Prostate: Prostate Cancer Data
In lasso2: L1 Constrained Estimation aka `lasso'
Description
Usage
Format
Source
Examples
Description
These data come from a study that examined the correlation between the
level of prostate specific antigen and a number of clinical measures
in men who were about to receive a radical prostatectomy. It is data
frame with 97 rows and 9 columns.
Usage
1
Format
The data frame has the following components:
lcavollog(cancer volume)
lweightlog(prostate weight)
ageage
lbphlog(benign prostatic hyperplasia amount)
sviseminal vesicle invasion
lcplog(capsular penetration)
gleasonGleason score
pgg45percentage Gleason scores 4 or 5
lpsalog(prostate specific antigen)
Source
Stamey, T.A., Kabalin, J.N., McNeal, J.E., Johnstone, I.M., Freiha,
F., Redwine, E.A. and Yang, N. (1989)
Prostate specific antigen in the diagnosis and treatment of
adenocarcinoma of the prostate: II. radical prostatectomy treated
patients,
Journal of Urology 141(5), 1076–1083.
Examples
1
2
3
4
5
6
7
8
9
Example output
R Package to solve regression problems while imposing
an L1 constraint on the parameters. Based on S-plus Release 2.1
Copyright (C) 1998, 1999
Justin Lokhorst <jlokhors@stats.adelaide.edu.au>
Berwin A. Turlach <bturlach@stats.adelaide.edu.au>
Bill Venables <wvenable@stats.adelaide.edu.au>
Copyright (C) 2002
Martin Maechler <maechler@stat.math.ethz.ch>
(Intercept) age lcp lpsa
0.063731165 0.002632999 0.279970078 0.471409992
$call
l1ce(formula = lcavol ~ ., data = Prostate)
$terms
lcavol ~ lweight + age + lbph + svi + lcp + gleason + pgg45 +
lpsa
attr(,"variables")
list(lcavol, lweight, age, lbph, svi, lcp, gleason, pgg45, lpsa)
attr(,"factors")
lweight age lbph svi lcp gleason pgg45 lpsa
lcavol 0 0 0 0 0 0 0 0
lweight 1 0 0 0 0 0 0 0
age 0 1 0 0 0 0 0 0
lbph 0 0 1 0 0 0 0 0
svi 0 0 0 1 0 0 0 0
lcp 0 0 0 0 1 0 0 0
gleason 0 0 0 0 0 1 0 0
pgg45 0 0 0 0 0 0 1 0
lpsa 0 0 0 0 0 0 0 1
attr(,"term.labels")
[1] "lweight" "age" "lbph" "svi" "lcp" "gleason" "pgg45"
[8] "lpsa"
attr(,"order")
[1] 1 1 1 1 1 1 1 1
attr(,"intercept")
[1] 1
attr(,"response")
[1] 1
attr(,".Environment")
<environment: R_GlobalEnv>
$bound
[1] 0.9552333
$relative.bound
[1] 0.5
$Lagrangian
[1] 9.919065
$residuals
[1] -0.184003307 -0.745963402 -0.304664739 -0.955683933 0.737401143
[6] -1.217931497 0.532192705 0.462043081 -1.069606614 -0.112062260
[11] -0.189364712 -1.785814580 0.953944533 0.989532403 0.453395902
[16] 1.009678835 -1.189235663 1.243180472 -1.080207051 -0.431565895
[21] 0.543805849 0.678402290 -1.175014492 0.414209422 -0.288344494
[26] 0.759546565 -0.347059679 -1.108792397 -0.084905253 0.828246485
[31] -0.633248949 -0.611125775 0.466117473 -0.760819570 -0.981405054
[36] 0.481003984 -0.314181037 -0.419864699 0.861529810 -0.441698039
[41] -0.296112346 0.499735027 -0.621257132 0.200622148 0.180472613
[46] 0.624031137 0.501349896 -0.169970367 0.735219623 -0.025319643
[51] -0.015152621 0.553765706 -0.998551269 0.210492510 2.047605249
[56] 0.136266824 -0.667459439 -0.658120119 -0.640554326 -0.100764950
[61] -0.750140654 -0.112019192 0.740955852 -0.152205269 0.870444506
[66] -0.006361599 0.033305355 0.668991482 -1.700217081 -0.237316632
[71] -0.148079520 -0.150169245 -0.533766061 -0.162326474 0.675214810
[76] 0.647371541 0.017972242 1.037097447 0.049364909 0.789722726
[81] -0.489591968 -0.016160939 0.509141588 0.269614391 -0.577667769
