HLmix {REBayes}

Kiefer-Wolfowitz NPMLE for Huber Location Mixtures

Description

Kiefer Wolfowitz Nonparametric MLE for Huber Location Mixtures

Usage

HLmix(x, v = 300, sigma = 1, k = 1.345, heps = hubereps(k), ...)

Arguments

x

Data: Sample Observations

v

Undata: Grid Values defaults equal spacing of with v bins, when v is a scalar

sigma

scale parameter of the Gaussian noise, may take vector values of length(x)

k

Huber k value

heps

Huber epsilon contamination value, should match k, by default this is automatically enforced.

...

other parameters to pass to KWDual to control optimization

Details

Kiefer Wolfowitz NPMLE for location mixtures with Huber (1964) base density The Huber k specifies the point at which the influence function of the Huber M-estimator kinks. The predict method for HLmix objects compute means, medians or modes of the posterior according to whether the Loss argument is 2, 1 or 0, or posterior quantiles if Loss is in (0,1).

Value

An object of class density with components:

x

points of evaluation on the domain of the density

y

estimated function values at the points v, the mixing density

g

marginal density values

logLik

log likelihood

sigma

sigma

dy

posterior means at the observed x values

k

Huber k

heps

Huber epsilon

Author(s)

Roger Koenker