R Under development (unstable) (2024-01-07 r85787 ucrt) -- "Unsuffered Consequences" Copyright (C) 2024 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. > library("compositions") Welcome to compositions, a package for compositional data analysis. Find an intro with "? compositions" Attaching package: 'compositions' The following objects are masked from 'package:stats': anova, cor, cov, dist, var The following object is masked from 'package:graphics': segments The following objects are masked from 'package:base': %*%, norm, scale, scale.default > set.seed(1334345) > data(SimulatedAmounts) > par(pch=20) > mydata <- simulateMissings(sa.groups5,dl=0.01,knownlimit=TRUE,MAR=0.05,MNARprob=0.05,SZprob=0.05) > > > cdata <- acomp(mydata) Warning message: In acomp(mydata) : Negative values in composition are used as detection limits > cdata Cu Zn Pb Cd Co [1,] "0.025707633" "0.03643146" "0.8941291179" " 1.043489e-02" " 3.329690e-02" [2,] "0.002823595" "0.03806539" "0.6767266974" " 5.233545e-02" " 2.300489e-01" [3,] "0.016021341" "0.10961981" "0.8743588467" "<5.269740e-04" "<5.269740e-04" [4,] "0.036751418" " MAR" "0.9590864323" " 1.212074e-03" " 2.950076e-03" [5,] "0.031228176" "0.06478130" "0.9038356221" " MNAR" " 1.549035e-04" [6,] "0.094265333" "0.13128330" "0.7744513679" " SZ" " MAR" [7,] "0.045414210" "0.21676984" "0.7350501198" " 9.575688e-04" " 1.808258e-03" [8,] "0.015051926" "0.13014259" "0.8495954565" " 1.774087e-03" " 3.435944e-03" [9,] "0.023557989" "0.08628553" "0.8894437402" " MAR" " 7.127360e-04" [10,] "0.046366661" "0.18292516" "0.7459267972" " 4.855792e-03" " 1.992559e-02" [11,] "0.030384679" "0.12097095" "0.8484870671" "<3.796757e-05" " 1.572995e-04" [12,] "0.004677034" "0.01131463" "0.9808424318" " 8.244257e-04" " 2.341481e-03" [13,] "0.007311120" "0.01762118" "0.9750676966" " MNAR" "<9.384200e-05" [14,] "0.015242934" "0.06559599" "0.9191610774" " MNAR" " SZ" [15,] "0.025594023" "0.04567862" "0.9246102010" " 1.194793e-03" " 2.922366e-03" [16,] "0.296443253" "0.31615112" "0.2927788273" " 3.582794e-02" " 5.879886e-02" [17,] "0.248760013" "0.38666433" " MAR" " MAR" " 3.645757e-01" [18,] "0.042507679" "0.07340114" "0.8792025014" " 8.319839e-04" " 4.056693e-03" [19,] "0.038913897" "0.10718908" "0.8440090605" " 2.971185e-03" " 6.916774e-03" [20,] "0.169898872" "0.41153637" "0.3192338168" " 3.960814e-02" " 5.972281e-02" [21,] "0.346366612" "0.59914466" "0.0544887250" " MNAR" "<2.028137e-04" [22,] " MNAR" "0.22656313" "0.7725473225" " MNAR" " 8.895456e-04" [23,] "0.403340691" "0.57379224" "0.0221005903" " 7.664739e-04" " SZ" [24,] " SZ" "0.99142126" " SZ" " 6.444118e-03" " 2.134621e-03" [25,] "0.259407999" "0.66397782" "0.0726755686" " MAR" " 3.938611e-03" [26,] "0.237816617" "0.58186649" "0.1791736366" " 1.143255e-03" " MNAR" [27,] "0.814775993" " SZ" "0.1721117021" " 1.311230e-02" " MNAR" [28,] "0.073518873" "0.29171359" "0.6328466335" " MNAR" " 1.920908e-03" [29,] "0.193080981" "0.32553302" "0.4813860022" "<2.664045e-04" "<2.664045e-04" [30,] "0.137161507" "0.49346235" "0.1262147251" " 1.962837e-01" " 4.687772e-02" [31,] "0.111117171" "0.86082957" "0.0267072309" " SZ" " 1.346028e-03" [32,] " MAR" "0.65975341" "0.2759764549" " 4.711820e-02" " 