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Exact Solution Paths for Regularized L_1 LASSO RegressionDescription
Details
Author(s)Kai Wang ReferencesWang K. (2013) Exact LASSO linear regression. Submitted. Exampleslibrary(ncvreg) data(prostate) myfit = exact.path(as.matrix(prostate[,-9]), prostate$lpsa, verbose=TRUE) myfit plot(myfit) library(ncvreg) data(heart) myfit = exact.path(as.matrix(heart[,-1]), heart$sbp) myfit plot(myfit) library(lars) data(diabetes) myfit = exact.path(diabetes$x, diabetes$y, verbose=TRUE) myfit plot(myfit) Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(ExactPath)
Loading required package: ncvreg
Loading required package: lars
Loaded lars 1.2
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/ExactPath/ExactPath-package.Rd_%03d_medium.png", width=480, height=480)
> ### Name: ExactPath-package
> ### Title: Exact Solution Paths for Regularized L_1 LASSO Regression
> ### Aliases: ExactPath-package ExactPath
>
> ### ** Examples
>
> library(ncvreg)
> data(prostate)
> myfit = exact.path(as.matrix(prostate[,-9]), prostate$lpsa, verbose=TRUE)
beta score breaks tau change
lcavol 0 0.7344603 0.7344603 1 +
lweight 0 0.4333194 0.4333194 0 |
age 0 0.1695928 0.1695928 0 |
lbph 0 0.1798094 0.1798094 0 |
svi 0 0.5662182 0.5662182 0 |
lcp 0 0.5488132 0.5488132 0 |
gleason 0 0.3689868 0.3689868 0 |
pgg45 0 0.4223159 0.4223159 0 |
lambda_1 = 0.7344603
beta score breaks tau change
lcavol 0.3648277 0.36963266 0.734460326 1 |
lweight 0.0000000 0.33097742 0.315905924 0 |
age 0.0000000 0.08750666 0.005599166 0 |
lbph 0.0000000 0.16983148 0.164213317 0 |
svi 0.0000000 0.36963266 0.369632655 1 +
lcp 0.0000000 0.30244122 0.162692091 0 |
gleason 0.0000000 0.21122910 0.090548236 0 |
pgg45 0.0000000 0.26410752 0.183306962 0 |
lambda_2 = 0.3696327
beta score breaks tau change
lcavol 0.39987516 0.31570000 0.931045893 1 |
lweight 0.00000000 0.31570000 0.315699999 1 +
age 0.00000000 0.07549736 0.006689277 0 |
lbph 0.00000000 0.17188153 0.177148069 0 |
svi 0.03504749 0.31570000 0.369632655 1 |
lcp 0.00000000 0.25518243 0.011433137 0 |
gleason 0.00000000 0.18484432 0.059513515 0 |
pgg45 0.00000000 0.23286969 0.118859665 0 |
lambda_3 = 0.3157
beta score breaks tau change
lcavol 0.4829234 0.124387656 1.236864149 1 |
lweight 0.1488355 0.124387656 0.315699999 1 |
age 0.0000000 -0.009501825 0.044843100 0 |
lbph 0.0000000 0.114381619 0.110081973 0 |
svi 0.1584829 0.124387656 0.370020043 1 |
lcp 0.0000000 0.091524348 0.008021252 0 |
gleason 0.0000000 0.100916555 0.082572420 0 |
