R Weekly 2026-W25 Posit Agents, Three Dots, Ulam Spiral

15 Jun 2026

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This week’s release was curated by Sam Parmar, with help from the R Weekly team members and contributors.

Highlight

Insights

R in the Real World

R in Organizations

Tutorials

New Packages

📦 Keep up to date wtih CRANberries 📦

CRAN

{SmokingHistoryGenerator} 6.5.3-1.0.1: R Package for the Smoking History Generator
{mx.crypto} 0.2.0: Matrix End-to-End Encryption Primitives
{gtfsrealtime} 0.2.1: Read GTFS-Realtime Files into Data Frames
{speechmatics} 0.1.0: Client for the ‘Speechmatics’ Speech-to-Text API
{scilintr} 0.1.1: Scientific Code Lint for R Analyses
{logcumulant} 0.1.0: Goodness-of-Fit Tests and Diagrams Based on Mellin Log-Cumulants
{coresynth} 0.2.0: Fast and Unified Synthetic Control Methods
{cookie} 1.0.0: HTTP Cookies Parser Middleware
{schemate} 0.1.0: Schema Inference, Editing, and Validation with ‘checkmate’
{pulso} 0.1.0: Load Microdata from Colombia’s ‘GEIH’ (‘DANE’)
{nlfh} 0.1.0: Nonlinear Fay-Herriot Models for Small Area Estimation
{CopulaSCR} 1.0.1: Analysis of Semi-Competing Risks Data Using Copula-Based Models
{tabular} 0.1.0: Render Tables and Listings for Clinical Submissions
{ShinyBlock} 0.1.3: Multi-Protocol Blockchain Simulator and Enterprise Ledger Framework
{punycoder} 1.0.0: Unicode and Punycode Domain Name Processing
{impower133} 1.0.0: Reproduce IMpower133 Clinical Trial Results
{tutorizeR} 0.4.5: Convert R Markdown or Quarto Content into Interactive Tutorials
{sysreqr} 0.1.0: Preflight Checks for ‘R’ Package System Requirements
{rtrees} 2.0.2: Deriving Phylogenies from Synthesis Trees
{pvarife} 0.1.1: Panel VAR Models with Interactive Fixed Effects
{myIO} 1.2.0: Interactive Data Visualizations Using ‘d3.js’
{mums2} 0.1.0: Microbial Ecology by Tandem Mass Spectrometry
{fluffy} 1.0.0: Schema-Based Validation of ‘R’ Objects with User-Defined Rules
{exeval} 0.0.1: External Evaluation of Population Pharmacokinetic-Pharmacodynamic (popPKPD) Models
{deepImp} 1.1.0: Imputation with Deep Learning Methods
{CircularRegression} 0.5.1: Circular Regression Models
{pkgmatch} 0.5.4: Find R Packages Matching Either Descriptions or Other R Packages
{hcinfer} 0.1.0: Heteroskedasticity-Consistent Inference for Linear Models
{dcorBSS} 1.0-0: Distance-Correlation Based Methods for Blind Source Separation and Dependence Analysis
{clusterindices} 1.0: Cluster Validity Indices
{tinydng} 0.1.0-0: ‘TinyDNG’ C++ Header Files
{stbimageheaders} 0.1.0: ‘stb’ Image C/C++ Header Files
{normality} 0.0.1: Tests for Departure from Normality
{wbCorr} 0.3.1: Bivariate Within- and Between-Cluster Correlations
{quak} 0.1.0: Query ‘Azure Data Lake Storage Gen2’ with ‘DuckDB’
{qtbi} 0.1.2: Quantum Toxic Burden Index
{plantmix} 1.0.2: Genetic Study of Plant Mixtures
{ofhsyn} 0.1.1: Synthetic Our Future Health Data Generator
{harness} 0.1.0: Curated Agentic Harnesses for R Professional Roles
{evoFE} 0.1.0: Evolutionary Feature Engineering
{cox.rvph} 0.1.1: Remedy the Violation of the Proportional Hazards Assumption of Cox Regression
{spDBL} 1.0.2: Dynamic Bayesian Learning for Spatiotemporal Mechanistic Models
{NeutroCODsAnalysis} 0.1.0: Neutrosophic Analysis Crossover Designs
{mimar} 0.8.0: Compact Multiple Imputation, Assessment, and Reporting
