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, and Koenker, R. et al. (2017) Handbook of Quantile Regression, CRC Press, .

Simple Features for R

Support for simple feature access, a standardized way to encode and analyze spatial vector data. Binds to 'GDAL' for reading and writing data, to 'GEOS' for geometrical operations, and to 'PROJ' for projection conversions and datum transformations. Uses by default the 's2' package for geometry operations on geodetic (long/lat degree) coordinates.

Lightweight Access to the 'Geospatial Data Abstraction Library' ('GDAL')

Provides low-level access to 'GDAL' functionality. 'GDAL' is the 'Geospatial Data Abstraction Library' a translator for raster and vector geospatial data formats that presents a single raster abstract data model and single vector abstract data model to the calling application for all supported formats < https://gdal.org/>. This package is focussed on providing exactly and only what GDAL does, to enable developing further tools.

Parametric Bootstrap, Kenward-Roger and Satterthwaite Based Methods for Test in Mixed Models

Computes p-values based on (a) Satterthwaite or Kenward-Rogers degree of freedom methods and (b) parametric bootstrap for mixed effects models as implemented in the 'lme4' package. Implements parametric bootstrap test for generalized linear mixed models as implemented in 'lme4' and generalized linear models. The package is documented in the paper by Halekoh and Højsgaard, (2012, ). Please see 'citation("pbkrtest")' for citation details.

Empirical Bayes Estimation and Inference

Kiefer-Wolfowitz maximum likelihood estimation for mixture models and some other density estimation and regression methods based on convex optimization. See Koenker and Gu (2017) REBayes: An R Package for Empirical Bayes Mixture Methods, Journal of Statistical Software, 82, 1--26, .

Automated Grading of R Scripts

Tools for grading the coding style and documentation of R scripts. This is the R component of Roger the Omni Grader, an automated grading system for computer programming projects based on Unix shell scripts; see < https://gitlab.com/roger-project>. The package also provides an R interface to the shell scripts. Inspired by the lintr package.

Tests in Linear Mixed Effects Models

Provides p-values in type I, II or III anova and summary tables for lmer model fits (cf. lme4) via Satterthwaite's degrees of freedom method. A Kenward-Roger method is also available via the pbkrtest package. Model selection methods include step, drop1 and anova-like tables for random effects (ranova). Methods for Least-Square means (LS-means) and tests of linear contrasts of fixed effects are also available.

Simple Key-Value Database

Implements a simple key-value style database where character string keys are associated with data values that are stored on the disk. A simple interface is provided for inserting, retrieving, and deleting data from the database. Utilities are provided that allow 'filehash' databases to be treated much like environments and lists are already used in R. These utilities are provided to encourage interactive and exploratory analysis on large datasets. Three different file formats for representing the database are currently available and new formats can easily be incorporated by third parties for use in the 'filehash' framework.

Comparative 'Phylogenetic' Analyses of Diversification

Contains a number of comparative 'phylogenetic' methods, mostly focusing on analysing diversification and character evolution. Contains implementations of 'BiSSE' (Binary State 'Speciation' and Extinction) and its unresolved tree extensions, 'MuSSE' (Multiple State 'Speciation' and Extinction), 'QuaSSE', 'GeoSSE', and 'BiSSE-ness' Other included methods include Markov models of discrete and continuous trait evolution and constant rate 'speciation' and extinction.

Random Coefficient Binary Response Estimation

Nonparametric maximum likelihood estimation methods for random coefficient binary response models and some related functionality for sequential processing of hyperplane arrangements. See J. Gu and R. Koenker (2020) .