WGLVmix: Weighted NPMLE of Longitudinal Gaussian Mean and Variances...

In REBayes: Empirical Bayes Estimation and Inference

Weighted NPMLE of Longitudinal Gaussian Mean and Variances Model

Description

A Kiefer-Wolfowitz procedure for ML estimation of a Gaussian model with dependent mean and variance components and weighted longitudinal data. This version assumes a general bivariate distribution for the mixing distribution. The defaults use a rather coarse bivariate gridding. In contrast to the function GLVmix the full longitudinal data structure is required for this function and the likelihood evaluation reflects this difference.

Usage

WGLVmix(y, id, w, u = 30, v = 30, ...)

Arguments

y	A vector of observations
id	A strata indicator vector of the same length
w	A vector of weights
u	A vector of bin boundaries for the mean effects
v	A vector of bin boundaries for the variance effects
...	optional parameters to be passed to KWDual to control optimization

Value

A list consisting of the following components:

u	midpoints of mean bin boundaries
v	midpoints of variance bin boundaries
fuv	the function values of the mixing density.
logLik	log likelihood value for mean problem
du	Bayes rule estimate of the mixing density means.
dv	Bayes rule estimate of the mixing density variances.
A	Constraint matrix
status	Mosek convergence status

Author(s)

R. Koenker and J. Gu

References

Gu, J. and R. Koenker (2014) Heterogeneous Income Dynamics: An Empirical Bayes Perspective, JBES,35, 1-16.

Koenker, R. and J. Gu, (2017) REBayes: An R Package for Empirical Bayes Mixture Methods, Journal of Statistical Software, 82, 1–26.

See Also

WTLVmix for an implementation assuming independent heterogeneity, GLVmix for an implementation that assumes the availability of only the summary statistics but not the full longitudinal data structure.

REBayes documentation built on Aug. 19, 2023, 5:10 p.m.