This is a simple package which provides a function that boosts pre-ready or custom-made classifiers. Package uses Discrete AdaBoost (<doi:10.1006/jcss.1997.1504>) and Real AdaBoost (<doi:10.1214/aos/1016218223>) for two class, SAMME (<doi:10.4310/SII.2009.v2.n3.a8>) and SAMME.R (<doi:10.4310/SII.2009.v2.n3.a8>) for multiclass classification.

Rho is used to test the generalization of inter rater reliability (IRR) statistics. Calculating rho starts by generating a large number of simulated, fully-coded data sets: a sizable collection of hypothetical populations, all of which have a kappa value below a given threshold -- which indicates unacceptable agreement. Then kappa is calculated on a sample from each of those sets in the collection to see if it is equal to or higher than the kappa in then real sample. If less than five percent of the distribution of samples from the simulated data sets is greater than actual observed kappa, the null hypothesis is rejected and one can conclude that if the two raters had coded the rest of the data, we would have acceptable agreement (kappa above the threshold).

This package provides a lightweight implementation of the geomorphon terrain form classification algorithm of Jasiewicz and Stepinski (2013) <doi:10.1016/j.geomorph.2012.11.005> based largely on the GRASS GIS r.geomorphon module. This implementation employs a novel algorithm written in C++ and RcppParallel'.

It offers random numbers generation from members of the truncated multivariate elliptical family of distribution such as the truncated versions of the Normal, Student-t, Laplace, Pearson VII, Slash, Logistic, among others. Particular distributions can be provided by specifying the density generating function. It also computes the first two moments (covariance matrix as well) for some particular distributions. References used for this package: Galarza, C. E., Matos, L. A., Castro, L. M., and Lachos, V. H. (2022). Moments of the doubly truncated selection elliptical distributions with emphasis on the unified multivariate skew-t distribution. Journal of Multivariate Analysis, 189, 104944 <doi:10.1016/j.jmva.2021.104944>; Ho, H. J., Lin, T. I., Chen, H. Y., and Wang, W. L. (2012). Some results on the truncated multivariate t distribution. Journal of Statistical Planning and Inference, 142(1), 25-40 <doi:10.1016/j.jspi.2011.06.006>; Valeriano, K. A., Galarza, C. E., and Matos, L. A. (2021). Moments and random number generation for the truncated elliptical family of distributions. Statistics and Computing, 33(1), 32 <doi:10.1007/s11222-022-10200-4>.

An implementation of the radviz projection in R. It enables the visualization of multidimensional data while maintaining the relation to the original dimensions. This package provides functions to create and plot radviz projections, and a number of summary plots that enable comparison and analysis. For reference see Hoffman *et al.* (1999) (<doi:10.1145/331770.331775>) for original implementation, see Di Caro *et al* (2012) (<doi:10.1007/978-3-642-13672-6_13>), for the original method for dimensional anchor arrangements, see Demsar *et al.* (2007) (<doi:10.1016/j.jbi.2007.03.010>) for the original Freeviz implementation.

Superclasses PostgreSQL connection to help enable full dplyr functionality on Redshift'.

This package provides a data structure and toolkit for documenting and recoding categorical data that can be shared in other statistical software.

This package provides a flexible framework for implementing hierarchical access control in shiny applications. Features include user permission management through a two-tier system of access panels and units, pluggable shiny module for administrative interfaces, and support for multiple storage backends (local, AWS S3', Posit Connect'). The system enables fine-grained control over application features, with built-in audit trails and user management capabilities. Integrates seamlessly with Posit Connect's authentication system.

This package provides a collection of functions related to the study of etiologic heterogeneity both across disease subtypes and across individual disease markers. The included functions allow one to quantify the extent of etiologic heterogeneity in the context of a case-control study, and provide p-values to test for etiologic heterogeneity across individual risk factors. Begg CB, Zabor EC, Bernstein JL, Bernstein L, Press MF, Seshan VE (2013) <doi:10.1002/sim.5902>.

An R interface to Weka (Version 3.9.3). Weka is a collection of machine learning algorithms for data mining tasks written in Java, containing tools for data pre-processing, classification, regression, clustering, association rules, and visualization. Package RWeka contains the interface code, the Weka jar is in a separate package RWekajars'. For more information on Weka see <https://www.cs.waikato.ac.nz/ml/weka/>.

