This package is a collection of several algorithms to obtain archetypoids with small and large databases and with both classical multivariate data and functional data (univariate and multivariate). Some of these algorithms also detect anomalies (outliers).

This package provides a ggplot2 extension for easy plotting of half-half geom combinations. Think half boxplot and half jitterplot, or half violinplot and half dotplot.

This package provides a set of tools for manipulating and reading geographic data, in particular ESRI Shapefiles. It includes binary access to GSHHG shoreline files. The package also provides interface wrappers for exchanging spatial objects with other R packages.

This package provides tools to convert plot function calls (using expression or formula) to grob or ggplot objects that are compatible with the grid and ggplot2 environment. With this package, we are able to e.g. use cowplot to align plots produced by base graphics, grid, lattice, vcd etc. by converting them to ggplot objects.

Similarly to Schafer's package pan, jomo is a package for multilevel joint modelling multiple imputation http://doi.org/10.1002/9781119942283. Novel aspects of jomo are the possibility of handling binary and categorical data through latent normal variables, the option to use cluster-specific covariance matrices and to impute compatibly with the substantive model.

This package provides code analysis tools for R to check R code for possible problems.

This package extends sparse matrix and vector classes from the Matrix package by providing:

1. Methods and operators that work natively on CSR formats (compressed sparse row, a.k.a. RsparseMatrix) such as slicing/sub-setting, assignment, rbind(), mathematical operators for CSR and COO such as addition or sqrt(), and methods such as diag();

2. Multi-threaded matrix multiplication and cross-product for many <sparse, dense> types, including the float32 type from float;

3. Coercion methods between pairs of classes which are not present in Matrix, such as from dgCMatrix to ngRMatrix, as well as convenience conversion functions;

4. Utility functions for sparse matrices such as sorting the indices or removing zero-valued entries;

5. Fast transposes that work by outputting in the opposite storage format;

6. Faster replacements for many Matrix methods for all sparse types, such as slicing and elementwise multiplication.

7. Convenience functions for sparse objects, such as mapSparse or a shorter show method.

This package provides some easy-to-use functions to extract and visualize the output of multivariate data analyses, including PCA (Principal Component Analysis), CA (Correspondence Analysis), MCA (Multiple Correspondence Analysis), FAMD (Factor Analysis of Mixed Data), MFA (Multiple Factor Analysis) and HMFA (Hierarchical Multiple Factor Analysis) functions from different R packages. It contains also functions for simplifying some clustering analysis steps and provides ggplot2-based elegant data visualization.

This package contains a list of functional time series, sliced functional time series, and functional data sets. Functional time series is a special type of functional data observed over time. Sliced functional time series is a special type of functional time series with a time variable observed over time.

The main function kcca implements a general framework for k-centroids cluster analysis supporting arbitrary distance measures and centroid computation. Further cluster methods include hard competitive learning, neural gas, and QT clustering. There are numerous visualization methods for cluster results (neighborhood graphs, convex cluster hulls, barcharts of centroids, ...), and bootstrap methods for the analysis of cluster stability.

This package provides fundamental physical constants (quantity, value, uncertainty, unit) for SI and non-SI units, plus unit conversions based on the data from NIST, USA.

This package provides efficient routines for manipulation of date-time objects while accounting for time-zones and daylight saving times. The package includes utilities for updating of date-time components (year, month, day etc.), modification of time-zones, rounding of date-times, period addition and subtraction etc. Parts of the CCTZ source code, released under the Apache 2.0 License, are included in this package.

This package provides miscellaneous functions for SciViews or general use, including tools to manage a temporary environment attached to the search path for temporary variables you do not want to save() or load(); test the current platform; showing progress bars, etc.

This package provides tools to create Class Cover Catch Digraphs, neighborhood graphs, and relatives.

This package provides different approaches for selecting the threshold in generalized Pareto distributions. Most of them are based on minimizing the AMSE-criterion or at least by reducing the bias of the assumed GPD-model. Others are heuristically motivated by searching for stable sample paths, i.e. a nearly constant region of the tail index estimator with respect to k, which is the number of data in the tail. The third class is motivated by graphical inspection. In addition, a sequential testing procedure for GPD-GoF-tests is also implemented here.

This is a package to read raw accelerometry from GT3X+ accelerometry data and plain table data to calculate the Activity Index from Bai et al. (2016) doi:10.1371/journal.pone.0160644.

This package provides an implementation of the FastICA algorithm to perform independent component analysis (ICA) and projection pursuit.

This is a collection of tools for assessment of feature importance and feature effects. Key functions are:

• feature_importance() for assessment of global level feature importance,

• ceteris_paribus() for calculation of the what-if plots,

• partial_dependence() for partial dependence plots,

• conditional_dependence() for conditional dependence plots,

• accumulated_dependence() for accumulated local effects plots,

• aggregate_profiles() and cluster_profiles() for aggregation of ceteris paribus profiles,

• generic print() and plot() for better usability of selected explainers,

• generic plotD3() for interactive, D3 based explanations, and

• generic describe() for explanations in natural language.

This package provides a tool for calculating z-scores and centiles for weight-for-age, length/height-for-age, weight-for-length/height, BMI-for-age, head circumference-for-age, age circumference-for-age, subscapular skinfold-for-age, triceps skinfold-for-age based on the WHO Child Growth Standards.

This is an R package for spell checking common document formats including LaTeX, markdown, manual pages, and DESCRIPTION files. It includes utilities to automate checking of documentation and vignettes as a unit test during R CMD check. Both British and American English are supported out of the box and other languages can be added. In addition, packages may define a wordlist to allow custom terminology without having to abuse punctuation.

This is an extension of the testthat package that lets you add parameters to your unit tests. Parameterized unit tests are often easier to read and more reliable, since they follow the DNRY (do not repeat yourself) rule.

This package provides tools for the maximum likelihood estimation of the parameters of a fractionally differenced ARIMA(p,d,q) model (Haslett and Raftery, Appl.Statistics, 1989); it includes inference and basic methods.

This package is designed to be used with Rscript to write shebang scripts that accept short and long options. Many users will prefer to use the packages optparse or argparse which add extra features like automatically generated help options and usage texts, support for default values, positional argument support, etc.

This package provides Ace editor bindings to enable a rich text editing environment within Shiny.