[86] 0.707355190 0.461037245 -0.329381613 0.004653119 -0.811153349
[91] 1.492145989 0.749968154 0.150238638 0.825856933 -0.407525218
[96] -0.378597894 -0.215738025
$coefficients
Value Std. Error Z score Pr(>|Z|)
(Intercept) 0.063731165 1.199016536 0.05315287 9.576101e-01
lweight 0.000000000 0.183332828 0.00000000 1.000000e+00
age 0.002632999 0.010450454 0.25195071 8.010792e-01
lbph 0.000000000 0.057378690 0.00000000 1.000000e+00
svi 0.000000000 0.265446589 0.00000000 1.000000e+00
lcp 0.279970078 0.083505159 3.35272793 8.001932e-04
gleason 0.000000000 0.155913663 0.00000000 1.000000e+00
pgg45 0.000000000 0.004210145 0.00000000 1.000000e+00
lpsa 0.471409992 0.087040399 5.41599069 6.095027e-08
$sigma
[1] 0.7390027
$sigma.provided
[1] FALSE
$df
[1] 8.647483 88.352517
$cov.unscaled
(Intercept) lweight age lbph
(Intercept) 2.632439099 -2.228716e-01 -4.315601e-03 2.499517e-02
lweight -0.222871641 6.154439e-02 -6.498758e-04 -7.510978e-03
age -0.004315601 -6.498758e-04 1.999762e-04 -1.182572e-04
lbph 0.024995166 -7.510978e-03 -1.182572e-04 6.028500e-03
svi -0.076153397 1.975010e-04 -1.334891e-04 4.342878e-03
lcp 0.051483631 2.917533e-04 -4.286151e-05 1.062060e-03
gleason -0.250882183 9.117477e-03 -8.815802e-04 1.699316e-03
pgg45 0.003373728 -8.416181e-06 4.897781e-06 -8.956487e-05
lpsa 0.041409306 -8.482809e-03 -8.702343e-05 -2.634989e-04
svi lcp gleason pgg45
(Intercept) -0.0761533966 5.148363e-02 -0.2508821826 3.373728e-03
lweight 0.0001975010 2.917533e-04 0.0091174769 -8.416181e-06
age -0.0001334891 -4.286151e-05 -0.0008815802 4.897781e-06
lbph 0.0043428776 1.062060e-03 0.0016993157 -8.956487e-05
svi 0.1290215590 -1.752261e-02 0.0139812959 -3.434002e-04
lcp -0.0175226146 1.276834e-02 -0.0046949368 -1.427475e-04
gleason 0.0139812959 -4.694937e-03 0.0445119208 -6.773287e-04
pgg45 -0.0003434002 -1.427475e-04 -0.0006773287 3.245653e-05
lpsa -0.0135536061 -3.490752e-03 -0.0057350112 7.437056e-05
lpsa
(Intercept) 4.140931e-02
lweight -8.482809e-03
age -8.702343e-05
lbph -2.634989e-04
svi -1.355361e-02
lcp -3.490752e-03
gleason -5.735011e-03
pgg45 7.437056e-05
lpsa 1.387234e-02
$correlation
(Intercept) lweight age lbph svi
(Intercept) 1.0000000 -0.553708784 -0.18809316 0.19841397 -0.130670926
lweight -0.5537088 1.000000000 -0.18524522 -0.38993986 0.002216378
age -0.1880932 -0.185245219 1.00000000 -0.10770454 -0.026280003
lbph 0.1984140 -0.389939860 -0.10770454 1.00000000 0.155719077
svi -0.1306709 0.002216378 -0.02628000 0.15571908 1.000000000
lcp 0.2808166 0.010407687 -0.02682323 0.12105343 -0.431718309
gleason -0.7329131 0.174197643 -0.29548438 0.10373643 0.184492246
pgg45 0.3649891 -0.005954836 0.06079379 -0.20247997 -0.167810234
lpsa 0.2166925 -0.290315750 -0.05224831 -0.02881372 -0.320367792
lcp gleason pgg45 lpsa
(Intercept) 0.28081655 -0.7329131 0.364989051 0.21669252
lweight 0.01040769 0.1741976 -0.005954836 -0.29031575
age -0.02682323 -0.2954844 0.060793794 -0.05224831
lbph 0.12105343 0.1037364 -0.202479970 -0.02881372
svi -0.43171831 0.1844922 -0.167810234 -0.32036779
lcp 1.00000000 -0.1969356 -0.221743156 -0.26228704
gleason -0.19693562 1.0000000 -0.563521294 -0.23079226
pgg45 -0.22174316 -0.5635213 1.000000000 0.11083455
lpsa -0.26228704 -0.2307923 0.110834555 1.00000000
attr(,"class")
[1] "summary.l1ce"
lasso2 documentation built on Oct. 8, 2021, 9:10 a.m.
