C++ implementation of Maximum Entropy (Maxent) species distribution modeling with R bindings via Rcpp'. Provides a high-performance reimplementation of the Maxent algorithm for modeling species geographic distributions from occurrence data and environmental variables, following Phillips et al. (2006) <doi:10.1016/j.ecolmodel.2005.03.026>. Supports linear, quadratic, product, hinge, and threshold feature transformations, spatial projection in raw, logistic, and cloglog scales, and model diagnostics including Area Under the ROC Curve (AUC), variable importance, response curves, and Multivariate Environmental Similarity Surfaces (MESS) maps.

Create tile grid maps, which are like choropleth maps except each region is represented with equal visual space.

This package provides a suite of convenience functions for generating US state and county thematic maps using datasets from the MazamaSpatialUtils package.

Fast masked KNN imputation for tabular data with support for single and multiple imputation.

Recursively partitions datasets on binary splits across multiple targets having different dependent variable types, including categorical, continuous, count, and survival outcomes. This overcomes single-target limitations of traditional decision trees while retaining model interpretability. See Ayton and Trevino (2023) <doi:10.1093/bioinformatics/btad507> and Ayton et al. (2025) <doi:10.1038/s44401-025-00025-4> for details.

This package provides a shiny web application to map scores from clinical instruments (PANSS, SQLS, WHODAS 2.0, PHQ-8, EQ-5D-5L) to preference-based EQ-5D-5L health utility values using validated regression-based and beta-mixture mapping algorithms developed from Singapore population studies. Intended for use in health economic evaluations and cost-utility analyses. Methods are based on: Abdin et al. (2019) <doi:10.1007/s11136-018-2037-7>, Seow et al. (2023) <doi:10.1080/14737167.2023.2215430>, Abdin et al. (2021) <doi:10.1186/s12888-021-03463-0>, Abdin et al. (2024) <doi:10.1080/14737167.2024.2376100>.

Extends finite mixtures of quantile regressions (the mixqr package) with a concomitant-covariate, quantile-indexed mixing gate. The mixing probabilities follow a multinomial-logit model whose coefficients may depend on a separate set of gating covariates and on the quantile level, so that latent-class membership can change across the conditional distribution. This turns the location-varying mixing idea of Furno (2025) into a likelihood and EM object with proper standard errors on the gate. Estimation reuses the mixqr component and error-density machinery; the gate is fit by a weighted multinomial-logistic M-step and reduces exactly to a constant gate when the gating model is an intercept only.

Visualization of decision rules for binary classification and Receiver Operating Characteristic (ROC) curve estimation under different generalizations proposed in the literature: - making the classification subsets flexible to cover those scenarios where both extremes of the marker are associated with a higher risk of being positive, considering two thresholds (gROC() function); - transforming the marker by a proper function trying to improve the classification performance (hROC() function); - when dealing with multivariate markers, considering a proper transformation to univariate space trying to maximize the resulting AUC of the TPR for each FPR (multiROC() function). The classification regions behind each point of the ROC curve are displayed in both static graphics (plot_buildROC(), plot_regions() or plot_funregions() function) or videos (movieROC() function).

Friendly implementation of the Mann-Whitney-Wilcoxon test for competitive gene set enrichment analysis.

An implementation of the mixed neighbourhood selection (MNS) algorithm. The MNS algorithm can be used to estimate multiple related precision matrices. In particular, the motivation behind this work was driven by the need to understand functional connectivity networks across multiple subjects. This package also contains an implementation of a novel algorithm through which to simulate multiple related precision matrices which exhibit properties frequently reported in neuroimaging analysis.

This package provides an extension to the lolog package by introducing the minTriadicClosure() statistic to capture higher-order interactions among triplets of nodes. This function facilitates improved modelling of group formations and triadic closure in networks. A smoothing parameter has been incorporated to avoid numerical errors.