{consolidatePacks} 1.0.0: Eliminate ‘@import’ by Incorporating Dependencies Directly into the Package
{cash} 1.0.2: Discrete Choice and Competitive Reactions: End-to-End Simulation
{NetSurvProx} 1.0.0: Network-Based Survival Analysis via Proximal Methods
{vizClust} 0.1.0: Visualization and Exploration of Cluster Transitions
{Uno} 2.7.3-1: R Interface to the ‘Uno’ Nonlinear Optimization Solver
{twinsvm} 0.0.2: Twin Support Vector Machines
{sparsediff} 0.4.0: R Interface to the ‘SparseDiffEngine’ Sparse Differentiation Backend
{rrstools} 1.1.0: Analyzing RoboCupRescue Simulation Data
{onnxr} 0.1.2: Bindings to ‘ONNX’ Runtime
{DrivePlotR} 0.1.0: Linked Plot Maps for Multivariate High-Resolution Spatio-Temporal Data
{data.checker} 2.0.0: Data Checker for Validating Data Frames Against Defined Schema
{bvars} 1.0: Bayesian Forecasting with Large Vector Autoregressions
{AdmixPoly} 1.0.0: Global and Local Admixture Inference in Polyploids
{saferDev} 1.0.0: Function and Pipeline Development
{rsgl} 0.1.0: An Implementation of the ‘SGL’ Graphics Language
{PMLE4SCR} 0.1.0: Pseudo Maximum Likelihood Estimation for Semi-Competing Risks Data
{irtbem2pl} 1.0.0: Marginalized Bayesian Item Parameter Estimation, 2pl Model IRT
{genefindr} 1.0.0: Rapid Gene Characterization Using Public Genomic Databases
{binest} 0.2-1: Estimation of Group Means and SDs from Binned Count Data
{tlgarima} 0.1.0: The Topp-Leone Garima Distribution
{spboost} 0.7.0: Gradient Boosting for Nonlinear Spatial Autoregressive Models
{NeutroRCDsAnalysis} 0.1.1: Neutrosophic Analysis of Row Column Designs
{iDIFr} 1.0.1: Intersectional Differential Item Functioning Analysis
{FastSegmentation} 0.0.1: Unsupervised Cell Segmentation by Fast Gaussian Processes
{easyRasch2} 0.8.0: Psychometric Analysis with Rasch Measurement Theory
{CIMEHR} 0.1.0: Gaussian Clinically Informative Visiting and Observation Processes in Electronic Health Record (EHR) Data
{chmsflow} 0.1.0: Transforming and Harmonizing CHMS Variables
{BayesForge} 0.0.1: Bayesian Inference using ‘numpyro’ and ‘XLA’
{autocodebook} 0.1.0: Automatic Codebook and Tracking for ‘Spark’ and ‘dplyr’ Pipelines
{aisdk.providers} 0.1.0: Additional Model Provider Adapters for the ‘aisdk’ Toolkit
{seine} 0.1.2: Semiparametric Ecological Inference
{autoLibLoad} 1.0: Automate Retrieving, Building, Installing and Loading Specified Packages
{wqrr} 1.0.0: Wavelet Quantile Regression Toolbox
{rsdv} 0.2.0: Synthetic Tabular Data Generation with Gaussian Copulas
{OlinkAnalyzeVignettes} 1.0.1: Vignettes for Analyzing Data using ‘OlinkAnalyze’
{DonutMap} 0.1.0: Donut Maps with ‘sf’, ‘ggplot2’, and ‘leaflet’
{HAMMER} 1.0: High-Dimensional Factor-Analytic Representation Modeling and Metrics
{yaap} 1.0.0: A Toolkit for Archetypal Analysis Methods
{ValidationExplorer} 0.1.1: Simulation-Based Tools for Bioacoustic Study Design
{SKBD} 0.1.1: Shared Keyboard Designs for Phase I Dose-Finding Trials
{shinyphaser} 0.1.0: An Interface to the ‘Phaser.js’ Game Framework
{PsiUEngineRL} 0.1.3: Homotopy Type Theory Engine for Reinforcement Learning
{NRMstatsML} 0.1.4: Statistical and Machine Learning Engine for Long-Term Natural Resource Management Data
{AutoMLR} 1.0.0: Automated Multi-Outcome Machine Learning Combination Models

