logliklasso: Estimation of Log-likelihood for Linear Mixed Model with...

In sahirbhatnagar/penfam: Variable Selection in Linear Mixed Models for SNP Data

Description

sigma2lasso estimates the value of the sigma2 for the linear mixed model with lasso penalty

Usage

logliklasso(ggmix_object, ...)

## Default S3 method:
logliklasso(ggmix_object, ...)

## S3 method for class 'fullrank'
logliklasso(ggmix_object, ..., eta, sigma2, beta, nt, x, y)

Arguments

ggmix_object	A ggmix_object object of class lowrank or fullrank
...	Extra parameters. Currently ignored.
eta	current estimate of the eta parameter
sigma2	current estimate of the sigma2 parameter
beta	current estimate of the beta parameter including the intercept. this should be of length p+1, where p is the number of variables.
nt	total number of observations
x	input matrix, of dimension n x p; where n is the number of observations and p are the number of predictors.
y	response variable. must be a quantitative variable

Value

A decreasing sequence of tuning parameters

Note

This function isn't meant to be called directly by the user.

See Also

ggmix

ggmix_data_object

sahirbhatnagar/penfam documentation built on April 14, 2021, 9:38 a.m.