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Distributions for Generalized Additive Models for Location Scale and Shape
A set of distributions which can be used for modelling the response variables in Generalized Additive Models for Location Scale and Shape, Rigby and Stasinopoulos (2005),
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,
Exchange Rate Regime Analysis
Exchange rate regression and structural change tools for estimating, testing, dating, and monitoring (de facto) exchange rate regimes.
Evolutionary Learning of Globally Optimal Trees
Commonly used classification and regression tree methods like the CART algorithm are recursive partitioning methods that build the model in a forward stepwise search. Although this approach is known to be an efficient heuristic, the results of recursive tree methods are only locally optimal, as splits are chosen to maximize homogeneity at the next step only. An alternative way to search over the parameter space of trees is to use global optimization methods like evolutionary algorithms. The 'evtree' package implements an evolutionary algorithm for learning globally optimal classification and regression trees in R. CPU and memory-intensive tasks are fully computed in C++ while the 'partykit' package is leveraged to represent the resulting trees in R, providing unified infrastructure for summaries, visualizations, and predictions.
Management of Survey Data and Presentation of Analysis Results
An infrastructure for the management of survey data including value labels, definable missing values, recoding of variables, production of code books, and import of (subsets of) 'SPSS' and 'Stata' files is provided. Further, the package allows to produce tables and data frames of arbitrary descriptive statistics and (almost) publication-ready tables of regression model estimates, which can be exported to 'LaTeX' and HTML.
Generalized Linear Mixed Model Trees
Recursive partitioning based on (generalized) linear mixed models
(GLMMs) combining lmer()/glmer() from 'lme4' and lmtree()/glmtree() from
'partykit'. The fitting algorithm is described in more detail in Fokkema,
Smits, Zeileis, Hothorn & Kelderman (2018;
Penn World Table (Version 8.x)
The Penn World Table 8.x provides information on relative levels of income, output, inputs, and productivity for 167 countries between 1950 and 2011.
R Fortunes
A collection of fortunes from the R community.
Psychometric Mixture Models
Psychometric mixture models based on 'flexmix' infrastructure. At the moment Rasch mixture models
with different parameterizations of the score distribution (saturated vs. mean/variance specification),
Bradley-Terry mixture models, and MPT mixture models are implemented. These mixture models can be estimated
with or without concomitant variables. See Frick et al. (2012)
Spatial Lag Model Trees
Model-based linear model trees adjusting for spatial correlation using a
simultaneous autoregressive spatial lag, Wagner and Zeileis (2019)