GitHub or Bitbucket or GitLab

Introducing shinyds

Updated Packages

🔍 Search on R-universe 🔍

{diversityArch} 0.3.0: Computes Diversity Indices with Archaeological Data - diffify
{ccar3} 0.1.2: Canonical Correlation Analysis via Reduced Rank Regression - diffify
{BayesERtools} 0.2.6: Bayesian Exposure-Response Analysis Tools - diffify
{rstanemax} 0.1.10: Emax Model Analysis with ‘Stan’ - diffify
{RGraphSpace} 1.4.0: A Lightweight Interface Between ‘igraph’ and ‘ggplot2’ Graphics - diffify
{bioRad} 0.12.0: Biological Analysis and Visualization of Weather Radar Data - diffify
{bbotk} 1.10.1: Black-Box Optimization Toolkit - diffify
{ProbeDeveloper} 1.1.2: Develop Hybridization Probes - diffify
{rcatfish} 1.0.3: An R Interface to the California Academy of Sciences Eschmeyer’s Catalog of Fishes - diffify
{harmony} 2.0.5: Fast, Sensitive, and Accurate Integration of Single Cell Data - diffify
{focus} 0.1.7: Online Changepoint Detection in Univariate and Multivariate Data Streams - diffify
{ledger} 2.1.1: Utilities for Importing Data from Plain Text Accounting Files - diffify
{joinspy} 0.8.2: Diagnostic Tools for Data Frame Joins - diffify
{h3sdm} 0.1.5: Species Distribution Modeling with H3 Grids - diffify
{earthdatalogin} 0.0.4: NASA ‘EarthData’ Access Utilities - diffify
{netUtils} 0.8.6: A Collection of Tools for Network Analysis - diffify
{MDP2} 2.2.2.0: Markov Decision Processes (MDPs) - diffify
{iccde} 0.3.9: Computation of the Double-Entry Intraclass Correlation - diffify
{TemporalHazard} 1.1.0: Temporal Parametric Hazard Modeling - diffify
{hellodatascience} 0.1.1: Datasets from the Hello Data Science Book - diffify
{sdcMicro} 5.8.2: Statistical Disclosure Control Methods for Anonymization of Data and Risk Estimation - diffify
{rayimage} 0.26.1: Image Processing for Simulated Cameras - diffify
{msPCA} 0.4.1: Sparse Principal Component Analysis with Multiple Principal Components - diffify
{mfrmr} 0.2.1: Estimation and Diagnostics for Many-Facet Measurement Models - diffify
{tabnet} 0.9.0: Fit ‘TabNet’ Models for Classification and Regression - diffify
{mtarm} 0.1.9: Bayesian Estimation of Multivariate Threshold Autoregressive Models - diffify
{metalite.sl} 0.1.2: Subject-Level Analysis Using ‘metalite’ - diffify
{JDCruncheR} 0.4.0: ‘JDemetra+’ Quality Report Generator - diffify
{boxly} 0.1.2: Interactive Box Plot - diffify
{admiralophtha} 1.5.0: ADaM in R Asset Library - Ophthalmology - diffify
{futurize} 1.0.0: Parallelize Common Functions via One Magic Function - diffify
{fastreg} 0.13.8: Fast Conversion and Querying of Danish Registers with ‘Parquet’ - diffify
{Rrepest} 1.6.14: An Analyzer of International Large Scale Assessments in Education - diffify
{IceSat2R} 1.1.0: ‘ICESat-2’ Altimeter Data using R - diffify
{cpp4r} 1.0.0: Header-Only ‘C++’ and ‘R’ Interface - diffify
{armadillo4r} 1.0.0: An ‘Armadillo’ Interface - diffify
{admiral} 1.5.0: ADaM in R Asset Library - diffify
{bayesefa} 0.0.0.6: Bayesian Exploratory Factor Analysis - diffify
{ebrahim.gof} 2.0.0: Ebrahim-Farrington Goodness-of-Fit Test for Logistic Regression - diffify
