estimate covariance matrix with regression

gistfile1.txt

# estimate covariance matrix with regression
library(GGMnonreg)

p = 20

pcors = GGMnonreg::gen_net(p = p)

y = MASS::mvrnorm(n = 500, 
                  mu = rep(0, p), 
                  Sigma = pcors$cors)

y = scale(y, scale = F)

precision_reg = matrix(0, p, p)
precision = solve(cov(y))

for(i in 1:p){
  fit_i <- lm(y[,i] ~ 0 + y[,-i])
  res_var <- var(residuals(fit_i))
  precision_reg[i,-i] <- (-coef(fit_i)) / res_var
  precision_reg[i,i] <- 1/res_var
}

all.equal(round(precision_reg, 5), round(precision, 5))