Algorithms for Electivity Indices (electivity)
Provides all electivity algorithms (including Vanderploeg and Scavia electivity) that were examined in Lechowicz (1982) <doi:10.1007/BF00349007>, plus the example data that were provided for moth resource utilisation.

Actuarial Functions for Non-Life Insurance Modelling (NetSimR)
Assists actuaries and other insurance modellers in pricing, reserving and capital modelling for non-life insurance and reinsurance modelling. Provides functions that help model excess levels, capping and pure Incurred but not reported claims (pure IBNR). Includes capped mean, exposure curves and increased limit factor curves (ILFs) for LogNormal, Gamma, Pareto, Sliced LogNormal-Pareto and Sliced Gamma-Pareto distributions. Includes mean, probability density function (pdf), cumulative probability function (cdf) and inverse cumulative probability function for Sliced LogNormal-Pareto and Sliced Gamma-Pareto distributions. Includes calculating pure IBNR exposure with LogNormal and Gamma distribution for reporting delay.

The Hellinger Correlation (HellCor)
Empirical value of the Hellinger correlation, a new measure of dependence between two continuous random variables that satisfies a set of 7 desirable axioms (existence, symmetry, normalisation, characterisation of independence, weak Gaussian conformity, characterisation of pure dependence, generalised Data Processing Inequality). More details can be found in Geenens and Lafaye De Micheaux (2018) <arXiv:1810.10276>.

Fast Embedding Guided by Self-Organizing Map (EmbedSOM)
Provides a smooth mapping of multidimensional points into low-dimensional space defined by a self-organizing map. Designed to work with ‘FlowSOM’ and flow-cytometry use-cases. See Kratochvil et al. (2019) <doi:10.1101/496869>.

Auto-Adaptive Parentage Inference Software Tolerant to Missing Parents (APIS)
Parentage assignment package. Parentage assignment is performed based on observed average Mendelian transmission probability distributions. The main function of this package is the function APIS(), which is the parentage assignment function.

Functional Latent Data Models for Clustering Heterogeneous Curves (‘FLaMingos’) (flamingos)
Provides a variety of original and flexible user-friendly statistical latent variable models for the simultaneous clustering and segmentation of heterogeneous functional data (i.e time series, or more generally longitudinal data, fitted by unsupervised algorithms, including EM algorithms. Functional Latent Data Models for Clustering heterogeneous curves (‘FLaMingos’) are originally introduced and written in ‘Matlab’ by Faicel Chamroukhi <https://…&type=public&language=matlab>. The references are mainly the following ones. Chamroukhi F. (2010) <https://…/FChamroukhi-PhD.pdf>. Chamroukhi F., Same A., Govaert, G. and Aknin P. (2010) <doi:10.1016/j.neucom.2009.12.023>. Chamroukhi F., Same A., Aknin P. and Govaert G. (2011). <doi:10.1109/IJCNN.2011.6033590>. Same A., Chamroukhi F., Govaert G. and Aknin, P. (2011) <doi:10.1007/s11634-011-0096-5>. Chamroukhi F., and Glotin H. (2012) <doi:10.1109/IJCNN.2012.6252818>. Chamroukhi F., Glotin H. and Same A. (2013) <doi:10.1016/j.neucom.2012.10.030>. Chamroukhi F. (2015) <https://…/FChamroukhi-HDR.pdf>. Chamroukhi F. and Nguyen H-D. (2019) <doi:10.1002/widm.1298>.

Create Split Packed Bubble Charts (hpackedbubble)
By binding R functions and the ‘Highcharts’ <http://…/> charting library, ‘hpackedbubble’ package provides a simple way to draw split packed bubble charts.

Count Transformation Models (cotram)
Count transformation models featuring parameters interpretable as discrete hazard ratios, odds ratios, reverse-time discrete hazard ratios, or transformed expectations. An appropriate data transformation for a count outcome and regression coefficients are simultaneously estimated by maximising the exact discrete log-likelihood using the computational framework provided in package ‘mlt’, technical details are given in Hothorn et al. (2018) <DOI:10.1111/sjos.12291>.

