estimate_invK: Estimate inverse of matrix K

In KatarzynaReluga/postcAIC: Post-cAIC selection inference under Linear Mixed Models

Description

Estimate inverse of matrix K

Usage

estimate_invK(X, sig_u, sig_e, model = "NERM", clusterID)

Arguments

X	Matrix with covariates for fixed effects
sig_u	Variance parameter of random effects
sig_e	Variance parameter of errors
model	Model we want to fit. Only NERM is supported for now.
clusterID	Vector with cluster labels

Value

K_inv

Inverse of Matrix K

Examples

n = 10
m_i = 5
m_total = 50

clusterID = rep(1:n, m_i)
p = 10
beta = rep(2, p)
u_i = rnorm(n, 0, 2)
u_i_aug = rep(u_i, each = m_i)
X = matrix(rnorm(m_total * p), m_total, p)
y = X%*%beta + u_i_aug + rnorm(m_total, 0, 1)

fit_nerm <- estimate_NERM(X = X, y = y,
                          clusterID = clusterID,
                          X_cluster = NULL)

invK = estimate_invK(X, sig_u = fit_nerm$sig_u,
                     sig_e = fit_nerm$sig_e,
                     clusterID = clusterID)

KatarzynaReluga/postcAIC documentation built on Jan. 25, 2022, 12:33 a.m.