R Weekly 2023-W00

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

Highlight

Insights

• Benchmark of R file formats using rio and friends

• Cloud-Native Geospatial If You Don’t Speak Snake

• Mountains

• Fast remote parquet

• Row Means in R: Calculating Row Averages with Ease

• Fisher’s Exact Test in R: How to Interpret & do Post Hoc Analysis

• RcppInt64 0.0.3 on CRAN: Now with nanotime Support

• Reflections on posit conf(2023)

• LIVE FROM CHICAGO: REAL WORLD DATA SCIENCE AT POSIT::CONF(2023)

R in the Real World

• Confidence Intervals in Election Polling: Understanding the Uncertainty of Political Forecasting

• Rugby World Cup explainer using data

R in Organizations

R in Academia

• Guide to understanding the intuition behind the Dirichlet distribution: Learn about the Dirichlet distribution and explore how it’s just a fancier version of the Beta distribution

Resources

• Styling and Templating Quarto Documents

• Introduction to webR

• Magic with WebAssembly and webR

• The notebook seen in Jeremy Howard’s keynote at posit::conf(2023)

• Parameterized Quarto reports improve understanding of soil health

• It’s All About Perspective, Making A Case for Generative Art

• Empowering Educators and Researchers with Interactive Quarto Documents Using webR

• GitHub Copilot in RStudio, it’s finally here!

• Graphic Design with ggplot2 by Cédric Scherer- Updated

• Practical Statistics in Medicine with R

• Field Guide to Writing Your First R package

New Packages

📦 Go Live for More New Pkgs 📦

CRAN

• {newscatcheR} 0.0.1: Programmatically Collect Normalized News from (Almost) Any Website
• {genius} 2.2.2: Easily Access Song Lyrics from Genius.com
• {almanac} 0.1.0: Tools for Working with Recurrence Rules
• {tidylo} 0.1.0: Weighted Tidy Log Odds Ratio
• {nombre} 0.1.0: Number Names
• {nhlapi} 0.1.2: A Minimum-Dependency ‘R’ Interface to the ‘NHL’ API
• {applicable} 0.0.1: A Compilation of Applicability Domain Methods
• {upsetjs} 1.0.2: ‘HTMLWidget’ Wrapper of ‘UpSet.s’ for Exploring Large Set Intersections
• {sketcher} 0.1.3: Pencil Sketch Effect
• {BOJ} 0.2.2: Interface to Bank of Japan Statistics
• {ROpenCVLite} 0.4.430: Install ‘OpenCV’

Bioconductor

GitHub or Bitbucket

Updated Packages

🔍 Search on R-universe 🔍

• {mirai} 0.10.0: Minimalist Async Evaluation Framework for R.

• {mirai.promises} 0.3.0: Make ‘Mirai’ ‘Promises’ in Shiny and Plumber Pipelines.