Extension to ‘spatstat’ for Large Datasets on a Linear Network (spatstat.Knet)
Extension to the ‘spatstat’ package, for analysing large datasets of spatial points on a network. Provides a memory-efficient algorithm for computing the geometrically-corrected K function, described in S. Rakshit, A. Baddeley and G. Nair (2019) <doi:10.18637/jss.v090.i01>

Create Trusted Timestamps of Datasets and Files (trustedtimestamping)
Trusted Timestamps (tts) are created by incorporating a hash of a file or dataset into a transaction on the decentralized blockchain (Stellar network). The package makes use of a free service provided by <https://stellarapi.io>.

Manage the Life Cycle of your Package Functions (lifecycle)
Manage the life cycle of your exported functions with shared conventions, documentation badges, and non-invasive deprecation warnings. The ‘lifecycle’ package defines four development stages (experimental, maturing, stable, and questioning) and three deprecation stages (soft-deprecated, deprecated, and defunct). It makes it easy to insert badges corresponding to these stages in your documentation. Usage of deprecated functions are signalled with increasing levels of non-invasive verbosity.

Markov Random Field Structure Estimator (mrfse)
A Markov random field structure estimator that uses a penalized maximum conditional likelihood method similar to the Bayesian Information Criterion (Frondana, 2016) <doi:10.11606/T.45.2018.tde-02022018-151123>.

Model Butcher (butcher)
Provides a set of five S3 generics to axe components of fitted model objects and help reduce the size of model objects saved to disk.

Parsing Semi-Structured Log Files into Tabular Format (tabulog)
Convert semi-structured log files (such as ‘Apache’ access.log files) into a tabular format (data.frame) using a standard template system.

Robust Quality Control Chart (rQCC)
Constructs robust quality control chart based on the median and Hodges-Lehmann estimators (location) and the median absolute deviation (MAD) and Shamos estimators (scale) which are unbiased with a sample of finite size. For more details, see Park, Kim and Wang (2019)<arXiv:1908.00462>. This work was partially supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (No. NRF-2017R1A2B4004169).

Data Frame Class for Tracking Data (trackdf)
Data frame class for storing collective movement data (e.g. fish schools, ungulate herds, baboon troops) collected from GPS trackers or computer vision tracking software.

Fill Missing Values in Vectors (fillr)
Edit vectors to fill missing values, based on the vector itself.

Weighted Metrics and Performance Measures for Machine Learning (MetricsWeighted)
Provides weighted versions of several metrics and performance measures used in machine learning, including average unit deviances of the Bernoulli, Tweedie, Poisson, and Gamma distributions, see e.g. Ohlsson E. and Johansson B. (2015, ISBN: 978-3642107900). The package also contains a weighted version of generalized R-squared, see e.g. Cohen, Jacob. et al. (2002, ISBN: 978-0805822236). Furthermore, ‘dplyr’ chains are supported.

Multivariate Hypothesis Tests (MVTests)
Multivariate hypothesis tests and the confidence intervals. This package can be used for hypothesis tests which are The Hotelling T Square Tests (One-Sample, Two Independent Samples, Paired Samples), The One Way MANOVA,The Multivariate Shapiro-Wilk Test for Multivariate Normality Test, The Bartlett Test for One Sample Covariance Matrix, The Box-M Test and The Bartlett’s Sphericity Test. For this package, we have benefited the studies Rencher (2003), Nel and Merwe (1986) <DOI: 10.1080/03610928608829342>, Tatlidil (1996), James (1994) <DOI: 10.2307/2333003>, Tsagris (2014), Villasenor Alva and Estrada (2009) <DOI: 10.1080/03610920802474465>.

Quadratic Inference Function (qif)
Developed to perform the estimation and inference for regression coefficient parameters in longitudinal marginal models using the method of quadratic inference functions. Like generalized estimating equations, this method is also a quasi-likelihood inference method. It has been showed that the method gives consistent estimators of the regression coefficients even if the correlation structure is misspecified, and it is more efficient than GEE when the correlation structure is misspecified. Based on Qu, A., Lindsay, B.G. and Li, B. (2000) <doi:10.1093/biomet/87.4.823>.

