regrlin: Linear regression with PRESS leave one out estimate

View source: R/lin.R

regrlinR Documentation

Linear regression with PRESS leave one out estimate

Description

Linear regression

Usage

regrlin(X, Y, X.ts = NULL, lambda = 0.001)

Arguments

X:

training input

Y:

training output

X.ts:

test input

lambda:

regularization parameter

Value

a list with fields:

  • e: training error,

  • beta.hat: coeffcients,

  • MSE.emp: training MSE,

  • sdse.emp: standard deviation of squared error,

  • var.hat: estimated noise variance;

  • MSE.loo: PRESS MSE,

  • sdse.loo: standard deviation of squared leave-one-out error error,

  • Y.hat: predicted training output,

  • Y.hat.ts: predicted test output,

  • e.loo: leave-one-out error

Author(s)

Gianluca Bontempi gbonte@ulb.ac.be

References

mlg.ulb.ac.be

Examples

N<-100
n<-10
X<-array(rnorm(N*n),c(N,n))
Y<-sin(X[,1]*X[,2])
R<-regrlin(X,Y,X)



gbonte/gbcode documentation built on Aug. 30, 2024, 1:11 a.m.