Gammamix: NPMLE for Gamma Mixtures

In REBayes: Empirical Bayes Estimation and Inference

NPMLE for Gamma Mixtures

Description

A Kiefer-Wolfowitz MLE for Gamma mixture models

Usage

Gammamix(x, v = 300, shape = 1, weights = NULL, eps = 1e-10, ...)

Arguments

x	vector of observed variances
v	A vector of bin boundaries, if scalar then v equally spaced bins are constructed
shape	vector of shape parameters corresponding to x
weights	replicate weights for x obervations, should sum to 1
eps	tolerance for default gridding
...	optional parameters passed to KWDual to control optimization

Value

An object of class density with components:

x	midpoints of the bin boundaries
y	estimated function values of the mixing density
g	function values of the mixture density at the observed x's.
logLik	the value of the log likelihood at the solution
dy	Bayes rule estimates of
status	the Mosek convergence status.

Author(s)

J. Gu and R. Koenker

References

Gu J. and R. Koenker (2014) Unobserved heterogeneity in 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

Gammamix for a general implementation for Gamma mixtures

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