mle {lglasso}

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

Description

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

Usage

mle(
  data,
  network,
  heter = TRUE,
  type = 1,
  tole = 0.01,
  lower = 0.01,
  upper = 10
)

Arguments

data

Data matrix in which the first column is subject id, the second column is time points of observations for temporal data or site id for spatial data. Columns 3 to (p+2) is the observations for p variables.

network

The network selected by function lglasso

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.

type

A positive number which specify the correlation function. The general form of correlation function is given by exp(tau|t_i-t_j|^type). in which type=0 can be used for spatial correlation while type>0 are used for temporal correlation. For latter, the default value is set to be type=1.

tole

Threshold for convergence. Default value is 1e-2. Iterations stop when maximum absolute difference between consecutive estimates of parameter change is less than tole.

lower

Lower bound for predicts of correlation parameter tau. Default value is 1e-2. The estimate of tau(alpha) will be searched in the interval [lower,upper], where parameter upper is explained in the following.

upper

Upper bound for predicts of correlation parameter tau.

Value

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)

Author(s)

Jie Zhou