pgg45 0.0000000 0.124387656 0.124387656 1 +
lambda_4 = 0.1243877
beta score breaks tau change
lcavol 0.487275262 0.10869606 1.86567157 1 |
lweight 0.161198691 0.10869606 0.31329310 1 |
age 0.000000000 -0.01816516 0.05036808 0 |
lbph 0.000000000 0.10869606 0.10869606 1 +
svi 0.165712510 0.10869606 0.46836949 1 |
lcp 0.000000000 0.07589476 0.01621793 0 |
gleason 0.000000000 0.08912116 0.02985989 0 |
pgg45 0.009168559 0.10869606 0.12438766 1 |
lambda_5 = 0.1086961
beta score breaks tau change
lcavol 0.50491055 0.05558212 1.57627146 1 |
lweight 0.18200727 0.05558212 0.52015610 1 |
age 0.00000000 -0.05558212 0.05558212 -1 +
lbph 0.04431172 0.05558212 0.10869606 1 |
svi 0.19858501 0.05558212 0.37644704 1 |
lcp 0.00000000 0.02313882 0.01608855 0 |
gleason 0.00000000 0.04774973 0.02015453 0 |
pgg45 0.03388032 0.05558212 0.12840240 1 |
lambda_6 = 0.05558212
beta score breaks tau change
lcavol 0.51741672 0.032103019 1.00350133 1 |
lweight 0.20157703 0.032103019 0.27394789 1 |
age -0.05185925 -0.032103019 0.05558212 -1 |
lbph 0.07629111 0.032103019 0.08811557 1 |
svi 0.21103160 0.032103019 0.43019063 1 |
lcp 0.00000000 -0.003996983 0.01906527 0 |
gleason 0.00000000 0.032103019 0.03210302 1 +
pgg45 0.05594893 0.032103019 0.09162786 1 |
lambda_7 = 0.03210302
beta score breaks tau change
lcavol 0.52231490 0.01913394 1.40208545 1 |
lweight 0.21336467 0.01913394 0.25388364 1 |
age -0.08120861 -0.01913394 0.05501892 -1 |
lbph 0.09366845 0.01913394 0.08904069 1 |
svi 0.21890832 0.01913394 0.37956812 1 |
lcp 0.00000000 -0.01913394 0.01913394 -1 +
gleason 0.01066560 0.01913394 0.03210302 1 |
pgg45 0.06064448 0.01913394 0.18663378 1 |
lambda_8 = 0.01913394
beta score breaks tau change
lcavol 0.57621928 1.214306e-16 0.20453520 1 |
lweight 0.23085294 -1.752071e-16 0.25257645 1 |
age -0.13704517 5.551115e-17 0.04696230 -1 |
lbph 0.12155214 8.673617e-19 0.08340974 1 |
svi 0.27317070 -8.673617e-17 0.09632513 1 |
lcp -0.12846050 -1.075529e-16 0.01913394 -1 |
gleason 0.03079639 1.630640e-16 0.02927139 1 |
pgg45 0.10891159 -4.943962e-17 0.04317448 1 |
lambda_9 = 0
beta score breaks tau change
lcavol 0.57621928 1.214306e-16 0.20453520 1 |
lweight 0.23085294 -1.752071e-16 0.25257645 1 |
age -0.13704517 5.551115e-17 0.04696230 -1 |
lbph 0.12155214 8.673617e-19 0.08340974 1 |
svi 0.27317070 -8.673617e-17 0.09632513 1 |
lcp -0.12846050 -1.075529e-16 0.01913394 -1 |
gleason 0.03079639 1.630640e-16 0.02927139 1 |
pgg45 0.10891159 -4.943962e-17 0.04317448 1 |
lambda_10 = 0
beta score breaks tau change