Some heavily used base R functions are reconstructed to also be compliant to data.table objects. Also, some general helper functions that could be of interest for working with data.table objects are included.

This package performs multinomial goodness-of-fit test on multinomially distributed data using the Randomized phi-divergence test statistics. Details of this kind of statistics can be found at Nikita Puchkin, Vladimir Ulyanov (2023) <doi:10.1214/22-AIHP1299>.

This package provides a collection of R Markdown templates for nicely structured, reproducible data analyses in R. The templates have embedded examples on how to write citations, footnotes, equations and use colored message/info boxes, how to cross-reference different parts/sections in the report, provide a nice table of contents (toc) with a References section and proper R session information as well as examples using DT tables and ggplot2 graphs. The bookdown Lite template theme supports code folding.

Open any data frame with visidata', a terminal-based spreadsheet application <https://www.visidata.org>.

Enhances the R Optimization Infrastructure ('ROI') package with the alabama solver for solving nonlinear optimization problems.

Retrieve, map and summarize data from the VertNet.org archives (<https://vertnet.org/>). Functions allow searching by many parameters, including taxonomic names, places, and dates. In addition, there is an interface for conducting spatially delimited searches, and another for requesting large datasets via email.

This package provides a collection of functions for computing "r-values" from various kinds of user input such as MCMC output or a list of effect size estimates and associated standard errors. Given a large collection of measurement units, the r-value, r, of a particular unit is a reported percentile that may be interpreted as the smallest percentile at which the unit should be placed in the top r-fraction of units.

Software for genomic prediction with the RR-BLUP mixed model (Endelman 2011, <doi:10.3835/plantgenome2011.08.0024>). One application is to estimate marker effects by ridge regression; alternatively, BLUPs can be calculated based on an additive relationship matrix or a Gaussian kernel.

This package provides a collection of efficient and effective tools and algorithms for subgroup discovery and analytics. The package integrates an R interface to the org.vikamine.kernel library of the VIKAMINE system <http://www.vikamine.org> implementing subgroup discovery, pattern mining and analytics in Java.

Perform a Relative Weights Analysis (RWA) (a.k.a. Key Drivers Analysis) as per the method described in Tonidandel & LeBreton (2015) <DOI:10.1007/s10869-014-9351-z>, with its original roots in Johnson (2000) <DOI:10.1207/S15327906MBR3501_1>. In essence, RWA decomposes the total variance predicted in a regression model into weights that accurately reflect the proportional contribution of the predictor variables, which addresses the issue of multi-collinearity. In typical scenarios, RWA returns similar results to Shapley regression, but with a significant advantage on computational performance.

This package provides string arithmetic, reassignment operators, logical operators that handle missing values, and extra logical operators such as floating point equality and all or nothing. The intent is to allow R users to write code that is easier to read, write, and maintain while providing a friendlier experience to new R users from other language backgrounds (such as Python') who are used to concepts such as x += 1 and foo + bar'. Includes operators for not in, easy floating point comparisons, === equivalent, and SQL-like like operations (), etc. We also added in some extra helper functions, such as OS checks, pasting in Oxford comma format, and functions to get the first, last, nth, or most common element of a vector or word in a string.

Package to Handle R Requests from R Service Bus Applications with JSON Payloads in a generic way. The incoming request is encoded as a string (character vector of length one) containing the JSON file passed through by the client.

An implementation of robust bent line regression. It can fit the bent line regression and test the existence of change point, for the paper, "Feipeng Zhang and Qunhua Li (2016). Robust bent line regression, submitted.".

Partitions the phenotypic variance of a plastic trait, studied through its reaction norm. The variance partition distinguishes between the variance arising from the average shape of the reaction norms (V_Plas) and the (additive) genetic variance . The latter is itself separated into an environment-blind component (V_G/V_A) and the component arising from plasticity (V_GxE/V_AxE). The package also provides a way to further partition V_Plas into aspects (slope/curvature) of the shape of the average reaction norm (pi-decomposition) and partition V_Add (gamma-decomposition) and V_AxE (iota-decomposition) into the impact of genetic variation in the reaction norm parameters. Reference: de Villemereuil & Chevin (2025) <doi:10.32942/X2NC8B>.