• • {pavo} 2.9.0: Perceptual Analysis, Visualization and Organization of Spectral Colour Data - diffify
• {markovchain} 0.9.5: Easy Handling Discrete Time Markov Chains - diffify
• {checkdown} 0.0.10: Check-Fields and Check-Boxes for ‘rmarkdown’ - diffify
• {lgpr} 1.2.4: Longitudinal Gaussian Process Regression - diffify
• {pedSimulate} 1.4.1: Pedigree, Genetic Merit, Phenotype, and Genotype Simulation - diffify
• {and} 0.1.5: Construct Natural-Language Lists with Internationalization - diffify
• {raqs} 1.0.1: Interface to the US EPA Air Quality System (AQS) API - diffify
• {rtsplot} 0.1.5: Time Series Plot - diffify
• {panelView} 1.1.17: Visualizing Panel Data - diffify
• {ctmm} 1.2.0: Continuous-Time Movement Modeling - diffify
• {csurvey} 1.9: Constrained Regression for Survey Data - diffify
• {clustermq} 0.9.0: Evaluate Function Calls on HPC Schedulers (LSF, SGE, SLURM, PBS/Torque) - diffify
• {blastula} 0.3.4: Easily Send HTML Email Messages - diffify
• {bayesm} 3.1-6: Bayesian Inference for Marketing/Micro-Econometrics - diffify
• {uci} 0.3.0: Urban Centrality Index - diffify
• {recmap} 1.0.17: Compute the Rectangular Statistical Cartogram - diffify
• {ohun} 1.0.0: Optimizing Acoustic Signal Detection - diffify
• {nodbi} 0.9.8: ‘NoSQL’ Database Connector - diffify
• {import} 1.3.1: An Import Mechanism for R - diffify
• {fastcpd} 0.7.2: Fast Change Point Detection via Sequential Gradient Descent - diffify
• {CopulaCenR} 1.2.3: Copula-Based Regression Models for Multivariate Censored Data - diffify
• {BTSR} 0.1.5: Bounded Time Series Regression - diffify
• {StanMoMo} 1.2.0: Bayesian Mortality Modelling with ‘Stan’ - diffify
• {plu} 0.3.0: Dynamically Pluralize Phrases - diffify
• {multifear} 0.1.3: Multiverse Analyses for Conditioning Data - diffify
• {forestploter} 1.1.1: Create Flexible Forest Plot - diffify
• {cpd} 0.3.2: Complex Pearson Distributions - diffify
• {Temporal} 0.3.0.1: Parametric Time to Event Analysis - diffify
• {UKFE} 0.3.0: UK Flood Estimation - diffify
• {dann} 1.0.0: Discriminant Adaptive Nearest Neighbor Classification - diffify
• {kernelshap} 0.3.8: Kernel SHAP - diffify
• {GeoModels} 1.1.3: Procedures for Gaussian and Non Gaussian Geostatistical (Large) Data Analysis - diffify
• {skmeans} 0.2-16: Spherical k-Means Clustering - diffify
• {clue} 0.3-65: Cluster Ensembles - diffify
• {funkyheatmap} 0.5.0: Generating Funky Heatmaps for Data Frames - diffify
• {radiant.multivariate} 1.6.1: Multivariate Menu for Radiant: Business Analytics using R and Shiny - diffify
• {halk} 0.0.4: Methods to Create Hierarchical Age Length Keys for Age Assignment - diffify
• {walkboutr} 0.2.0: Generate Walk Bouts from GPS and Accelerometry Data - diffify
• {phylosem} 1.0.2: Phylogenetic Structural Equation Model - diffify
• {OmicSense} 0.2.0: Biosensor Development using Omics Data - diffify
• {ggseqplot} 0.8.3: Render Sequence Plots using ‘ggplot2’ - diffify
• {geostatsp} 2.0.1: Geostatistical Modelling with Likelihood and Bayes - diffify
• {RchivalTag} 0.1.7: Analyzing and Interactive Visualization of Archival Tagging Data - diffify
• {consort} 1.2.1: Create Consort Diagram - diffify
• {RcppColors} 0.5.0: Color Mappings and ‘C++’ Header Files for Color Conversion - diffify
• {colorednoise} 1.1.1: Simulate Temporally Autocorrelated Populations - diffify
• {varTestnlme} 1.3.5: Variance Components Testing for Linear and Nonlinear Mixed Effects Models - diffify
• {ExactMed} 0.3.0: Exact Mediation Analysis for Binary Outcomes - diffify
• {condir} 0.1.4: Computation of P Values and Bayes Factors for Conditioning Data - diffify
• {tigris} 2.0.4: Load Census TIGER/Line Shapefiles - diffify
• {mcompanion} 0.5.8: Objects and Methods for Multi-Companion Matrices - diffify
• {timetk} 2.8.4: A Tool Kit for Working with Time Series - diffify
• {RMixtCompUtilities} 4.1.6: Utility Functions for ‘MixtComp’ Outputs - diffify
