ananke v0.1.0: Implements tools for calibration of radiocarbon ages and modern carbon fraction values using multiple calibration curves. Functions calculate the highest density region intervals and credible intervals, and visualize results. Look here for examples.

emend v0.1.0: Provides functions to clean and standardize messy data, including textual categories and free-text addresses, using Large Language Models. Functions correct typos, expand abbreviations, and map inconsistent entries to standardized values. Ideal for Bioinformatics, business, and general data cleaning tasks. See the README for examples.

PacketLLM v0.1.0: Implements interactive RStudio gadget interface for communicating with OpenAI LLMs e.g., gpt-4o, gpt-4o-mini, gpt-4.1, o1, and o3-mini, enabling users to conduct multiple chat conversations simultaneously in separate tabs. See the vignette.

pangoling v1.0.3: Provides access to word predictability estimates using large language models (LLMs) based on transformer architectures via integration with the Hugging Face ecosystem. The package interfaces with pre-trained neural networks and supports both causal/auto-regressive LLMs (e.g., ‘GPT-2’) and masked/bidirectional LLMs (e.g., ‘BERT’) to compute the probability of words, phrases, or tokens given their linguistic context. For details on GPT-2 and causal models, see Radford et al. (2019). For details on BERT and masked models, see Devlin et al. (2019). There are four vignettes, including Using BERT and Using GPT2.

clockSim v0.1.2: Provides tools to open up system-level exploration of the circadian clock to wet-lab experimentalists. Current models are based on Leloup and Goldbeter (1998). There are three vignettes including [Simulation of the circadian clock]{https://cran.r-project.org/web/packages/clockSim/vignettes/clock-models.html) and noisy LG model.

PhotoGEA v1.3.2: Provides functions to read, process, fit, and analyze photosynthetic gas exchange measurements. See Lochocki, Salesse-Smith, & McGrath (2025)](https://onlinelibrary.wiley.com/doi/10.1111/pce.15501) for background and the vignette to get started.

puff v0.1.0: Provides functions to simulate the Gaussian puff forward atmospheric model in sensor (specific sensor coordinates) or grid (across the grid of a full oil and gas operations site) modes, following Jia et al. (2024) and offers numerous visualization options, including static and animated, 2D and 3D, and a site map generator. See the vignette to get started.

connector v0.1.1: Facilitates clinical research by providing a consistent interface for connecting to various data sources, including file systems and databases such as ADAM and SDTM. See the vignettes connector and How to extend connector.

verdata v1.0.0: Facilitates use and analysis of data about the armed conflict in Colombia resulting from the joint project between La Jurisdicción Especial para la Paz (JEP), La Comisión para el Esclarecimiento de la Verdad, la Convivencia y la No repetición (CEV), and the Human Rights Data Analysis Group (HRDAG). The data are 100 replicates from a multiple imputation through chained equations as described in Van Buuren and Groothuis-Oudshoorn (2011). See the README to get started.

RRgeo v0.0.3: Provides tools to perform accurate species distribution modeling for rare species. See Mondanaro et al. (2023) and Mondanaro et al. (2025) for background on finding the area of origin of species and past inter-species contact while considering climatic variability. There are four vignettes, including ENphylo and Preparing Data.

spotr v0.1.0: Provides functions to compute relative or absolute population trends across space and time using predictions from models fitted to ecological population abundance data, as described in Knape (2025). See the vignette.

branchingprocess v0.1.0: Provides tools to quantify outbreak risk posed by individual importers of a transmissible pathogen and calculate probabilities of final outbreak size and generations of transmission. See Toth et al. (2015) and Toth et al. (2016) for the theory and the vignette for an example.

simBKMRdata v0.3.1: Provides functions to support Bayesian Kernel Machine Regression analyses in environmental health research. It enables the simulation of realistic multivariate exposure data, estimation of distributional parameters by subgroup, and application of adaptive, data-driven thresholds for feature selection via Posterior Inclusion Probabilities. See Hasan et al. (2025). There are three vignettes, including Calculate PIP Threshold from Response Vector and Simulation and Estimation.

