Weighted Likelihood Estimation

[Up] [Top]

Documentation for package ‘wle’ version 0.9-91

Help Pages

A B C E F H M P R S W X Y

-- A --

anova.wle.glm.root Robust Analysis of Deviance for Generalized Linear Model Fits
anova.wleglmlist Robust Analysis of Deviance for Generalized Linear Model Fits
artificial Hawkins, Bradu, Kass's Artificial Data

-- B --

binary Convert decimal base number to binary base

-- C --

cavendish Cavendish's determinations of the mean density of the earth Data
coef.wle.lm Accessing Linear Model Fits for wle.lm

-- E --

extractRoot Extract a Root from a result of a wle function
extractRoot.wle.glm Extract a Root from a result of a wle function

-- F --

family.wle.glm Accessing Generalized Linear Model Robust Fits
fitted.wle.lm Accessing Linear Model Fits for wle.lm
formula.wle.lm Accessing Linear Model Fits for wle.lm

-- H --

hald Hald Data

-- M --

mde.vonmises von Mises Minimum Distance Estimates
mde.wrappednormal Wrapped Normal Minimum Distance Estimates
mle.aic Akaike Information Criterion
mle.cp Mallows Cp
mle.cv Cross Validation Selection Method
mle.stepwise Stepwise, Backward and Forward selection methods
model.frame.wle.lm Accessing Linear Model Fits for wle.lm

-- P --

plot.mle.cp Plot the Mallows Cp
plot.wle.cp Plot the Weighted Mallows Cp
plot.wle.lm Plots for the Linear Model
print.mde.vonmises von Mises Minimum Distance Estimates
print.mde.wrappednormal Wrapped Normal Minimum Distance Estimates
print.mle.aic Summaries and methods for mle.aic
print.mle.cp Summaries and methods for mle.cp
print.mle.cv Summaries and methods for mle.cv
print.mle.stepwise Accessing summaries for mle.stepwise
print.summary.mle.aic Summaries and methods for mle.aic
print.summary.mle.cp Summaries and methods for mle.cp
print.summary.mle.cv Summaries and methods for mle.cv
print.summary.mle.stepwise Accessing summaries for mle.stepwise
print.summary.wle.aic Summaries and methods for wle.aic
print.summary.wle.aic.ar Summaries and methods for wle.aic.ar
print.summary.wle.cp Summaries and methods for wle.cp
print.summary.wle.cv Summaries and methods for wle.cv
print.summary.wle.glm Summarizing Generalized Linear Model Robust Fits
print.summary.wle.lm Accessing Linear Model Fits for wle.lm
print.summary.wle.lm.root Accessing Linear Model Fits for wle.lm
print.summary.wle.stepwise Accessing summaries for wle.stepwise
print.wle.aic Summaries and methods for wle.aic
print.wle.aic.ar Summaries and methods for wle.aic.ar
print.wle.binomial Robust Estimation in the Binomial Model
print.wle.cp Summaries and methods for wle.cp
print.wle.cv Summaries and methods for wle.cv
print.wle.gamma Robust Estimation in the Gamma model
print.wle.glm Robust Fitting Generalized Linear Models using Weighted Likelihood
print.wle.lm Accessing Linear Model Fits for wle.lm
print.wle.negativebinomial Robust Estimation in the Negative Binomial Model
print.wle.normal Summaries and methods for wle.normal
print.wle.normal.mixture Robust Estimation in the Normal Mixture Model
print.wle.normal.multi Summaries and methods for wle.normal.multi
print.wle.onestep Summaries and methods for wle.onestep
print.wle.poisson Robust Estimation in the Poisson Model
print.wle.smooth Bandwidth selection for the normal kernel and normal model.
print.wle.stepwise Accessing summaries for wle.stepwise
print.wle.t.test Weighted Likelihood Student's t-Test
print.wle.vonmises von Mises Weighted Likelihood Estimates
print.wle.wrappednormal Wrapped Normal Weighted Likelihood Estimates

-- R --

residuals.wle.glm Accessing Generalized Linear Model Robust Fits
residualsAnscombe Anscombe residuals
rocky Rockwell hardness, 100 coils produced in sequence at a Chicago Steel Mill Data

-- S --

selection Selection's Data
summary.mle.aic Summaries and methods for mle.aic
summary.mle.cp Summaries and methods for mle.cp
summary.mle.cv Summaries and methods for mle.cv
summary.mle.stepwise Accessing summaries for mle.stepwise
summary.wle.aic Summaries and methods for wle.aic
summary.wle.aic.ar Summaries and methods for wle.aic.ar
summary.wle.cp Summaries and methods for wle.cp
summary.wle.cv Summaries and methods for wle.cv
summary.wle.glm Summarizing Generalized Linear Model Robust Fits
summary.wle.lm Accessing Linear Model Fits for wle.lm
summary.wle.lm.root Accessing Linear Model Fits for wle.lm
summary.wle.stepwise Accessing summaries for wle.stepwise

-- W --

weights.wle.glm Robust Fitting Generalized Linear Models using Weighted Likelihood
weights.wle.lm Accessing Linear Model Fits for wle.lm
wle.aic Weighted Akaike Information Criterion
wle.aic.ar Weighted Akaike Information Criterion for AR models
wle.ar Fit Autoregressive Models to Time Series - Preliminary Version
wle.ar.ao Fit Autoregressive Models to Time Series - Preliminary Version
wle.ar.matrix Fit Autoregressive Models to Time Series - Preliminary Version
wle.ar.start Fit Autoregressive Models to Time Series - Preliminary Version
wle.ar.step Fit Autoregressive Models to Time Series - Preliminary Version
wle.ar.wls Weighted Akaike Information Criterion for AR models
wle.binomial Robust Estimation in the Binomial Model
wle.cp Weighted Mallows Cp
wle.cv Model Selection by Weighted Cross-Validation
wle.fracdiff Fit Fractional Models to Time Series - Preliminary Version
wle.gamma Robust Estimation in the Gamma model
wle.glm Robust Fitting Generalized Linear Models using Weighted Likelihood
wle.glm.control Auxiliary for Controlling GLM Robust Fitting
wle.glm.fit Robust Fitting Generalized Linear Models using Weighted Likelihood
wle.glm.weights Weights based on Weighted Likelihood for the GLM model
wle.lm Fitting Linear Models using Weighted Likelihood
wle.negativebinomial Robust Estimation in the Negative Binomial Model
wle.normal Robust Estimation in the Normal Model
wle.normal.mixture Robust Estimation in the Normal Mixture Model
wle.normal.mixture.start Robust Estimation in the Normal Mixture Model
wle.normal.multi Robust Estimation in the Normal Multivariate Model
wle.onestep A One-Step Weighted Likelihood Estimator for Linear model
wle.poisson Robust Estimation in the Poisson Model
wle.smooth Bandwidth selection for the normal kernel and normal model.
wle.stepwise Weighted Stepwise, Backward and Forward selection methods
wle.t.test Weighted Likelihood Student's t-Test
wle.var.test Weighted F Test to Compare Two Variances
wle.vonmises von Mises Weighted Likelihood Estimates
wle.weights Weights based on Weighted Likelihood for the normal model
wle.wrappednormal Wrapped Normal Weighted Likelihood Estimates

-- X --

x.artificial Hawkins, Bradu, Kass's Artificial Data
x.hald Hald Data
xdata Selection's Data

-- Y --

y.artificial Hawkins, Bradu, Kass's Artificial Data
y.hald Hald Data
ydata Selection's Data