• {accumulate} 0.9.3: Split-Apply-Combine with Dynamic Groups - diffify
• {pedquant} 0.2.3: Public Economic Data and Quantitative Analysis - diffify
• {gnonadd} 1.0.2: Various Non-Additive Models for Genetic Associations - diffify
• {easy.utils} 0.0.2: Frequently Used Functions for Easy R Programming - diffify
• {arrow} 13.0.0.1: Integration to ‘Apache’ ‘Arrow’ - diffify
• {REPPlabShiny} 0.4.2: ‘REPPlab’ via a Shiny Application - diffify
• {oosse} 1.0.10: Out-of-Sample R² with Standard Error Estimation - diffify
• {lakemorpho} 1.3.2: Lake Morphometry Metrics - diffify
• {gRbase} 2.0.0: A Package for Graphical Modelling in R - diffify
• {R3port} 0.2.5: Report Functions to Create HTML and PDF Files - diffify
• {vdiffr} 1.0.7: Visual Regression Testing and Graphical Diffing - diffify
• {pkgload} 1.3.3: Simulate Package Installation and Attach - diffify
• {piecepackr} 1.13.8: Board Game Graphics - diffify
• {mvMAPIT} 2.0.2: Multivariate Genome Wide Marginal Epistasis Test - diffify
• {MazamaTimeSeries} 0.2.15: Core Functionality for Environmental Time Series - diffify
• {malariaAtlas} 1.2.0: An R Interface to Open-Access Malaria Data, Hosted by the ‘Malaria Atlas Project’ - diffify
• {hdf5r.Extra} 0.0.2: Extensions for ‘HDF5’ R Interfaces - diffify
• {fqar} 0.4.2: Floristic Quality Assessment Tools for R - diffify
• {dtwSat} 1.0.0: Time-Weighted Dynamic Time Warping for Satellite Image Time Series Analysis - diffify
• {palm} 1.1.5: Fitting Point Process Models via the Palm Likelihood - diffify
• {smacpod} 2.6: Statistical Methods for the Analysis of Case-Control Point Data - diffify
• {BayesFactor} 0.9.12-4.5: Computation of Bayes Factors for Common Designs - diffify
• {survstan} 0.0.4: Fitting Survival Regression Models via ‘Stan’ - diffify
• {prqlr} 0.5.3: R Bindings for the ‘prql-compiler’ Rust Library - diffify
• {isotracer} 1.1.5: Isotopic Tracer Analysis Using MCMC - diffify
• {diseasemapping} 2.0.3: Modelling Spatial Variation in Disease Risk for Areal Data - diffify
• {PheVis} 1.0.3: Automatic Phenotyping of Electronic Health Record at Visit Resolution - diffify
• {paws.common} 0.6.1: Paws Low-Level Amazon Web Services API - diffify
• {fqadata} 1.1.0: Contains Regional Floristic Quality Assessment Databases - diffify
• {clarify} 0.2.0: Simulation-Based Inference for Regression Models - diffify
• {limSolve} 1.5.7: Solving Linear Inverse Models - diffify
• {neighbours} 0.1-3: Neighbourhood Functions for Local-Search Algorithms - diffify
• {ExclusionTable} 1.1.0: Creating Tables of Excluded Observations - diffify
• {tabr} 0.4.9: Music Notation Syntax, Manipulation, Analysis and Transcription in R - diffify
• {mapmisc} 2.0.1: Utilities for Producing Maps - diffify
• {rootSolve} 1.8.2.4: Nonlinear Root Finding, Equilibrium and Steady-State Analysis of Ordinary Differential Equations - diffify
• {chromer} 0.6: Interface to Chromosome Counts Database API - diffify
• {bvpSolve} 1.4.4.1: Solvers for Boundary Value Problems of Differential Equations - diffify
• {wdpar} 1.3.7: Interface to the World Database on Protected Areas - diffify
• {rbioacc} 1.2-0: Inference and Prediction of ToxicoKinetic (TK) Models - diffify
• {AzureRMR} 2.4.4: Interface to ‘Azure Resource Manager’ - diffify
• {ICS} 1.4-1: Tools for Exploring Multivariate Data via ICS/ICA - diffify
• {snowFT} 1.6-1: Fault Tolerant Simple Network of Workstations - diffify
• {NMsim} 0.0.4: Seamless ‘Nonmem’ Simulation Platform - diffify
• {ISRaD} 2.5.5: Tools and Data for the International Soil Radiocarbon Database - diffify
• {geobr} 1.8.1: Download Official Spatial Data Sets of Brazil - diffify
• {fastcpd} 0.7.2: Fast Change Point Detection via Sequential Gradient Descent - diffify
• {romic} 1.1.3: R for High-Dimensional Omic Data - diffify
• {geocausal} 0.2.0: Causal Inference with Spatio-Temporal Data - diffify
