R Under development (unstable) (2024-08-17 r87027 ucrt) -- "Unsuffered Consequences"
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> ## VT::15.09.2013 - this will render the output independent
> ## from the version of the package
> suppressPackageStartupMessages(library(rrcov))
> library(MASS)
>
> ## VT::14.01.2020
> ## On some platforms minor differences are shown - use
> ## IGNORE_RDIFF_BEGIN
> ## IGNORE_RDIFF_END
>
> dodata <- function(method) {
+
+ options(digits = 5)
+ set.seed(101) # <<-- sub-sampling algorithm now based on R's RNG and seed
+
+ tmp <- sys.call()
+ cat("\nCall: ", deparse(substitute(tmp)),"\n")
+ cat("===================================================\n")
+
+ cat("\nData: ", "hemophilia\n")
+ data(hemophilia)
+ show(rlda <- Linda(as.factor(gr)~., data=hemophilia, method=method))
+ show(predict(rlda))
+
+ cat("\nData: ", "anorexia\n")
+ data(anorexia)
+ show(rlda <- Linda(Treat~., data=anorexia, method=method))
+ show(predict(rlda))
+
+ cat("\nData: ", "Pima\n")
+ data(Pima.tr)
+ show(rlda <- Linda(type~., data=Pima.tr, method=method))
+ show(predict(rlda))
+
+ cat("\nData: ", "Forest soils\n")
+ data(soil)
+ soil1983 <- soil[soil$D == 0, -2] # only 1983, remove column D (always 0)
+
+ ## This will not work within the function, of course
+ ## - comment it out
+ ## IGNORE_RDIFF_BEGIN
+ rlda <- Linda(F~., data=soil1983, method=method)
+ ## show(rlda)
+ ## IGNORE_RDIFF_END
+ show(predict(rlda))
+
+ cat("\nData: ", "Raven and Miller diabetes data\n")
+ data(diabetes)
+ show(rlda <- Linda(group~insulin+glucose+sspg, data=diabetes, method=method))
+ show(predict(rlda))
+
+ cat("\nData: ", "iris\n")
+ data(iris)
+ if(method != "mcdA")
+ {
+ show(rlda <- Linda(Species~., data=iris, method=method, l1med=TRUE))
+ show(predict(rlda))
+ }
+
+ cat("\nData: ", "crabs\n")
+ data(crabs)
+ show(rlda <- Linda(sp~., data=crabs, method=method))
+ show(predict(rlda))
+
+ cat("\nData: ", "fish\n")
+ data(fish)
+ fish <- fish[-14,] # remove observation #14 containing missing value
+
+ # The height and width are calculated as percentages
+ # of the third length variable
+ fish[,5] <- fish[,5]*fish[,4]/100
+ fish[,6] <- fish[,6]*fish[,4]/100
+
+ ## There is one class with only 6 observations (p=6). Normally
+ ## Linda will fail, therefore use l1med=TRUE.
+ ## This works only for methods mcdB and mcdC
+
+ table(fish$Species)
+ if(method != "mcdA")
+ {
+ ## IGNORE_RDIFF_BEGIN
+ rlda <- Linda(Species~., data=fish, method=method, l1med=TRUE)
+ ## show(rlda)
+ ## IGNORE_RDIFF_END
+ show(predict(rlda))
+ }
+
+ cat("\nData: ", "pottery\n")
+ data(pottery)
+ show(rlda <- Linda(origin~., data=pottery, method=method))
+ show(predict(rlda))
+
+ cat("\nData: ", "olitos\n")
+ data(olitos)
+ if(method != "mcdA")
+ {
+ ## IGNORE_RDIFF_BEGIN
+ rlda <- Linda(grp~., data=olitos, method=method, l1med=TRUE)
+ ## show(rlda)
+ ## IGNORE_RDIFF_END
+ show(predict(rlda))
+ }
+
+ cat("===================================================\n")
+ }
>
>
> ## -- now do it:
> dodata(method="mcdA")
Call: dodata(method = "mcdA")
===================================================
Data: hemophilia
Call:
Linda(as.factor(gr) ~ ., data = hemophilia, method = method)
Prior Probabilities of Groups:
carrier normal
0.6 0.4
Group means:
AHFactivity AHFantigen
carrier -0.30795 -0.0059911
normal -0.12920 -0.0603000
Within-groups Covariance Matrix:
AHFactivity AHFantigen
AHFactivity 0.018036 0.011853
AHFantigen 0.011853 0.019185
Linear Coeficients:
AHFactivity AHFantigen
carrier -28.4029 17.2368
normal -8.5834 2.1602
Constants:
carrier normal
-4.8325 -1.4056
Apparent error rate 0.1333
Classification table
Predicted
Actual carrier normal
carrier 39 6
normal 4 26
Confusion matrix
Predicted
Actual carrier normal
carrier 0.867 0.133
normal 0.133 0.867
Data: anorexia
Call:
Linda(Treat ~ ., data = anorexia, method = method)
Prior Probabilities of Groups:
CBT Cont FT
0.40278 0.36111 0.23611
Group means:
Prewt Postwt
CBT 82.633 82.950
Cont 81.558 81.108
FT 84.331 94.762
Within-groups Covariance Matrix:
Prewt Postwt
Prewt 26.9291 3.3862
Postwt 3.3862 18.2368
Linear Coeficients:
Prewt Postwt
CBT 2.5563 4.0738
Cont 2.5284 3.9780
FT 2.5374 4.7250
Constants:
CBT Cont FT
-275.49 -265.45 -332.31
Apparent error rate 0.3889
Classification table
Predicted
Actual CBT Cont FT
CBT 16 5 8
Cont 11 15 0
FT 0 4 13
Confusion matrix
Predicted
Actual CBT Cont FT
CBT 0.552 0.172 0.276
Cont 0.423 0.577 0.000
FT 0.000 0.235 0.765
Data: Pima
Call:
Linda(type ~ ., data = Pima.tr, method = method)
Prior Probabilities of Groups:
No Yes
0.66 0.34
Group means:
npreg glu bp skin bmi ped age
No 1.8602 107.69 67.344 25.29 30.642 0.40777 24.667
Yes 5.3167 145.85 74.283 31.80 34.095 0.49533 37.883
Within-groups Covariance Matrix:
npreg glu bp skin bmi ped age
npreg 8.51105 -5.61029 4.756672 1.52732 0.82066 -0.010070 12.382693
glu -5.61029 656.11894 49.855724 16.67486 23.07833 -0.352475 17.724967
bp 4.75667 49.85572 119.426757 29.64563 12.90698 -0.049538 21.287178
skin 1.52732 16.67486 29.645632 113.19900 44.15972 -0.157594 6.741105
