mle_alpha

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

data

Initial value for the parameter in exponential distribution

alpha0

omega

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

type

Error tolerance for determination of convergence of EM algorithm

tole

Lower bound for prediction of correlation parameter tau

lower

Upper bound for prediction of correlation parameter tau

upper

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

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>.

mle_alpha: Maximum likelihood estimate of correlation parameter for given structure of precision matrix

Description

Usage

Arguments