An implementation of the nodiv algorithm, see Borregaard, M.K., Rahbek, C., Fjeldsaa, J., Parra, J.L., Whittaker, R.J. & Graham, C.H. (2014) "Node-based analysis of species distributions." Methods in Ecology and Evolution 5(11): 1225-1235. <doi:10.1111/2041-210X.12283>. Package for phylogenetic analysis of species distributions. The main function goes through each node in the phylogeny, compares the distributions of the two descendant nodes, and compares the result to a null model. This highlights nodes where major distributional divergence have occurred. The distributional divergence for these nodes is mapped.

Utilities and kinship information for behavior genetics and developmental research using the National Longitudinal Survey of Youth (NLSY; <https://www.nlsinfo.org/>).

User-friendly functions for extracting a data table (row for each match, column for each group) from non-tabular text data using regular expressions, and for melting columns that match a regular expression. Patterns are defined using a readable syntax that makes it easy to build complex patterns in terms of simpler, re-usable sub-patterns. Named R arguments are translated to column names in the output; capture groups without names are used internally in order to provide a standard interface to three regular expression C libraries ('PCRE', RE2', ICU'). Output can also include numeric columns via user-specified type conversion functions.

This package provides pseudo-weighted estimates of means and prevalences for finite population inference from nonprobability samples using auxiliary information from one or multiple probability reference surveys. The package supports estimation with multiple reference surveys, allowing auxiliary information to be combined when no single survey contains all variables relevant to participation. Optional cumulative precalibration can be applied to align weighted totals of shared variables across surveys. Methods are based on the generalized estimating equations framework of Landsman et al. (2026) <doi:10.1002/sim.70403> for correcting participation bias. For a single reference survey, the package implements the raking ratio calibration method and includes the adjusted logistic propensity (ALP) method of Wang, Valliant, and Li (2021) <doi:10.1002/sim.9122>, as well as the Chen-Li-Wu (CLW) method of Chen, Li, and Wu (2020) <doi:10.1080/01621459.2019.1677241>. Analytic variance estimation uses Taylor linearization and accounts for complex sampling designs in the reference surveys via integration with the survey package.

This package provides efficient implementation of the Narrowest-Over-Threshold methodology for detecting an unknown number of change-points occurring at unknown locations in one-dimensional data following deterministic signal + noise model. Currently implemented scenarios are: piecewise-constant signal, piecewise-constant signal with a heavy-tailed noise, piecewise-linear signal, piecewise-quadratic signal, piecewise-constant signal and with piecewise-constant variance of the noise. For details, see Baranowski, Chen and Fryzlewicz (2019) <doi:10.1111/rssb.12322>.

This package provides tools for drawing Statistical Process Control (SPC) charts. This package supports the NHS Making Data Count programme, and allows users to draw XmR charts, use change points and apply rules with summary indicators for when rules are breached.

Estimates network histograms, a blockmodel approximation to the graphon underlying a network's connectivity pattern, for both single-layer and multilayer networks. Implements graphon estimation methods including the profile-likelihood method of Olhede and Wolfe (2014) <doi:10.1073/pnas.1400374111> and the least-squares method of Gao, Lu, and Zhou (2015) <doi:10.1214/15-AOS1354> for single-layer networks, and the multilayer extension of Song and Olhede (2026) <doi:10.48550/arXiv.2608.14536>.

This package contains the following 5 nonparametric hypothesis tests: The Sign Test, The 2 Sample Median Test, Miller's Jackknife Procedure, Cochran's Q Test, & The Stuart-Maxwell Test.

Many tools for calculating network, node, or tie marks, measures, motifs and memberships of many different types of networks. Marks identify structural positions, measures quantify network properties, memberships classify nodes into groups, and motifs tabulate substructure participation. All functions operate with all classes of network data covered in manynet', and on directed, undirected, multiplex, multimodal, signed, and other networks.

Includes functions and examples to compute NEAT, the Network Enrichment Analysis Test described in Signorelli et al. (2016, <DOI:10.1186/s12859-016-1203-6>).

Wraps the nametag library <https://github.com/ufal/nametag>, allowing users to find and extract entities (names, persons, locations, addresses, ...) in raw text and build your own entity recognition models. Based on a maximum entropy Markov model which is described in Strakova J., Straka M. and Hajic J. (2013) <https://ufal.mff.cuni.cz/~straka/papers/2013-tsd_ner.pdf>.

Base package for Neuroconductor', which includes many helper functions that interact with objects of class nifti', implemented by package oro.nifti', for reading/writing and also other manipulation functions.

