stabsel {mboost} | R Documentation |
Selection of influential variables or model components with error control.
stabsel(object, FWER = 0.05, cutoff, q, folds = cv(model.weights(object), type = "subsampling"), papply = if (require("multicore")) mclapply else lapply, ...)
object |
an |
FWER |
family-wise error rate to be controlled by the selection procedure. |
cutoff |
cutoff between 0.5 and 1. |
q |
average number of selected variables. |
folds |
a weight matrix with number of rows equal to the number
of observations, see |
papply |
(parallel) apply function. In the absence of package |
... |
additional arguments to |
This function implements the "stability selection" procedure by Meinshausen and Buehlmann (2010).
Either cutoff
or q
must be specified. The probability
of selecting at least one non-influential variable (or model component)
is less than FWER
.
An object of class stabsel
with elements
phat |
selection probabilities. |
selected |
elements with maximal selection probability greater |
max |
maximum of selection probabilities. |
cutoff |
cutoff used. |
q |
average number of selected variables used. |
FWER |
family-wise error rate. |
N. Meinshausen and P. Buehlmann (2010), Stability selection. Journal of the Royal Statistical Society, Series B, 72(4).
### (too) low-dimensional example sbody <- stabsel(glmboost(DEXfat ~ ., data = bodyfat), q = 3, papply = lapply) sbody opar <- par(mai = par("mai") * c(1, 1, 1, 2.7)) plot(sbody) par(opar)