Kiefer Wolfowitz Nonparametric MLE for Huber Location Mixtures
HLmix(x, v = 300, sigma = 1, k = 1.345, heps = hubereps(k), ...)An object of class density with components:
points of evaluation on the domain of the density
estimated function values at the points v, the mixing density
marginal density values
log likelihood
sigma
posterior means at the observed x values
Huber k
Huber epsilon
Data: Sample Observations
Undata: Grid Values defaults equal spacing of with v bins, when v is a scalar
scale parameter of the Gaussian noise, may take vector values of length(x)
Huber k value
Huber epsilon contamination value, should match k, by default this is automatically enforced.
other parameters to pass to KWDual to control optimization
Roger Koenker
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).