This is a set of tools for dendrograms and tree plots using ggplot2. The ggplot2 philosophy is to clearly separate data from the presentation. Unfortunately the plot method for dendrograms plots directly to a plot device with out exposing the data. The ggdendro package resolves this by making available functions that extract the dendrogram plot data. The package provides implementations for tree, rpart, as well as diana and agnes cluster diagrams.

This package contains functions to perform Bayesian inference using posterior simulation for a number of statistical models. Most simulation is done in compiled C++ written in the Scythe Statistical Library. All models return coda mcmc objects that can then be summarized using the coda package. Some useful utility functions such as density functions, pseudo-random number generators for statistical distributions, a general purpose Metropolis sampling algorithm, and tools for visualization are provided.

This package contains functions to implement the methodology and considerations laid out by Marks et al. in the article "Measuring abnormality in high dimensional spaces: applications in biomechanical gait analysis". Using high-dimensional datasets to measure a subject's overall level of abnormality as compared to a reference population is often needed in outcomes research.

This is a C/C++ based package for advanced data transformation and statistical computing in R that is extremely fast, class-agnostic, robust and programmer friendly. Core functionality includes a rich set of S3 generic grouped and weighted statistical functions for vectors, matrices and data frames, which provide efficient low-level vectorizations, OpenMP multithreading, and skip missing values by default. These are integrated with fast grouping and ordering algorithms (also callable from C), and efficient data manipulation functions. The package also provides a flexible and rigorous approach to time series and panel data in R. It further includes fast functions for common statistical procedures, detailed (grouped, weighted) summary statistics, powerful tools to work with nested data, fast data object conversions, functions for memory efficient R programming, and helpers to effectively deal with variable labels, attributes, and missing data.

This package lets you standardize country names, convert them into one of 40 different coding schemes, convert between coding schemes, and assign region descriptors.

This package implements a successive halving and hyperband optimization algorithm for the mlr3 ecosystem. The implementation in mlr3hyperband features improved scheduling and parallelizes the evaluation of configurations. The package includes tuners for hyperparameter optimization in mlr3tuning and optimizers for black-box optimization in bbotk.

This package provides functionality to dynamically define R functions and S4 methods with inlined C, C++ or Fortran code supporting .C and .Call calling conventions.

The ROI is a framework for handling optimization problems in R.

This package provides an improved implementation (based on k-nearest neighbors) of the density peak clustering algorithm, originally described by Alex Rodriguez and Alessandro Laio (Science, 2014 vol. 344). It can handle large datasets (> 100,000 samples) very efficiently.

Iterated race is an extension of the Iterated F-race method for the automatic configuration of optimization algorithms, that is, (offline) tuning their parameters by finding the most appropriate settings given a set of instances of an optimization problem.

This package implements affinity propagation clustering introduced by Frey and Dueck (2007). The package further provides leveraged affinity propagation and an algorithm for exemplar-based agglomerative clustering that can also be used to join clusters obtained from affinity propagation. Various plotting functions are available for analyzing clustering results.

This package provides a close to zero dependency package to draw and display Venn diagrams up to 7 sets, and any Boolean union of set intersections.

In S3 generics, it's useful to take ... so that methods can have additional arguments. But this flexibility comes at a cost: misspelled arguments will be silently ignored. The ellipsis package is an experiment that allows a generic to warn if any arguments passed in ... are not used.

This package provides type-stable rolling window functions over any R data type. Cumulative and expanding windows are also supported. For more advanced usage, an index can be used as a secondary vector that defines how sliding windows are to be created.

This package provides a helper that tests DBI back ends for conformity to the interface.

This package provides C-based tools for converting large scatterplot data to rasters. It speeds up plotting of data with millions of points.

Tidyft is an extension of data.table. It uses modifification by reference whenever possible. This toolkit is designed for big data analysis in high-performance desktop or laptop computers. The syntax of the package is similar or identical to tidyverse.

This package provides tools to fit and predict with the high-dimensional principal fitted components model. This model is described by Cook, Forzani, and Rothman (2012) doi:10.1214/11-AOS962.

This package extends shinydashboard with AdminLTE2 components. AdminLTE2 is a Bootstrap 3 dashboard template. Customize boxes, add timelines and a lot more.

This package provides data sets and scripts to accompany Time Series Analysis and Its Applications: With R Examples (4th ed), by R.H. Shumway and D.S. Stoffer. Springer Texts in Statistics, 2017, https://doi.org/10.1007/978-3-319-52452-8, and Time Series: A Data Analysis Approach Using R. Chapman-Hall, 2019, https://doi.org/10.1201/9780429273285.

Missing values are ubiquitous in data and need to be explored and handled in the initial stages of analysis. The package provides data structures and functions that facilitate the plotting of missing values and examination of imputations. This allows missing data dependencies to be explored with minimal deviation from the common work patterns of ggplot2 and tidy data.

This package performs optimization in R using C++. A unified wrapper interface is provided to call C functions of the five optimization algorithms (Nelder-Mead, BFGS, CG, L-BFGS-B and SANN) underlying optim().

Ggfittext is a ggplot2 extension for fitting text into boxes.

This package lets you import Excel files into R. It supports .xls via the embedded libxls C library and .xlsx via the embedded RapidXML C++ library.