logdensity

Data matrix for the subject i in which the first column is id for subject, the second column is
the time points of observation. Columns 2 to (p+2) is the observations for p variables.

idata

omega

Parameter in exponential distribution

alpha

Type of correlation function, which can take either "abs" or "qua".

type

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

For high-dimensional correlated observations, this package carries out the L_1 penalized maximum likelihood
estimation of the precision matrix (network) and the correlation parameters. The correlated data can be
longitudinal data (may be irregularly spaced) with dampening correlation or clustered data with uniform correlation.
For the details of the algorithms, please see the paper Jie Zhou et al. Identifying Microbial Interaction Networks Based on Irregularly Spaced
Longitudinal 16S rRNA sequence data <doi:10.1101/2021.11.26.470159>.

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

Description

Usage

Arguments

Value