WGLVmix: Weighted NPMLE ofLongitudinal Gaussian Mean and Variances...

Description Usage Arguments Value Author(s) References See Also

View source: R/WGLVmix.R

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.

Usage

1
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.

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


REBayes documentation built on Feb. 14, 2018, 5:03 p.m.