DeSciDe v1.0.0: Facilitates genomic and proteomic data analysis by providing tools for unbiased PubMed searching, protein interaction network visualization, and comprehensive data summarization. See Szklarczyk et al. (2023) and Winter (2017) for background and the vignette for examples.

HTGM2D v1.1: Provides a two-dimensional heat map to be used with GoMiner for the ontological analysis of microarray and proteomics studies that leverage the Gene Ontology Consortium GO resource. The heat map reflects the Jaccard metric p-value for the number of genes in common for each corresponding pair. See the vignette.

geoprofiler v0.0.2: Implements a tool set to create perpendicular profile graphs and swath profiles. Method is based on the coordinate rotation algorithm by Schaeben et al. (2024). There are two vignettes: Distances Along Oriented Profiles and Swath Profiles.

tabs v0.1.1: Implements a standardized workflow to reconstruct spatial configurations of altitude-bounded biogeographic systems over time; for example, model how island archipelagos expand or contract with changing sea levels or how alpine biomes shift in response to tree line movements. For details, see De Groeve et al. (2025) and look here to get started.

assertHE v1.0.0: Provides tools to help health economic modelers when building and reviewing models. The visualization functions allow users to more easily review the network of functions in a project and get lay summaries of them. The asserts included are intended to check for common errors. See Smith et al. (2024) for details and the README for examples.

tlda v0.1.0: Provides support functions and datasets to facilitate the analysis of linguistic data with a focus on the calculation of corpus-linguistic dispersion measures as described in Gries (2021) and Soenning (2025). See the vignettes Dispersion Analysis and Frequency adjusted dispersion scores.

ClassificationEnsembles v0.5.0: Automatically builds 12 individual classification models, including error (RMSE) and predictions. These results are used to create an ensemble, which is then modeled using eight methods. See the vignette and the two sister packages by the same author: LogisticEnsembles and NumericEnsembles.

e2tree v0.1.2: Implements the explainable ensemble trees ’approach proposed by Aria et al. (2024), which aims to explain and interpret decision tree ensemble models using a single tree-like structure. See the README for examples.

lsoda v1.2: Provides an implementation of the lsoda function from the ODEPACK library for solving initial value problems for first-order ordinary differential equations Hindmarsh (1982), which can be called inline using Rcpp, and an R function, ode. Look here for examples.

MCSimMod v0.0.1: Provides tools to facilitate ordinary differential equation (ODE) modeling by performing simulations for ODE models that are encoded in the GNU MCSim model specification language (Bois (2009)) using ODE solvers from deSolve (Soetaert et al. (2010)). There are seven vignettes, including an Introduction and A Model of Newton’s Law of Cooling.

riemtan v0.1.0: Implements various Riemannian metrics for symmetric positive definite matrices, including AIRM (Affine Invariant Riemannian Metric, see Pennec et al. (2006); Log-Euclidean, see Arsigny et al. (2006); Euclidean; Log-Cholesky. see Lin (2019); and Bures-Wasserstein metrics, see Bhatia et al. (2019). It also provides functions for computing logarithmic and exponential maps, vectorization, and statistical operations on the manifold of positive definite matrices. See the vignette.

neuroim2 v0.8.1: Provides data structures and methods for handling volumetric brain imaging data, with a focus on functional magnetic resonance imaging (fMRI) and efficient representations for three-dimensional and four-dimensional neuroimaging data. Implements methods for image resampling, spatial filtering, region of interest analysis, and connected component labeling. See Poldrack et al. (2024). There are four vignettes, including Working with Image Volumes and Regions of Interest.

NHSRwaitinglist v0.1.1: Provides queueing theory functions to assist with waiting list management based on the approach described in Fong et al. (2022). There are three vignettes including Three example waiting lists and Exploring with Simulation.

ernm v1.0.0: Provides functions to estimate fully and partially observed Exponential-Family Random Network Models (ERNM). Exponential-family Random Graph Models (ERGM) and Gibbs Fields are special cases of ERNMs and can also be estimated with the package. See Fellows and Handcock (2012).