bmi 0.82066 23.07833 12.906985 44.15972 35.54164 0.038640 1.481520
ped -0.01007 -0.35247 -0.049538 -0.15759 0.03864 0.062664 -0.069636
age 12.38269 17.72497 21.287178 6.74110 1.48152 -0.069636 64.887154
Linear Coeficients:
npreg glu bp skin bmi ped age
No -0.45855 0.092789 0.45848 -0.30675 1.0075 6.2670 0.30749
Yes -0.22400 0.150013 0.44787 -0.26148 1.0015 8.2935 0.45187
Constants:
No Yes
-37.050 -51.586
Apparent error rate 0.22
Classification table
Predicted
Actual No Yes
No 107 25
Yes 19 49
Confusion matrix
Predicted
Actual No Yes
No 0.811 0.189
Yes 0.279 0.721
Data: Forest soils
Apparent error rate 0.3103
Classification table
Predicted
Actual 1 2 3
1 7 2 2
2 3 13 7
3 1 3 20
Confusion matrix
Predicted
Actual 1 2 3
1 0.636 0.182 0.182
2 0.130 0.565 0.304
3 0.042 0.125 0.833
Data: Raven and Miller diabetes data
Call:
Linda(group ~ insulin + glucose + sspg, data = diabetes, method = method)
Prior Probabilities of Groups:
normal chemical overt
0.52414 0.24828 0.22759
Group means:
insulin glucose sspg
normal 163.939 345.8 99.076
chemical 299.448 476.9 223.621
overt 95.958 1026.4 343.000
Within-groups Covariance Matrix:
insulin glucose sspg
insulin 7582.0 -1263.1 1095.8
glucose -1263.1 18952.4 4919.3
sspg 1095.8 4919.3 3351.2
Linear Coeficients:
insulin glucose sspg
normal 0.027694 0.023859 -0.014514
chemical 0.040288 0.022532 0.020479
overt 0.017144 0.048768 0.025158
Constants:
normal chemical overt
-6.3223 -15.0879 -31.6445
Apparent error rate 0.1862
Classification table
Predicted
Actual normal chemical overt
normal 69 7 0
chemical 13 23 0
overt 2 5 26
Confusion matrix
Predicted
Actual normal chemical overt
normal 0.908 0.092 0.000
chemical 0.361 0.639 0.000
overt 0.061 0.152 0.788
Data: iris
Data: crabs
Call:
Linda(sp ~ ., data = crabs, method = method)
Prior Probabilities of Groups:
B O
0.5 0.5
Group means:
sexM index FL RW CL CW BD
B 0.34722 27.333 14.211 12.253 30.397 35.117 12.765
O 0.56627 25.554 17.131 13.405 34.247 38.155 15.525
Within-groups Covariance Matrix:
sexM index FL RW CL CW BD
sexM 0.26391 0.76754 0.18606 -0.33763 0.65944 0.59857 0.28932
index 0.76754 191.38080 38.42685 26.32923 82.43953 91.89091 38.13688
FL 0.18606 38.42685 8.50147 5.68789 18.13749 20.30739 8.30920
RW -0.33763 26.32923 5.68789 4.95782 11.90225 13.61117 5.45814
CL 0.65944 82.43953 18.13749 11.90225 39.60115 44.10886 18.09504
CW 0.59857 91.89091 20.30739 13.61117 44.10886 49.42616 20.17554
BD 0.28932 38.13688 8.30920 5.45814 18.09504 20.17554 8.39525
Linear Coeficients:
sexM index FL RW CL CW BD
B 29.104 -2.4938 10.809 15.613 0.8320 -4.2978 -0.46788
O 42.470 -3.9361 26.427 22.857 2.8582 -17.1526 12.31048
Constants:
B O
-78.317 -159.259
Apparent error rate 0
Classification table
Predicted
Actual B O
B 100 0
O 0 100
Confusion matrix
Predicted
Actual B O
B 1 0
O 0 1
Data: fish
Data: pottery
Call:
Linda(origin ~ ., data = pottery, method = method)
Prior Probabilities of Groups:
Attic Eritrean
0.48148 0.51852
Group means:
SI AL FE MG CA TI
Attic 55.36 13.73 9.82 5.45 6.03 0.863
Eritrean 52.52 16.23 9.13 3.09 6.26 0.814
Within-groups Covariance Matrix:
SI AL FE MG CA TI
SI 13.5941404 2.986675 -0.651132 0.173577 -0.350984 -0.0051996
AL 2.9866747 1.622412 0.485167 0.712400 0.077443 0.0133306
FE -0.6511317 0.485167 1.065427 -0.403601 -1.936552 0.0576472
MG 0.1735766 0.712400 -0.403601 2.814948 3.262786 -0.0427129
CA -0.3509837 0.077443 -1.936552 3.262786 7.720320 -0.1454065
TI -0.0051996 0.013331 0.057647 -0.042713 -0.145406 0.0044093
Linear Coeficients:
SI AL FE MG CA TI
Attic 63.235 -196.99 312.92 7.28960 57.082 -1272.23
Eritrean 41.554 -123.49 201.47 -0.95431 43.616 -597.91
Constants:
Attic Eritrean
-1578.14 -901.13
Apparent error rate 0.1111
Classification table
Predicted
Actual Attic Eritrean
Attic 12 1
Eritrean 2 12
Confusion matrix
Predicted
Actual Attic Eritrean
Attic 0.923 0.077
Eritrean 0.143 0.857
Data: olitos
===================================================
> dodata(method="mcdB")
Call: dodata(method = "mcdB")
===================================================
Data: hemophilia
Call:
Linda(as.factor(gr) ~ ., data = hemophilia, method = method)
Prior Probabilities of Groups:
carrier normal
0.6 0.4
Group means:
AHFactivity AHFantigen
carrier -0.31456 -0.014775
normal -0.13582 -0.069084
Within-groups Covariance Matrix:
AHFactivity AHFantigen
AHFactivity 0.0125319 0.0086509
AHFantigen 0.0086509 0.0182424
Linear Coeficients:
AHFactivity AHFantigen
carrier -36.486 16.4923
normal -12.226 2.0107
Constants:
carrier normal
-6.1276 -1.6771
Apparent error rate 0.16
Classification table
Predicted
Actual carrier normal
carrier 38 7
normal 5 25
Confusion matrix
Predicted
Actual carrier normal
carrier 0.844 0.156
normal 0.167 0.833
Data: anorexia
Call:
Linda(Treat ~ ., data = anorexia, method = method)
Prior Probabilities of Groups:
CBT Cont FT
0.40278 0.36111 0.23611
Group means:
Prewt Postwt
CBT 83.254 82.381
Cont 82.178 80.539
FT 84.951 94.193
Within-groups Covariance Matrix:
Prewt Postwt
Prewt 19.1751 8.8546
Postwt 8.8546 25.2326
Linear Coeficients:
Prewt Postwt
