[Mboost-commits] r764 - in pkg/mboostDevel: R man tests
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Mon Mar 24 16:33:40 CET 2014
Author: hofner
Date: 2014-03-24 16:33:40 +0100 (Mon, 24 Mar 2014)
New Revision: 764
Modified:
pkg/mboostDevel/R/inference.R
pkg/mboostDevel/man/stabsel.Rd
pkg/mboostDevel/tests/regtest-inference.R
Log:
- added argumnent eval to stabsel to extract stabsel parameter combinations
for fitted mboost models
Modified: pkg/mboostDevel/R/inference.R
===================================================================
--- pkg/mboostDevel/R/inference.R 2014-02-21 09:45:25 UTC (rev 763)
+++ pkg/mboostDevel/R/inference.R 2014-03-24 15:33:40 UTC (rev 764)
@@ -4,7 +4,7 @@
B = ifelse(sampling.type == "MB", 100, 50)),
assumption = c("unimodal", "r-concave", "none"),
sampling.type = c("SS", "MB"),
- papply = mclapply, verbose = TRUE, FWER, ...) {
+ papply = mclapply, verbose = TRUE, FWER, eval = TRUE, ...) {
call <- match.call()
p <- length(variable.names(object))
@@ -18,10 +18,14 @@
B <- ncol(folds)
- pars <- stabsel_parameters(cutoff = cutoff, q = q,
- PFER = PFER, p = p, B = B,
+ pars <- stabsel_parameters(p = p, cutoff = cutoff, q = q,
+ PFER = PFER, B = B,
verbose = verbose, sampling.type = sampling.type,
assumption = assumption)
+ ## return parameter combination only if eval == FALSE
+ if (!eval)
+ return(pars)
+
cutoff <- pars$cutoff
q <- pars$q
PFER <- pars$PFER
@@ -77,7 +81,7 @@
ret
}
-stabsel_parameters <- function(cutoff, q, PFER, p,
+stabsel_parameters <- function(p, cutoff, q, PFER,
B = ifelse(sampling.type == "MB", 100, 50),
assumption = c("unimodal", "r-concave", "none"),
sampling.type = c("SS", "MB"),
Modified: pkg/mboostDevel/man/stabsel.Rd
===================================================================
--- pkg/mboostDevel/man/stabsel.Rd 2014-02-21 09:45:25 UTC (rev 763)
+++ pkg/mboostDevel/man/stabsel.Rd 2014-03-24 15:33:40 UTC (rev 764)
@@ -1,6 +1,8 @@
\name{stabsel}
\alias{stabsel}
\alias{stabsel_parameters}
+\alias{stabsel_parameters.default}
+\alias{stabsel_parameters.mboost}
\title{
Stability Selection
}
@@ -13,11 +15,11 @@
B = ifelse(sampling.type == "MB", 100, 50)),
assumption = c("unimodal", "r-concave", "none"),
sampling.type = c("SS", "MB"),
- papply = mclapply, verbose = TRUE, FWER, ...)
+ papply = mclapply, verbose = TRUE, FWER, eval = TRUE, ...)
## function to compute missing parameter from the other two parameters
## (internally used within stabsel)
-stabsel_parameters(cutoff, q, PFER, p,
+stabsel_parameters(p, cutoff, q, PFER,
B = ifelse(sampling.type == "MB", 100, 50),
assumption = c("unimodal", "r-concave", "none"),
sampling.type = c("SS", "MB"),
@@ -56,9 +58,11 @@
\code{warnings} should be issued. }
\item{FWER}{ deprecated. Only for compatibility with older versions,
use PFER instead.}
- \item{\dots}{additional arguments to \code{\link{cvrisk}} and
- further arguments to parallel apply methods such as
- \code{\link{mclapply}}.}
+ \item{eval}{ logical. Determines whether stability selection is
+ evaluated (\code{eval = TRUE}; default) or if only the parameter
+ combination is returned.}
+ \item{\dots}{additional arguments to \code{\link{cvrisk}} and further
+ arguments to parallel apply methods such as \code{\link{mclapply}}.}
}
\details{
@@ -116,6 +120,8 @@
## p = ncol(bodyfat) - 1 (= Outcome) + 1 ( = Intercept)
stabsel_parameters(q = 3, PFER = 1, p = ncol(bodyfat) - 1 + 1,
sampling.type = "MB")
+ ## the same:
+ stabsel(mod, q = 3, PFER = 1, sampling.type = "MB", eval = FALSE)
## now run stability selection; to make results reproducible
set.seed(1234)
Modified: pkg/mboostDevel/tests/regtest-inference.R
===================================================================
--- pkg/mboostDevel/tests/regtest-inference.R 2014-02-21 09:45:25 UTC (rev 763)
+++ pkg/mboostDevel/tests/regtest-inference.R 2014-03-24 15:33:40 UTC (rev 764)
@@ -155,7 +155,10 @@
(sbody <- stabsel(mod, q = 3, PFER = 0.2, sampling.type = "SS"))
dim(sbody$phat)
+## check interface of stabsel_parameters
+stabsel(mod, q = 3, PFER = 0.2, sampling.type = "SS", eval = FALSE)
+
## check stabsel_parameters and (theoretical) error control
cutoff <- 0.6
for (i in 1:10) {
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