IRTM v0.0.1.1: Implements a semi-supervised approach based on Bayesian Item Response Theory that produces theoretically identified underlying dimensions from input data and a constraints matrix. The methodology is described in Morucci et al. (2024). See the vignette to get started.

RStanTVA v0.3.0: Provides a Stan implementation of the Theory of Visual Attention described in Bundesen (1990) along with numerous convenience functions for generating, compiling, fitting, and analyzing TVA models. See the README for examples.

ctsmTMB v1.0.0: Provides an interface for defining and fitting continuous-time state space models built with the R6 ctsmTMB class. Available inter-inference methods include Kalman filters and a Laplace approximation-based smoothing method. For details on the methods, see the documentation) for the CTSMR package and Thygesen (2025). There are six vignettes, including a Getting Started guide and Moment Predictions.

fitdistcp v0.1.1: Provides functions to generate predictive distributions based on calibrating priors for various commonly used statistical models, including models with predictors. Functions are provided for densities, probabilities, quantiles, random deviates, and the parameter posterior. Predictions are generated from the Bayesian prediction integral, with priors chosen to give good reliability (also known as calibration). See Jewson et al. (2024) for background, and look here for detailed documentation.

funMoDisco v1.0.0: Implements two complementary methodologies for discovering motifs in functional data: ProbKMA, a probabilistic K-Means algorithm (Cremona and Chiaromonte (2023)), and FunBIalign, a hierarchical algorithm for functional motif discovery based on mean square residue (Cremona, and Chiaromonte (2023)). See the vignette for examples.

hdMTD v0.1.0: Provides functions to estimate parameters in Mixture Transition Distribution (MTD) models, a class of high-order Markov chains. Estimated parameters include pasts (lags), transition probabilities, and oscillations. A perfect sampling algorithm generates samples of an MTD model from its invariant distribution. See Ost & Takahashi (2023) for the theory and the README for examples.

joker v0.14.2: Extends the range of available distribution families and facilitates the computation of key parametric quantities, such as moments and information-theoretic measures. All package features are available both in a stats-like syntax for entry-level users, and in an S4 object-oriented programming system for more experienced ones. See the vignette.

postcard v1.0.0: Provides functions to perform power analysis and inference on marginal effects using plug-in estimation and influence functions that optionally leverage historical data to increase precision with prognostic covariate adjustment. The methods are described in Højbjerre-Frandsen et al. (2025). There are three vignettes, including an Introduction and Prospective Power Estimation.

tvcure v0.1.0: Implements a double additive cure survival model with time-varying covariates. The additive terms in the long- and short-term survival submodels, modelling the cure probability and the event timing for susceptible units, are estimated using Laplace P-splines. See Lambert and Kreyenfeld (2025) for details and look here for examples.

butterfly v1.1.2: Provides functions to verify continually updating time series data where new values are expected, but previous data should remain unchanged. See the vignette.

tsissm v1.0.1: Implements an unobserved components time series model using the linear innovations state space representation with a choice of error distributions and an option for dynamic variance. Features include automatic differentiation, automatic model selection and ensembling, prediction, filtering, simulation and backtesting. See Hyndman et al. (2012) for background. There are five vignettes, including The Innovations State Space Model and Filtering and Prediction.

cheetahR: Provides an interface to Cheetah Grid, a high-performance JavaScript table widget. See Get Started.

whirl v0.2.0: Enables execution of scripts in batch, while simultaneously creating logs for the execution of each script, and providing an overview summary log of the entire batch execution. The package is suitable for clinical trials using Quarto to create nice human-readable logs. See the vignette to get started.

vayr v1.0.0: Implements position adjustment “visualize as you randomize” principles for ggplot2, which can be especially useful when plotting experimental data. See README for examples.