CBT 3.3822 2.0780
Cont 3.3555 2.0144
FT 3.2299 2.5996
Constants:
CBT Cont FT
-227.29 -220.01 -261.06
Apparent error rate 0.4444
Classification table
Predicted
Actual CBT Cont FT
CBT 16 5 8
Cont 12 11 3
FT 0 4 13
Confusion matrix
Predicted
Actual CBT Cont FT
CBT 0.552 0.172 0.276
Cont 0.462 0.423 0.115
FT 0.000 0.235 0.765
Data: Pima
Call:
Linda(type ~ ., data = Pima.tr, method = method)
Prior Probabilities of Groups:
No Yes
0.66 0.34
Group means:
npreg glu bp skin bmi ped age
No 2.0767 109.45 67.790 26.158 30.930 0.41455 24.695
Yes 5.5938 145.40 74.748 33.754 34.501 0.49898 37.821
Within-groups Covariance Matrix:
npreg glu bp skin bmi ped age
npreg 6.601330 9.54054 7.33480 3.5803 1.66539 -0.019992 10.661763
glu 9.540535 573.03642 60.57124 28.3698 30.28444 -0.436611 28.318034
bp 7.334803 60.57124 112.03792 27.7566 13.54085 -0.040510 24.692240
skin 3.580339 28.36976 27.75661 112.0036 47.22411 0.100399 13.408195
bmi 1.665393 30.28444 13.54085 47.2241 38.37753 0.175891 6.640765
ped -0.019992 -0.43661 -0.04051 0.1004 0.17589 0.062551 -0.070673
age 10.661763 28.31803 24.69224 13.4082 6.64077 -0.070673 40.492363
Linear Coeficients:
npreg glu bp skin bmi ped age
No -1.3073 0.10851 0.48404 -0.30638 0.86002 5.9796 0.55388
Yes -1.3136 0.16260 0.44480 -0.25518 0.79826 8.1199 0.86269
Constants:
No Yes
-38.774 -53.654
Apparent error rate 0.25
Classification table
Predicted
Actual No Yes
No 104 28
Yes 22 46
Confusion matrix
Predicted
Actual No Yes
No 0.788 0.212
Yes 0.324 0.676
Data: Forest soils
Apparent error rate 0.3448
Classification table
Predicted
Actual 1 2 3
1 4 3 4
2 2 14 7
3 2 2 20
Confusion matrix
Predicted
Actual 1 2 3
1 0.364 0.273 0.364
2 0.087 0.609 0.304
3 0.083 0.083 0.833
Data: Raven and Miller diabetes data
Call:
Linda(group ~ insulin + glucose + sspg, data = diabetes, method = method)
Prior Probabilities of Groups:
normal chemical overt
0.52414 0.24828 0.22759
Group means:
insulin glucose sspg
normal 152.405 346.55 99.387
chemical 288.244 478.80 226.226
overt 84.754 1028.28 345.605
Within-groups Covariance Matrix:
insulin glucose sspg
insulin 5061.46 289.69 2071.71
glucose 289.69 1983.07 385.31
sspg 2071.71 385.31 3000.17
Linear Coeficients:
insulin glucose sspg
normal 0.021952 0.17236 -0.0041671
chemical 0.034852 0.23217 0.0215200
overt -0.045700 0.50940 0.0813292
Constants:
normal chemical overt
-31.976 -64.433 -275.502
Apparent error rate 0.0966
Classification table
Predicted
Actual normal chemical overt
normal 73 3 0
chemical 4 32 0
overt 0 7 26
Confusion matrix
Predicted
Actual normal chemical overt
normal 0.961 0.039 0.000
chemical 0.111 0.889 0.000
overt 0.000 0.212 0.788
Data: iris
Call:
Linda(Species ~ ., data = iris, method = method, l1med = TRUE)
Prior Probabilities of Groups:
setosa versicolor virginica
0.33333 0.33333 0.33333
Group means:
Sepal.Length Sepal.Width Petal.Length Petal.Width
setosa 4.9834 3.4153 1.4532 0.22474
versicolor 5.8947 2.8149 4.2263 1.35024
virginica 6.5255 3.0017 5.4485 2.06756
Within-groups Covariance Matrix:
Sepal.Length Sepal.Width Petal.Length Petal.Width
Sepal.Length 0.201176 0.084299 0.102984 0.037019
Sepal.Width 0.084299 0.108394 0.050253 0.031757
Petal.Length 0.102984 0.050253 0.120215 0.045016
Petal.Width 0.037019 0.031757 0.045016 0.032825
Linear Coeficients:
Sepal.Length Sepal.Width Petal.Length Petal.Width
setosa 22.536 27.422168 -3.6855 -40.0445
versicolor 17.559 6.374082 24.1965 -18.0178
virginica 16.488 0.015576 29.9586 3.2926
Constants:
setosa versicolor virginica
-96.901 -100.790 -139.937
Apparent error rate 0.0267
Classification table
Predicted
Actual setosa versicolor virginica
setosa 50 0 0
versicolor 0 48 2
virginica 0 2 48
Confusion matrix
Predicted
Actual setosa versicolor virginica
setosa 1 0.00 0.00
versicolor 0 0.96 0.04
virginica 0 0.04 0.96
Data: crabs
Call:
Linda(sp ~ ., data = crabs, method = method)
Prior Probabilities of Groups:
B O
0.5 0.5
Group means:
sexM index FL RW CL CW BD
B 0.41060 25.420 13.947 11.922 29.783 34.404 12.470
O 0.60279 23.202 16.782 13.086 33.401 37.230 15.131
Within-groups Covariance Matrix:
sexM index FL RW CL CW BD
sexM 0.27470 0.24656 0.12787 -0.34713 0.48937 0.41525 0.20253
index 0.24656 204.06823 42.17347 28.25816 89.28109 100.21077 40.74069
FL 0.12787 42.17347 9.45366 6.24808 19.97936 22.49310 9.03804
RW -0.34713 28.25816 6.24808 5.12921 13.01576 14.90535 5.89729
CL 0.48937 89.28109 19.97936 13.01576 43.06030 48.30814 19.44568
CW 0.41525 100.21077 22.49310 14.90535 48.30814 54.45265 21.82356
BD 0.20253 40.74069 9.03804 5.89729 19.44568 21.82356 8.89498
Linear Coeficients:
sexM index FL RW CL CW BD
B 12.295 -2.3199 7.2512 9.4085 2.2846 -2.6196 -0.42557
O 13.138 -3.7530 21.1374 11.5680 5.0125 -13.9120 12.61928
Constants:
B O
-66.688 -134.375
Apparent error rate 0
Classification table
Predicted
Actual B O
B 100 0
O 0 100
Confusion matrix
Predicted
Actual B O
B 1 0
O 0 1
Data: fish
Apparent error rate 0.0949
Classification table
Predicted
Actual 1 2 3 4 5 6 7
1 34 0 0 0 0 0 0
2 0 6 0 0 0 0 0
3 0 0 20 0 0 0 0
4 0 0 0 11 0 0 0
5 0 0 0 0 13 0 1
