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

 `1` ```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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20``` ```# 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 May 29, 2017, 12:27 p.m.