Robust Estimation of the ACF from the M-Periodogram (acfMPeriod)
Non-robust and robust computations of the sample autocovariance (ACOVF) and sample autocorrelation functions (ACF) of univariate and multivariate processes. The methodology consists in reversing the diagonalization procedure involving the periodogram or the cross-periodogram and the Fourier transform vectors, and, thus, obtaining the ACOVF or the ACF as discussed in Fuller (1995) <doi:10.1002/9780470316917>. The robust version is obtained by fitting robust M-regressors to obtain the M-periodogram or M-cross-periodogram as discussed in Reisen et al. (2017) <doi:10.1016/j.jspi.2017.02.008>.

Generate High-Dimensional Binary Data with Correlation Structures (CorBin)
We design algorithms with linear time complexity with respect to the dimension for three commonly studied correlation structures, including exchangeable, decaying-product and K-dependent correlation structures, and extend the algorithms to generate binary data of general non-negative correlation matrices with quadratic time complexity. Jiang, W., Song, S., Hou, L. and Zhao, H. ‘CorBin: An efficient R package to generate high-dimensional binary data with correlation structures.’ Submitted to Journal of Statistical Software.

Mixtures of Continuous Time Markov Models (ClickClustCont)
Provides an expectation maximization (EM) algorithm to fit a mixture of continuous time Markov models for use with clickstream or other sequence type d …

Gillespie’s Stochastic Simulation Algorithm for Impatient People (GillespieSSA2)
A fast, scalable, and versatile framework for simulating large systems with Gillespie’s Stochastic Simulation Algorithm (‘SSA’). This package is the sp …

Generates Messages with Facts Sourced from the Wikipedia Main Page (wikifacts)
Creates messages containing random facts from the Wikipedia homepage. Intended to keep users interested during long waiting periods.

Integration to ‘Apache’ ‘Arrow’ (arrow)
Apache’ ‘Arrow’ <https://…/> is a cross-language development platform for in-memory d …

Thurstonian IRT Models (thurstonianIRT)
Fit Thurstonian Item Response Theory (IRT) models in R. This package supports fitting Thurstonian IRT models and its extensions using ‘Stan’, ‘lavaan’, …

Multiway Clustering via Tensor Block Models (tensorsparse)
Implements the multiway sparse clustering approach of Zeng and Wang (2019) <arXiv:1906.03807>.

Creates Ideal Data for Generalized Linear Models (GlmSimulatoR)
Have you ever struggled to find ‘good data’ for a generalized linear model? Would you like to test how quickly statistics converge to parameters, or le …

Compare H20 or Spark Supervised Regression Models Using Shiny App (shinyML)
Implementation of a shiny app to easily compare supervised regression model performances. You provide the data and configure each model parameter direc …

Wizardry Code Offensive Programming (wyz.code.offensiveProgramming)
Allows to change R coding from defensive programming (i.e. many input parameter checks implementation required) to offensive programming (none/reduced …

Data Science for Psychologists (ds4psy)
All data sets required for the examples and exercises in the book ‘Data Science for Psychologists’ (by Hansjoerg Neth, Konstanz University, 2019), free …

Bayesian Model Selection under Constraints (BMSC)
A Bayesian regression package supporting constrained coefficient estimation and variable selection using Stan. This includes a robust variable selectio …

Rendering Word Clouds (hwordcloud)
Provides a way to display word clouds in R. The word cloud is a html widget, so you can use it in interactive documents and ‘shiny’ applications.