lcavol 0.57621928 1.214306e-16 0.20453520 1 |
lweight 0.23085294 -1.752071e-16 0.25257645 1 |
age -0.13704517 5.551115e-17 0.04696230 -1 |
lbph 0.12155214 8.673617e-19 0.08340974 1 |
svi 0.27317070 -8.673617e-17 0.09632513 1 |
lcp -0.12846050 -1.075529e-16 0.01913394 -1 |
gleason 0.03079639 1.630640e-16 0.02927139 1 |
pgg45 0.10891159 -4.943962e-17 0.04317448 1 |
lambda_11 = 0
beta score breaks tau change
lcavol 0.57621928 1.214306e-16 0.20453520 1 |
lweight 0.23085294 -1.752071e-16 0.25257645 1 |
age -0.13704517 5.551115e-17 0.04696230 -1 |
lbph 0.12155214 8.673617e-19 0.08340974 1 |
svi 0.27317070 -8.673617e-17 0.09632513 1 |
lcp -0.12846050 -1.075529e-16 0.01913394 -1 |
gleason 0.03079639 1.630640e-16 0.02927139 1 |
pgg45 0.10891159 -4.943962e-17 0.04317448 1 |
lambda_12 = 0
> myfit
breaks:
[1] 0.7345 0.3696 0.3157 0.1244 0.1087 0.0556 0.0321 0.0191 0.0000 0.0000
[11] 0.0000 0.0000
Indicator matrix (parameters x breaks):
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1 1 1 1 1 1 1 1 1 1 1 1
[2,] 0 0 1 1 1 1 1 1 1 1 1 1
[3,] 0 0 0 0 0 -1 -1 -1 -1 -1 -1 -1
[4,] 0 0 0 0 1 1 1 1 1 1 1 1
[5,] 0 1 1 1 1 1 1 1 1 1 1 1
[6,] 0 0 0 0 0 0 0 -1 -1 -1 -1 -1
[7,] 0 0 0 0 0 0 1 1 1 1 1 1
[8,] 0 0 0 1 1 1 1 1 1 1 1 1
Beta matrix (parameters x breaks):
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 0 0.3648 0.3999 0.4829 0.4873 0.5049 0.5174 0.5223 0.5762 0.5762
[2,] 0 0.0000 0.0000 0.1488 0.1612 0.1820 0.2016 0.2134 0.2309 0.2309
[3,] 0 0.0000 0.0000 0.0000 0.0000 0.0000 -0.0519 -0.0812 -0.1370 -0.1370
[4,] 0 0.0000 0.0000 0.0000 0.0000 0.0443 0.0763 0.0937 0.1216 0.1216
[5,] 0 0.0000 0.0350 0.1585 0.1657 0.1986 0.2110 0.2189 0.2732 0.2732
[6,] 0 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 -0.1285 -0.1285
[7,] 0 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0107 0.0308 0.0308
[8,] 0 0.0000 0.0000 0.0000 0.0092 0.0339 0.0559 0.0606 0.1089 0.1089
[,11] [,12]
[1,] 0.5762 0.5762
[2,] 0.2309 0.2309
[3,] -0.1370 -0.1370
[4,] 0.1216 0.1216
[5,] 0.2732 0.2732
[6,] -0.1285 -0.1285
[7,] 0.0308 0.0308
[8,] 0.1089 0.1089
Score matrix (parameters x breaks):
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 0.7345 0.3696 0.3157 0.1244 0.1087 0.0556 0.0321 0.0191 0 0
[2,] 0.4333 0.3310 0.3157 0.1244 0.1087 0.0556 0.0321 0.0191 0 0
[3,] 0.1696 0.0875 0.0755 -0.0095 -0.0182 -0.0556 -0.0321 -0.0191 0 0
[4,] 0.1798 0.1698 0.1719 0.1144 0.1087 0.0556 0.0321 0.0191 0 0
[5,] 0.5662 0.3696 0.3157 0.1244 0.1087 0.0556 0.0321 0.0191 0 0