• {accessibility} 1.2.0: Transport Accessibility Measures - diffify
• {rbmi} 1.2.5: Reference Based Multiple Imputation - diffify
• {nonmemica} 1.0.8: Create and Evaluate NONMEM Models in a Project Context - diffify
• {NMsim} 0.0.4: Seamless ‘Nonmem’ Simulation Platform - diffify
• {EloSteepness} 0.5.0: Bayesian Dominance Hierarchy Steepness via Elo Rating and David’s Scores - diffify
• {ggstatsplot} 0.12.1: ‘ggplot2’ Based Plots with Statistical Details - diffify
• {echarty} 1.6.0: Minimal R/Shiny Interface to JavaScript Library ‘ECharts’ - diffify
• {ottrpal} 1.2: Companion Tools for Open-Source Tools for Training Resources (OTTR) - diffify
• {connectwidgets} 0.2.1: Organize and Curate Your Content Within ‘Posit Connect’ - diffify
• {jqr} 1.3.0: Client for ‘jq’, a ‘JSON’ Processor - diffify
• {europepmc} 0.4.3: R Interface to the Europe PubMed Central RESTful Web Service - diffify
• {envalysis} 0.6.0: Miscellaneous Functions for Environmental Analyses - diffify
• {datetimeutils} 0.6-2: Utilities for Dates and Times - diffify
• {sisireg} 1.1.1: Sign-Simplicity-Regression-Solver - diffify
• {reslife} 0.1.2: Calculate Mean Residual Life (MRL) and Related Values for Different Distributions - diffify
• {harmony} 1.0.1: Fast, Sensitive, and Accurate Integration of Single Cell Data - diffify
• {BFS} 0.5.5: Get Data from the Swiss Federal Statistical Office - diffify
• {regspec} 2.7: Non-Parametric Bayesian Spectrum Estimation for Multirate Data - diffify
• {crew.cluster} 0.1.2: Crew Launcher Plugins for Traditional High-Performance Computing Clusters - diffify
• {caretEnsemble} 2.0.3: Ensembles of Caret Models - diffify
• {MTest} 1.0.1: A Procedure for Multicollinearity Testing using Bootstrap - diffify
• {newscatcheR} 0.1.2: Programmatically Collect Normalized News from (Almost) Any Website - diffify
• {IOHanalyzer} 0.1.8.2: Data Analysis Part of ‘IOHprofiler’ - diffify
• {mlr3misc} 0.13.0: Helper Functions for ‘mlr3’ - diffify
• {zen4R} 0.9: Interface to ‘Zenodo’ REST API - diffify
• {timsac} 1.3.8-3: Time Series Analysis and Control Package - diffify
• {SqlRender} 1.16.0: Rendering Parameterized SQL and Translation to Dialects - diffify
• {RoBTT} 1.2.1: Robust Bayesian T-Test - diffify
• {FrF2} 2.3-3: Fractional Factorial Designs with 2-Level Factors - diffify
• {exactextractr} 0.10.0: Fast Extraction from Raster Datasets using Polygons - diffify
• {reReg} 1.4.6: Recurrent Event Regression - diffify
• {recommenderlab} 1.0.6: Lab for Developing and Testing Recommender Algorithms - diffify
• {MixSemiRob} 1.1.0: Mixture Models: Parametric, Semiparametric, and Robust - diffify
• {ie2misc} 0.9.1: Irucka Embry’s Miscellaneous USGS Functions - diffify
• {himach} 0.3.2: High Mach Finds Routes for Supersonic Aircraft - diffify
• {fastverse} 0.3.2: A Suite of High-Performance Packages for Statistics and Data Manipulation - diffify
• {CoxAIPW} 0.0.3: Doubly Robust Inference for Cox Marginal Structural Model with Informative Censoring - diffify
• {CalibrationCurves} 2.0.0: Calibration Performance - diffify
• {BGmisc} 1.0: An R Package for Extended Behavior Genetics Analysis - diffify
• {aggTrees} 2.0.2: Aggregation Trees - diffify
• {VedicDateTime} 0.1.9: Vedic Calendar System - diffify
• {PDtoolkit} 1.2.0: Collection of Tools for PD Rating Model Development and Validation - diffify
• {yulab.utils} 0.1.0: Supporting Functions for Packages Maintained by ‘YuLab-SMU’ - diffify
• {rsm} 2.10.4: Response-Surface Analysis - diffify
• {NEONiso} 0.6.4: Tools to Calibrate and Work with NEON Atmospheric Isotope Data - diffify
• {rugarch} 1.5-1: Univariate GARCH Models - diffify
• {rmass2} 0.0.0.2: Repeated Measures with Attrition: Sample Sizes and Power Levels for 2 Groups - diffify
• {jab.adverse.reactions} 1.0.3: Possible Adverse Events/Reactions from the Vaccinations/Experimental Gene Therapies - diffify
