Data sets are often corrupted by outliers. When data are multivariate outliers can be classified as case-wise or cell-wise. The latters are particularly challenge to handle. We implement a robust estimation procedure for Seemingly Unrelated Regression Models which is able to cope well with both type of outliers. Giovanni Saraceno, Fatemah Alqallaf, Claudio Agostinelli (2021) <doi:10.48550/arXiv.2107.00975>.

Calculate common survey data quality indicators for multi-item scales and matrix questions. Currently supports the calculation of response style indicators and response distribution indicators. For an overview on response quality indicators see Bhaktha N, Henning S, Clemens L (2024). Characterizing response quality in surveys with multi-item scales: A unified framework <https://osf.io/9gs67/>.

Processing logical operations such as AND/OR/NOT operations dynamically. It also handles nesting in the operations.

Make your workflow faster and easier. Easily customizable plots (via ggplot2'), nice APA tables (following the style of the *American Psychological Association*) exportable to Word (via flextable'), easily run statistical tests or check assumptions, and automatize various other tasks.

Since the early 1970s eyewitness testimony researchers have recognised the importance of estimating properties such as lineup bias (is the lineup biased against the suspect, leading to a rate of choosing higher than one would expect by chance?), and lineup size (how many reasonable choices are in fact available to the witness? A lineup is supposed to consist of a suspect and a number of additional members, or foils, whom a poor-quality witness might mistake for the perpetrator). Lineup measures are descriptive, in the first instance, but since the earliest articles in the literature researchers have recognised the importance of reasoning inferentially about them. This package contains functions to compute various properties of laboratory or police lineups, and is intended for use by researchers in forensic psychology and/or eyewitness testimony research. Among others, the r4lineups package includes functions for calculating lineup proportion, functional size, various estimates of effective size, diagnosticity ratio, homogeneity of the diagnosticity ratio, ROC curves for confidence x accuracy data and the degree of similarity of faces in a lineup.

We implement full-ranked, rank-penalized, and adaptive nuclear norm penalized estimation methods using multivariate mixture models proposed by Kang, Chen, and Yao (2022+).

This package provides a set of functions for receiver operating characteristic (ROC) curve estimation and area under the curve (AUC) calculation. All functions are designed to work with aggregated data; nevertheless, they can also handle raw samples. In ROCket', we distinguish two types of ROC curve representations: 1) parametric curves - the true positive rate (TPR) and the false positive rate (FPR) are functions of a parameter (the score), 2) functions - TPR is a function of FPR. There are several ROC curve estimation methods available. An introduction to the mathematical background of the implemented methods (and much more) can be found in de Zea Bermudez, Gonçalves, Oliveira & Subtil (2014) and Cai & Pepe (2004).

Linguistic Descriptions of Complex Phenomena (LDCP) is an architecture and methodology that allows us to model complex phenomena, interpreting input data, and generating automatic text reports customized to the user needs (see <doi:10.1016/j.ins.2016.11.002> and <doi:10.1007/s00500-016-2430-5>). The proposed package contains a set of methods that facilitates the development of LDCP systems. It main goal is increasing the visibility and practical use of this research line.

This package provides an intuitive and user-friendly interface for working with emojis in R'. It allows users to search, insert, and manage emojis by keyword, category, or through an interactive shiny'-based drop-down. The package enables integration of emojis into R scripts, R Markdown', Quarto', shiny apps, and ggplot2 plots. Also includes built-in mappings for commit messages, useful for version control. It builds on established emoji libraries and Unicode standards, adding expressiveness and visual cues to documentation, user interfaces, and reports. For more details see Emojipedia (2024) <https://emojipedia.org> and GitHub Emoji Cheat Sheet <https://github.com/ikatyang/emoji-cheat-sheet/tree/master>.

This package provides functions that compute rational approximations of fractional elliptic stochastic partial differential equations. The package also contains functions for common statistical usage of these approximations. The main references for rSPDE are Bolin, Simas and Xiong (2023) <doi:10.1080/10618600.2023.2231051> for the covariance-based method and Bolin and Kirchner (2020) <doi:10.1080/10618600.2019.1665537> for the operator-based rational approximation. These can be generated by the citation function in R.

