Abstract
Package <b>distrMod</b> provides an object oriented (more specifically <b>S</b>4-style) implementation of probability models. Moreover, it contains functions and methods to compute minimum criterion estimators - in particular, maximum likelihood and minimum distance estimators.
Highlights
DistrMod is not the first package to provide infrastructure for ML estimation, we compete in some sense with such prominent functions as fitdistr from package MASS (Venables and Ripley 2002) and, already using the S4 paradigm, mle from package stats4 (R Development Core Team 2010a)
We present the new model S4 classes and demonstrate how package distrMod can be used to compute minimum criterion estimators
Models in Statistics and in R In Statistics, a probability model or shortly model is a family of probability distributions
Summary
What is distrMod? It is an extension package for the statistical software R, (R Development Core Team 2010a) and is the latest member of a family of packages, which we call distr-family. Package distrMod makes extensive use of the distribution classes of package distr as well as the functions and methods of package distrEx. Its purpose is to extend support in base R for distributions and in particular for parametric modelling by “object oriented” implementation of probability models via several new S4 classes and methods; see Section 2 and Chambers (1998) for more details. The return value of the model fit, an estimate of the parameter, is an object of class Estimator or subclasses for which one may want to have confidence intervals, some profiling, etc For objects of these classes we provide various methods for standard R functions; see Sections 3 and 4 for more details. The development version of the distr-family is located at R-Forge; see Theußl and Zeileis (2009)
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