[6,] 0.5488 0.3024 0.2552 0.0915 0.0759 0.0231 -0.0040 -0.0191 0 0
[7,] 0.3690 0.2112 0.1848 0.1009 0.0891 0.0477 0.0321 0.0191 0 0
[8,] 0.4223 0.2641 0.2329 0.1244 0.1087 0.0556 0.0321 0.0191 0 0
[,11] [,12]
[1,] 0 0
[2,] 0 0
[3,] 0 0
[4,] 0 0
[5,] 0 0
[6,] 0 0
[7,] 0 0
[8,] 0 0
> plot(myfit)
>
> library(ncvreg)
> data(heart)
> myfit = exact.path(as.matrix(heart[,-1]), heart$sbp)
> myfit
breaks:
[1] 0.3888 0.3025 0.1072 0.0695 0.0677 0.0483 0.0339 0.0189 0.0046 0.0000
[11] 0.0000 0.0000 0.0000
Indicator matrix (parameters x breaks):
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0 0 0 0 1 1 1 1 1 1 1 1
[2,] 0 0 0 0 0 0 0 0 -1 -1 -1 -1 -1
[3,] 0 1 1 1 1 1 1 1 1 1 1 1 1
[4,] 0 0 0 0 0 0 0 -1 -1 -1 -1 -1 -1
[5,] 0 0 0 0 0 0 -1 -1 -1 -1 -1 -1 -1
[6,] 0 0 0 0 1 1 1 1 1 1 1 1 1
[7,] 0 0 1 1 1 1 1 1 1 1 1 1 1
[8,] 1 1 1 1 1 1 1 1 1 1 1 1 1
[9,] 0 0 0 1 1 1 1 1 1 1 1 1 1
Beta matrix (parameters x breaks):
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 0 0.0000 0.0000 0.0000 0.0000 0.0000 0.0062 0.0128 0.0175 0.0191
[2,] 0 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 -0.0084
[3,] 0 0.0000 0.1201 0.1412 0.1423 0.1371 0.1332 0.1265 0.1200 0.1209
[4,] 0 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 -0.0222 -0.0290
[5,] 0 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 -0.0180 -0.0344 -0.0393
[6,] 0 0.0000 0.0000 0.0000 0.0000 0.0177 0.0309 0.0484 0.0661 0.0722
[7,] 0 0.0000 0.0000 0.0334 0.0350 0.0520 0.0637 0.0768 0.0905 0.0942
[8,] 0 0.0863 0.2064 0.2274 0.2280 0.2385 0.2440 0.2472 0.2542 0.2566
[9,] 0 0.0000 0.0000 0.0000 0.0013 0.0152 0.0246 0.0375 0.0545 0.0613
[,11] [,12] [,13]
[1,] 0.0191 0.0191 0.0191
[2,] -0.0084 -0.0084 -0.0084
[3,] 0.1209 0.1209 0.1209
[4,] -0.0290 -0.0290 -0.0290
[5,] -0.0393 -0.0393 -0.0393
[6,] 0.0722 0.0722 0.0722
[7,] 0.0942 0.0942 0.0942
[8,] 0.2566 0.2566 0.2566
[9,] 0.0613 0.0613 0.0613
Score matrix (parameters x breaks):
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
[1,] 0.2122 0.1734 0.0849 0.0626 0.0614 0.0483 0.0339 0.0189 0.0046
[2,] 0.1583 0.1314 0.0410 0.0263 0.0254 0.0154 0.0080 0.0010 -0.0046
[3,] 0.3565 0.3025 0.1072 0.0695 0.0677 0.0483 0.0339 0.0189 0.0046
[4,] 0.0856 0.0650 0.0143 0.0028 0.0020 -0.0068 -0.0130 -0.0189 -0.0046
[5,] -0.0575 -0.0486 -0.0311 -0.0293 -0.0294 -0.0320 -0.0339 -0.0189 -0.0046
[6,] 0.2381 0.2129 0.0918 0.0688 0.0677 0.0483 0.0339 0.0189 0.0046
[7,] 0.1401 0.1314 0.1072 0.0695 0.0677 0.0483 0.0339 0.0189 0.0046
[8,] 0.3888 0.3025 0.1072 0.0695 0.0677 0.0483 0.0339 0.0189 0.0046