Estimate the correlation between two NIfTI images across random parcellations of the images (Fortea et al., under review). This approach overcomes the problems of both voxel-based correlations (neighbor voxels may be spatially dependent) and atlas-based correlations (the correlation may depend on the atlas used).

This package provides utility functions and custom probability distribution for Bayesian analyses of radiocarbon dates within the nimble modelling framework. It includes various population growth models, nimbleFunction objects, as well as a suite of functions for prior and posterior predictive checks for demographic inference (Crema and Shoda (2021) <doi:10.1371/journal.pone.0251695>) and other analyses.

This package provides functions to construct a normative latent cognitive structure (N-LCS) from cognitive test data standardized to healthy controls, and to compute cognitive deviation magnitude (CDM) and cognitive deviation angle (CDA). Methods are described in Chen (2026) <doi:10.1080/23279095.2026.2691088>.

Estimate nonlinear vector autoregression models (also known as the next generation reservoir computing) for nonlinear dynamic systems. The algorithm was described by Gauthier et al. (2021) <doi:10.1038/s41467-021-25801-2>.

This package provides tools to support research on vowel covariation. Methods are provided to support Principal Component Analysis workflows (as in Brand et al. (2021) <doi:10.1016/j.wocn.2021.101096> and Wilson Black et al. (2023) <doi:10.1515/lingvan-2022-0086>).

Utility to retrieve data from the National Health and Nutrition Examination Survey (NHANES) website <https://www.cdc.gov/nchs/nhanes/>.

This data package contains the Item Response Theory (IRT) parameters for the National Center for Education Statistics (NCES) items used on the National Assessment of Education Progress (NAEP) from 1990 to 2015. The values in these tables are used along with NAEP data to turn student item responses into scores and include information about item difficulty, discrimination, and guessing parameter for 3 parameter logit (3PL) items. Parameters for Generalized Partial Credit Model (GPCM) items are also included. The adjustments table contains the information regarding the treatment of items (e.g., deletion of an item or a collapsing of response categories), when these items did not appear to fit the item response models used to describe the NAEP data. Transformation constants change the score estimates that are obtained from the IRT scaling program to the NAEP reporting metric. Values from the years 2000 - 2013 were taken from the NCES website <https://nces.ed.gov/nationsreportcard/> and values from 1990 - 1998 and 2015 were extracted from their NAEP data files. All subtest names were reduced and homogenized to one word (e.g. "Reading to gain information" became "information"). The various subtest names for univariate transformation constants were all homogenized to "univariate".

Accompanies the book "Nonparametric Statistical Methods Using R, 2nd Edition" by Kloke and McKean (2024, ISBN:9780367651350). Includes methods, datasets, and random number generation useful for the study of robust and/or nonparametric statistics. Emphasizes classical nonparametric methods for a variety of designs --- especially one-sample and two-sample problems. Includes methods for general scores, including estimation and testing for the two-sample location problem as well as Hogg's adaptive method.

Factorize binary matrices into rank-k components using the logistic function in the updating process. See e.g. Tomé et al (2015) <doi:10.1007/s11045-013-0240-9> .

An interface to Neptune. A metadata store for MLOps, built for teams that run a lot of experiments. It gives you a single place to log, store, display, organize, compare, and query all your model-building metadata. Neptune is used for: â ¢ Experiment tracking: Log, display, organize, and compare ML experiments in a single place. â ¢ Model registry: Version, store, manage, and query trained models, and model building metadata. â ¢ Monitoring ML runs live: Record and monitor model training, evaluation, or production runs live For more information see <https://neptune.ai/>.

Implementation of a probabilistic method to calculate nicheROVER (_niche_ _r_egion and niche _over_lap) metrics using multidimensional niche indicator data (e.g., stable isotopes, environmental variables, etc.). The niche region is defined as the joint probability density function of the multidimensional niche indicators at a user-defined probability alpha (e.g., 95%). Uncertainty is accounted for in a Bayesian framework, and the method can be extended to three or more indicator dimensions. It provides directional estimates of niche overlap, accounts for species-specific distributions in multivariate niche space, and produces unique and consistent bivariate projections of the multivariate niche region. The article by Swanson et al. (2015) <doi:10.1890/14-0235.1> provides a detailed description of the methodology. See the package vignette for a worked example using fish stable isotope data.

This package provides routines for plotting linkage and association results along a chromosome, with marker names displayed along the top border. There are also routines for generating BED and BedGraph custom tracks for viewing in the UCSC genome browser. The data reformatting program Mega2 uses this package to plot output from a variety of programs.