1.715194e-02" [33,] "0.017059650" "0.10398122" "0.8751200168" " 3.193523e-03" " 6.455902e-04" [34,] " MAR" "0.55301265" "0.4465040678" " 4.832814e-04" "<1.649183e-04" [35,] "0.179542248" "0.59951369" "0.2209440588" " MAR" "<3.945291e-04" [36,] "0.189886426" "0.32240436" "0.4719551740" " 1.035730e-02" " 5.396731e-03" [37,] "0.114140952" "0.49657931" "0.3845670172" " 2.854052e-03" " 1.858667e-03" [38,] "0.165514761" "0.11752629" "0.7169589481" "<9.907019e-05" "<9.907019e-05" [39,] "0.197920058" "0.63609342" "0.1659865170" " MAR" " MAR" [40,] "0.317223962" "0.60869330" " SZ" " 7.408274e-02" " SZ" [41,] "0.179951965" "0.80253489" "0.0134339418" " 3.617760e-03" " 4.614417e-04" [42,] " MAR" "0.99798599" "0.0020140133" " MNAR" " MNAR" [43,] "0.098303161" "0.78001715" "0.1179230373" " 3.035157e-03" " 7.214930e-04" [44,] "0.056530869" "0.33612559" "0.0142737775" " 5.930698e-01" " SZ" [45,] "0.042824195" "0.93975590" "0.0018639968" " 1.369969e-02" " 1.856224e-03" [46,] "0.045973462" "0.94622012" "0.0071749009" " 5.435390e-04" " 8.798179e-05" [47,] " SZ" "0.94095796" "0.0165693013" " 4.247274e-02" " MNAR" [48,] "0.041319850" "0.84287121" "0.0131916717" " SZ" " 1.026173e-01" [49,] "0.038874054" "0.94001457" "0.0079907027" " 1.157016e-02" " 1.550513e-03" [50,] "0.132514868" "0.86719219" "0.0002333100" " 5.963531e-05" "<1.266900e-05" [51,] "0.079504084" "0.80237211" "0.0134767533" " 8.853465e-02" " 1.611240e-02" [52,] "0.047088550" "0.94999577" "0.0008309680" " 1.914018e-03" " 1.706902e-04" [53,] "0.101504083" "0.89236770" "0.0056924052" " 3.524936e-04" " 8.332227e-05" [54,] "0.159039041" "0.83500845" "0.0059525091" " SZ" " MNAR" [55,] "0.071745979" "0.44722880" "0.0080950802" " 4.131260e-01" " 5.980414e-02" [56,] "0.115202196" "0.87377137" "0.0003904268" " 9.659659e-03" " 9.763446e-04" [57,] "0.081108589" "0.91802503" "0.0008055710" " 6.080595e-05" " MNAR" [58,] "0.033306898" "0.95483424" "0.0118588628" " SZ" "<8.889540e-05" [59,] "0.041409246" "0.93038002" " MAR" " 2.445150e-02" " 3.759227e-03" [60,] "0.294617957" " MAR" "0.0082785534" " 6.053351e-01" " 9.176842e-02" attr(,"class") [1] "acomp" > mean(cdata) Cu Zn Pb Cd Co "0.136537179" "0.650471225" "0.193404813" "0.012412507" "0.007174275" attr(,"class") [1] "acomp" Warning message: In acomp(x) : Negative values in composition are used as detection limits > mean(acomp(sa.groups5)) Cu Zn Pb Cd Co "0.141647429" "0.659658588" "0.190494272" "0.005344234" "0.002855477" attr(,"class") [1] "acomp" > plot(acomp(sa.groups5)) > plot(mean(cdata),add=T,col="red") Warning message: In acomp(x) : Negative values in composition are used as detection limits > plot(mean(acomp(sa.groups5)),add=T,col="green") > mean(cdata - mean(cdata)) Cu Zn Pb Cd Co " 0.2" " 0.2" " 0.2" " 0.2" " 0.2" attr(,"class") [1] "acomp" Warning messages: 1: In acomp(x) : Negative values in composition are used as detection limits 2: In acomp(gsi.div(x, y)) : Negative values in composition are used as detection limits 3: In acomp(x) : Negative values in composition are used as detection limits > mm <-mean(cdata) Warning message: In acomp(x) : Negative values in composition are used as detection limits > erg <-var(cdata) > print(erg) Cu Zn Pb Cd Co Cu 1.4584600 