6 0 0 0 0 0 17 0
7 0 13 0 0 1 0 42
Confusion matrix
Predicted
Actual 1 2 3 4 5 6 7
1 1 0.000 0 0 0.000 0 0.000
2 0 1.000 0 0 0.000 0 0.000
3 0 0.000 1 0 0.000 0 0.000
4 0 0.000 0 1 0.000 0 0.000
5 0 0.000 0 0 0.929 0 0.071
6 0 0.000 0 0 0.000 1 0.000
7 0 0.232 0 0 0.018 0 0.750
Data: pottery
Call:
Linda(origin ~ ., data = pottery, method = method)
Prior Probabilities of Groups:
Attic Eritrean
0.48148 0.51852
Group means:
SI AL FE MG CA TI
Attic 55.362 13.847 10.0065 5.3141 5.5371 0.87124
Eritrean 52.522 16.347 9.3165 2.9541 5.7671 0.82224
Within-groups Covariance Matrix:
SI AL FE MG CA TI
SI 9.708953 2.3634831 -0.112005 0.514666 -0.591122 0.0253885
AL 2.363483 0.8510105 0.044491 0.485132 0.241384 0.0023349
FE -0.112005 0.0444910 0.247768 -0.263894 -0.503218 0.0163218
MG 0.514666 0.4851316 -0.263894 1.608899 1.516228 -0.0292787
CA -0.591122 0.2413842 -0.503218 1.516228 2.455516 -0.0531548
TI 0.025389 0.0023349 0.016322 -0.029279 -0.053155 0.0017412
Linear Coeficients:
SI AL FE MG CA TI
Attic 112.705 -368.69 530.54 7.5837 149.60 -927.45
Eritrean 77.198 -244.65 366.95 -3.7987 116.88 -260.83
Constants:
Attic Eritrean
-3252.6 -1961.9
Apparent error rate 0.1111
Classification table
Predicted
Actual Attic Eritrean
Attic 12 1
Eritrean 2 12
Confusion matrix
Predicted
Actual Attic Eritrean
Attic 0.923 0.077
Eritrean 0.143 0.857
Data: olitos
Apparent error rate 0.15
Classification table
Predicted
Actual 1 2 3 4
1 44 1 4 1
2 2 23 0 0
3 6 1 26 1
4 1 1 0 9
Confusion matrix
Predicted
Actual 1 2 3 4
1 0.880 0.020 0.080 0.020
2 0.080 0.920 0.000 0.000
3 0.176 0.029 0.765 0.029
4 0.091 0.091 0.000 0.818
===================================================
> dodata(method="mcdC")
Call: dodata(method = "mcdC")
===================================================
Data: hemophilia
Call:
Linda(as.factor(gr) ~ ., data = hemophilia, method = method)
Prior Probabilities of Groups:
carrier normal
0.6 0.4
Group means:
AHFactivity AHFantigen
carrier -0.32583 -0.011545
normal -0.12783 -0.071377
Within-groups Covariance Matrix:
AHFactivity AHFantigen
AHFactivity 0.0120964 0.0075536
AHFantigen 0.0075536 0.0164883
Linear Coeficients:
AHFactivity AHFantigen
carrier -37.117 16.30377
normal -11.015 0.71742
Constants:
carrier normal
-6.4636 -1.5947
Apparent error rate 0.16
Classification table
Predicted
Actual carrier normal
carrier 38 7
normal 5 25
Confusion matrix
Predicted
Actual carrier normal
carrier 0.844 0.156
normal 0.167 0.833
Data: anorexia
Call:
Linda(Treat ~ ., data = anorexia, method = method)
Prior Probabilities of Groups:
CBT Cont FT
0.40278 0.36111 0.23611
Group means:
Prewt Postwt
CBT 82.477 82.073
Cont 82.039 80.835
FT 85.242 94.750
Within-groups Covariance Matrix:
Prewt Postwt
Prewt 19.6589 8.3891
Postwt 8.3891 22.8805
Linear Coeficients:
Prewt Postwt
CBT 3.1590 2.4288
Cont 3.1599 2.3743
FT 3.0454 3.0245
Constants:
CBT Cont FT
-230.85 -226.60 -274.53
Apparent error rate 0.4583
Classification table
Predicted
Actual CBT Cont FT
CBT 16 5 8
Cont 14 10 2
FT 0 4 13
Confusion matrix
Predicted
Actual CBT Cont FT
CBT 0.552 0.172 0.276
Cont 0.538 0.385 0.077
FT 0.000 0.235 0.765
Data: Pima
Call:
Linda(type ~ ., data = Pima.tr, method = method)
Prior Probabilities of Groups:
No Yes
0.66 0.34
Group means:
npreg glu bp skin bmi ped age
No 2.3056 110.63 67.991 26.444 31.010 0.41653 25.806
Yes 5.0444 142.58 74.267 33.067 34.309 0.49422 35.156
Within-groups Covariance Matrix:
npreg glu bp skin bmi ped age
npreg 6.164422 8.43753 6.879286 3.252980 1.54269 -0.020158 9.543745
glu 8.437528 542.79578 57.156929 26.218837 28.63494 -0.421819 23.809124
bp 6.879286 57.15693 106.687356 26.315526 12.86691 -0.039577 22.992973
skin 3.252980 26.21884 26.315526 106.552759 44.95420 0.094311 12.005740
bmi 1.542689 28.63494 12.866911 44.954202 36.56262 0.167258 6.112925
ped -0.020158 -0.42182 -0.039577 0.094311 0.16726 0.059609 -0.072712
age 9.543745 23.80912 22.992973 12.005740 6.11292 -0.072712 35.594886
Linear Coeficients:
npreg glu bp skin bmi ped age
No -1.4165 0.11776 0.49336 -0.31564 0.88761 6.5013 0.67462
Yes -1.3784 0.17062 0.46662 -0.26771 0.83745 8.5204 0.90557
Constants:
No Yes
-41.716 -55.056
Apparent error rate 0.235
Classification table
Predicted
Actual No Yes
No 107 25
Yes 22 46
Confusion matrix
Predicted
Actual No Yes
No 0.811 0.189
Yes 0.324 0.676
Data: Forest soils
Apparent error rate 0.3276
Classification table
Predicted
Actual 1 2 3
1 5 2 4
2 2 13 8
3 1 2 21
Confusion matrix
Predicted
Actual 1 2 3
1 0.455 0.182 0.364
2 0.087 0.565 0.348
3 0.042 0.083 0.875
Data: Raven and Miller diabetes data
Call:
Linda(group ~ insulin + glucose + sspg, data = diabetes, method = method)
Prior Probabilities of Groups:
normal chemical overt
0.52414 0.24828 0.22759
Group means:
insulin glucose sspg
normal 167.31 348.69 106.44
chemical 247.18 478.18 213.36
overt 101.83 932.92 322.42
Within-groups Covariance Matrix:
insulin glucose sspg
insulin 4070.84 118.89 1701.54
glucose 118.89 2195.95 426.95
sspg 1701.54 426.95 2664.49
Linear Coeficients:
insulin glucose sspg
normal 0.041471 0.15888 -0.011992
