R Weekly 2024-W25 CRAN deadlines, R-universe, {handwriter} package

This article is originally published at https://rweekly.org/

Hello and welcome to this new issue!

• How to have (my) content shared by R Weekly?

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

Highlight

• Expose CRAN deadlines and DOIs

• A fresh new look for R-universe!

• {handwriter} 3.1.1: Handwriting Analysis in R

Insights

• Keith Karani Wachira: Leading the Dekut R Community in Kenya and Innovating with R?

• Expose CRAN deadlines and DOIs

• A fresh new look for R-universe!

• Hack your way to a good Git history

R in the Real World

• Forecasting the UEFA Euro 2024 with a machine learning ensemble

• Simulations for 2024 Euro Cup and Copa America

New Packages

📦 Go Live for More New Pkgs 📦

CRAN

• {bidask} 2.0.4: Efficient Estimation of Bid-Ask Spreads from Open, High, Low, and Close Prices
• {RPregression} 0.1.0: A Simple Regression and Plotting Tool
• {PerMat} 0.1.0: Performance Metrics in Predictive Modeling
• {CITMIC} 0.1.0: Estimation of Cell Infiltration Based on Cell Crosstalk
• {parTimeROC} 0.1.0: Parametric Time-Dependent Receiver Operating Characteristic
• {ehymet} 0.1.0: Methodologies for Functional Data Based on the Epigraph and Hypograph Indices
• {sched} 1.0.1: Request Scheduler
• {rioplot} 1.1.1: Turn a Regression Model Inside Out
• {M3} 0.4: Reading M3 Files
• {smile} 1.0.5: Spatial Misalignment: Interpolation, Linkage, and Estimation
• {repeated} 1.1.8: Non-Normal Repeated Measurements Models
• {datadriftR} 0.0.1: Concept Drift Detection Methods for Stream Data
• {cumulcalib} 0.0.1: Cumulative Calibration Assessment for Prediction Models
• {VertexWiseR} 1.0.0: Simplified Vertex-Wise Analyses of Whole-Brain and Hippocampal Surface
• {synthesizer} 0.2.0: Synthesize Data Based on Emperical Multivariate Distributions and Rank Order Matching
• {scCAN} 1.0.5: Single-Cell Clustering using Autoencoder and Network Fusion
• {samplrData} 1.0.0: Datasets from the SAMPLING Project
• {pci} 1.0.1: A Collection of Process Capability Index Functions
• {Rtapas} 1.2: Random Tanglegram Partitions
• {SurveyDefense} 0.1.0: Survey Defense Tool
• {settingsSync} 3.0.2: ‘Rstudio’ Addin to Sync Settings and Keymaps
• {hdcuremodels} 0.0.1: Penalized Mixture Cure Models for High-Dimensional Data
• {margins} 0.3.27: Marginal Effects for Model Objects
• {RMSDp} 0.1.1: Refined Modified Stahel-Donoho (MSD) Estimators for Outlier Detection (Parallel Version)
• {optiSel} 2.0.8: Optimum Contribution Selection and Population Genetics
• {prediction} 0.3.18: Tidy, Type-Safe ‘prediction()’ Methods
• {piecewiseSEM} 2.3.0.1: Piecewise Structural Equation Modeling
• {VAR.spec} 1.0: Allows Specifying a Bivariate VAR (Vector Autoregression) with Desired Spectral Characteristics
• {SoilSaltIndex} 0.1.0: Soil Salinity Indices Generation using Satellite Data
• {ppgm} 1.0.3: PaleoPhyloGeographic Modeling of Climate Niches and Species Distributions
• {numberize} 1.0.0: Convert Words to Numbers in Multiple Languages
• {multinma} 0.7.1: Bayesian Network Meta-Analysis of Individual and Aggregate Data
• {mcstatsim} 0.1.0: Monte Carlo Statistical Simulation Tools Using a Functional Approach
• {mauricer} 2.5.4: Work with ‘BEAST2’ Packages
• {colocPropTest} 0.9.1: Proportional Testing for Colocalisation Analysis
• {catregs} 0.2.0: Post-Estimation Functions for Generalized Linear Mixed Models
• {birdie} 0.6.1: Bayesian Instrumental Regression for Disparity Estimation
• {PAMscapes} 0.5.8: Tools for Summarising and Analysing Soundscape Data
• {qlcVisualize} 0.3: Visualization for Quantitative Language Comparison
• {multilevelcoda} 1.3.0: Estimate Bayesian Multilevel Models for Compositional Data
• {ecochange} 2.9.3.2: Integrating Ecosystem Remote Sensing Products to Derive EBV Indicators
• {qlcData} 0.3: Processing Data for Quantitative Language Comparison
• {ncdfCF} 0.1.1: Easy Access to NetCDF Files with CF Metadata Conventions
• {lakhesis} 0.0.1: Consensus Seriation for Binary Data
• {jstager} 0.0.2: Retrieve Information Published on J-STAGE
• {igraphwalshdata} 0.1.0: ‘igraph’ Datasets from Melanie Walsh
• {gwzinbr} 0.1.0: Geographically Weighted Zero Inflated Negative Binomial Regression
• {cassandRa} 0.2.0: Finds Missing Links and Metric Confidence Intervals in Ecological Bipartite Networks
• {bcc} 1.5: Beta Control Charts
• {rsides} 0.1: SIDES-Based Subgroup Search Algorithms
• {PredictorSelect} 0.1.0: Out-of-Sample Predictability in Predictive Regressions with Many Predictor Candidates
• {ICompELM} 0.1.0: Independent Component Analysis Based Extreme Learning Machine
• {gmtFD} 0.1.0: General Multiple Tests for Univariate and Multivariate Functional Data
• {arrowheadr} 1.0.1: Make Custom Arrowheads
• {geodata} 0.6-2: Download Geographic Data
• {blandr} 0.6.0: Bland-Altman Method Comparison
• {cryptotrackr} 1.3.3: An Interface to Crypto Data Sources

