Artifacts using Sandwich (93)

Sort by:Popular▼

✓Popular✓Newest

A collection of tests, data sets, and examples for diagnostic checking in linear regression models. Furthermore, some generic tools for inference in parametric models are provided.

Simultaneous tests and confidence intervals for general linear hypotheses in parametric models, including linear, generalized linear, linear mixed effects, and survival models. The package includes demos reproducing analyzes presented in the book "Multiple Comparisons Using R" (Bretz, Hothorn, Westfall, 2010, CRC Press).

A toolkit with infrastructure for representing, summarizing, and visualizing tree-structured regression and classification models. This unified infrastructure can be used for reading/coercing tree models from different sources ('rpart', 'RWeka', 'PMML') yielding objects that share functionality for print()/plot()/predict() methods. Furthermore, new and improved reimplementations of conditional inference trees (ctree()) and model-based recursive partitioning (mob()) from the 'party' package are provided ...

Functions, data sets, examples, demos, and vignettes for the book Christian Kleiber and Achim Zeileis (2008), Applied Econometrics with R, Springer-Verlag, New York. ISBN 978-0-387-77316-2. (See the vignette "AER" for a package overview.)

Functions for Maximum Likelihood (ML) estimation and non-linear optimization, and related tools. It includes a unified way to call different optimizers, and classes and methods to handle the results from the ML viewpoint. It also includes a number of convenience tools for testing and developing your own models.

Bayesian analysis of item-response theory (IRT) models, roll call analysis; computing highest density regions; maximum likelihood estimation of zero-inflated and hurdle models for count data; goodness-of-fit measures for GLMs; data sets used in writing and teaching at the Political Science Computational Laboratory; seats-votes curves.

A computational toolbox for recursive partitioning. The core of the package is ctree(), an implementation of conditional inference trees which embed tree-structured regression models into a well defined theory of conditional inference procedures. This non-parametric class of regression trees is applicable to all kinds of regression problems, including nominal, ordinal, numeric, censored as well as multivariate response variables and arbitrary measurement scales of the covariates. Based on conditional ...

Testing, monitoring and dating structural changes in (linear) regression models. strucchange features tests/methods from the generalized fluctuation test framework as well as from the F test (Chow test) framework. This includes methods to fit, plot and test fluctuation processes (e.g., CUSUM, MOSUM, recursive/moving estimates) and F statistics, respectively. It is possible to monitor incoming data online using fluctuation processes. Finally, the breakpoints in regression models with structural changes can ...

A set of estimators and tests for panel data econometrics.

Infrastructure for psychometric modeling such as data classes (for item response data and paired comparisons), basic model fitting functions (for Bradley-Terry, Rasch, parametric logistic IRT, generalized partial credit, rating scale, multinomial processing tree models), extractor functions for different types of parameters (item, person, threshold, discrimination, guessing, upper asymptotes), unified inference and visualizations, and various datasets for illustration. Intended as a common lightweight and ...