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Multiple Heat Maps for Projected Coordinates
Functions for displaying multiple images or scatterplots with a color scale, i.e., heat maps, possibly with projected coordinates. The package relies on the base graphics system, so graphics are rendered rapidly.
Dunn's Test of Multiple Comparisons Using Rank Sums
Computes Dunn's test (1964) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for 0th-order stochastic dominance among k groups (Kruskal and Wallis, 1952). 'dunn.test' makes k(k-1)/2 multiple pairwise comparisons based on Dunn's z-test-statistic approximations to the actual rank statistics. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Dunn's test may be understood as a test for median difference and for mean difference. 'dunn.test' accounts for tied ranks.
Visualizations of Distributions and Uncertainty
Provides primitives for visualizing distributions using 'ggplot2' that are particularly tuned for
visualizing uncertainty in either a frequentist or Bayesian mode. Both analytical distributions (such as
frequentist confidence distributions or Bayesian priors) and distributions represented as samples (such as
bootstrap distributions or Bayesian posterior samples) are easily visualized. Visualization primitives include
but are not limited to: points with multiple uncertainty intervals,
eye plots (Spiegelhalter D., 1999) < https://ideas.repec.org/a/bla/jorssa/v162y1999i1p45-58.html>,
density plots, gradient plots, dot plots (Wilkinson L., 1999)
Create 'Formattable' Data Structures
Provides functions to create formattable vectors and data frames. 'Formattable' vectors are printed with text formatting, and formattable data frames are printed with multiple types of formatting in HTML to improve the readability of data presented in tabular form rendered in web pages.
Unified Multiple Testing Procedures
Designed to ease the application and comparison of multiple hypothesis testing procedures for FWER, gFWER, FDR and FDX. Methods are standardized and usable by the accompanying 'mutossGUI'.
Multilingual Stopword Lists
Provides multiple sources of stopwords, for use in text analysis and natural language processing.
Regression Models for Ordinal Data
Implementation of cumulative link (mixed) models also known as ordered regression models, proportional odds models, proportional hazards models for grouped survival times and ordered logit/probit/... models. Estimation is via maximum likelihood and mixed models are fitted with the Laplace approximation and adaptive Gauss-Hermite quadrature. Multiple random effect terms are allowed and they may be nested, crossed or partially nested/crossed. Restrictions of symmetry and equidistance can be imposed on the thresholds (cut-points/intercepts). Standard model methods are available (summary, anova, drop-methods, step, confint, predict etc.) in addition to profile methods and slice methods for visualizing the likelihood function and checking convergence.
Non-Parametric Multiple Change-Point Analysis of Multivariate Data
Implements various procedures for finding
multiple change-points from Matteson D. et al (2013)
Parallel Distance Matrix Computation using Multiple Threads
A fast parallelized alternative to R's native 'dist' function to calculate distance matrices for continuous, binary, and multi-dimensional input matrices, which supports a broad variety of 41 predefined distance functions from the 'stats', 'proxy' and 'dtw' R packages, as well as user- defined functions written in C++. For ease of use, the 'parDist' function extends the signature of the 'dist' function and uses the same parameter naming conventions as distance methods of existing R packages. The package is mainly implemented in C++ and leverages the 'RcppParallel' package to parallelize the distance computations with the help of the 'TinyThread' library. Furthermore, the 'Armadillo' linear algebra library is used for optimized matrix operations during distance calculations. The curiously recurring template pattern (CRTP) technique is applied to avoid virtual functions, which improves the Dynamic Time Warping calculations while the implementation stays flexible enough to support different DTW step patterns and normalization methods.
Probability Computations on Pedigrees
An implementation of the Elston-Stewart algorithm for
calculating pedigree likelihoods given genetic marker data (Elston and
Stewart (1971)