leapp (version 1.2)

ridge: Outlier detection with a ridge penalty

Description

Outlier detection and robust regression with a ridge type penalty on the outlier indicator gamma. Allow non sparse outliers and require known noise standard deviation.

Usage

ridge(X, Y, H, sigma)

Arguments

X
an N by k design matrix
Y
an N by 1 response vector
H
an N by N projection matrix X(X'X)^{-1}X'
sigma
a numeric, noise standard deviation

Value

  • pan N by 1 vector of p-values for each of the N genes
  • gammaan N by 1 vector of estimated primary variable gamma