The Echo nest <http://the.echonest.com> is the industry's leading music intelligence company, providing developer with deepest understanding of music content and music fans. This package can be used to access artist's data including songs, blogs, news, reviews etc. Song's data including audio summary, style, danceability, tempo etc can also be accessed.

Este paquete proporciona una interfaz grafica de usuario (GUI) para algunos de los procedimientos estadisticos detallados en un curso de Estadistica aplicada a las Ciencias Sociales mediante el programa informatico R (EACSPIR). LA GUI se ha desarrollado como un Plugin del programa R-Commander.

This package provides various features to streamline and enhance the styling of interactive reactable tables with easy-to-use and highly-customizable functions and themes. Apply conditional formatting to cells with data bars, color scales, color tiles, and icon sets. Utilize custom table themes inspired by popular websites such and bootstrap themes. Apply sparkline line & bar charts (note this feature requires the dataui package which can be downloaded from <https://github.com/timelyportfolio/dataui>). Increase the portability and reproducibility of reactable tables by embedding images from the web directly into cells. Save the final table output as a static image or interactive file.

Compiling regression results into a publishable format, conducting post-hoc hypothesis testing, and plotting moderating effects (the effect of X on Y becomes stronger/weaker as Z increases).

An easy way to analyze international large-scale assessments and surveys in education or any other dataset that includes replicated weights (Balanced Repeated Replication (BRR) weights, Jackknife replicate weights,...) while also allowing for analysis with multiply imputed variables (plausible values). It supports the estimation of univariate statistics (e.g. mean, variance, standard deviation, quantiles), frequencies, correlation, linear regression and any other model already implemented in R that takes a data frame and weights as parameters. It also includes options to prepare the results for publication, following the table formatting standards of the Organization for Economic Cooperation and Development (OECD).

This package implements a high performance C++ parser for ActiGraph GT3X'/'GT3X+ data format (with extension .gt3x') for accelerometer samples. Activity samples can be easily read into a matrix or data.frame. This allows for storing the raw accelerometer samples in the original binary format to reserve space.

R Commander plug-in for repeated-measures and mixed-design ('split-plot') ANOVA. It adds a new menu entry for repeated measures that allows to deal with up to three within-subject factors and optionally with one or several between-subject factors. It also provides supplementary options to oneWayAnova() and multiWayAnova() functions, such as choice of ANOVA type, display of effect sizes and post hoc analysis for multiWayAnova().

Build regular expressions piece by piece using human readable code. This package is designed for interactive use. For package development, use the rebus.* dependencies.

Allows work with MyTarget Statistics API v2 <https://target.my.com/adv/api-marketing/doc/stat-v2> and MyTarget Statistics API v3 <https://target.my.com/adv/api-marketing/doc/stat-v2#statisticsv3> load data by ads, campaigns, agency clients and statistic from your ads account.

This package provides functions to perform robust stepwise split regularized regression. The approach first uses a robust stepwise algorithm to split the variables into the models of an ensemble. An adaptive robust regularized estimator is then applied to each subset of predictors in the models of an ensemble.

The Streamulus (template, header-only) library by Irit Katriel (at <https://github.com/iritkatriel/streamulus>) provides a very powerful yet convenient framework for stream processing. This package connects Streamulus to R by providing both the header files and all examples.

Within this package the XML-RPC API to NEOS <https://neos-server.org/neos/> is implemented. This enables the user to pass optimization problems to NEOS and retrieve results within R.

Client for the Ocean Biodiversity Information System (<https://obis.org>).

We provide functions to perform taxometric analyses. This package contains 46 functions, but only 5 should be called directly by users. CheckData() should be run prior to any taxometric analysis to ensure that the data are appropriate for taxometric analysis. RunTaxometrics() performs taxometric analyses for a sample of data. RunCCFIProfile() performs a series of taxometric analyses to generate a CCFI profile. CreateData() generates a sample of categorical or dimensional data. ClassifyCases() assigns cases to groups using the base-rate classification method.