ridge {leapp} | R Documentation |
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 |
sigma |
a numeric, noise standard deviation |
Value
p |
an N by 1 vector of p-values for each of the N genes |
gamma |
an N by 1 vector of estimated primary variable gamma |
Author(s)
Yunting Sun yunting.sun@gmail.com, Nancy R.Zhang nzhang@stanford.edu, Art B.Owen owen@stanford.edu
[Package leapp version 1.3 Index]