The fence procedure for generalised linear models

This function implements the fence procedure to find the best generalised linear model.

Usage

glmfence(mf, cstar, nvmax, adaptive = TRUE, trace = TRUE, ...)

Arguments

mf

an object of class glm specifying the full model.

cstar

the boundary of the fence, typically found through bootstrapping.

nvmax

the maximum number of variables that will be be considered in the model.

adaptive

logical. If TRUE the boundary of the fence is given by cstar. Otherwise, it the original (non-adaptive) fence is performed where the boundary is \(c^* \hat{\sigma}_{M,\tilde{M}}\).

trace

logical. If TRUE the function prints out its progress as it iterates up through the dimensions.

...

further arguments (currently unused)

References

Jiming Jiang, Thuan Nguyen, J. Sunil Rao, A simplified adaptive fence procedure, Statistics & Probability Letters, Volume 79, Issue 5, 1 March 2009, Pages 625-629, http://dx.doi.org/10.1016/j.spl.2008.10.014.

See also

af, lmfence

Other fence: af(), lmfence()