[9,] 0.1924 0.1602 0.0848 0.0695 0.0677 0.0483 0.0339 0.0189 0.0046
[,10] [,11] [,12] [,13]
[1,] 0 0 0 0
[2,] 0 0 0 0
[3,] 0 0 0 0
[4,] 0 0 0 0
[5,] 0 0 0 0
[6,] 0 0 0 0
[7,] 0 0 0 0
[8,] 0 0 0 0
[9,] 0 0 0 0
> plot(myfit)
>
> library(lars)
> data(diabetes)
> myfit = exact.path(diabetes$x, diabetes$y, verbose=TRUE)
beta score breaks tau change
age 0 0.1878888 0.1878888 0 |
sex 0 0.0430620 0.0430620 0 |
bmi 0 0.5864501 0.5864501 1 +
map 0 0.4414838 0.4414838 0 |
tc 0 0.2120225 0.2120225 0 |
ldl 0 0.1740536 0.1740536 0 |
hdl 0 -0.3947893 -0.3947893 0 |
tch 0 0.4304529 0.4304529 0 |
ltg 0 0.5658834 0.5658834 0 |
glu 0 0.3824835 0.3824835 0 |
lambda_1 = 0.5864501
beta score breaks tau change
age 0.00000000 0.18101569 0.097366953 0 |
sex 0.00000000 0.03978816 0.007940243 0 |
bmi 0.03713466 0.54931548 0.586450134 1 |
map 0.00000000 0.42680024 0.346671836 0 |
tc 0.00000000 0.20274708 0.087361378 0 |
ldl 0.00000000 0.16435513 0.028275050 0 |
hdl 0.00000000 -0.38116785 0.283758715 0 |
tch 0.00000000 0.41508632 0.320331051 0 |
ltg 0.00000000 0.54931548 0.549315476 1 +
glu 0.00000000 0.36804999 0.252800576 0 |
lambda_2 = 0.5493155
beta score breaks tau change
age 0.0000000 0.096042421 0.01147702 0 |
sex 0.0000000 -0.004590128 0.04348583 0 |
bmi 0.2235362 0.279749284 0.60301808 1 |
map 0.0000000 0.279749284 0.27974928 1 +
tc 0.0000000 0.060098053 0.05750773 0 |
ldl 0.0000000 0.056331097 0.03981747 0 |
hdl 0.0000000 -0.238498355 0.19212009 0 |
tch 0.0000000 0.222782566 0.08099422 0 |
ltg 0.1864015 0.279749284 0.54931548 1 |
glu 0.0000000 0.208984151 0.10711738 0 |
lambda_3 = 0.2797493
beta score breaks tau change
age 0.00000000 0.05906256 0.01833811 0 |
sex 0.00000000 -0.02712679 0.06251665 0 |
bmi 0.26854265 0.19523361 0.69951820 1 |
map 0.04894302 0.19523361 0.27974928 1 |
tc 0.00000000 0.01370014 0.06034938 0 |
ldl 0.00000000 0.02111255 0.04252338 0 |
hdl 0.00000000 -0.19523361 0.19523361 -1 +
tch 0.00000000 0.16363492 0.08995998 0 |
ltg 0.23157918 0.19523361 0.62845827 1 |
glu 0.00000000 0.15138953 0.05758998 0 |
lambda_4 = 0.1952336
beta score breaks tau change
age 0.00000000 0.01161673 0.01527698 0 |
sex 0.00000000 -0.08037963 0.08037963 -1 +
bmi 0.31233737 0.08037963 0.89950095 1 |
map 0.11814418 0.08037963 0.27646490 1 |
tc 0.00000000 -0.03100414 0.04483793 0 |
ldl 0.00000000 -0.02974431 0.04528435 0 |
hdl -0.07047825 -0.08037963 0.19523361 -1 |
tch 0.00000000 0.05092393 0.01410960 0 |
ltg 0.27157361 0.08037963 0.86027098 1 |
glu 0.00000000 0.06947530 0.04235850 0 |
lambda_5 = 0.08037963