{secretbase} 1.3.0: Cryptographic Hash Functions and Data Encoding - diffify
{srlars} 3.0.0: Fast and Scalable Cellwise-Robust Ensemble - diffify
{RaceID} 0.4.1: Identification of Cell Types, Inference of Lineage Trees, and Prediction of Noise Dynamics from Single-Cell RNA-Seq Data - diffify
{paisaje} 0.3.0: Spatial and Environmental Data Tools for Landscape Ecology - diffify
{graphonmix} 0.1.1: Generates Dense and Sparse Graphs using Graphon Extensions - diffify
{glmx} 0.2-2: Generalized Linear Models Extended - diffify
{forestly} 0.1.5: Interactive Forest Plot - diffify
{dataSDA} 0.2.6: Datasets and Basic Statistics for Symbolic Data Analysis - diffify
{tidyusmacro} 0.2.0: Downloading and Cleaning U.S. Macroeconomic Data - diffify
{rsynthbio} 4.2.0: Synthesize Bio API Wrapper - diffify
{pkglite} 0.2.6: Compact Package Representations - diffify
{heritability} 1.5: Marker-Based Estimation of Heritability Using Individual Plant or Plot Data - diffify
{autoMR} 1.2.0: Automated Mendelian Randomization Workflows and Visualizations - diffify
{semmcci} 1.1.6: Monte Carlo Confidence Intervals in Structural Equation Modeling - diffify
{vectra} 0.7.1: Columnar Query Engine for Larger-than-RAM Data - diffify
{rstudioapi} 0.19.0: Safely Access the RStudio API - diffify
{RcppThread} 2.4.0: R-Friendly Threading in C++ - diffify
{betaNB} 1.0.7: Bootstrap for Regression Effect Sizes - diffify
{betaMC} 1.3.4: Monte Carlo for Regression Effect Sizes - diffify
{colleyRstats} 0.1.0: Functions to Streamline Statistical Analysis and Reporting - diffify
{betaSandwich} 1.0.9: Robust Confidence Intervals for Standardized Regression Coefficients - diffify
{betaDelta} 1.0.7: Confidence Intervals for Standardized Regression Coefficients - diffify
{surveysd} 2.0.3: Survey Standard Error Estimation for Cumulated Estimates and their Differences in Complex Panel Designs - diffify
{MacroFilters} 0.2.1: Robust Trend-Cycle Decomposition for Macroeconomic Time Series - diffify
{demofit} 0.1.4: Parametric Mortality Curve Fitting and Mortality Forecasting Tools - diffify
{compindexR} 0.1.4: Calculates Composite Index - diffify
{tidyhydat} 1.0.1: Extract and Tidy Canadian ‘Hydrometric’ Data - diffify
{flexFitR} 1.2.3: Flexible Non-Linear Least Square Model Fitting - diffify
{Rapp} 0.4.0: Easily Build Command Line Applications - diffify
{ggRandomForests} 3.1.0: Visually Exploring Random Forests - diffify
{getRad} 0.3.0: Download Radar Data for Biological Research - diffify
{fixes} 0.11.2: Staggered DiD Tools: Event Studies and ATT Aggregation - diffify
{wpeR} 0.2.0: Streamlined Analysis of Wild Pedigree Data - diffify
{rtmpinvi} 2.0.0: Interactive Tabular Matrix Problems via Pseudoinverse Estimation - diffify
{rlppinv} 2.0.0: Linear Programming via Regularized Least Squares - diffify
{risk.assessr} 4.1.0: Assessing Package Risk Metrics - diffify
{restriktor} 0.6-50: Restricted Statistical Estimation and Inference for Linear Models - diffify
{prioritizrdata} 0.3.3: Conservation Planning Datasets - diffify
{discnorm} 0.2.2: Test for Discretized Normality in Ordinal Data - diffify