Coefficient of Variation (CV) with Confidence Intervals (CI) (cvcqv)
Provides some easy-to-use functions and classes to calculate variability measures such as coefficient of variation with confidence intervals provided w …

Mixture Models with Heterogeneous and (Partially) Missing Data (RMixtCompIO)
Mixture Composer <https://…/MixtComp> is a project to build mixture mod …

Key Derivation Functions for R Based on Scrypt (scrypt)
Functions for working with the scrypt key derivation functions originally described by Colin Percival <DistributionTest)
Provides new types of omnibus tests which are generally much more powerful than traditional tests (including the Kolmogorov-Smirnov, Cramer-von Mises a …

Double Generalized Linear Models Extending Poisson Regression (DGLMExtPois)
Model estimation, dispersion testing and diagnosis of hyper-Poisson Saez-Castillo, A.J. and Conde-Sanchez, A. (2013) <doi:10.1016/j.csda.2012.12.009 …

Obfuscation Game Designs (obfuscatoR)
When people make decisions, they may do so using a wide variety of decision rules. The package allows users to easily create obfuscation games to test …

Residual Randomization Inference for Regression Models (RRI)
Testing and inference for regression models using residual randomization methods. The basis of inference is an invariance assumption on the regression …

Distance Sampling Survey Design (dssd)
Creates survey designs for distance sampling surveys. These designs can be assessed for various effort and coverage statistics. Once the user is satisf …

Brace Expansions (bracer)
Performs brace expansions on strings. Made popular by Unix shells, brace expansion allows users to quickly generate certain character vectors by taking …

Fast and Easy Data Cleaning (clean)
Data cleaning functions for classes ‘logical’, ‘factor’, ‘numeric’, ‘character’ and ‘Date’ to make data cleaning fast and easy. Relying on very few dep …

Solves Minimum Cost Bipartite Matching Problems (RcppHungarian)
Header library and R functions to solve minimum cost bipartite matching problem using Huhn-Munkres algorithm (Hungarian algorithm; <RMaCzek)
Allows for production of Czekanowski’s Diagrams. See A. Vasterlund (2019) Master thesis, Linkoping University.

App for Scheduling Interim Analyses in Clinical Trials (interimApp)
Allows an interactive assessment of the timing of interim analyses. The algorithm simulates both the recruitment and treatment/event phase of a clinica …

Sensitivity Analysis Tools for OLS (sensemakr)
Implements a suite of sensitivity analysis tools that extends the traditional omitted variable bias framework and makes it easier to understand the imp …

Detect Differentiation Problems (diffman)
An algorithm based on graph theory tools to detect differentiation problems. A differentiation problem occurs when aggregated data are disseminated acc …

Lasso with High Missing Rate (hmlasso)
A simple implementation of HMLasso (Lasso with High Missing rate). Takada, M., Fujisawa, H., & Nishikawa, T. (2019) <arXiv:1811.00255>.

Interact with the ‘Python’ Module ‘Featuretools’ (featuretoolsR)
A ‘reticulate’-based interface to the ‘Python’ module ‘Featuretools’. The package grants functionality to interact with ‘Pythons’ ‘Featuretools’ module …

Bayesian Aggregate Treatment Effects (baggr)
Running and comparing meta-analyses of data with hierarchical Bayesian models in Stan, including convenience functions for formatting data, plotting an …

Methods and Measures for Semantic Network Analysis (SemNeT)
Implements several functions for the analysis of semantic networks including partial node bootstrapping (Kenett, Anaki, & Faust, 2014 <doi:10.33 …

Combine Categories Using Greenacre’s Method (greenclust)
Implements a method of iteratively collapsing the rows of a contingency table, two at a time, by selecting the pair of categories whose combination yie …

Machine Learning in R – Next Generation (mlr3)
Efficient, object-oriented programming on the building blocks of machine learning. Provides ‘R6’ objects for tasks, learners, resamplings, and measures …

Robust Clustering Procedures (ktaucenters)
A clustering algorithm similar to K-Means is implemented, it has two main advantages, namely (a) The estimator is resistant to outliers, that means tha …

Computation and Plots of Influence Functions for Risk and Performance Measures (RPEIF)
Computes the influence functions time series of the returns for the risk and performance measures as mentioned in Zhang and Martin (2017) <