solcov: Calculate covariance matrix and precision matrix

In equSA: Learning High-Dimensional Graphical Models

Description

Calculate the adjusted covriance matrix and precision matrix given the network structure from high dimesional dataset.

Usage

solcov(data, struct, tol=10^-5)

Arguments

data	A nxp data matrix.
struct	A preacquired adjacency matrix
tol	Tolerant value, default is 10^-5

Value

A list of two elements:

COV	Adjusted covriance matrix
PRE	Precision matrix

Author(s)

Bochao [e-mail] & Runmin Shi

References

Friedman, J., Hastie, T., and Tibshirani, R. (2001). The elements of statistical learning (Vol. 1). Springer, Berlin: Springer series in statistics.

Examples

  
      
library(equSA)
data <- GauSim(100,200)
solcov(data$data,data$theta)
      

equSA documentation built on May 6, 2019, 1:06 a.m.