beta score breaks tau change
age 0.00000000 0.00569819 0.005691132 0 |
sex -0.04627467 -0.05483941 0.080379630 -1 |
bmi 0.31585107 0.05483941 2.350684568 1 |
map 0.14463335 0.05483941 0.194291389 1 |
tc 0.00000000 -0.03840588 0.042098341 0 |
ldl 0.00000000 -0.03788847 0.041986845 0 |
hdl -0.10482786 -0.05483941 0.132782843 -1 |
tch 0.00000000 0.02844749 0.010538828 0 |
ltg 0.27836968 0.05483941 1.100978007 1 |
glu 0.00000000 0.05483941 0.054839408 1 +
lambda_6 = 0.05483941
beta score breaks tau change
age 0.000000000 0.002026865 0.008269386 0 |
sex -0.069167263 -0.042598653 0.079582642 -1 |
bmi 0.316280991 0.042598653 9.047830952 1 |
map 0.155981676 0.042598653 0.210846751 1 |
tc 0.000000000 -0.042598653 0.042598653 -1 +
ldl 0.000000000 -0.042544022 0.042559075 0 |
hdl -0.121093961 -0.042598653 0.133725704 -1 |
tch 0.000000000 0.017165205 0.011499160 0 |
ltg 0.279435352 0.042598653 3.252298089 1 |
glu 0.007460471 0.042598653 0.054839408 1 |
lambda_7 = 0.04259865
beta score breaks tau change
age 0.00000000 -0.002166684 0.003405317 0 |
sex -0.12215085 -0.012342084 0.082096998 -1 |
bmi 0.32259418 0.012342084 1.558405741 1 |
map 0.18355055 0.012342084 0.213786990 1 |
tc -0.06420584 -0.012342084 0.042598653 -1 |
ldl 0.00000000 -0.007487901 0.003155702 0 |
hdl -0.13831533 -0.012342084 0.255351056 -1 |
tch 0.00000000 0.012342084 0.012342084 1 +
ltg 0.31795207 0.012342084 0.262107387 1 |
glu 0.03382907 0.012342084 0.051159147 1 |
lambda_8 = 0.01234208
beta score breaks tau change
age 0.00000000 -0.002995721 0.003028553 0 |
sex -0.13967895 -0.003383343 0.074774310 -1 |
bmi 0.32544826 0.003383343 1.024941235 1 |
map 0.19419295 0.003383343 0.166854508 1 |
tc -0.12051358 -0.003383343 0.022557439 -1 |
ldl 0.00000000 0.003383343 0.003383343 1 +
hdl -0.09418263 -0.003383343 -0.015735310 -1 |
tch 0.06568616 0.003383343 0.012342084 1 |
ltg 0.32732019 0.003383343 0.316399857 1 |
glu 0.03983279 0.003383343 0.062821789 1 |
lambda_9 = 0.003383343
beta score breaks tau change
age 0.00000000 -0.0031435 0.003143500 -1 +
sex -0.14032266 -0.0031435 0.055426929 -1 |
bmi 0.32514258 0.0031435 -0.251974729 1 |
map 0.19453959 0.0031435 0.137746439 1 |
tc -0.14660151 -0.0031435 0.004491299 -1 |
ldl 0.02077162 0.0031435 0.003383343 1 |
hdl -0.08313975 -0.0031435 0.001337770 -1 |
tch 0.06880010 0.0031435 0.008442640 1 |
ltg 0.33693539 0.0031435 0.011548053 1 |
glu 0.03990645 0.0031435 0.133081872 1 |
lambda_10 = 0.0031435
beta score breaks tau change
age -3.532498e-03 -0.001347939 0.003143500 -1 |
