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wle (version 0.5)

Weighted Likelihood Estimation

Description

Approach to the robustness via Weigheted Likelihood.

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Version

Install

install.packages('wle')

Monthly Downloads

26

Version

0.5

License

GNU GPL version 2

Maintainer

Claudio Agostinelli

Last Published

February 15th, 2017

Functions in wle (0.5)

plot.wle.cp

Plot the Weighted Mallows Cp
wle.lm

Fitting Linear Models using Weighted Likelihood
cavendish

Cavendish's determinations of the mean density of the earth Data
mle.aic

Akaike Information Criterion
hald

Hald Data
plot.mle.cp

Plot the Mallows Cp
mle.stepwise

Stepwise, Backward and Forward selection methods
mle.stepwise.summaries

Accessing summaries for mle.stepwise
wle.t.test

Weighted Likelihood Student's t-Test
wle.stepwise.summaries

Accessing summaries for wle.stepwise
artificial

Hawkins, Bradu, Kass's Artificial Data
mle.cp.summaries

Summaries and methods for mle.cp
wle.aic.summaries

Summaries and methods for wle.aic
wle.cv.summaries

Summaries and methods for wle.cv
wle.binomial

Robust Estimation in the Binomial Model
wle.cp.summaries

Summaries and methods for wle.cp
wle.aic

Weighted Akaike Information Criterion
wle.normal.multi.summaries

Summaries and methods for wle.normal.multi
wle.gamma

Robust Estimation in the Gamma model
plot.wle.lm

Plots for the Linear Model
mle.cv

Cross Validation Selection Method
wle.normal

Robust Estimation in the Normal Model
selection

Selection's Data
wle.onestep.summaries

Summaries and methods for wle.onestep
mle.aic.summaries

Summaries and methods for mle.aic
wle.onestep

A One-Step Weighted Likelihood Estimator for Linear model
wle.cv

Model Selection by Weighted Cross-Validation
wle.lm.summaries

Accessing Linear Model Fits for wle.lm
wle.poisson

Robust Estimation in the Poisson Model
wle.smooth

Bandwidth selection for the normal kernel and normal model.
mle.cp

Mallows Cp
wle.normal.summaries

Summaries and methods for wle.normal
wle.cp

Weighted Mallows Cp
mle.cv.summaries

Summaries and methods for mle.cv
wle.stepwise

Weighted Stepwise, Backward and Forward selection methods
wle.var.test

Weighted F Test to Compare Two Variances
wle.normal.multi

Robust Estimation in the Normal Multivariate Model