chemical 0.048103 0.21216 0.015359
overt -0.013579 0.41323 0.063462
Constants:
normal chemical overt
-31.177 -59.703 -203.775
Apparent error rate 0.0828
Classification table
Predicted
Actual normal chemical overt
normal 72 4 0
chemical 2 34 0
overt 0 6 27
Confusion matrix
Predicted
Actual normal chemical overt
normal 0.947 0.053 0.000
chemical 0.056 0.944 0.000
overt 0.000 0.182 0.818
Data: iris
Call:
Linda(Species ~ ., data = iris, method = method, l1med = TRUE)
Prior Probabilities of Groups:
setosa versicolor virginica
0.33333 0.33333 0.33333
Group means:
Sepal.Length Sepal.Width Petal.Length Petal.Width
setosa 5.0163 3.4510 1.4653 0.2449
versicolor 5.9435 2.7891 4.2543 1.3239
virginica 6.3867 3.0033 5.3767 2.0700
Within-groups Covariance Matrix:
Sepal.Length Sepal.Width Petal.Length Petal.Width
Sepal.Length 0.186186 0.082478 0.094998 0.035445
Sepal.Width 0.082478 0.100137 0.049723 0.030678
Petal.Length 0.094998 0.049723 0.113105 0.043078
Petal.Width 0.035445 0.030678 0.043078 0.030885
Linear Coeficients:
Sepal.Length Sepal.Width Petal.Length Petal.Width
setosa 23.678 30.2896 -3.1124 -44.9900
versicolor 20.342 4.6372 27.3265 -23.2006
virginica 18.377 -2.0004 31.4235 4.0906
Constants:
setosa versicolor virginica
-104.96 -110.79 -145.49
Apparent error rate 0.0333
Classification table
Predicted
Actual setosa versicolor virginica
setosa 50 0 0
versicolor 0 48 2
virginica 0 3 47
Confusion matrix
Predicted
Actual setosa versicolor virginica
setosa 1 0.00 0.00
versicolor 0 0.96 0.04
virginica 0 0.06 0.94
Data: crabs
Call:
Linda(sp ~ ., data = crabs, method = method)
Prior Probabilities of Groups:
B O
0.5 0.5
Group means:
sexM index FL RW CL CW BD
B 0.50000 23.956 13.790 11.649 29.390 33.934 12.274
O 0.51087 24.478 16.903 13.330 33.707 37.595 15.276
Within-groups Covariance Matrix:
sexM index FL RW CL CW BD
sexM 0.25272 0.39179 0.14054 -0.30017 0.51191 0.45114 0.21708
index 0.39179 192.47099 39.97343 26.56698 84.63152 94.99987 38.67917
FL 0.14054 39.97343 8.97950 5.91408 18.98672 21.38046 8.60313
RW -0.30017 26.56698 5.91408 4.81389 12.31798 14.10613 5.58933
CL 0.51191 84.63152 18.98672 12.31798 40.94109 45.94330 18.52367
CW 0.45114 94.99987 21.38046 14.10613 45.94330 51.80106 20.79704
BD 0.21708 38.67917 8.60313 5.58933 18.52367 20.79704 8.49355
Linear Coeficients:
sexM index FL RW CL CW BD
B 13.993 -2.5515 9.152 9.9187 2.2321 -2.9774 -0.66797
O 14.362 -4.0280 23.369 12.1556 5.3672 -14.9236 12.94057
Constants:
B O
-72.687 -142.365
Apparent error rate 0
Classification table
Predicted
Actual B O
B 100 0
O 0 100
Confusion matrix
Predicted
Actual B O
B 1 0
O 0 1
Data: fish
Apparent error rate 0.0316
Classification table
Predicted
Actual 1 2 3 4 5 6 7
1 34 0 0 0 0 0 0
2 0 5 0 0 1 0 0
3 0 0 20 0 0 0 0
4 0 0 0 11 0 0 0
5 0 0 0 0 13 0 1
6 0 0 0 0 0 17 0
7 0 0 0 0 3 0 53
Confusion matrix
Predicted
Actual 1 2 3 4 5 6 7
1 1 0.000 0 0 0.000 0 0.000
2 0 0.833 0 0 0.167 0 0.000
3 0 0.000 1 0 0.000 0 0.000
4 0 0.000 0 1 0.000 0 0.000
5 0 0.000 0 0 0.929 0 0.071
6 0 0.000 0 0 0.000 1 0.000
7 0 0.000 0 0 0.054 0 0.946
Data: pottery
Call:
Linda(origin ~ ., data = pottery, method = method)
Prior Probabilities of Groups:
Attic Eritrean
0.48148 0.51852
Group means:
SI AL FE MG CA TI
Attic 55.450 13.738 10.0000 5.0750 5.0750 0.87375
Eritrean 52.444 16.444 9.3222 3.1667 6.1778 0.82000
Within-groups Covariance Matrix:
SI AL FE MG CA TI
SI 6.565481 1.6098148 -0.075259 0.369556 -0.359407 0.0169667
AL 1.609815 0.5640648 0.029407 0.302056 0.112426 0.0018583
FE -0.075259 0.0294074 0.167704 -0.180222 -0.343704 0.0110667
MG 0.369556 0.3020556 -0.180222 1.031667 0.915222 -0.0192167
CA -0.359407 0.1124259 -0.343704 0.915222 1.447370 -0.0348167
TI 0.016967 0.0018583 0.011067 -0.019217 -0.034817 0.0011725
Linear Coeficients:
SI AL FE MG CA TI
Attic 190.17 -622.48 922.21 1.5045 293.30 -990.323
Eritrean 135.34 -431.40 666.59 -14.3288 237.68 -44.025
Constants:
Attic Eritrean
-5924.2 -3802.9
Apparent error rate 0.1111
Classification table
Predicted
Actual Attic Eritrean
Attic 12 1
Eritrean 2 12
Confusion matrix
Predicted
Actual Attic Eritrean
Attic 0.923 0.077
Eritrean 0.143 0.857
Data: olitos
Apparent error rate 0.1667
Classification table
Predicted
Actual 1 2 3 4
1 44 1 2 3
2 2 22 0 1
3 5 2 25 2
4 1 1 0 9
Confusion matrix
Predicted
Actual 1 2 3 4
1 0.880 0.020 0.040 0.060
2 0.080 0.880 0.000 0.040
3 0.147 0.059 0.735 0.059
4 0.091 0.091 0.000 0.818
===================================================
> dodata(method="mrcd")
Call: dodata(method = "mrcd")
===================================================
Data: hemophilia
Call:
Linda(as.factor(gr) ~ ., data = hemophilia, method = method)
Prior Probabilities of Groups:
carrier normal
0.6 0.4
Group means:
AHFactivity AHFantigen
carrier -0.34048 -0.055943
normal -0.13566 -0.081191
Within-groups Covariance Matrix:
AHFactivity AHFantigen
AHFactivity 0.0133676 0.0088055
AHFantigen 0.0088055 0.0221225
Linear Coeficients:
AHFactivity AHFantigen
carrier -32.264 10.31334
normal -10.478 0.50044
Constants:
carrier normal
-5.7149 -1.6067
Apparent error rate 0.16