Supports visual interpretation of hierarchical composite endpoints (HCEs). HCEs are complex constructs used as primary endpoints in clinical trials, combining outcomes of different types into ordinal endpoints, in which each patient contributes the most clinically important event (one and only one) to the analysis. See Karpefors M et al. (2022) <doi:10.1177/17407745221134949>.

Local linear estimation of psychometric functions. Provides functions for nonparametric estimation of a psychometric function and for estimation of a derived threshold and slope, and their standard deviations and confidence intervals.For more details see Zychaluk and Foster (2009) <doi:10.3758/APP.71.6.1414> and Foster and Zychaluk (2007) <doi:10.1109/MSP.2007.4286564>.

This package provides methods for calculating and testing the significance of pairwise monotonic association from and based on the work of Pimentel (2009) <doi:10.4135/9781412985291.n2>. Computation of association of vectors from one or multiple sets can be performed in parallel thanks to the packages foreach and doMC'.

Use standard genomics file format (BED) and a table of orthologs to illustrate synteny conservation at the genome-wide scale. Significantly conserved linkage groups are identified as described in Simakov et al. (2020) <doi:10.1038/s41559-020-1156-z> and displayed on an Oxford Grid (Edwards (1991) <doi:10.1111/j.1469-1809.1991.tb00394.x>) or a chord diagram as in Simakov et al. (2022) <doi:10.1126/sciadv.abi5884>. The package provides a function that uses a network-based greedy algorithm to find communities (Clauset et al. (2004) <doi:10.1103/PhysRevE.70.066111>) and so automatically order the chromosomes on the plot to improve interpretability.

This package performs Multiple Factor Analysis method for quantitative, categorical, frequency and mixed data, in addition to generating a lot of graphics, also has other useful functions.

Focus-glue-context (FGC) fisheye transformations to two-dimensional coordinates and spatial vector geometries. Implements a smooth radial distortion that enlarges a focal region, transitions through a glue ring, and preserves outside context. Methods build on generalized fisheye views and focus+context mapping. For more details see Furnas (1986) <doi:10.1145/22339.22342>, Furnas (2006) <doi:10.1145/1124772.1124921> and Yamamoto et al. (2009) <doi:10.1145/1653771.1653788>.

Facilitates tidy calculation of popular quantitative marketing metrics. It also includes functions for doing analysis that will help marketers and data analysts better understand the drivers and/or trends of these metrics. These metrics include Customer Experience Index <https://go.forrester.com/analytics/cx-index/> and Net Promoter Score <https://www.netpromoter.com/know/>.

Compare microbial co-occurrence networks created from trans_network class of microeco package <https://github.com/ChiLiubio/microeco>. This package is the extension of trans_network class of microeco package and especially useful when different networks are constructed and analyzed simultaneously.

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.

This package provides an interface with the Meteo France Synop data API (see <https://donneespubliques.meteofrance.fr/?fond=produit&id_produit=90&id_rubrique=32> for more information). The Meteo France Synop data are made of meteorological data recorded every three hours on 62 French meteorological stations.

Multivariate joint models of longitudinal and time-to-event data based on functional principal components implemented with bamlss'. Implementation for Volkmann, Umlauf, Greven (2023) <arXiv:2311.06409>.

The Multivariate Asymptotic Non-parametric Test of Association (MANTA) enables non-parametric, asymptotic P-value computation for multivariate linear models. MANTA relies on the asymptotic null distribution of the PERMANOVA test statistic. P-values are computed using a highly accurate approximation of the corresponding cumulative distribution function. Garrido-Martà n et al. (2022) <doi:10.1101/2022.06.06.493041>.

This package provides methods for maximum likelihood and Bayesian estimation for the Wishart mixture model and the mixture-of-experts Wishart (MoE-Wishart) model. The package provides four inference algorithms for these models, each implemented using the expectationâ maximization (EM) algorithm for maximum likelihood estimation and a fully Bayesian approach via Gibbs-within-Metropolisâ Hastings sampling.