Port of the S+ "Robust Library"
Overlaid Density Plot
Build a Model in a Stepwise Fashion
ANOVA for Robust Generalized Linear Model Fits
Side-by-Side Mahalanobis Distance Plot
ANOVA for Robust Linear Model Fits
Breslow Data
Classical Covariance Estimation
Control Parameters for Robust Covariance Estimation
Robust Covariance/Correlation Matrix Estimation
Distance - Distance Plot
Compute an Anova Object by Dropping Terms
Ellipses Plot - Visual Correlation Matrix Comparison
Maximum-likelihood Fitting of Univariate Distributions
Robust Fitting of Univariate Distributions
Control Parameters for gammaRob
Mallows Type Estimator
Robust Estimation of Gamma Distribution Parameters
Generate Data With Contamination
glmRob Control Parameters
Control Parameters for the Bounded Influence Robust GLM Estimator
Robust GLM CUBIF Fitter
Control for Mallows-type Robust GLM Estimator
Control Parameters for weibullRob
Control for Misclassification Robust GLM Estimator
Consistent Misclassification Estimator
Robust Generalized Linear Model Fit
Fit a Robust Generalized Linear Model
Leuk Data
Control Parameters for Robust Linear Regression
Fit a Robust Linear Model
Robust Fitter Functions for Linear Models
Robust Linear Model Objects
High Breakdown and High Efficiency Robust Linear Regression
Robust Final Prediction Errors
Control Parameters for lognormRob
Robust Estimation of Lognormal Distribution Parameters
Bias Test for Least-Squares Regression Estimates
Mallows Data
Plot Method
fdfm Plot Method
Diagnostic Regression Plots
Diagnostic Regression Plots
Robust Estimation of Weibull Distribution Parameters
Predict Method for Robust Generalized Linear Model Fits
Use predict() on an lmRob Object
Comparison Quantile-Quantile Plot
Robust Bootstrap Standard Errors
Residuals Methods for glmRob Objects
Comparison Screeplot
Brownlee's Stack-Loss Data
Summary Method
Summarizing Robust Generalized Linear Model Fits
Summarizing Robust Linear Model Fits
Various Tests of Robust Regression Estimates
Update an lmRob Model Object
Weight Functions Psi, Rho, Chi
Modified Wood Data
Methods for robust statistics, a state of the art in the early 2000s, notably for robust regression and robust multivariate analysis.