{rclsp} 2.0.1: A Modular Two-Step Convex Optimization Estimator for Ill-Posed Problems - diffify
{palaeoverse} 1.5.0: Prepare and Explore Data for Palaeobiological Analyses - diffify
{mlr3} 1.7.1: Machine Learning in R - Next Generation - diffify
{wrGraph} 1.3.16: Graphics in the Context of Analyzing High-Throughput Data - diffify
{fluidsynth} 1.0.3: Read and Play Digital Music (MIDI) - diffify
{bbk} 0.11.0: Client for Central Bank APIs - diffify
{BAwiR} 1.5.2: Analysis of Basketball Data - diffify
{spada} 0.1.6: A ‘shiny’ Package for Data Analysis - diffify
{mlr3cluster} 0.4.0: Cluster Extension for ‘mlr3’ - diffify
{equil2} 1.1.0: Calculate Urinary Saturation with the EQUIL2 Algorithm - diffify
{standardlastprofile} 2.0.0: BDEW Standard Load Profiles for Electricity and Gas - diffify
{SQMtools} 1.8.0: Analyze Results Generated by the ‘SqueezeMeta’ Pipeline - diffify
{SdeaR} 1.1.0: Stochastic Data Envelopment Analysis - diffify
{InsuSensCalc} 0.1.0: Insulin Sensitivity Indices Calculator - diffify
{W3CMarkupValidator} 0.2-4: R Interface to W3C Markup Validation Services - diffify
{INLAvaan} 0.2.5: Approximate Bayesian Latent Variable Analysis - diffify
{BMisc} 1.4.9: Miscellaneous Functions for Panel Data, Quantiles, and Printing Results - diffify
{FactoMineR} 2.15: Multivariate Exploratory Data Analysis and Data Mining - diffify
{tgml} 0.5.0: Tree Guided Machine Learning for Personalized Predictions and Precision Diagnostics - diffify
{plmmr} 4.3.0: Penalized Linear Mixed Models for Correlated Data - diffify
{Andromeda} 1.2.1: Asynchronous Disk-Based Representation of Massive Data - diffify
{SuperSurv} 0.1.7: A Unified Framework for Machine Learning Ensembles in Survival Analysis - diffify
{nascaR.data} 3.1.0: NASCAR Race Data - diffify
{lang} 0.1.2: Translates R Help Documentation using Large Language Models - diffify
{ibkrcp} 0.1.2: R Client for the Interactive Brokers Client Portal API - diffify
{symengine} 0.2.13: Interface to the ‘SymEngine’ Library - diffify
{restfulr} 0.0.17: R Interface to RESTful Web Services - diffify
{nlmixr2plot} 5.0.2: Nonlinear Mixed Effects Models in Population PK/PD, Plot Functions - diffify
{distributional} 0.7.1: Vectorised Probability Distributions - diffify
{dream} 2.1.3: Dynamic Relational Event Analysis and Modeling - diffify
{OPI} 3.1.1: Open Perimetry Interface - diffify
{LBI} 0.2.5: Likelihood Based Inference - diffify
{jrt} 1.2.0: Item Response Theory Modeling and Scoring for Judgment Data - diffify
{fitPS} 1.0.6: Fit Zeta Distributions to Forensic Data - diffify
{DFA.CANCOR} 0.4.3: Linear Discriminant Function and Canonical Correlation Analysis - diffify
{shrinkem} 0.3.0: Approximate Bayesian Regularization for Parsimonious Estimates - diffify
{tbm} 0.3-11: Transformation Boosting Machines - diffify
{mx.api} 0.3.0: Minimal Matrix Client-Server API - diffify
{joinpointR} 1.0.0: Tidy Tools for Joinpoint Regression Models - diffify
{wizaRdry} 0.6.16: A Magical Framework for Collaborative & Reproducible Data Analysis - diffify
{vennDiagramLab} 2.4.2: Headless Venn Diagram Analysis and Rendering - diffify