Classification table
Predicted
Actual carrier normal
carrier 38 7
normal 5 25
Confusion matrix
Predicted
Actual carrier normal
carrier 0.844 0.156
normal 0.167 0.833
Data: anorexia
Call:
Linda(Treat ~ ., data = anorexia, method = method)
Prior Probabilities of Groups:
CBT Cont FT
0.40278 0.36111 0.23611
Group means:
Prewt Postwt
CBT 83.114 84.009
Cont 80.327 80.125
FT 85.161 94.371
Within-groups Covariance Matrix:
Prewt Postwt
Prewt 22.498 11.860
Postwt 11.860 20.426
Linear Coeficients:
Prewt Postwt
CBT 2.1994 2.8357
Cont 2.1653 2.6654
FT 1.9451 3.4907
Constants:
CBT Cont FT
-211.42 -194.77 -248.97
Apparent error rate 0.3889
Classification table
Predicted
Actual CBT Cont FT
CBT 15 6 8
Cont 6 16 4
FT 0 4 13
Confusion matrix
Predicted
Actual CBT Cont FT
CBT 0.517 0.207 0.276
Cont 0.231 0.615 0.154
FT 0.000 0.235 0.765
Data: Pima
Call:
Linda(type ~ ., data = Pima.tr, method = method)
Prior Probabilities of Groups:
No Yes
0.66 0.34
Group means:
npreg glu bp skin bmi ped age
No 1.9925 108.32 66.240 24.856 30.310 0.37382 24.747
Yes 5.8855 145.88 75.715 32.541 33.915 0.39281 38.857
Within-groups Covariance Matrix:
npreg glu bp skin bmi ped age
npreg 4.090330 7.9547 3.818380 3.35899 2.470242 0.032557 9.5929
glu 7.954730 770.4187 76.377665 53.32216 54.100400 -1.139087 28.5677
bp 3.818380 76.3777 108.201622 42.61184 18.574983 -0.089151 20.3558
skin 3.358992 53.3222 42.611844 146.81170 65.210794 -0.277335 15.0162
bmi 2.470242 54.1004 18.574983 65.21079 52.871847 0.062145 9.0741
ped 0.032557 -1.1391 -0.089151 -0.27733 0.062145 0.063490 0.1762
age 9.592948 28.5677 20.355803 15.01616 9.074109 0.176201 53.5163
Linear Coeficients:
npreg glu bp skin bmi ped age
No -1.30832 0.065773 0.54772 -0.32738 0.70207 5.2556 0.40900
Yes -0.76566 0.106435 0.55777 -0.28044 0.61709 5.9199 0.54892
Constants:
No Yes
-33.429 -45.434
Apparent error rate 0.28
Classification table
Predicted
Actual No Yes
No 105 27
Yes 29 39
Confusion matrix
Predicted
Actual No Yes
No 0.795 0.205
Yes 0.426 0.574
Data: Forest soils
Apparent error rate 0.3448
Classification table
Predicted
Actual 1 2 3
1 7 2 2
2 4 14 5
3 3 4 17
Confusion matrix
Predicted
Actual 1 2 3
1 0.636 0.182 0.182
2 0.174 0.609 0.217
3 0.125 0.167 0.708
Data: Raven and Miller diabetes data
Call:
Linda(group ~ insulin + glucose + sspg, data = diabetes, method = method)
Prior Probabilities of Groups:
normal chemical overt
0.52414 0.24828 0.22759
Group means:
insulin glucose sspg
normal 154.014 346.07 91.606
chemical 248.841 451.10 221.936
overt 89.766 1064.16 335.100
Within-groups Covariance Matrix:
insulin glucose sspg
insulin 4948.1 1007.61 1471.12
glucose 1007.6 2597.38 358.57
sspg 1471.1 358.57 3180.04
Linear Coeficients:
insulin glucose sspg
normal 0.00027839 0.13121 0.013882
chemical 0.00148074 0.16615 0.050371
overt -0.10102404 0.43466 0.103100
Constants:
normal chemical overt
-24.008 -44.642 -245.497
Apparent error rate 0.0966
Classification table
Predicted
Actual normal chemical overt
normal 71 5 0
chemical 2 34 0
overt 0 7 26
Confusion matrix
Predicted
Actual normal chemical overt
normal 0.934 0.066 0.000
chemical 0.056 0.944 0.000
overt 0.000 0.212 0.788
Data: iris
Call:
Linda(Species ~ ., data = iris, method = method, l1med = TRUE)
Prior Probabilities of Groups:
setosa versicolor virginica
0.33333 0.33333 0.33333
Group means:
Sepal.Length Sepal.Width Petal.Length Petal.Width
setosa 4.9755 3.3826 1.4608 0.22053
versicolor 5.8868 2.7823 4.2339 1.34603
virginica 6.5176 2.9691 5.4560 2.06335
Within-groups Covariance Matrix:
Sepal.Length Sepal.Width Petal.Length Petal.Width
Sepal.Length 0.238417 0.136325 0.086377 0.036955
Sepal.Width 0.136325 0.148452 0.067500 0.034804
Petal.Length 0.086377 0.067500 0.100934 0.035968
Petal.Width 0.036955 0.034804 0.035968 0.023856
Linear Coeficients:
Sepal.Length Sepal.Width Petal.Length Petal.Width
setosa 17.106 15.693 7.8806 -52.031
versicolor 21.744 -15.813 38.0139 -11.505
virginica 23.032 -26.567 43.6391 23.777
Constants:
setosa versicolor virginica
-70.214 -115.832 -180.294
Apparent error rate 0.02
Classification table
Predicted
Actual setosa versicolor virginica
setosa 50 0 0
versicolor 0 49 1
virginica 0 2 48
Confusion matrix
Predicted
Actual setosa versicolor virginica
setosa 1 0.00 0.00
versicolor 0 0.98 0.02
virginica 0 0.04 0.96
Data: crabs
Call:
Linda(sp ~ ., data = crabs, method = method)
Prior Probabilities of Groups:
B O
0.5 0.5
Group means:
sexM index FL RW CL CW BD
B 0 25.5 13.270 12.138 28.102 32.624 11.816
O 1 25.5 16.626 12.262 33.688 37.188 15.324
Within-groups Covariance Matrix:
sexM index FL RW CL CW BD
sexM 1.5255e-07 0.000 0.0000 0.0000 0.000 0.000 0.000
index 0.0000e+00 337.501 62.8107 46.5073 137.713 154.451 63.514
FL 0.0000e+00 62.811 15.3164 9.8612 29.911 33.479 13.805
RW 0.0000e+00 46.507 9.8612 8.6949 21.878 24.604 10.092
CL 0.0000e+00 137.713 29.9112 21.8779 73.888 73.891 30.486
CW 0.0000e+00 154.451 33.4788 24.6038 73.891 92.801 34.122
BD 0.0000e+00 63.514 13.8053 10.0923 30.486 34.122 15.854
Linear Coeficients:
sexM index FL RW CL CW BD