1.65184942 -1.3766795 -0.33655679 -1.3970731 Zn 1.6518494 2.68214514 -2.5332217 0.03317017 -1.8339431 Pb -1.3766795 -2.53322167 5.4296947 -2.08907090 0.5692774 Cd -0.3365568 0.03317017 -2.0890709 1.63133485 0.7611227 Co -1.3970731 -1.83394307 0.5692774 0.76112267 1.9006161 > svd(erg) $d [1] 8.412440e+00 4.201802e+00 3.119081e-01 1.761007e-01 4.592042e-16 $u [,1] [,2] [,3] [,4] [,5] [1,] -0.3075737 0.3424609 0.6985826 -0.3163878 0.4472136 [2,] -0.4997854 0.3365634 -0.4535459 0.4808698 0.4472136 [3,] 0.7465851 0.4143280 -0.2251489 -0.1423061 0.4472136 [4,] -0.1891317 -0.5408317 -0.3672873 -0.5803708 0.4472136 [5,] 0.2499058 -0.5525206 0.3473995 0.5581950 0.4472136 $v [,1] [,2] [,3] [,4] [,5] [1,] -0.3075737 0.3424609 0.6985826 -0.3163878 -0.4472136 [2,] -0.4997854 0.3365634 -0.4535459 0.4808698 -0.4472136 [3,] 0.7465851 0.4143280 -0.2251489 -0.1423061 -0.4472136 [4,] -0.1891317 -0.5408317 -0.3672873 -0.5803708 -0.4472136 [5,] 0.2499058 -0.5525206 0.3473995 0.5581950 -0.4472136 > ellipses(mm,erg) > ellipses(mean(acomp(sa.groups5)),var(acomp(sa.groups5))) > > cdata <- acomp(mydata) Warning message: In acomp(mydata) : Negative values in composition are used as detection limits > plot(cdata) There were 50 or more warnings (use warnings() to see the first 50) > plot(mean(cdata),add=T,col="blue") There were 50 or more warnings (use warnings() to see the first 50) > plot(mean(acomp(sa.groups5)),add=T,col="green") There were 50 or more warnings (use warnings() to see the first 50) > mean(cdata - mean(cdata)) Cu Zn Pb Cd Co " 0.2" " 0.2" " 0.2" " 0.2" " 0.2" attr(,"class") [1] "acomp" Warning messages: 1: In acomp(x) : Negative values in composition are used as detection limits 2: In acomp(gsi.div(x, y)) : Negative values in composition are used as detection limits 3: In acomp(x) : Negative values in composition are used as detection limits > mm <-mean(cdata) Warning message: In acomp(x) : Negative values in composition are used as detection limits > #erg <-var(cdata) > svd(erg) $d [1] 8.412440e+00 4.201802e+00 3.119081e-01 1.761007e-01 4.592042e-16 $u [,1] [,2] [,3] [,4] [,5] [1,] -0.3075737 0.3424609 0.6985826 -0.3163878 0.4472136 [2,] -0.4997854 0.3365634 -0.4535459 0.4808698 0.4472136 [3,] 0.7465851 0.4143280 -0.2251489 -0.1423061 0.4472136 [4,] -0.1891317 -0.5408317 -0.3672873 -0.5803708 0.4472136 [5,] 0.2499058 -0.5525206 0.3473995 0.5581950 0.4472136 $v [,1] [,2] [,3] [,4] [,5] [1,] -0.3075737 0.3424609 0.6985826 -0.3163878 -0.4472136 [2,] -0.4997854 0.3365634 -0.4535459 0.4808698 -0.4472136 [3,] 0.7465851 0.4143280 -0.2251489 -0.1423061 -0.4472136 [4,] -0.1891317 -0.5408317 -0.3672873 -0.5803708 -0.4472136 [5,] 0.2499058 -0.5525206 0.3473995 0.5581950 -0.4472136 > ellipses(mm,erg) There were 50 or more warnings (use warnings() to see the first 50) > ellipses(mm,erg,r=2) There were 50 or more warnings (use warnings() to see the first 50) > > > > #cdata <- rcomp(mydata) > #cdata > > #mean(cdata) > #mean(rcomp(sa.groups5)) > #plot(rcomp(sa.groups5)) > #plot(mean(cdata),add=T,col="red",pch=20) > #plot(mean(rcomp(sa.groups5)),add=T,col="green",pch=20) > #mean(cdata - mean(cdata)) # Nonsense because the difference is noncompositional > > > cdata <- aplus(mydata) > cdata Cu Zn Pb Cd Co [1,] " 2.32560998" " 3.2957280" " 80.8863102" " 0.94398005" " 3.01216337" [2,] " 0.05819293" " 0.7845092" " 13.9470095" " 1.07860821" " 4.74119583" [3,] " 0.30402525" " 2.0801748" " 16.5920669" "<0.01000000" "<0.01000000" [4,] " 2.90108035" " MAR" " 75.7082851" " 0.09567857" " 0.23287289" [5,] " 5.74951568" " 11.9270845" "166.4079616" " MNAR" " 0.02851976" [6,] " 3.09984060" " 4.3171470" " 25.4672180" " SZ" " MAR" [7,] " 2.95684364" " 14.1135236" " 47.8578897" " 0.06234571" " 0.11773265" [8,] " 3.06234225" " 26.4777503" "172.8517697" " 0.36094134" " 0.69904915" [9,] " 3.08324786" " 11.2929712" "116.4095761" " MAR" " 0.09328223" [10,] " 2.07666904" " 8.1928484" " 33.4085541" " 0.21748113" " 0.89242687" [11,] " 8.00279898" " 31.8616572" "223.4768193" "<0.01000000" " 0.04142996" [12,] " 0.79144603" " 1.9146573" "165.9778114" " 0.13950902" " 0.39622464" [13,] " 0.77908829" " 1.8777502" "103.9052563" " MNAR" "<0.01000000" [14,] " 0.41623431" " 1.7912103" " 25.0992607" " MNAR" " SZ" [15,] " 3.20107658" " 5.7130820" "115.6421587" " 0.14943429" " 0.36550397" [16,] " 8.12173391" " 8.6616754" " 8.0213387" " 0.98158755" " 1.61092791" [17,] " 3.34773718" " 5.2036119" " MAR" " MAR" " 4.90634916" [18,] " 3.90181325" " 6.7375485" " 80.7026878" " 0.07636845" " 0.37236699" [19,] " 2.89945563" " 7.9866066" " 62.8867060" " 0.22138159" " 0.51536549" [20,] " 6.56268069" " 15.8964079" " 12.3310390" " 1.52994294" " 2.30691173" [21,] " 17.07806483" " 29.5416217" " 2.6866388" " MNAR" "<0.01000000" [22,] " MNAR" " 4.3183778" " 14.7250399" " MNAR" " 0.01695507" [23,] " 20.54410986" " 29.2260393" " 1.1256909" " 0.03904026" " SZ" [24,] " SZ" " 35.4935764" " SZ" " 0.23070396" " 0.07642094" [25,] " 16.10576105" " 41.2241264" " 4.5121791" " MAR" " 0.24453498" [26,] " 22.77938611" " 55.7343791" " 17.1622383" " 0.10950726" " MNAR" [27,] " 23.58064507" " SZ" " 4.9811298" " 0.37948663" " MNAR" [28,] " 1.83244165" " 7.2708966" " 15.7735623" " MNAR" " 0.04787820" [29,] " 7.24766118" " 12.2194998" " 18.0697375" "<0.01000000" "<0.01000000" [30,] " 7.63069488" " 27.4527504" " 7.0216935" " 10.91983495" " 2.60794446" [31,] " 26.62950316" " 206.2999218" " 6.4004535" " SZ" " 0.32257893" [32,] " MAR" " 22.4674773" " 9.3982004" " 1.60457988" " 0.58409817" [33,] " 0.81109644" " 4.9437589" " 41.6073436" " 0.15183519" " 0.03069441" [34,] " MAR" " 33.5325182" " 27.0742554" " 0.02930429" "<0.01000000" [35,] " 4.55079806" " 15.1956755" " 5.6001961" " MAR" "<0.01000000" [36,] " 4.97063214" " 8.4395369" " 12.3543088" " 0.27112180" " 0.14126952" [37,] " 2.20930598" " 9.6117618" " 7.4436580" " 0.05524286" " 0.03597626" [38,] " 16.70681690" " 11.8629313" " 72.3687834" "<0.01000000" "<0.01000000" [39,] " 14.48399049" " 46.5499617" " 12.1470616" " MAR" " MAR" [40,] " 3.66342116" " 7.0294182" " SZ" " 0.85553525" " SZ" [41,] " 10.95300809" " 48.8473197" " 0.8176742" " 0.22019960" " 0.02808624" [42,] " MAR" " 615.2700400" " 1.2416628" " MNAR" " MNAR" [43,] " 3.89677070" " 30.9201450" " 4.6745093" " 0.12031465" " 0.02860023" [44,] " 19.81539452" " 117.8198968" " 5.0032936" "207.88485371" " SZ" [45,] " 13.87302392" " 304.4366853" " 0.6038472" " 4.43805373" " 0.60132928" [46,] " 