ridgePvals: Significance testing in linear ridge regression
In bkaczkowski/xcore: xcore expression regulators inference

ridgePvals

R Documentation

Significance testing in linear ridge regression

Description

Standard error estimation and significance testing for coefficients estimated in linear ridge regression. ridgePvals re-implement original method by (Cule et al. BMC Bioinformatics 2011.) found in ridge-package. This function is intended to use with cv.glmnet output.

Usage

ridgePvals(x, y, beta, lambda, standardizex = TRUE, svdX = NULL)

Arguments

`x`	input matrix, same as used in `cv.glmnet`.
`y`	response variable, same as used in `cv.glmnet`.
`beta`	matrix of coefficients, estimated using `cv.glmnet`.
`lambda`	lambda value for which `beta` was estimated.
`standardizex`	logical flag for x variable standardization, should be set to same value as `standarize` flag in `cv.glmnet`.
`svdX`	optional singular-value decomposition of `x` matrix. One can be obtained using `link[base]{svd}`. Passing this argument omits internal call to `link[base]{svd}`, this is useful when calling `ridgePvals` repeatedly using same `x`.