GitHub or Bitbucket

• Utility Functions and Composite Goods in Economics

Updated Packages

🔍 Search on R-universe 🔍

• {lightgbm} 4.3.0: Light Gradient Boosting Machine - diffify
• {alone} 0.4: Datasets from the Survival TV Series Alone - diffify
• {handwriter} 3.1.1: Handwriting Analysis in R - diffify
• {ggplate} 0.1.3: Create Layout Plots of Biological Culture Plates and Microplates - diffify
• {CAST} 1.0.2: ‘caret’ Applications for Spatial-Temporal Models - diffify
• {troopdata} 1.0.0: Tools for Analyzing Cross-National Military Deployment and Basing Data - diffify
• {torchvision} 0.6.0: Models, Datasets and Transformations for Images - diffify
• {modelsummary} 2.1.1: Summary Tables and Plots for Statistical Models and Data: Beautiful, Customizable, and Publication-Ready - diffify
• {marginaleffects} 0.21.0: Predictions, Comparisons, Slopes, Marginal Means, and Hypothesis Tests - diffify
• {settingsSync} 3.0.2: ‘Rstudio’ Addin to Sync Settings and Keymaps - diffify
• {CohortConstructor} 0.2.1: Build and Manipulate Study Cohorts Using a Common Data Model - diffify
• {Apoderoides} 2.0.0: Prioritize and Delete Erroneous Taxa in a Large Phylogenetic Tree - diffify
• {ggblanket} 9.1.1: Simplify ‘ggplot2’ Visualisation - diffify
• {duckdb} 1.0.0: DBI Package for the DuckDB Database Management System - diffify
• {MASS} 7.3-61: Support Functions and Datasets for Venables and Ripley’s MASS - diffify
• {fixest} 0.12.1: Fast Fixed-Effects Estimations - diffify
• {geomtextpath} 0.1.4: Curved Text in ‘ggplot2’ - diffify
• {geoarrow} 0.2.1: Extension Types for Spatial Data for Use with ‘Arrow’ - diffify
• {Epi} 2.51: Statistical Analysis in Epidemiology - diffify
• {cfr} 0.1.1: Estimate Disease Severity and Case Ascertainment - diffify
• {poputils} 0.3.1: Demographic Analysis and Data Manipulation - diffify
• {diffviewer} 0.1.2: HTML Widget to Show File Differences - diffify
• {vitae} 0.6.0: Curriculum Vitae for R Markdown - diffify
• {mlr} 2.19.2: Machine Learning in R - diffify
• {swagger} 5.17.14: Dynamically Generates Documentation from a ‘Swagger’ Compliant API - diffify
• {soilDB} 2.8.3: Soil Database Interface - diffify
• {nanostringr} 0.4.2: Performs Quality Control, Data Normalization, and Batch Effect Correction for ‘NanoString nCounter’ Data - diffify
• {SchoolDataIT} 0.1.2: Retrieve, Harmonise and Map Open Data Regarding the Italian School System - diffify
• {mapSpain} 0.9.1: Administrative Boundaries of Spain - diffify
• {khisr} 1.0.4: An R Client to Retrieve Data from DHIS2 - diffify
• {ggfoundry} 0.2.0: Shape Foundry & Geom for ‘ggplot2’ - diffify
• {nimble} 1.2.0: MCMC, Particle Filtering, and Programmable Hierarchical Modeling - diffify

Videos and Podcasts

• Listen to the R-Weekly Highlights Podcast

• Scraping the R-Weekly Highlights Podcast

Shiny Apps

• 3MW (Shiny’s module-first approach)

R Internationally

• R para la Ciencia de datos

Tutorials

• Automatic transformation of standard errors?

• Extracting Numbers from Strings in R

• Supercharge your #rstats web searching in Google Chrome with Site Search Shortcuts

• Incorporating time-varying seasonality in forecast models

• {cryptoQuotes}: Open access to cryptocurrency market data in R (Update)

• Traditional Frequentist Inference Uses Unrealistic Priors

• Automatic transformation of standard errors?

• Deal with extreme values

R Project Updates

Updates from R Core:

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

• Meta-Analysis in R workshop, July 11th 18:00-20:00 CEST

Jobs

💼 Explore Jobs & Gigs Board on RStudio Community 💼

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