11.75363784" " 241.9119212" " 1.8343449" " 0.13896191" " 0.02249354" [47,] " SZ" " 80.2172745" " 1.4125437" " 3.62082849" " MNAR" [48,] " 5.03541513" " 102.7159212" " 1.6075940" " SZ" "12.50538258" [49,] " 5.79177975" " 140.0511873" " 1.1905213" " 1.72381849" " 0.23100839" [50,] "104.59774771" " 684.4994158" " 0.1841582" " 0.04707184" "<0.01000000" [51,] " 6.42154600" " 64.8076064" " 1.0885176" " 7.15094526" " 1.30139867" [52,] " 60.77708084" "1226.1573067" " 1.0725284" " 2.47041878" " 0.22030942" [53,] " 66.57712168" " 585.3091893" " 3.7336819" " 0.23120261" " 0.05465156" [54,] " 16.86023960" " 88.5219277" " 0.6310446" " SZ" " MNAR" [55,] " 6.27202842" " 39.0967097" " 0.7076713" " 36.11544583" " 5.22807356" [56,] " 58.91700620" " 446.8664238" " 0.1996731" " 4.94016780" " 0.49932471" [57,] " 33.98383856" " 384.6450147" " 0.3375277" " 0.02547720" " MNAR" [58,] " 3.74675153" " 107.4109817" " 1.3340243" " SZ" "<0.01000000" [59,] " 7.16929149" " 161.0791359" " MAR" " 4.23335288" " 0.65084480" [60,] " 26.39789963" " MAR" " 0.7417621" " 54.23829107" " 8.22249084" attr(,"class") [1] "aplus" > mean(cdata) [1] " 5.9688392" "26.9654212" " 8.2389925" " 0.5742044" " 0.3264231" attr(,"class") [1] "aplus" > mean(aplus(sa.groups5)) Cu Zn Pb Cd Co " 6.1194322" "28.4984768" " 8.2297065" " 0.2308808" " 0.1233619" attr(,"class") [1] "aplus" > plot(aplus(sa.groups5)) > plot(mean(cdata),add=T,col="red",pch=20) > plot(mean(aplus(sa.groups5)),add=T,col="green",pch=20) > mean(cdata - mean(cdata)) [1] " 1" " 1" " 1" " 1" " 1" attr(,"class") [1] "aplus" > > cdata <- rplus(mydata) > cdata Cu Zn Pb Cd Co [1,] " 2.32560998" " 3.2957280" " 80.8863102" " 0.94398005" " 3.01216337" [2,] " 0.05819293" " 0.7845092" " 13.9470095" " 1.07860821" " 4.74119583" [3,] " 0.30402525" " 2.0801748" " 16.5920669" "<0.01000000" "<0.01000000" [4,] " 2.90108035" " MAR" " 75.7082851" " 0.09567857" " 0.23287289" [5,] " 5.74951568" " 11.9270845" "166.4079616" " MNAR" " 0.02851976" [6,] " 3.09984060" " 4.3171470" " 25.4672180" " SZ" " MAR" [7,] " 2.95684364" " 14.1135236" " 47.8578897" " 0.06234571" " 0.11773265" [8,] " 3.06234225" " 26.4777503" "172.8517697" " 0.36094134" " 0.69904915" [9,] " 3.08324786" " 11.2929712" "116.4095761" " MAR" " 0.09328223" [10,] " 2.07666904" " 8.1928484" " 33.4085541" " 0.21748113" " 0.89242687" [11,] " 8.00279898" " 31.8616572" "223.4768193" "<0.01000000" " 0.04142996" [12,] " 0.79144603" " 1.9146573" "165.9778114" " 0.13950902" " 0.39622464" [13,] " 0.77908829" " 1.8777502" "103.9052563" " MNAR" "<0.01000000" [14,] " 0.41623431" " 1.7912103" " 25.0992607" " MNAR" " SZ" [15,] " 3.20107658" " 5.7130820" "115.6421587" " 0.14943429" " 0.36550397" [16,] " 8.12173391" " 8.6616754" " 8.0213387" " 0.98158755" " 1.61092791" [17,] " 3.34773718" " 5.2036119" " MAR" " MAR" " 4.90634916" [18,] " 3.90181325" " 6.7375485" " 80.7026878" " 0.07636845" " 0.37236699" [19,] " 2.89945563" " 7.9866066" " 62.8867060" " 0.22138159" " 0.51536549" [20,] " 6.56268069" " 15.8964079" " 12.3310390" " 1.52994294" " 2.30691173" [21,] " 17.07806483" " 29.5416217" " 2.6866388" " MNAR" "<0.01000000" [22,] " MNAR" " 4.3183778" " 14.7250399" " MNAR" " 0.01695507" [23,] " 20.54410986" " 29.2260393" " 1.1256909" " 