B 0 -0.64890 0.95529 2.7299 0.20747 0.28549 -0.23815
O 6555120 -0.83294 1.67920 1.8896 0.32330 0.23479 0.51136
Constants:
B O
-2.1491e+01 -3.2776e+06
Apparent error rate 0.5
Classification table
Predicted
Actual B O
B 50 50
O 50 50
Confusion matrix
Predicted
Actual B O
B 0.5 0.5
O 0.5 0.5
Data: fish
Apparent error rate 0.2532
Classification table
Predicted
Actual 1 2 3 4 5 6 7
1 33 0 0 1 0 0 0
2 0 3 0 0 0 0 3
3 0 2 5 0 0 0 13
4 0 0 0 11 0 0 0
5 0 0 0 0 14 0 0
6 0 0 0 0 0 17 0
7 0 19 0 0 2 0 35
Confusion matrix
Predicted
Actual 1 2 3 4 5 6 7
1 0.971 0.000 0.00 0.029 0.000 0 0.000
2 0.000 0.500 0.00 0.000 0.000 0 0.500
3 0.000 0.100 0.25 0.000 0.000 0 0.650
4 0.000 0.000 0.00 1.000 0.000 0 0.000
5 0.000 0.000 0.00 0.000 1.000 0 0.000
6 0.000 0.000 0.00 0.000 0.000 1 0.000
7 0.000 0.339 0.00 0.000 0.036 0 0.625
Data: pottery
Call:
Linda(origin ~ ., data = pottery, method = method)
Prior Probabilities of Groups:
Attic Eritrean
0.48148 0.51852
Group means:
SI AL FE MG CA TI
Attic 55.872 13.986 10.113 5.0235 4.7316 0.88531
Eritrean 52.487 16.286 9.499 2.4520 5.3745 0.83959
Within-groups Covariance Matrix:
SI AL FE MG CA TI
SI 12.795913 3.2987125 -0.35496855 0.9399999 -0.0143514 0.01132392
AL 3.298713 1.0829436 -0.03394751 0.2838724 0.0501000 0.00117721
FE -0.354969 -0.0339475 0.08078156 0.0341568 -0.0457411 0.00043177
MG 0.940000 0.2838724 0.03415675 0.4350013 0.1417876 0.00396576
CA -0.014351 0.0501000 -0.04574114 0.1417876 0.4196628 -0.00104893
TI 0.011324 0.0011772 0.00043177 0.0039658 -0.0010489 0.00026205
Linear Coeficients:
SI AL FE MG CA TI
Attic 36.451 -63.784 352.90 -124.07 110.08 3826.6
Eritrean 29.763 -41.039 325.12 -128.32 107.36 3938.1
Constants:
Attic Eritrean
-4000.1 -3776.1
Apparent error rate 0.1111
Classification table
Predicted
Actual Attic Eritrean
Attic 12 1
Eritrean 2 12
Confusion matrix
Predicted
Actual Attic Eritrean
Attic 0.923 0.077
Eritrean 0.143 0.857
Data: olitos
Apparent error rate 0.125
Classification table
Predicted
Actual 1 2 3 4
1 44 2 3 1
2 1 23 1 0
3 4 1 27 2
4 0 0 0 11
Confusion matrix
Predicted
Actual 1 2 3 4
1 0.880 0.040 0.060 0.020
2 0.040 0.920 0.040 0.000
3 0.118 0.029 0.794 0.059
4 0.000 0.000 0.000 1.000
===================================================
> dodata(method="ogk")
Call: dodata(method = "ogk")
===================================================
Data: hemophilia
Call:
Linda(as.factor(gr) ~ ., data = hemophilia, method = method)
Prior Probabilities of Groups:
carrier normal
0.6 0.4
Group means:
AHFactivity AHFantigen
carrier -0.29043 -0.00052902
normal -0.12463 -0.06715037
Within-groups Covariance Matrix:
AHFactivity AHFantigen
AHFactivity 0.015688 0.010544
AHFantigen 0.010544 0.016633
Linear Coeficients:
AHFactivity AHFantigen
carrier -32.2203 20.3935
normal -9.1149 1.7409
Constants:
carrier normal
-5.1843 -1.4259
Apparent error rate 0.1467
Classification table
Predicted
Actual carrier normal
carrier 38 7
normal 4 26
Confusion matrix
Predicted
Actual carrier normal
carrier 0.844 0.156
normal 0.133 0.867
Data: anorexia
Call:
Linda(Treat ~ ., data = anorexia, method = method)
Prior Probabilities of Groups:
CBT Cont FT
0.40278 0.36111 0.23611
Group means:
Prewt Postwt
CBT 82.634 82.060
Cont 81.605 80.459
FT 85.157 93.822
Within-groups Covariance Matrix:
Prewt Postwt
Prewt 15.8294 4.4663
Postwt 4.4663 19.6356
Linear Coeficients:
Prewt Postwt
CBT 4.3183 3.1970
Cont 4.2734 3.1256
FT 4.3080 3.7983
Constants:
CBT Cont FT
-310.50 -301.12 -363.05
Apparent error rate 0.4583
Classification table
Predicted
Actual CBT Cont FT
CBT 15 5 9
Cont 14 11 1
FT 0 4 13
Confusion matrix
Predicted
Actual CBT Cont FT
CBT 0.517 0.172 0.310
Cont 0.538 0.423 0.038
FT 0.000 0.235 0.765
Data: Pima
Call:
Linda(type ~ ., data = Pima.tr, method = method)
Prior Probabilities of Groups:
No Yes
0.66 0.34
Group means:
npreg glu bp skin bmi ped age
No 2.4175 109.93 67.332 26.324 30.344 0.38740 26.267
Yes 5.1853 142.29 75.194 33.151 34.878 0.47977 37.626
Within-groups Covariance Matrix:
npreg glu bp skin bmi ped age
npreg 7.218576 7.52457 6.96595 4.86613 0.45567 -0.054245 14.42648
glu 7.524571 517.38370 58.53812 31.57321 22.68396 -0.200222 22.88780
bp 6.965950 58.53812 101.50317 27.86784 10.89215 -0.152784 25.41819
skin 4.866127 31.57321 27.86784 95.16949 37.45066 -0.117375 14.60676
bmi 0.455675 22.68396 10.89215 37.45066 30.89491 0.043400 4.05584
ped -0.054245 -0.20022 -0.15278 -0.11737 0.04340 0.051268 -0.18131
age 14.426479 22.88780 25.41819 14.60676 4.05584 -0.181311 57.89570
Linear Coeficients:
npreg glu bp skin bmi ped age
No -0.99043 0.12339 0.54101 -0.35335 1.0721 8.4945 0.45482
Yes -1.01369 0.17577 0.53898 -0.35554 1.1563 11.0474 0.63966
Constants:
No Yes
-43.449 -60.176
Apparent error rate 0.23
Classification table
Predicted
Actual No Yes
No 108 24
Yes 22 46
Confusion matrix
Predicted
Actual No Yes
No 0.818 0.182
Yes 0.324 0.676
Data: Forest soils
Apparent error rate 0.3621
Classification table
Predicted
Actual 1 2 3
1 7 3 1
2 4 13 6
3 3 4 17
Confusion matrix
Predicted
Actual 1 2 3
1 0.636 0.273 0.091
2 0.174 0.565 0.261
3 0.125 0.167 0.708