{nuggets} 2.2.1: Extensible Framework for Data Pattern Exploration - diffify
{scaledescr} 0.2.7: Descriptive, Reliability, and Inferential Tables for Psychometric Scales and Demographic Data - diffify
{opticskxi} 1.2.2: OPTICS K-Xi Density-Based Clustering - diffify
{CohortSymmetry} 0.3.0: Sequence Symmetry Analysis Using the Observational Medical Outcomes Partnership Common Data Model - diffify
{zip} 3.0.0: Cross-Platform ‘zip’ Compression - diffify
{TreeDist} 2.14.1: Calculate and Map Distances Between Phylogenetic Trees - diffify
{rhino} 1.12.0: A Framework for Enterprise Shiny Applications - diffify
{NeutroRCDsAnalysis} 0.1.1: Neutrosophic Analysis of Row Column Designs - diffify
{metamorphr} 0.4.1: Tidy and Streamlined Metabolomics Data Workflows - diffify
{LFM} 0.3.4: Laplace Factor Model Analysis and Evaluation - diffify
{gmwmx2} 0.0.5: Estimate Functional and Stochastic Parameters of Linear Models with Correlated Residuals and Missing Data - diffify
{test.assessr} 2.1.2: Assessing Package Test Reliability and Quality - diffify
{scpi} 4.0.1: Synthetic Control Methods - diffify
{admiraldev} 1.5.0: Utility Functions and Development Tools for the Admiral Package Family - diffify
{rYWAASB} 0.4: Simultaneous Selection by Trait and WAASB Index - diffify
{rtdists} 0.11-6: Response Time Distributions - diffify
{outstandR} 2.0.0: Model-Based Standardisation for Indirect Treatment Comparison with Limited Subject-Level Data - diffify
{factorana} 1.7.1: Factor Model Estimation with Latent Variables - diffify
{NeutroCODsAnalysis} 0.1.0: Neutrosophic Analysis Crossover Designs - diffify
{goldilocks} 0.5.0: Goldilocks Adaptive Trial Designs for Time-to-Event Endpoints - diffify
{AIUQ} 0.5.5: Ab Initio Uncertainty Quantification - diffify
{spmodel} 0.13.0: Spatial Statistical Modeling and Prediction - diffify
{r2rtf} 1.3.1: Easily Create Production-Ready Rich Text Format (RTF) Tables and Figures - diffify
{plotthis} 0.12.1: High-Level Plotting Built Upon ‘ggplot2’ and Other Plotting Packages - diffify
{netmeta} 3.6-0: Network Meta-Analysis using Frequentist Methods - diffify
{mlr3misc} 0.22.0: Helper Functions for ‘mlr3’ - diffify
{epsiwal} 0.2.0: Exact Post Selection Inference with Applications to the Lasso - diffify
{DRDID} 1.3.0: Doubly Robust Difference-in-Differences Estimators - diffify
{autoFC} 1.0.0.1001: Automatic Toolkit for Construction, Optimization, Scoring and Simulation of Forced-Choice Tests - diffify
{betaselectr} 0.2.1: Betas-Select in Structural Equation Models and Linear Models - diffify
{soilassessment} 1.3.1: Soil Health Assessment Models for Assessing Soil Conditions and Suitability - diffify
{twinsvm} 0.0.2: Twin Support Vector Machines - diffify
{reproducer} 0.6.0: Reproduce Statistical Analyses and Meta-Analyses - diffify
{manydist} 0.5.0: Distance-Based Learning for Mixed-Type Data - diffify
{confMeta} 0.1.1: Confidence Curves and P-Value Functions for Meta-Analysis - diffify
{vol2birdR} 1.3.0: Vertical Profiles of Biological Signals in Weather Radar Data - diffify