0.03904026" " SZ" [24,] " SZ" " 35.4935764" " SZ" " 0.23070396" " 0.07642094" [25,] " 16.10576105" " 41.2241264" " 4.5121791" " MAR" " 0.24453498" [26,] " 22.77938611" " 55.7343791" " 17.1622383" " 0.10950726" " MNAR" [27,] " 23.58064507" " SZ" " 4.9811298" " 0.37948663" " MNAR" [28,] " 1.83244165" " 7.2708966" " 15.7735623" " MNAR" " 0.04787820" [29,] " 7.24766118" " 12.2194998" " 18.0697375" "<0.01000000" "<0.01000000" [30,] " 7.63069488" " 27.4527504" " 7.0216935" " 10.91983495" " 2.60794446" [31,] " 26.62950316" " 206.2999218" " 6.4004535" " SZ" " 0.32257893" [32,] " MAR" " 22.4674773" " 9.3982004" " 1.60457988" " 0.58409817" [33,] " 0.81109644" " 4.9437589" " 41.6073436" " 0.15183519" " 0.03069441" [34,] " MAR" " 33.5325182" " 27.0742554" " 0.02930429" "<0.01000000" [35,] " 4.55079806" " 15.1956755" " 5.6001961" " MAR" "<0.01000000" [36,] " 4.97063214" " 8.4395369" " 12.3543088" " 0.27112180" " 0.14126952" [37,] " 2.20930598" " 9.6117618" " 7.4436580" " 0.05524286" " 0.03597626" [38,] " 16.70681690" " 11.8629313" " 72.3687834" "<0.01000000" "<0.01000000" [39,] " 14.48399049" " 46.5499617" " 12.1470616" " MAR" " MAR" [40,] " 3.66342116" " 7.0294182" " SZ" " 0.85553525" " SZ" [41,] " 10.95300809" " 48.8473197" " 0.8176742" " 0.22019960" " 0.02808624" [42,] " MAR" " 615.2700400" " 1.2416628" " MNAR" " MNAR" [43,] " 3.89677070" " 30.9201450" " 4.6745093" " 0.12031465" " 0.02860023" [44,] " 19.81539452" " 117.8198968" " 5.0032936" "207.88485371" " SZ" [45,] " 13.87302392" " 304.4366853" " 0.6038472" " 4.43805373" " 0.60132928" [46,] " 11.75363784" " 241.9119212" " 1.8343449" " 0.13896191" " 0.02249354" [47,] " SZ" " 80.2172745" " 1.4125437" " 3.62082849" " MNAR" [48,] " 5.03541513" " 102.7159212" " 1.6075940" " SZ" "12.50538258" [49,] " 5.79177975" " 140.0511873" " 1.1905213" " 1.72381849" " 0.23100839" [50,] "104.59774771" " 684.4994158" " 0.1841582" " 0.04707184" "<0.01000000" [51,] " 6.42154600" " 64.8076064" " 1.0885176" " 7.15094526" " 1.30139867" [52,] " 60.77708084" "1226.1573067" " 1.0725284" " 2.47041878" " 0.22030942" [53,] " 66.57712168" " 585.3091893" " 3.7336819" " 0.23120261" " 0.05465156" [54,] " 16.86023960" " 88.5219277" " 0.6310446" " SZ" " MNAR" [55,] " 6.27202842" " 39.0967097" " 0.7076713" " 36.11544583" " 5.22807356" [56,] " 58.91700620" " 446.8664238" " 0.1996731" " 4.94016780" " 0.49932471" [57,] " 33.98383856" " 384.6450147" " 0.3375277" " 0.02547720" " MNAR" [58,] " 3.74675153" " 107.4109817" " 1.3340243" " SZ" "<0.01000000" [59,] " 7.16929149" " 161.0791359" " MAR" " 4.23335288" " 0.65084480" [60,] " 26.39789963" " MAR" " 0.7417621" " 54.23829107" " 8.22249084" attr(,"class") [1] "rplus" > mean(cdata) [1] " 12.809024" "107.743522" " 32.007732" " 7.252143" " 1.039128" attr(,"class") [1] "rplus" Warning message: In sumMissingProjector.rplus(.orig) : sumMissingProjector.rplus: There is no established theory available for missings in nonrelative positive geometry. Results are experimental. > mean(rplus(sa.groups5)) Cu Zn Pb Cd Co " 13.183423" "121.515630" " 31.862701" " 6.996818" " 1.399201" attr(,"class") [1] "rplus" > plot(rplus(sa.groups5)) > plot(mean(cdata),add=T,col="red",pch=20) Warning message: In