Data: Raven and Miller diabetes data
Call:
Linda(group ~ insulin + glucose + sspg, data = diabetes, method = method)
Prior Probabilities of Groups:
normal chemical overt
0.52414 0.24828 0.22759
Group means:
insulin glucose sspg
normal 159.540 344.06 99.486
chemical 252.992 478.16 219.442
overt 79.635 1094.96 338.517
Within-groups Covariance Matrix:
insulin glucose sspg
insulin 3844.877 67.238 1456.55
glucose 67.238 2228.396 324.21
sspg 1456.548 324.205 2181.73
Linear Coeficients:
insulin glucose sspg
normal 0.040407 0.15379 -0.0042303
chemical 0.047858 0.20764 0.0377766
overt -0.026158 0.47736 0.1016873
Constants:
normal chemical overt
-30.115 -61.233 -278.996
Apparent error rate 0.0966
Classification table
Predicted
Actual normal chemical overt
normal 71 5 0
chemical 2 34 0
overt 0 7 26
Confusion matrix
Predicted
Actual normal chemical overt
normal 0.934 0.066 0.000
chemical 0.056 0.944 0.000
overt 0.000 0.212 0.788
Data: iris
Call:
Linda(Species ~ ., data = iris, method = method, l1med = TRUE)
Prior Probabilities of Groups:
setosa versicolor virginica
0.33333 0.33333 0.33333
Group means:
Sepal.Length Sepal.Width Petal.Length Petal.Width
setosa 4.9654 3.3913 1.4507 0.21639
versicolor 5.8767 2.7909 4.2238 1.34189
virginica 6.5075 2.9777 5.4459 2.05921
Within-groups Covariance Matrix:
Sepal.Length Sepal.Width Petal.Length Petal.Width
Sepal.Length 0.180280 0.068876 0.101512 0.036096
Sepal.Width 0.068876 0.079556 0.047722 0.029409
Petal.Length 0.101512 0.047722 0.111492 0.038658
Petal.Width 0.036096 0.029409 0.038658 0.029965
Linear Coeficients:
Sepal.Length Sepal.Width Petal.Length Petal.Width
setosa 28.582 46.5236 -13.859 -54.9877
versicolor 19.837 11.9601 20.865 -17.7704
virginica 16.999 1.9046 29.808 7.9189
Constants:
setosa versicolor virginica
-134.94 -108.22 -148.56
Apparent error rate 0.0133
Classification table
Predicted
Actual setosa versicolor virginica
setosa 50 0 0
versicolor 0 49 1
virginica 0 1 49
Confusion matrix
Predicted
Actual setosa versicolor virginica
setosa 1 0.00 0.00
versicolor 0 0.98 0.02
virginica 0 0.02 0.98
Data: crabs
Call:
Linda(sp ~ ., data = crabs, method = method)
Prior Probabilities of Groups:
B O
0.5 0.5
Group means:
sexM index FL RW CL CW BD
B 0.48948 24.060 13.801 11.738 29.491 34.062 12.329
O 0.56236 24.043 16.825 13.158 33.574 37.418 15.223
Within-groups Covariance Matrix:
sexM index FL RW CL CW BD
sexM 0.24961 0.50421 0.16645 -0.28574 0.54159 0.48449 0.22563
index 0.50421 186.86616 38.46284 25.26749 82.29121 92.11253 37.67723
FL 0.16645 38.46284 8.58830 5.56769 18.33015 20.58235 8.32030
RW -0.28574 25.26749 5.56769 4.52038 11.70881 13.37643 5.32779
CL 0.54159 82.29121 18.33015 11.70881 39.78186 44.52112 18.01179
CW 0.48449 92.11253 20.58235 13.37643 44.52112 50.06150 20.16852
BD 0.22563 37.67723 8.32030 5.32779 18.01179 20.16852 8.25884
Linear Coeficients:
sexM index FL RW CL CW BD
B 16.497 -2.5896 8.3966 11.518 1.7536 -2.5325 -0.67361
O 17.010 -4.0452 23.5400 13.702 4.7871 -14.8264 13.04556
Constants:
B O
-77.695 -147.287
Apparent error rate 0
Classification table
Predicted
Actual B O
B 100 0
O 0 100
Confusion matrix
Predicted
Actual B O
B 1 0
O 0 1
Data: fish
Apparent error rate 0.0063
Classification table
Predicted
Actual 1 2 3 4 5 6 7
1 34 0 0 0 0 0 0
2 0 6 0 0 0 0 0
3 0 0 20 0 0 0 0
4 0 0 0 11 0 0 0
5 0 0 0 0 14 0 0
6 0 0 0 0 0 17 0
7 0 0 0 0 1 0 55
Confusion matrix
Predicted
Actual 1 2 3 4 5 6 7
1 1 0 0 0 0.000 0 0.000
2 0 1 0 0 0.000 0 0.000
3 0 0 1 0 0.000 0 0.000
4 0 0 0 1 0.000 0 0.000
5 0 0 0 0 1.000 0 0.000
6 0 0 0 0 0.000 1 0.000
7 0 0 0 0 0.018 0 0.982
Data: pottery
Call:
Linda(origin ~ ., data = pottery, method = method)
Prior Probabilities of Groups:
Attic Eritrean
0.48148 0.51852
Group means:
SI AL FE MG CA TI
Attic 55.381 14.088 10.1316 4.9588 4.7684 0.88444
Eritrean 53.559 16.251 9.1145 2.6213 5.8980 0.82501
Within-groups Covariance Matrix:
SI AL FE MG CA TI
SI 7.878378 1.9064112 -0.545403 0.4167407 -0.11589 0.01850748
AL 1.906411 0.6678763 -0.037744 0.1120891 -0.10733 0.00805556
FE -0.545403 -0.0377438 0.213914 -0.0192356 -0.23121 0.00582800
MG 0.416741 0.1120891 -0.019236 0.2336721 0.17284 -0.00183128
CA -0.115888 -0.1073297 -0.231213 0.1728385 0.71388 -0.01895968
TI 0.018507 0.0080556 0.005828 -0.0018313 -0.01896 0.00081815
Linear Coeficients:
SI AL FE MG CA TI
Attic 57.784 -107.297 319.31 -152.94 241.66 3813.6
Eritrean 52.523 -86.545 306.58 -165.71 242.36 3734.1
Constants:
Attic Eritrean
-4346 -4139
Apparent error rate 0.1111
Classification table
Predicted
Actual Attic Eritrean
Attic 12 1
Eritrean 2 12
Confusion matrix
Predicted
Actual Attic Eritrean
Attic 0.923 0.077
Eritrean 0.143 0.857
Data: olitos
Apparent error rate 0.1
Classification table
Predicted
Actual 1 2 3 4
1 45 2 2 1
2 0 25 0 0
3 4 1 27 2
4 0 0 0 11
Confusion matrix
Predicted
Actual 1 2 3 4
1 0.900 0.040 0.040 0.020
2 0.000 1.000 0.000 0.000
3 0.118 0.029 0.794 0.059
4 0.000 0.000 0.000 1.000
===================================================
> #dodata(method="fsa")
>
> proc.time()
user system elapsed
3.98 0.50 4.46