Hello all,
I was writing to see if there was any way to always include a variable of interest in eNetXplorer models? By that, I mean to force a penalty to be 0 all the time. My hope was to have a "control" variable in all models, but allow others to be penalized, etc.
I thought I could simply add "penalty.factor" (from glmnet) in my eNetXplorer call, something like this:
fit01 = eNetXplorer(x=data, y=mtcars$disp,family="gaussian", penalty.factor=penalty,n_run=20, n_perm_null=10, seed=111)
(Per this webpage How can I force cv.glmnet not to drop one specific variable?)
But that didn't seem to work. I keep getting this error
Error in glmnet.control(...) : unused argument (penalty.factor = c(0, 1, 1))
Here's my R sessionInfo()
R version 4.1.3 (2022-03-10)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Monterey 12.1
Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] eNetXplorer_1.1.3
loaded via a namespace (and not attached):
[1] Rcpp_1.0.8.3 survcomp_1.44.1 compiler_4.1.3 RColorBrewer_1.1-3
[5] bitops_1.0-7 pec_2022.03.06 prettyunits_1.1.1 iterators_1.0.14
[9] tools_4.1.3 progress_1.2.2 digest_0.6.29 lifecycle_1.0.1
[13] lattice_0.20-45 pkgconfig_2.0.3 rlang_1.0.2 Matrix_1.4-0
[17] foreach_1.5.2 cli_3.2.0 parallel_4.1.3 expm_0.999-6
[21] mvtnorm_1.1-3 prodlim_2019.11.13 bootstrap_2019.6 caTools_1.18.2
[25] gtools_3.9.2 vctrs_0.4.1 SuppDists_1.1-9.7 globals_0.14.0
[29] hms_1.1.1 glmnet_4.1-4 grid_4.1.3 calibrate_1.7.7
[33] listenv_0.8.0 R6_2.5.1 timereg_2.0.2 future.apply_1.8.1
[37] parallelly_1.31.0 survival_3.2-13 lava_1.6.10 rmeta_3.0
[41] gplots_3.1.1 timeROC_0.4 survivalROC_1.0.3 codetools_0.2-18
[45] ellipsis_0.3.2 MASS_7.3-55 splines_4.1.3 future_1.24.0
[49] shape_1.4.6 numDeriv_2016.8-1.1 KernSmooth_2.23-20 crayon_1.5.1
And I should say I was trying some test data, so I just specified the penalty before the enet call with this syntax:
penalty<-c(0, rep(1, ncol(data) - 1))
Any thoughts or suggestions are much appreciated!
Thanks,
Jamie.
Hello all,
I was writing to see if there was any way to always include a variable of interest in eNetXplorer models? By that, I mean to force a penalty to be 0 all the time. My hope was to have a "control" variable in all models, but allow others to be penalized, etc.
I thought I could simply add "penalty.factor" (from glmnet) in my eNetXplorer call, something like this:
fit01 = eNetXplorer(x=data, y=mtcars$disp,family="gaussian", penalty.factor=penalty,n_run=20, n_perm_null=10, seed=111)(Per this webpage How can I force cv.glmnet not to drop one specific variable?)
But that didn't seem to work. I keep getting this error
Error in glmnet.control(...) : unused argument (penalty.factor = c(0, 1, 1))Here's my R sessionInfo()
R version 4.1.3 (2022-03-10)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Monterey 12.1
Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] eNetXplorer_1.1.3
loaded via a namespace (and not attached):
[1] Rcpp_1.0.8.3 survcomp_1.44.1 compiler_4.1.3 RColorBrewer_1.1-3
[5] bitops_1.0-7 pec_2022.03.06 prettyunits_1.1.1 iterators_1.0.14
[9] tools_4.1.3 progress_1.2.2 digest_0.6.29 lifecycle_1.0.1
[13] lattice_0.20-45 pkgconfig_2.0.3 rlang_1.0.2 Matrix_1.4-0
[17] foreach_1.5.2 cli_3.2.0 parallel_4.1.3 expm_0.999-6
[21] mvtnorm_1.1-3 prodlim_2019.11.13 bootstrap_2019.6 caTools_1.18.2
[25] gtools_3.9.2 vctrs_0.4.1 SuppDists_1.1-9.7 globals_0.14.0
[29] hms_1.1.1 glmnet_4.1-4 grid_4.1.3 calibrate_1.7.7
[33] listenv_0.8.0 R6_2.5.1 timereg_2.0.2 future.apply_1.8.1
[37] parallelly_1.31.0 survival_3.2-13 lava_1.6.10 rmeta_3.0
[41] gplots_3.1.1 timeROC_0.4 survivalROC_1.0.3 codetools_0.2-18
[45] ellipsis_0.3.2 MASS_7.3-55 splines_4.1.3 future_1.24.0
[49] shape_1.4.6 numDeriv_2016.8-1.1 KernSmooth_2.23-20 crayon_1.5.1
And I should say I was trying some test data, so I just specified the penalty before the enet call with this syntax:
penalty<-c(0, rep(1, ncol(data) - 1))Any thoughts or suggestions are much appreciated!
Thanks,
Jamie.