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Description Usage Format Source Examples
Description
These data come from a study that examined the correlation between the level of prostate specific antigen and a number of clinical measures in men who were about to receive a radical prostatectomy. It is data frame with 97 rows and 9 columns.
Usage
1 |
Format
The data frame has the following components:
lcavollog(cancer volume)
lweightlog(prostate weight)
ageage
lbphlog(benign prostatic hyperplasia amount)
sviseminal vesicle invasion
lcplog(capsular penetration)
gleasonGleason score
pgg45percentage Gleason scores 4 or 5
lpsalog(prostate specific antigen)
Source
Stamey, T.A., Kabalin, J.N., McNeal, J.E., Johnstone, I.M., Freiha,
F., Redwine, E.A. and Yang, N. (1989)
Prostate specific antigen in the diagnosis and treatment of
adenocarcinoma of the prostate: II. radical prostatectomy treated
patients,
Journal of Urology 141(5), 1076–1083.
Examples
1 2 3 4 5 6 7 8 9 |
Example output
R Package to solve regression problems while imposing
an L1 constraint on the parameters. Based on S-plus Release 2.1
Copyright (C) 1998, 1999
Justin Lokhorst <jlokhors@stats.adelaide.edu.au>
Berwin A. Turlach <bturlach@stats.adelaide.edu.au>
Bill Venables <wvenable@stats.adelaide.edu.au>
Copyright (C) 2002
Martin Maechler <maechler@stat.math.ethz.ch>
(Intercept) age lcp lpsa
0.063731165 0.002632999 0.279970078 0.471409992
$call
l1ce(formula = lcavol ~ ., data = Prostate)
$terms
lcavol ~ lweight + age + lbph + svi + lcp + gleason + pgg45 +
lpsa
attr(,"variables")
list(lcavol, lweight, age, lbph, svi, lcp, gleason, pgg45, lpsa)
attr(,"factors")
lweight age lbph svi lcp gleason pgg45 lpsa
lcavol 0 0 0 0 0 0 0 0
lweight 1 0 0 0 0 0 0 0
age 0 1 0 0 0 0 0 0
lbph 0 0 1 0 0 0 0 0
svi 0 0 0 1 0 0 0 0
lcp 0 0 0 0 1 0 0 0
gleason 0 0 0 0 0 1 0 0
pgg45 0 0 0 0 0 0 1 0
lpsa 0 0 0 0 0 0 0 1
attr(,"term.labels")
[1] "lweight" "age" "lbph" "svi" "lcp" "gleason" "pgg45"
[8] "lpsa"
attr(,"order")
[1] 1 1 1 1 1 1 1 1
attr(,"intercept")
[1] 1
attr(,"response")
[1] 1
attr(,".Environment")
<environment: R_GlobalEnv>
$bound
[1] 0.9552333
$relative.bound
[1] 0.5
$Lagrangian
[1] 9.919065
$residuals
[1] -0.184003307 -0.745963402 -0.304664739 -0.955683933 0.737401143
[6] -1.217931497 0.532192705 0.462043081 -1.069606614 -0.112062260
[11] -0.189364712 -1.785814580 0.953944533 0.989532403 0.453395902
[16] 1.009678835 -1.189235663 1.243180472 -1.080207051 -0.431565895
[21] 0.543805849 0.678402290 -1.175014492 0.414209422 -0.288344494
[26] 0.759546565 -0.347059679 -1.108792397 -0.084905253 0.828246485
[31] -0.633248949 -0.611125775 0.466117473 -0.760819570 -0.981405054
[36] 0.481003984 -0.314181037 -0.419864699 0.861529810 -0.441698039
[41] -0.296112346 0.499735027 -0.621257132 0.200622148 0.180472613
[46] 0.624031137 0.501349896 -0.169970367 0.735219623 -0.025319643
[51] -0.015152621 0.553765706 -0.998551269 0.210492510 2.047605249
[56] 0.136266824 -0.667459439 -0.658120119 -0.640554326 -0.100764950
[61] -0.750140654 -0.112019192 0.740955852 -0.152205269 0.870444506
[66] -0.006361599 0.033305355 0.668991482 -1.700217081 -0.237316632
[71] -0.148079520 -0.150169245 -0.533766061 -0.162326474 0.675214810
[76] 0.647371541 0.017972242 1.037097447 0.049364909 0.789722726
[81] -0.489591968 -0.016160939 0.509141588 0.269614391 -0.577667769
