meleCov: Estimate the covariance matrix of the MELE

In drmdel: Dual Empirical Likelihood Inference under Density Ratio Models in the Presence of Multiple Samples

Description

Estimate the covariance matrix of the maximum empirical likelihood estimator (MELE).

Usage

meleCov(drmfit)

Arguments

drmfit

a fitted DRM object (an output from the drmdel function). See drmdel for details.

Value

The estimated covariance matrix of the MELE.

Examples

# Data generation
set.seed(25)
n_samples <- c(100, 200, 180, 150, 175)  # sample sizes
x0 <- rgamma(n_samples[1], shape=5, rate=1.8)
x1 <- rgamma(n_samples[2], shape=12, rate=1.2)
x2 <- rgamma(n_samples[3], shape=12, rate=1.2)
x3 <- rgamma(n_samples[4], shape=18, rate=5)
x4 <- rgamma(n_samples[5], shape=25, rate=2.6)
x <- c(x0, x1, x2, x3, x4)

# Fit a DRM with the basis function q(x) = (x, log(abs(x))),
# which is the basis function for gamma family. This basis
# function is the built-in basis function 6.
drmfit <- drmdel(x=x, n_samples=n_samples, basis_func=6)

# Check MELE
drmfit$mele

# Estimate the covariance matrix of the MELE
meleCov(drmfit)

drmdel documentation built on Oct. 25, 2021, 5:07 p.m.