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lglasso

The goal of lglasso is to estimate the Gaussian graphical model(network) based on the high-dimensional longitudinal data.

Installation

You will be able to install the released version of lglasso soon from CRAN with:

install.packages("lglasso")

And currently the development version can be installed from GitHub with:

# install.packages("devtools")
devtools::install_github("jiezhou-2/lglasso")

For the usage of lglasso package, please check the vignette at https://jiezhou-2.github.io/lglasso/articles/Introduction_of_lglasso_package.html for details.

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Version

Install

install.packages('lglasso')

Monthly Downloads

194

Version

0.1.0

License

GPL-3

Issues

1

Pull Requests

0

Stars

1

Forks

0

Maintainer

Jie Zhou

Last Published

January 15th, 2022

Functions in lglasso (0.1.0)

mle_alpha

Maximum likelihood estimate of correlation parameter for given structure of precision matrix
lglasso

Graphical Lasso for Longitudinal Data
sample_data

Sample Data
mle_net

Title
logdensity

Complete likelihood function used in EM algorithm of heterogeneous marginal graphical lasso model
lli_homo

full log likelihood used in EBIC computation
iss

Quasi covariance matrix for subject i
ll_homo

Value of likelihood function at given parameter
mle

Maximum Likelihood Estimate of Precision Matrix and Correlation Parameters for Given Network
heterlongraph

Estimates of correlation parameters and precision matrix
homolongraph

Estiamte of precision matrix and autocorrelaton parameter for homogeneous model
mle_tau

Estiamte of precision matrix and autocorrelaton parameter for homogeneous model
phifunction

Construct the temporal component fo correlation function