• {greenclust} 1.1.1: Combine Categories Using Greenacre’s Method - diffify
• {epoxy} 1.0.0: String Interpolation for Documents, Reports and Apps - diffify
• {Nmix} 2.0.5: Bayesian Inference on Univariate Normal Mixtures - diffify
• {IRTest} 1.11.0: Parameter Estimation of Item Response Theory with Estimation of Latent Distribution - diffify
• {apcluster} 1.4.11: Affinity Propagation Clustering - diffify
• {skilljaR} 0.1.2: Connect to Your ‘Skilljar’ Data - diffify
• {SpatEntropy} 2.2-1: Spatial Entropy Measures - diffify
• {diseasemapping} 2.0.3: Modelling Spatial Variation in Disease Risk for Areal Data - diffify
• {RcppInt64} 0.0.3: ‘Rcpp’-Based Helper Functions to Pass ‘Int64’ and ‘nanotime’ Values Between ‘R’ and ‘C++’ - diffify
• {alone} 0.3: Datasets from the Survival TV Series Alone - diffify
• {abess} 0.4.8: Fast Best Subset Selection - diffify
• {selection.index} 1.2.0: Analysis of Selection Index in Plant Breeding - diffify
• {rio} 1.0.1: A Swiss-Army Knife for Data I/O - diffify
• {mvQuad} 1.0-8: Methods for Multivariate Quadrature - diffify
• {ggblanket} 5.1.0: Simplify ‘ggplot2’ Visualisation - diffify
• {graphlayouts} 1.0.1: Additional Layout Algorithms for Network Visualizations - diffify
• {editbl} 0.9.6: ‘DT’ Extension for CRUD (Create, Read, Update, Delete) Applications in ‘shiny’ - diffify
• {restatapi} 0.22.1: Search and Retrieve Data from Eurostat Database - diffify
• {LDATS} 0.3.0: Latent Dirichlet Allocation Coupled with Time Series Analyses - diffify
• {volesti} 1.1.2-7: Volume Approximation and Sampling of Convex Polytopes - diffify
• {rngSetSeed} 0.3-3: Seeding the Default RNG with a Numeric Vector - diffify
• {renv} 1.0.3: Project Environments - diffify
• {r3PG} 0.1.6: Simulating Forest Growth using the 3-PG Model - diffify
• {puniform} 0.2.7: Meta-Analysis Methods Correcting for Publication Bias - diffify
• {MBHdesign} 2.3.14: Spatial Designs for Ecological and Environmental Surveys - diffify
• {htsr} 2.1.1: Hydro-Meteorology Time-Series - diffify
• {collin} 0.0.4: Visualization the Effects of Collinearity in Distributed Lag Models and Other Linear Models - diffify
• {cauphy} 1.0.1: Trait Evolution on Phylogenies Using the Cauchy Process - diffify
• {gpbStat} 0.4.1: Comprehensive Statistical Analysis of Plant Breeding Experiments - diffify
• {r2redux} 1.0.16: R2 Statistic - diffify
• {GenSA} 1.1.10.1: R Functions for Generalized Simulated Annealing - diffify
• {fude} 0.3.4: Utilities for Fude Polygon - diffify
• {VGAM} 1.1-9: Vector Generalized Linear and Additive Models - diffify
• {sctransform} 0.4.0: Variance Stabilizing Transformations for Single Cell UMI Data - diffify
• {quarto} 1.3: R Interface to ‘Quarto’ Markdown Publishing System - diffify
• {phylosem} 1.0.2: Phylogenetic Structural Equation Model - diffify
• {RcppHNSW} 0.5.0: ‘Rcpp’ Bindings for ‘hnswlib’, a Library for Approximate Nearest Neighbors - diffify
• {jlmerclusterperm} 1.0.6: Cluster-Based Permutation Analysis for Densely Sampled Time Data - diffify
• {updater} 0.1.2: Utilities for Updating R - diffify
• {netplot} 0.2-0: Beautiful Graph Drawing - diffify
• {nlmixr2est} 2.1.7: Nonlinear Mixed Effects Models in Population PK/PD, Estimation Routines - diffify
• {eventPred} 0.2.0: Event Prediction - diffify
• {mark} 0.6.1: Miscellaneous, Analytic R Kernels - diffify
• {DEPONS2R} 1.2.2: Read, Plot and Analyse Output from the DEPONS Model - diffify
• {valr} 0.7.0: Genome Interval Arithmetic - diffify
• {randomizeR} 3.0.2: Randomization for Clinical Trials - diffify
• {TraMineR} 2.2-8: Trajectory Miner: a Sequence Analysis Toolkit - diffify
• {Matrix} 1.6-1.1: Sparse and Dense Matrix Classes and Methods - diffify
• {BSDA} 1.2.2: Basic Statistics and Data Analysis - diffify
• {webSDM} 1.1-4: Including Known Interactions in Species Distribution Models - diffify