{tikatuwq} 0.9.0: Water Quality Assessment and Environmental Compliance in Brazil - diffify
{savvyPR} 0.1.2: Savvy Parity Regression Model Estimation with ‘savvyPR’ - diffify
{wjake} 1.0.1: Personal Themes and Formatting Preferences - diffify
{serpstatr} 0.4.2: ‘Serpstat’ API Wrapper - diffify
{dbscan} 1.2.5: Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Related Algorithms - diffify
{CKNNRLD} 0.1.4: Clustering-Based K-Nearest Neighbor Regression for Longitudinal Data - diffify
{WMAP} 1.3.1: Weighted Meta-Analysis with Pseudo-Populations - diffify
{REDCapSync} 0.1.1: Encapsulated ‘REDCap’ Projects for Synchronized Data Pipelines - diffify
{llmclean} 0.1.1: LLM-Assisted Data Cleaning with Multi-Provider Support - diffify
{tesouror} 0.2.3: Access Brazilian National Treasury Open Data APIs - diffify
{semTests} 0.9.0: Robust Test Statistics for Structural Equation Models - diffify
{qtl2convert} 0.34: Convert Data among QTL Mapping Packages - diffify
{openssl} 2.4.2: Toolkit for Encryption, Signatures and Certificates Based on OpenSSL - diffify
{mlr3learners} 0.15.0: Recommended Learners for ‘mlr3’ - diffify
{deckroadmap} 0.1.5: Roadmap Footers for ‘Reveal.js’ Slides in ‘Quarto’ and ‘R Markdown’ - diffify
{cABCanalysis} 1.0.1: Computed ABC Analysis - diffify
{mlt.docreg} 1.1-13: Most Likely Transformations: Documentation and Regression Tests - diffify
{dtw} 1.23-3: Dynamic Time Warping Algorithms - diffify
{decompr} 6.9.0: Global Value Chain Decomposition - diffify
{multiRL} 0.4.5: Reinforcement Learning Tools for Multi-Armed Bandit - diffify
{cv} 2.0.6: Cross-Validating Regression Models - diffify
{survPen} 2.0.5: Multidimensional Penalized Splines for (Excess) Hazard Models, Relative Mortality Ratio Models and Marginal Intensity Models - diffify
{pre} 1.0.9: Prediction Rule Ensembles - diffify
{mvglmmRank} 1.2-5: Multivariate Generalized Linear Mixed Models for Ranking Sports Teams - diffify
{fb4package} 2.1.0: ‘Fish Bioenergetics 4.0’ Model Implementation with High-Performance ‘TMB’ Backend - diffify
{climatehealth} 1.0.2: Statistical Tools for Modelling Climate-Health Impacts - diffify
{pleioh2g} 0.1.3: Estimation of Pleiotropic Heritability from Genome-Wide Association Studies (GWAS) Summary Statistics - diffify
{mori} 0.2.1: Shared Memory for R Objects - diffify
{catekappa} 0.1.1: Design and Analysis of Consistency Tests Based on Kappa Statistic - diffify
{extr} 1.1.1: Extinction Risk Estimation - diffify
{cotram} 0.6-1: Count Transformation Models - diffify
{rsdv} 0.2.0: Synthetic Tabular Data Generation with Gaussian Copulas - diffify
{nmw} 0.3.1: Understanding Nonlinear Mixed Effects Modeling for Population Pharmacokinetics - diffify
{ICSNP} 1.1-3: Tools for Multivariate Nonparametrics - diffify
{HaploCatcher} 2.0.1: A Predictive Haplotyping Package - diffify
{CVXR} 1.9.1: Disciplined Convex Optimization - diffify
{CCMnet} 1.1.2: Congruence Class Models for Networks - diffify
{simcross} 0.10: Simulate Experimental Crosses - diffify
{qtl2} 0.42: Quantitative Trait Locus Mapping in Experimental Crosses - diffify
{broman} 0.94: Karl Broman’s R Code - diffify