Letters[7:9], repl = 3, randomize = FALSE) $creator$original[[3]] oa.design(nlevels = c(2, 2, 2), factor.names = Letters[4:6], randomize = FALSE) $creator$modify cross.design(oa12, oa4rep, oa4, randomize = FALSE) $cross.nruns [1] 12 4 4 $cross.replications [1] 1 3 1 $cross.nfactors [1] 3 3 3 $cross.types [1] "oa" "oa" "oa" $cross.randomize [1] FALSE FALSE FALSE $cross.seed $cross.seed[[1]] NULL $cross.seed[[2]] NULL $cross.seed[[3]] NULL $seed NULL $cross.repeat.only [1] FALSE FALSE FALSE $cross.selected.columns $cross.selected.columns[[1]] [1] 1 3 2 $cross.selected.columns[[2]] [1] 1 2 3 $cross.selected.columns[[3]] [1] 1 2 3 $cross.nlevels $cross.nlevels[[1]] [1] 2 6 2 $cross.nlevels[[2]] [1] 2 2 2 $cross.nlevels[[3]] [1] 2 2 2 > factor.names(cross2) <- Letters[1:design.info(cross2)$nfactors] > summary.data.frame(cross2) A B C D E F G H J 1:288 1:96 1:288 1:288 1:288 1:288 1:288 1:288 1:288 2:288 2:96 2:288 2:288 2:288 2:288 2:288 2:288 2:288 3:96 4:96 5:96 6:96 > > param1 <- param.design(oa12, oa4, direction="wide") Warning message: In param.design(oa12, oa4, direction = "wide") : inner array should be randomized > param1 run.no run.no.std.rp first second third y.1 y.2 y.3 y.4 1 1 1 1 1 1 NA NA NA NA 2 2 2 1 3 1 NA NA NA NA 3 3 3 1 5 1 NA NA NA NA 4 4 4 1 2 2 NA NA NA NA 5 5 5 1 4 2 NA NA NA NA 6 6 6 1 6 2 NA NA NA NA 7 7 7 2 2 1 NA NA NA NA 8 8 8 2 4 1 NA NA NA NA 9 9 9 2 6 1 NA NA NA NA 10 10 10 2 1 2 NA NA NA NA 11 11 11 2 3 2 NA NA NA NA 12 12 12 2 5 2 NA NA NA NA class=design, type= oa.paramwide NOTE: columns run.no and run.no.std.rp are annotation, not part of the data frame Outer array: D E F 1 1 1 1 2 1 2 2 3 2 1 2 4 2 2 1 > summary(param1) Multi-step-call: $original $original[[1]] oa.design(nlevels = c(2, 6, 2), factor.names = c("first", "second", "third"), randomize = FALSE) $original[[2]] oa.design(nlevels = c(2, 2, 2), factor.names = Letters[4:6], randomize = FALSE) $modify cross.design(inner, outer, randomize = FALSE) Experimental design of type oa.paramwide 12 runs Factor settings (scale ends): first second third 1 1 1 1 2 2 2 2 3 3 4 4 5 5 6 6 Responses: y 1 y.1 2 y.2 3 y.3 4 y.4 Outer array: D E F 1 1 1 1 2 1 2 2 3 2 1 2 4 2 2 1 The design itself: run.no run.no.std.rp first second third y.1 y.2 y.3 y.4 1 1 1 1 1 1 NA NA NA NA 2 2 2 1 3 1 NA NA NA NA 3 3 3 1 5 1 NA NA NA NA 4 4 4 1 2 2 NA NA NA NA 5 5 5 1 4 2 NA NA NA NA 6 6 6 1 6 2 NA NA NA NA 7 7 7 2 2 1 NA NA NA NA 8 8 8 2 4 1 NA NA NA NA 9 9 9 2 6 1 NA NA NA NA 10 10 10 2 1 2 NA NA NA NA 11 11 11 2 3 2 NA NA NA NA 12 12 12 2 5 2 NA NA NA NA class=design, type= oa.paramwide NOTE: columns run.no and run.no.std.rp are annotation, not part of the data frame Outer array: D E F 1 1 1 1 2 1 2 2 3 2 1 2 4 2 2 1 > > proc.time() user system elapsed 0.57 0.14 0.68