Last updated on 2014-10-10 15:49:11.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.6.6 | 34.18 | 78.86 | 113.04 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.6.6 | 34.61 | 78.47 | 113.08 | OK | |
| r-devel-linux-x86_64-fedora-clang | 1.6.6 | 205.09 | OK | |||
| r-devel-linux-x86_64-fedora-gcc | 1.6.6 | 201.59 | OK | |||
| r-devel-osx-x86_64-clang | 1.6.6 | 174.47 | OK | |||
| r-devel-windows-ix86+x86_64 | 1.6.6 | 77.00 | 155.00 | 232.00 | OK | |
| r-patched-linux-x86_64 | 1.6.6 | 34.33 | 80.86 | 115.18 | OK | |
| r-patched-solaris-sparc | 1.6.6 | 1661.80 | OK | |||
| r-patched-solaris-x86 | 1.6.6 | 341.70 | ERROR | |||
| r-release-linux-ix86 | 1.6.6 | 58.58 | 107.48 | 166.06 | OK | |
| r-release-linux-x86_64 | 1.6.6 | 34.63 | 81.30 | 115.92 | OK | |
| r-release-osx-x86_64-mavericks | 1.6.6 | WARN | ||||
| r-release-osx-x86_64-snowleopard | 1.6.6 | OK | ||||
| r-release-windows-ix86+x86_64 | 1.6.6 | 60.00 | 158.00 | 218.00 | OK | |
| r-oldrel-windows-ix86+x86_64 | 1.6.6 | 60.00 | 164.00 | 224.00 | OK |
Version: 1.6.6
Check: examples
Result: ERROR
Running examples in ‘lcmm-Ex.R’ failed
The error most likely occurred in:
> ### Name: Diffepoce
> ### Title: Computation of the difference of expected prognostic
> ### cross-entropy (EPOCE) estimators and its 95% tracking interval
> ### between two joint latent class models estimated with 'Jointlcmm'
> ### Aliases: Diffepoce
>
> ### ** Examples
>
> #### estimation with 2 latent classes (ng=2)
> data(data_Jointlcmm)
> m2 <- Jointlcmm(fixed= Ydep1~Time*X1,random=~Time,mixture=~Time,subject='ID'
+ ,survival = Surv(Tevent,Event)~ X1+X2 ,hazard="Weibull"
+ ,hazardtype="PH",ng=2,data=data_Jointlcmm,
+ B=c( 0.7608, -9.4974, 1.0242, 1.4331, 0.1063 , 0.6714, 10.4679, 11.3178,
+ -2.5671, -0.5386, 1.4616, -0.0605, 0.9489, 0.1020, 0.2079, 1.5045),logscale=TRUE)
Be patient, Jointlcmm is running ...
The program took 1.79 seconds
> m1 <- Jointlcmm(fixed= Ydep1~Time*X1,random=~Time,subject='ID'
+ ,survival = Surv(Tevent,Event)~ X1+X2 ,hazard="Weibull"
+ ,hazardtype="PH",ng=1,data=data_Jointlcmm,
+ B=c(-7.6634, 0.9136, 0.1002, 0.6641, 10.5675, -1.6589, 1.4767, -0.0806,
+ 0.9240,0.5643, 1.2277, 1.5004))
Be patient, Jointlcmm is running ...
The program took 6.66 seconds
>
> ## EPOCE computation for predictions times from 1 to 6 on the dataset used
> ## for estimation of m.
> VecTime <- c(1,3,5,7,9,11,13,15)
> cvpol1 <- epoce(m1,var.time="Time",pred.times=VecTime)
Be patient, epoce function is running ...
The program took 1.11 seconds
> cvpol1
Expected Prognostic Observed Cross-Entropy (EPOCE) of the joint latent class model:
Jointlcmm(fixed = Ydep1 ~ Time * X1, random = ~Time, subject = "ID",
ng = 1, survival = Surv(Tevent, Event) ~ X1 + X2, hazard = "Weibull",
hazardtype = "PH", data = data_Jointlcmm)
EPOCE estimators on data used for estimation:
Mean Prognostic Observed Log-likelihood (MPOL)
and Cross-validated Prognostic Observed Log-likelihood (CVPOL)
(CVPOL is the bias-corrected MPOL obtained by approximated cross-validation)
pred. times N at risk N events MPOL CVPOL
1 300 150 1.892619 .
3 299 150 1.889431 .
5 291 149 1.899210 .
7 258 127 1.785964 .
9 205 107 1.850733 .
11 158 81 1.793531 .
13 129 68 1.772987 .
15 99 49 1.656587 .
> cvpol2 <- epoce(m2,var.time="Time",pred.times=VecTime)
Be patient, epoce function is running ...
The program took 2.38 seconds
> cvpol2
Expected Prognostic Observed Cross-Entropy (EPOCE) of the joint latent class model:
Jointlcmm(fixed = Ydep1 ~ Time * X1, mixture = ~Time, random = ~Time,
subject = "ID", ng = 2, survival = Surv(Tevent, Event) ~
X1 + X2, hazard = "Weibull", hazardtype = "PH", data = data_Jointlcmm,
logscale = TRUE)
EPOCE estimators on data used for estimation:
Mean Prognostic Observed Log-likelihood (MPOL)
and Cross-validated Prognostic Observed Log-likelihood (CVPOL)
(CVPOL is the bias-corrected MPOL obtained by approximated cross-validation)
pred. times N at risk N events MPOL CVPOL
1 300 150 1.869272 2.548325
3 299 150 1.840027 2.490995
5 291 149 1.853149 2.514241
7 258 127 1.735359 2.464496
9 205 107 1.773111 2.734627
11 158 81 1.672144 2.812987
13 129 68 1.628349 2.956976
15 99 49 1.463446 3.152357
> DeltaEPOCE <- Diffepoce(cvpol1,cvpol2)
> summary(DeltaEPOCE)
Difference in Expected Prognostic Observed Cross-Entropy (EPOCE) estimates
from the two following joint latent class models:
Jointlcmm(fixed = Ydep1 ~ Time * X1, random = ~Time, subject = "ID",
ng = 1, survival = Surv(Tevent, Event) ~ X1 + X2, hazard = "Weibull",
hazardtype = "PH", data = data_Jointlcmm)
Jointlcmm(fixed = Ydep1 ~ Time * X1, mixture = ~Time, random = ~Time,
subject = "ID", ng = 2, survival = Surv(Tevent, Event) ~
X1 + X2, hazard = "Weibull", hazardtype = "PH", data = data_Jointlcmm,
logscale = TRUE)
Difference in the Cross-Validated Prognostic Observed Log-likelihood (CVPOL)
and its 95% tracking interval
pred. times Diff CVPOL 95%TIinf 95%TIsup
1 . . .
3 . . .
5 . . .
7 . . .
9 . . .
11 . . .
13 . . .
15 . . .
> plot(DeltaEPOCE,bty="l")
Error in plot.Diffepoce(DeltaEPOCE, bty = "l") :
can't produce the plot with missing differences in EPOCE
Calls: plot -> plot.Diffepoce
Execution halted
Flavor: r-patched-solaris-x86
Version: 1.6.6
Check: whether package can be installed
Result: WARN
Found the following significant warnings:
Warning: Possible change of value in conversion from REAL(8) to INTEGER(4) at (1)
Flavor: r-release-osx-x86_64-mavericks