sex -1.447835e-01 -0.001347939 0.059626189 -1 |
bmi 3.228313e-01 0.001347939 -0.249452648 1 |
map 1.978702e-01 0.001347939 0.108021772 1 |
tc -3.423610e-01 -0.001347939 0.004488170 -1 |
ldl 1.771121e-01 0.001347939 0.003382061 1 |
hdl 6.938894e-18 -0.001347939 0.001347939 0 -
tch 9.197329e-02 0.001347939 0.008474434 1 |
ltg 4.095445e-01 0.001347939 0.011475627 1 |
glu 4.097151e-02 0.001347939 0.070420793 1 |
lambda_11 = 0.001347939
beta score breaks tau change
age -0.004330728 -0.0008094337 0.0037310460 -1 |
sex -0.146453153 -0.0008094337 0.0480429582 -1 |
bmi 0.321859313 0.0008094337 -0.1775025279 1 |
map 0.198615406 0.0008094337 0.1443318080 1 |
tc -0.358527126 -0.0008094337 0.0127521927 -1 |
ldl 0.193867341 0.0008094337 0.0070402302 1 |
hdl 0.000000000 0.0008094337 0.0008094337 1 +
tch 0.086387844 0.0008094337 -0.0075194059 1 |
ltg 0.416896956 0.0008094337 0.0313434791 1 |
glu 0.041495581 0.0008094337 0.0434479835 1 |
lambda_12 = 0.0008094337
beta score breaks tau change
age -0.006184366 -3.062871e-17 0.0027005460 -1 |
sex -0.148132204 -7.008147e-16 0.0714113308 -1 |
bmi 0.321096262 4.805726e-17 -0.3406144843 1 |
map 0.200370492 -1.654764e-16 0.0924095415 1 |
tc -0.489318785 6.683564e-16 0.0030282599 -1 |
ldl 0.294477857 -1.716021e-16 0.0023691391 1 |
hdl 0.062413526 -2.586364e-16 0.0008094337 1 |
tch 0.109369553 -4.500117e-16 0.0038520811 1 |
ltg 0.464052556 -4.467506e-16 0.0079655395 1 |
glu 0.041771060 -3.242866e-16 0.1227351912 1 |
lambda_13 = 0
beta score breaks tau change
age -0.006184366 -3.062871e-17 0.0027005460 -1 |
sex -0.148132204 -7.008147e-16 0.0714113308 -1 |
bmi 0.321096262 4.805726e-17 -0.3406144843 1 |
map 0.200370492 -1.654764e-16 0.0924095415 1 |
tc -0.489318785 6.683564e-16 0.0030282599 -1 |
ldl 0.294477857 -1.716021e-16 0.0023691391 1 |
hdl 0.062413526 -2.586364e-16 0.0008094337 1 |
tch 0.109369553 -4.500117e-16 0.0038520811 1 |
ltg 0.464052556 -4.467506e-16 0.0079655395 1 |
glu 0.041771060 -3.242866e-16 0.1227351912 1 |
lambda_14 = 0
> myfit
breaks:
[1] 0.5865 0.5493 0.2797 0.1952 0.0804 0.0548 0.0426 0.0123 0.0034 0.0031
[11] 0.0013 0.0008 0.0000 0.0000
Indicator matrix (parameters x breaks):
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0 0 0 0 0 0 0 0 -1 -1 -1 -1
[2,] 0 0 0 0 -1 -1 -1 -1 -1 -1 -1 -1 -1
[3,] 1 1 1 1 1 1 1 1 1 1 1 1 1
[4,] 0 0 1 1 1 1 1 1 1 1 1 1 1
[5,] 0 0 0 0 0 0 -1 -1 -1 -1 -1 -1 -1
[6,] 0 0 0 0 0 0 0 0 1 1 1 1 1
[7,] 0 0 0 -1 -1 -1 -1 -1 -1 -1 0 1 1
[8,] 0 0 0 0 0 0 0 1 1 1 1 1 1
[9,] 0 1 1 1 1 1 1 1 1 1 1 1 1
[10,] 0 0 0 0 0 1 1 1 1 1 1 1 1