Videos and Podcasts

• Listen to the R-Weekly Highlights Podcast

Gist & Cookbook

Shiny Apps

R Internationally

• A Continental Movement: LatinR Event is Face-to-Face in Montevideo, Uruguay This Year

Tutorials

• Calibrating Binary Probabilities

• Reproducible data science with Nix, part 6 – CI/CD has never been easier

• Snap Slides: a Lightweight HTML Presentation Framework

• Add Client-side Searching via Fuse.js to Static Sites

• Parallel raster processing in stars

• Finding a circle in a chart by @ellis2013nz

R Project Updates

Updates from R Core:

The 2023 ISC Grant Program

Upcoming Events in 3 Months

Events in 3 Months:

• A list of R conferences and meetings

• This week’s local R-User and applied stats events

• Weekly R Workshops for Ukraine

Grants & Funding

Mark your calendars! The final call for the RUGS grant opportunity is approaching fast - The deadline is September 30th, 2023. Everything you need to know is right here: https://t.co/1MS9KNBecZ #rstats #opensource #RLadiesSaoPaulo pic.twitter.com/DjoU0o1oH9

— R Consortium (@RConsortium) September 22, 2023

Datasets

Jobs

💼 Explore Jobs & Gigs Board on RStudio Community 💼

rtistry

Got a request for this one on my website, curious how y'all feel about the border lines and country annotations?#rstats + #rayshader pic.twitter.com/51Es5BYyNs

— Spencer Schien (@MrPecners) September 19, 2023

Quotes of the Week

What is the most difficult part of becoming a data scientist?

I’ve had to battle through each of these.

And here are 3 tips that worked for me. 🧵#datascience #rstats #python pic.twitter.com/zw0Lm7MiW5

— Matt Dancho (Business Science) (@mdancho84) September 22, 2023

Error messages can be so cruel 😭 #rstats pic.twitter.com/7cCi94Abdy

— Mike Kearney📊 (@kearneymw) September 20, 2023