Abstractions for Promise-Based Asynchronous Programming

Provides fundamental abstractions for doing asynchronous programming in R using promises. Asynchronous programming is useful for allowing a single R process to orchestrate multiple tasks in the background while also attending to something else. Semantics are similar to 'JavaScript' promises, but with a syntax that is idiomatic R.

Turn Geospatial Polygons into Regular or Hexagonal Grids

Turn irregular polygons (such as geographical regions) into regular or hexagonal grids. This package enables the generation of regular (square) and hexagonal grids through the package 'sp' and then assigns the content of the existing polygons to the new grid using the Hungarian algorithm, Kuhn (1955) (). This prevents the need for manual generation of hexagonal grids or regular grids that are supposed to reflect existing geography.

Methods for Changepoint Detection

Implements various mainstream and specialised changepoint methods for finding single and multiple changepoints within data. Many popular non-parametric and frequentist methods are included. The cpt.mean(), cpt.var(), cpt.meanvar() functions should be your first point of call.

Calculate Pairwise Multiple Comparisons of Mean Rank Sums Extended

For one-way layout experiments the one-way ANOVA can be performed as an omnibus test. All-pairs multiple comparisons tests (Tukey-Kramer test, Scheffe test, LSD-test) and many-to-one tests (Dunnett test) for normally distributed residuals and equal within variance are available. Furthermore, all-pairs tests (Games-Howell test, Tamhane's T2 test, Dunnett T3 test, Ury-Wiggins-Hochberg test) and many-to-one (Tamhane-Dunnett Test) for normally distributed residuals and heterogeneous variances are provided. Van der Waerden's normal scores test for omnibus, all-pairs and many-to-one tests is provided for non-normally distributed residuals and homogeneous variances. The Kruskal-Wallis, BWS and Anderson-Darling omnibus test and all-pairs tests (Nemenyi test, Dunn test, Conover test, Dwass-Steele-Critchlow- Fligner test) as well as many-to-one (Nemenyi test, Dunn test, U-test) are given for the analysis of variance by ranks. Non-parametric trend tests (Jonckheere test, Cuzick test, Johnson-Mehrotra test, Spearman test) are included. In addition, a Friedman-test for one-way ANOVA with repeated measures on ranks (CRBD) and Skillings-Mack test for unbalanced CRBD is provided with consequent all-pairs tests (Nemenyi test, Siegel test, Miller test, Conover test, Exact test) and many-to-one tests (Nemenyi test, Demsar test, Exact test). A trend can be tested with Pages's test. Durbin's test for a two-way balanced incomplete block design (BIBD) is given in this package as well as Gore's test for CRBD with multiple observations per cell is given. Outlier tests, Mandel's k- and h statistic as well as functions for Type I error and Power analysis as well as generic summary, print and plot methods are provided.

Circular Visualization

Circular layout is an efficient way for the visualization of huge amounts of information. Here this package provides an implementation of circular layout generation in R as well as an enhancement of available software. The flexibility of the package is based on the usage of low-level graphics functions such that self-defined high-level graphics can be easily implemented by users for specific purposes. Together with the seamless connection between the powerful computational and visual environment in R, it gives users more convenience and freedom to design figures for better understanding complex patterns behind multiple dimensional data. The package is described in Gu et al. 2014 .

Assigns Colours to Values

Maps one of the viridis colour palettes, or a user-specified palette to values. Viridis colour maps are created by Stéfan van der Walt and Nathaniel Smith, and were set as the default palette for the 'Python' 'Matplotlib' library < https://matplotlib.org/>. Other palettes available in this library have been derived from 'RColorBrewer' < https://CRAN.R-project.org/package=RColorBrewer> and 'colorspace' < https://CRAN.R-project.org/package=colorspace> packages.

Small Multiples for Leaflet Web Maps

Create small multiples of several leaflet web maps with (optional) synchronised panning and zooming control. When syncing is enabled all maps respond to mouse actions on one map. This allows side-by-side comparisons of different attributes of the same geometries. Syncing can be adjusted so that any combination of maps can be synchronised.

Estimation/Multiple Imputation for Mixed Categorical and Continuous Data

Estimation/multiple imputation programs for mixed categorical and continuous data.

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.