[,14]
[1,] -1
[2,] -1
[3,] 1
[4,] 1
[5,] -1
[6,] 1
[7,] 1
[8,] 1
[9,] 1
[10,] 1
Beta matrix (parameters x breaks):
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 0 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
[2,] 0 0.0000 0.0000 0.0000 0.0000 -0.0463 -0.0692 -0.1222 -0.1397 -0.1403
[3,] 0 0.0371 0.2235 0.2685 0.3123 0.3159 0.3163 0.3226 0.3254 0.3251
[4,] 0 0.0000 0.0000 0.0489 0.1181 0.1446 0.1560 0.1836 0.1942 0.1945
[5,] 0 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 -0.0642 -0.1205 -0.1466
[6,] 0 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0208
[7,] 0 0.0000 0.0000 0.0000 -0.0705 -0.1048 -0.1211 -0.1383 -0.0942 -0.0831
[8,] 0 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0657 0.0688
[9,] 0 0.0000 0.1864 0.2316 0.2716 0.2784 0.2794 0.3180 0.3273 0.3369
[10,] 0 0.0000 0.0000 0.0000 0.0000 0.0000 0.0075 0.0338 0.0398 0.0399
[,11] [,12] [,13] [,14]
[1,] -0.0035 -0.0043 -0.0062 -0.0062
[2,] -0.1448 -0.1465 -0.1481 -0.1481
[3,] 0.3228 0.3219 0.3211 0.3211
[4,] 0.1979 0.1986 0.2004 0.2004
[5,] -0.3424 -0.3585 -0.4893 -0.4893
[6,] 0.1771 0.1939 0.2945 0.2945
[7,] 0.0000 0.0000 0.0624 0.0624
[8,] 0.0920 0.0864 0.1094 0.1094
[9,] 0.4095 0.4169 0.4641 0.4641
[10,] 0.0410 0.0415 0.0418 0.0418
Score matrix (parameters x breaks):
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
[1,] 0.1879 0.1810 0.0960 0.0591 0.0116 0.0057 0.0020 -0.0022 -0.0030
[2,] 0.0431 0.0398 -0.0046 -0.0271 -0.0804 -0.0548 -0.0426 -0.0123 -0.0034
[3,] 0.5865 0.5493 0.2797 0.1952 0.0804 0.0548 0.0426 0.0123 0.0034
[4,] 0.4415 0.4268 0.2797 0.1952 0.0804 0.0548 0.0426 0.0123 0.0034
[5,] 0.2120 0.2027 0.0601 0.0137 -0.0310 -0.0384 -0.0426 -0.0123 -0.0034
[6,] 0.1741 0.1644 0.0563 0.0211 -0.0297 -0.0379 -0.0425 -0.0075 0.0034
[7,] -0.3948 -0.3812 -0.2385 -0.1952 -0.0804 -0.0548 -0.0426 -0.0123 -0.0034
[8,] 0.4305 0.4151 0.2228 0.1636 0.0509 0.0284 0.0172 0.0123 0.0034
[9,] 0.5659 0.5493 0.2797 0.1952 0.0804 0.0548 0.0426 0.0123 0.0034
[10,] 0.3825 0.3680 0.2090 0.1514 0.0695 0.0548 0.0426 0.0123 0.0034
[,10] [,11] [,12] [,13] [,14]
[1,] -0.0031 -0.0013 -8e-04 0 0
[2,] -0.0031 -0.0013 -8e-04 0 0
[3,] 0.0031 0.0013 8e-04 0 0
[4,] 0.0031 0.0013 8e-04 0 0
[5,] -0.0031 -0.0013 -8e-04 0 0
[6,] 0.0031 0.0013 8e-04 0 0
[7,] -0.0031 -0.0013 8e-04 0 0
[8,] 0.0031 0.0013 8e-04 0 0
[9,] 0.0031 0.0013 8e-04 0 0
[10,] 0.0031 0.0013 8e-04 0 0
> plot(myfit)
>
>
>
>
>
> dev.off()
null device
1
>
|
Created & Maintained by Osamu Ogasawara (osamu.ogasawara@gmail.com) and