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Color Schemes for Dichromats
Collapse red-green or green-blue distinctions to simulate the effects of different types of color-blindness
based on the work of Françoise Viénot and co-authors, especially
Quantile Regression
Estimation and inference methods for models for conditional quantile functions:
Linear and nonlinear parametric and non-parametric (total variation penalized) models
for conditional quantiles of a univariate response and several methods for handling
censored survival data. Portfolio selection methods based on expected shortfall
risk are also now included. See Koenker, R. (2005) Quantile Regression, Cambridge U. Press,
Conditional Inference Procedures in a Permutation Test Framework
Conditional inference procedures for the general independence
problem including two-sample, K-sample (non-parametric ANOVA),
correlation, censored, ordered and multivariate problems described
in
Generalized Linear Models Extended
Extended techniques for generalized linear models (GLMs), especially for binary responses, including parametric links and heteroscedastic latent variables.
Generalized Additive Models for Location Scale and Shape
Functions for fitting the Generalized Additive Models for Location Scale and Shape introduced by Rigby and Stasinopoulos (2005),
Fitting and Testing Generalized Logistic Distributions
Tools for the generalized logistic distribution (Type I, also known as skew-logistic distribution), encompassing basic distribution functions (p, q, d, r, score), maximum likelihood estimation, and structural change methods.
Censored Regression with Conditional Heteroscedasticity
Different approaches to censored or truncated regression with conditional heteroscedasticity are provided. First, continuous distributions can be used for the (right and/or left censored or truncated) response with separate linear predictors for the mean and variance. Second, cumulative link models for ordinal data (obtained by interval-censoring continuous data) can be employed for heteroscedastic extended logistic regression (HXLR). In the latter type of models, the intercepts depend on the thresholds that define the intervals. Infrastructure for working with censored or truncated normal, logistic, and Student-t distributions, i.e., d/p/q/r functions and distributions3 objects.
Truncated Gaussian Regression Models
Estimation of models for truncated Gaussian variables by maximum likelihood.
Visualizing Categorical Data
Visualization techniques, data sets, summary and inference procedures aimed particularly at categorical data. Special emphasis is given to highly extensible grid graphics. The package was package was originally inspired by the book "Visualizing Categorical Data" by Michael Friendly and is now the main support package for a new book, "Discrete Data Analysis with R" by Michael Friendly and David Meyer (2015).
Tools and Classes for Statistical Models
A collection of tools to deal with statistical models. The functionality is experimental and the user interface is likely to change in the future. The documentation is rather terse, but packages `coin' and `party' have some working examples. However, if you find the implemented ideas interesting we would be very interested in a discussion of this proposal. Contributions are more than welcome!