Diagnostic tools as residual analysis, global, local and total-local influence for the multivariate model from the random intercept Poisson generalized log gamma model are available in this package. Including also, the estimation process by maximum likelihood method, for details see Fabio, L. C; Villegas, C. L.; Carrasco, J.M.F and de Castro, M. (2023) <doi:10.1080/03610926.2021.1939380> and Fábio, L. C.; Villegas, C.; Mamun, A. S. M. A. and Carrasco, J. M. F. (2025) <doi:10.28951/bjb.v43i1.728>.

This package provides functions to enhance the available statistical analysis procedures in R by providing simple functions to analysis and visualize the 16S rRNA data.Here we present a tutorial with minimum working examples to demonstrate usage and dependencies.

This package provides classes to implement, analyze and plot cohort life tables for actuarial calculations. Birth-year dependent cohort mortality tables using a yearly trend to extrapolate from a base year are implemented, as well as period life table, cohort life tables using an age shift, and merged life tables. Additionally, several data sets from various countries are included to provide widely-used tables out of the box.

Analysis and visualisation of synchrony, interaction, and joint movements from audio and video movement data of a group of music performers. The demo is data described in Clayton, Leante, and Tarsitani (2021) <doi:10.17605/OSF.IO/KS325>, while example analyses can be found in Clayton, Jakubowski, and Eerola (2019) <doi:10.1177/1029864919844809>. Additionally, wavelet analysis techniques have been applied to examine movement-related musical interactions, as shown in Eerola et al. (2018) <doi:10.1098/rsos.171520>.

Computational tools to represent phylogenetic signals using adapted eigenvector maps.

Datasets and functions for the book "Modélisation statistique par la pratique avec R", F. Bertrand, E. Claeys and M. Maumy-Bertrand (2019, ISBN:9782100793525, Dunod, Paris). The first chapter of the book is dedicated to an introduction to the R statistical software. The second chapter deals with correlation analysis: Pearson, Spearman and Kendall simple, multiple and partial correlation coefficients. New wrapper functions for permutation tests or bootstrap of matrices of correlation are provided with the package. The third chapter is dedicated to data exploration with factorial analyses (PCA, CA, MCA, MDA) and clustering. The fourth chapter is dedicated to regression analysis: fitting and model diagnostics are detailed. The exercises focus on covariance analysis, logistic regression, Poisson regression, two-way analysis of variance for fixed or random factors. Various example datasets are shipped with the package: for instance on pokemon, world of warcraft, house tasks or food nutrition analyses.

Includes support for Mapbox Navigation APIs, including directions, isochrones, and route optimization; the Search API for forward and reverse geocoding; the Maps API for interacting with Mapbox vector tilesets and visualizing Mapbox maps in R; and Mapbox Tiling Service and tippecanoe for generating map tiles. See <https://docs.mapbox.com/api/> for more information about the Mapbox APIs.

Relatively easy access is provided to 2023 version of the Maddison project data downloaded 2025-08-28. This project collates all the credible data on population and GDP for 169 countries, with some dating back to the year 1 of the current era. One function makes it easy to find the leaders for each year, allowing users to delete countries like OPEC with narrow economies to focus on technology leaders. Another function makes it easy to plot data for only selected countries or years. Another function makes it relatively easy to obtain references to the original sources, which must be cited per the copyright rules of the Maddison Project for different uses of their data.

Conducts and simulates the MABOUST design, including making interim decisions to stop a treatment for inferiority or stop the trial early for superiority or equivalency.

Quick and simple Tcl/Tk Graphical User Interface to call functions. Also comprises a very simple experimental GUI framework.

Perform the Model Confidence Set procedure of Hansen et.al (2011).

This package implements Multi-Group Sparse Discriminant Analysis proposal of I.Gaynanova, J.Booth and M.Wells (2016), Simultaneous sparse estimation of canonical vectors in the p>>N setting, JASA <doi:10.1080/01621459.2015.1034318>.

This package provides an interface to MetaPost (Hobby, 1998) <http://www.tug.org/docs/metapost/mpman.pdf>. There are functions to generate an R description of a MetaPost curve, functions to generate MetaPost code from an R description, functions to process MetaPost code, and functions to read solved MetaPost paths back into R.

