mle: Estimate the precision matrix for multivariate normal...

In hoenlab/SBIC: Structural Bayesian Information Criterion for Graphical Models

Description

This function find the maximum likelihood estimate of the precision matrix with given adjacency matrix for multivariate normal distribution.

Usage

mle(data, priori)

Arguments

data	An n by p dataframe representing the observations
priori	A p by p matrix representing the given adjacency matrix

Details

The methods are based on the relationship between precision matrix of the multivariate normal distribution and regression coefficients.

Value

Returns a p by p matrix estimate of the precision matrix

Author(s)

Jie Zhou

Examples

  set.seed(1)
  d=simulate(n=100,p=200, m1=100, m2=30)
  data=d$data
  priori=d$realnetwork
  precision=mle(data=data,priori=priori)

hoenlab/SBIC documentation built on March 6, 2021, 11:58 a.m.