`mle.Rd`

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

`mle(data,network,heter,ty,tole,lower,upper)`

- data
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.

- heter
Binary variable

`TRUE`

or`FALSE`

, indicating heterogeneous model or homogeneous model is fitted. In heterogeneous model, subjects are allowed to have his/her own temporal correlation parameter`tau_i`

; while in homogeneous model, all the subjects are assumed to share the same temporal correlation parameter,i.e.,`tau_1=tau_2=...tau_m`

.- network
The structure of precision matrix

- tole
Error tolerance for determination of convergence of EM algorithm

- lower
Lower bound for prediction of correlation parameter tau

- upper
Upper bound for prediction of correlation parameter tau

- ty
Type of correlation function

A list which include the maximum likelihood estimate of precision matrix, correlation parameter `tau`

. If `heter=TRUE`

,
the output also include the estimate of alpha where `tau~exp(alpha)`