This package provides a collection of miscellaneous helper function for running multilevel/mixed models in lme4'. This package aims to provide functions to compute common tasks when estimating multilevel models such as computing the intraclass correlation and design effect, centering variables, estimating the proportion of variance explained at each level, pseudo-R squared, random intercept and slope reliabilities, tests for homogeneity of variance at level-1, and cluster robust and bootstrap standard errors. The tests and statistics reported in the package are from Raudenbush & Bryk (2002, ISBN:9780761919049), Hox et al. (2018, ISBN:9781138121362), and Snijders & Bosker (2012, ISBN:9781849202015).

This package provides a comprehensive package for comparing multiple Structural Equation Models (SEM). Supports both nested and non-nested model comparisons, chi-square difference tests, and extraction of multiple fit indices including AIC (Akaike Information Criterion), BIC (Bayesian Information Criterion), CFI (Comparative Fit Index), TLI (Tucker-Lewis Index), RMSEA (Root Mean Square Error of Approximation), and SRMR (Standardized Root Mean Square Residual). Built on top of the lavaan package for seamless SEM model comparison workflows. The Vuong test (Vuong, 1989) for non-nested models is used as the statistical test.

This package provides readers for easy and consistent importing of Mouse Genome Informatics (MGI) report files: <https://www.informatics.jax.org/downloads/reports/index.html>. These data are provided by Baldarelli RM, Smith CL, Ringwald M, Richardson JE, Bult CJ, Mouse Genome Informatics Group (2024) <doi:10.1093/genetics/iyae031>.

Fits sphere-sphere regression models by estimating locally weighted rotations. Simulation of sphere-sphere data according to non-rigid rotation models. Provides methods for bias reduction applying iterative procedures within a Newton-Raphson learning scheme. Cross-validation is exploited to select smoothing parameters. See Marco Di Marzio, Agnese Panzera & Charles C. Taylor (2018) <doi:10.1080/01621459.2017.1421542>.

Systematically creates and modifies NONMEM(R) control streams. Harvests NONMEM output, builds run logs, creates derivative data, generates diagnostics. NONMEM (ICON Development Solutions <https://www.iconplc.com/>) is software for nonlinear mixed effects modeling. See package?nonmemica'.

This package provides access to the Native Status Resolver (NSR) <https://github.com/ojalaquellueva/nsr> API through R. The user supplies plant taxonomic names and political divisions and the package returns information about their likely native status (e.g., native, non-native,endemic), along with information on how those decisions were made.

The Needleman-Wunsch global alignment algorithm can be used to find approximate matches between sample names in different data sets. See Wang et al. (2010) <doi:10.4137/CIN.S5613>.

Fit univariate non-linear scale mixture of skew-normal(NL-SMSN) regression, details in Garay, Lachos and Abanto-Valle (2011) <doi:10.1016/j.jkss.2010.08.003> and Lachos, Bandyopadhyay and Garay (2011) <doi:10.1016/j.spl.2011.03.019>.

This package provides a Software Development Kit for working with Nixtla''s TimeGPT', a foundation model for time series forecasting. API is an acronym for application programming interface'; this package allows users to interact with TimeGPT via the API'. You can set and validate API keys and generate forecasts via API calls. It is compatible with tsibble and base R. For more details visit <https://docs.nixtla.io/>.

NanoString nCounter data are gene expression assays where there is no need for the use of enzymes or amplification protocols and work with fluorescent barcodes (Geiss et al. (2018) <doi:10.1038/nbt1385>). Each barcode is assigned a messenger-RNA/micro-RNA (mRNA/miRNA) which after bonding with its target can be counted. As a result each count of a specific barcode represents the presence of its target mRNA/miRNA. NACHO (NAnoString quality Control dasHbOard) is able to analyse the exported NanoString nCounter data and facilitates the user in performing a quality control. NACHO does this by visualising quality control metrics, expression of control genes, principal components and sample specific size factors in an interactive web application.

Simplify the exploratory data analysis process for multiple network data sets with the help of hierarchical clustering, consensus clustering and heatmaps. Multiple network data consists of multiple disjoint networks that have common variables (e.g. ego networks). This package contains the necessary tools for exploring such data, from the data pre-processing stage to the creation of dynamic visualizations.