sumMissingProjector.rplus(.orig) : sumMissingProjector.rplus: There is no established theory available for missings in nonrelative positive geometry. Results are experimental. > plot(mean(rplus(sa.groups5)),add=T,col="green",pch=20) > mean(cdata - mean(cdata)) # Nonsense because the difference is non compositonal Warning message: In sumMissingProjector.rplus(.orig) : sumMissingProjector.rplus: There is no established theory available for missings in nonrelative positive geometry. Results are experimental. > > > plot(acomp(mydata)) There were 50 or more warnings (use warnings() to see the first 50) > plot(aplus(mydata)) There were 40 warnings (use warnings() to see them) > plot(rcomp(mydata)) There were 40 warnings (use warnings() to see them) > plot(rplus(mydata)) There were 40 warnings (use warnings() to see them) > > boxplot(acomp(mydata)) There were 50 or more warnings (use warnings() to see the first 50) > boxplot(aplus(mydata)) Warning messages: 1: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 4 does not name a graphical parameter 2: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 5 does not name a graphical parameter 3: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 4 does not name a graphical parameter 4: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 5 does not name a graphical parameter 5: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 4 does not name a graphical parameter 6: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 5 does not name a graphical parameter 7: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 4 does not name a graphical parameter 8: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 5 does not name a graphical parameter 9: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 4 does not name a graphical parameter 10: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 5 does not name a graphical parameter > boxplot(rcomp(mydata)) There were 41 warnings (use warnings() to see them) > boxplot(rplus(mydata)) Warning messages: 1: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 4 does not name a graphical parameter 2: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 5 does not name a graphical parameter 3: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 4 does not name a graphical parameter 4: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 5 does not name a graphical parameter 5: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 4 does not name a graphical parameter 6: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 5 does not name a graphical parameter 7: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 4 does not name a graphical parameter 8: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 5 does not name a graphical parameter 9: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 4 does not name a graphical parameter 10: In par(xlog = FALSE, ylog = FALSE, xpd = xpd, par(), opar) : argument 5 does not name a graphical parameter > > barplot(acomp(mydata)) Warning message: In acomp(mydata) : Negative values in composition are used as detection limits > barplot(aplus(mydata)) > barplot(rcomp(mydata)) > barplot(rplus(mydata)) > > proc.time() user system elapsed 4.84 0.60 5.43