This package converts between GeoJSON and Simple Feature objects.

This package provides a set of tools for post processing the outcomes of species distribution modeling exercises. It includes novel methods for comparing models and tracking changes in distributions through time. It further includes methods for visualizing outcomes, selecting thresholds, calculating measures of accuracy and landscape fragmentation statistics, etc.

This package provides means to run simulations for adaptive seamless designs with and without early outcomes for treatment selection and subpopulation type designs.

ExtRemes is a suite of functions for carrying out analyses on the extreme values of a process of interest; be they block maxima over long blocks or excesses over a high threshold.

This package provides the header files for a stripped-down version of the plog header-only C++ logging library, and a method to log to R's standard error stream.

This is a package for mixture and flexible discriminant analysis, multivariate adaptive regression splines (MARS), BRUTO, and so on.

This package provides functionality to create pretty word clouds, visualize differences and similarity between documents, and avoid over-plotting in scatter plots with text.

This package provides text and label geometries for ggplot2 that help to avoid overlapping text labels. Labels repel away from each other and away from the data points.

This package provides tools for exploratory data analysis and data visualization of biological sequence (DNA and protein) data. It also includes utilities for sequence data management under the ACNUC system.

This package provides a %<-% operator to perform multiple, unpacking, and destructuring assignment in R. The operator unpacks the right-hand side of an assignment into multiple values and assigns these values to variables on the left-hand side of the assignment.

This package provides functions related to human natural ordering. It handles adjacent digits in a character sequence as a number so that natural sort function arranges a character vector by their numbers, not digit characters.

Tools to access data from the data web service of the OeNB, https://www.oenb.at/en/Statistics/User-Defined-Tables/webservice.html.

This package provides functions for analyzing multivariate data. Dependencies of the distribution of the specified variable (response variable) to other variables (explanatory variables) are derived and evaluated by the Akaike Information Criterion (AIC).

This package provides a set of predicates and assertions for checking the properties of (country independent) complex data types. This is mainly for use by other package developers who want to include run-time testing features in their own packages.

This package contains functions to compute the nonparametric maximum likelihood estimator (MLE) for the bivariate distribution of (X,Y), when realizations of (X,Y) cannot be observed directly. To be more precise, we consider the situation where we observe a set of rectangles that are known to contain the unobservable realizations of (X,Y). We compute the MLE based on such a set of rectangles. The methods can also be used for univariate censored data (see data set cosmesis), and for censored data with competing risks (see data set menopause). The package also provides functions to visualize the observed data and the MLE.

This package contains R-functions to perform an fMRI analysis as described in Polzehl and Tabelow (2019) <DOI:10.1007/978-3-030-29184-6>, Tabelow et al. (2006) <DOI:10.1016/j.neuroimage.2006.06.029>, Polzehl et al. (2010) <DOI:10.1016/j.neuroimage.2010.04.241>, Tabelow and Polzehl (2011) <DOI:10.18637/jss.v044.i11>.

This package provides exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, Multiple Factor Analysis when variables are structured in groups, etc. and hierarchical cluster analysis.

Multiple imputation using Fully Conditional Specification (FCS) implemented by the MICE algorithm as described in http://doi.org/10.18637/jss.v045.i03. Each variable has its own imputation model. Built-in imputation models are provided for continuous data (predictive mean matching, normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical data (proportional odds). MICE can also impute continuous two-level data (normal model, pan, second-level variables). Passive imputation can be used to maintain consistency between variables. Various diagnostic plots are available to inspect the quality of the imputations.

This package provides medium to high level functions for 3D interactive graphics, including functions modelled on base graphics (plot3d(), etc.) as well as functions for constructing representations of geometric objects (cube3d(), etc.). Output may be on screen using OpenGL, or to various standard 3D file formats including WebGL, PLY, OBJ, STL as well as 2D image formats, including PNG, Postscript, SVG, PGF.

This package provides a placeholder for the Liberation fontset intended for the fontquiver package. This fontset covers the 12 combinations of families (sans, serif, mono) and faces (plain, bold, italic, bold italic) supported in R graphics devices.

The Ziggurat pseudo-random number generator (or PRNG) offers a lightweight and very fast PRNG for the normal, exponential, and uniform distributions. It is provided here in a small zero-dependency package. It can be used from R as well as from C/C++ code in other packages as is demonstrated by four included sample packages using four distinct methods to use the PRNG presented here in client package.

This package provides lots of predicates (is_* functions) to check the state of your variables, and assertions (assert_* functions) to throw errors if they aren't in the right form.

This package provides a utility for R to parse a bibtex file.

This package provides tools for making the descriptive "Table 1" used in medical articles, a transition plot for showing changes between categories (also known as a Sankey diagram), flow charts by extending the grid package, a method for variable selection based on the SVD, Bezier lines with arrows complementing the ones in the grid package, and more.