[86] 0.707355190 0.461037245 -0.329381613 0.004653119 -0.811153349
[91] 1.492145989 0.749968154 0.150238638 0.825856933 -0.407525218
[96] -0.378597894 -0.215738025
$coefficients
Value Std. Error Z score Pr(>|Z|)
(Intercept) 0.063731165 1.199016536 0.05315287 9.576101e-01
lweight 0.000000000 0.183332828 0.00000000 1.000000e+00
age 0.002632999 0.010450454 0.25195071 8.010792e-01
lbph 0.000000000 0.057378690 0.00000000 1.000000e+00
svi 0.000000000 0.265446589 0.00000000 1.000000e+00
lcp 0.279970078 0.083505159 3.35272793 8.001932e-04
gleason 0.000000000 0.155913663 0.00000000 1.000000e+00
pgg45 0.000000000 0.004210145 0.00000000 1.000000e+00
lpsa 0.471409992 0.087040399 5.41599069 6.095027e-08
$sigma
[1] 0.7390027
$sigma.provided
[1] FALSE
$df
[1] 8.647483 88.352517
$cov.unscaled
(Intercept) lweight age lbph
(Intercept) 2.632439099 -2.228716e-01 -4.315601e-03 2.499517e-02
lweight -0.222871641 6.154439e-02 -6.498758e-04 -7.510978e-03
age -0.004315601 -6.498758e-04 1.999762e-04 -1.182572e-04
lbph 0.024995166 -7.510978e-03 -1.182572e-04 6.028500e-03
svi -0.076153397 1.975010e-04 -1.334891e-04 4.342878e-03
lcp 0.051483631 2.917533e-04 -4.286151e-05 1.062060e-03
gleason -0.250882183 9.117477e-03 -8.815802e-04 1.699316e-03
pgg45 0.003373728 -8.416181e-06 4.897781e-06 -8.956487e-05
lpsa 0.041409306 -8.482809e-03 -8.702343e-05 -2.634989e-04
svi lcp gleason pgg45
(Intercept) -0.0761533966 5.148363e-02 -0.2508821826 3.373728e-03
lweight 0.0001975010 2.917533e-04 0.0091174769 -8.416181e-06
age -0.0001334891 -4.286151e-05 -0.0008815802 4.897781e-06
lbph 0.0043428776 1.062060e-03 0.0016993157 -8.956487e-05
svi 0.1290215590 -1.752261e-02 0.0139812959 -3.434002e-04
lcp -0.0175226146 1.276834e-02 -0.0046949368 -1.427475e-04
gleason 0.0139812959 -4.694937e-03 0.0445119208 -6.773287e-04
pgg45 -0.0003434002 -1.427475e-04 -0.0006773287 3.245653e-05
lpsa -0.0135536061 -3.490752e-03 -0.0057350112 7.437056e-05
lpsa
(Intercept) 4.140931e-02
lweight -8.482809e-03
age -8.702343e-05
lbph -2.634989e-04
svi -1.355361e-02
lcp -3.490752e-03
gleason -5.735011e-03
pgg45 7.437056e-05
lpsa 1.387234e-02
$correlation
(Intercept) lweight age lbph svi
(Intercept) 1.0000000 -0.553708784 -0.18809316 0.19841397 -0.130670926
lweight -0.5537088 1.000000000 -0.18524522 -0.38993986 0.002216378
age -0.1880932 -0.185245219 1.00000000 -0.10770454 -0.026280003
lbph 0.1984140 -0.389939860 -0.10770454 1.00000000 0.155719077
svi -0.1306709 0.002216378 -0.02628000 0.15571908 1.000000000
lcp 0.2808166 0.010407687 -0.02682323 0.12105343 -0.431718309
gleason -0.7329131 0.174197643 -0.29548438 0.10373643 0.184492246
pgg45 0.3649891 -0.005954836 0.06079379 -0.20247997 -0.167810234
lpsa 0.2166925 -0.290315750 -0.05224831 -0.02881372 -0.320367792
lcp gleason pgg45 lpsa
(Intercept) 0.28081655 -0.7329131 0.364989051 0.21669252
lweight 0.01040769 0.1741976 -0.005954836 -0.29031575
age -0.02682323 -0.2954844 0.060793794 -0.05224831
lbph 0.12105343 0.1037364 -0.202479970 -0.02881372
svi -0.43171831 0.1844922 -0.167810234 -0.32036779
lcp 1.00000000 -0.1969356 -0.221743156 -0.26228704
gleason -0.19693562 1.0000000 -0.563521294 -0.23079226
pgg45 -0.22174316 -0.5635213 1.000000000 0.11083455
lpsa -0.26228704 -0.2307923 0.110834555 1.00000000
attr(,"class")
[1] "summary.l1ce"
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