R Weekly 2020-48 Your first R package, magrittr, engineering Shiny
Release Date: 2020-11-30
This week’s release was curated by Maëlle Salmon, with help from the R Weekly team members and contributors.
Highlights
Insights
R in the Real World
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Reverse Engineering AstraZeneca’s Vaccine Trial Press Release
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To peek or not to peek after 32 cases? Exploring that question in Biontech/Pfizer’s vaccine trial
R in Organizations
R in Education
New Packages
CRAN
2020-11-29 12:42:00 new-pkgs of the last 7 days with the server time
- {SeleMix} 1.0.2: Selective Editing via Mixture Models
- {stpm} 1.7.9: Stochastic Process Model for Analysis of Longitudinal and Time-to-Event Outcomes
- {transx} 0.0.1: Transform Univariate Time Series
- {oxcgrt} 0.1.0: An Interface to the Oxford COVID-19 Government Response Tracker API
- {geodimension} 1.0.0: Definition of Geographic Dimensions
- {archeofrag} 0.6.0: Refitting and Stratigraphic Analysis in Archeology
- {iNZightRegression} 1.3.0: Tools for Exploring Regression Models with ‘iNZight’
- {IMEC} 0.2.0: Ising Model of Explanatory Coherence
- {GPP} 0.1: Gaussian Process Projection
- {arctools} 1.0.0: Processing and Physical Activity Summaries of Minute Level Activity Data
- {campfin} 1.0.4: Wrangle Campaign Finance Data
- {gfiExtremes} 1.0.0: Generalized Fiducial Inference for Extremes
- {etrader} 0.1.2: ‘ETRADE’ API Interface for R
- {diathor} 0.0.1: Calculate Ecological Information and Diatom Based Indices
- {affinitymatrix} 0.1.0: Estimation of Affinity Matrix
- {NPMLEmix} 1.1: Two-Groups Mixture Model with Covariates
- {LMoFit} 0.1.6: Advanced L-Moment Fitting of Distributions
- {EwR} 1.4: Econometrics with R
- {stevedata} 0.1.0: Steve’s Toy Data for Teaching About a Variety of Methodological, Social, and Political Topics
- {statswalesr} 0.1.1: Easily Extract Data from ‘StatsWales’
- {ifultools} 2.0-19: Insightful Research Tools
- {geomnet} 0.3.1: Network Visualization in the ‘ggplot2’ Framework
- {fdaoutlier} 0.1.1: Outlier Detection Tools for Functional Data Analysis
- {mitre} 0.1.1: Cybersecurity MITRE Standards Data and Digraphs
- {envir} 0.1.0: Manage R Environments Better
- {twowaytests} 1.0: Two-Way Tests in Independent Groups Designs
- {tvem} 1.0-0: Time-Varying Effect Models
- {ResearchAssociate} 0.0.1: Retrieving Publications from PubMed Database Based on User Query
- {DatastreamDSWS2R} 1.7.9: Provides a Link Between the ‘Refinitiv Datastream’ System and R
- {vindecodr} 0.1.1: Provides an Interface to the Department of Transportation VIN Decoder
- {spfda} 0.9.0: Function-on-Scalar Regression with Group-Bridge Penalty
- {reconstructKM} 0.3.0: Reconstruct Individual-Level Data from Published KM Plots
- {GREMLINS} 0.2.0: Generalized Multipartite Networks
- {DPQmpfr} 0.3-0: DPQ (Density, Probability, Quantile) Distribution Computations using MPFR
- {CME.assistant} 1.1.0: Reusable Assisting Functions for Child Mortality Estimation
- {chess} 1.0.0: Read, Write, Create and Explore Chess Games
- {kim} 0.1.11: Functions for Behavioral Science Researchers
- {htsr} 1.0.4: Hydro-Meteo Time-Series
- {gfpop} 1.0.0: Graph-Constrained Functional Pruning Optimal Partitioning
- {ezr} 0.1.5: Easy Use of R via Shiny App for Basic Analyses of Experimental Data
- {EigenR} 1.0.0: Complex Matrix Algebra with ‘Eigen’
- {eatGADS} 0.15.2: Data Management of Large Hierarchical Data
- {wal} 0.0.1: Read and Write ‘wal’ Bitmap Image Files
- {Q7} 0.1.0: Types and Features for Object Oriented Programming
- {pencal} 0.1.1: Penalized Regression Calibration (PRC)
- {CFAcoop} 0.1.0: Colony Formation Assay: Taking into Account Cellular Cooperation
- {wikifacts} 0.4.1: Get Facts and Data from Wikipedia and Wikidata
- {SpatialRegimes} 0.2: Spatial Constrained Clusterwise Regression
- {rwa} 0.0.3: Perform a Relative Weights Analysis
- {mixcure} 2.0: Mixture Cure Models
- {migrate} 0.2.0: Create Credit State Migration (Transition) Matrices
- {ennet} 0.1.0: Utilities to Extract and Analyse Text Data from the Emergency Nutrition Network Forum
- {LPsmooth} 0.1.3: LP Smoothed Inference and Graphics
- {eBsc} 4.12: “Empirical Bayes Smoothing Splines with Correlated Errors”
- {gwasforest} 1.0.0: Make Forest Plot with GWAS Data
- {aRbs} 0.0.1: Find Arbitrage Opportunities for Sports Matches
- {gwer} 2.1: Geographically Weighted Elliptical Regression
- {phonfieldwork} 0.0.10: Linguistic Phonetic Fieldwork Tools
- {LatticeDesign} 2.0-2: Lattice-Based Space-Filling Designs
- {UKFE} 0.1.1: UK Flood Estimation
- {tidyseurat} 0.1.17: Brings Seurat to the Tidyverse
- {Q2q} 0.1.0: Interpolating Age-Specific Mortality Rates at All Ages
- {NADIA} 0.4.0: NA Data Imputation Algorithms
- {mappoly} 0.2.1: Genetic Linkage Maps in Autopolyploids
- {joinet} 0.0.6: Multivariate Elastic Net Regression
- {FSinR} 2.0.5: Feature Selection
- {TGST} 1.0: Targeted Gold Standard Testing
- {text} 0.9.0: Analyses of Text using Natural Language Processing and Machine Learning
- {scTenifoldKnk} 1.0.0: In-Silico Knockout Experiments from Single-Cell Gene Regulatory Networks
- {personalr} 1.0.1: Automated Personal Package Setup
- {NFLSimulatoR} 0.1.0: Simulating Plays and Drives in the NFL
- {mikropml} 0.0.1: User-Friendly R Package for Supervised Machine Learning Pipelines
- {IAcsSPCR} 1.2.1: Data and Functions for “An Intro. to Accept. Samp. & SPC/R”
- {graphhopper} 0.1.1: An R Interface to the ‘GraphHopper’ Directions API
- {CVEK} 0.1-1: Cross-Validated Kernel Ensemble
- {cpss} 0.0.2: Change-Point Detection by Sample-Splitting Methods
- {cmfrec} 2.3.2: Collective Matrix Factorization for Recommender Systems
- {BCT} 1.0: Bayesian Context Trees for Discrete Time Series
- {bcr} 0.1.0: Extract Moroccan Financial Data
- {WinRatio} 1.0: Win Ratio for Prioritized Outcomes and 95% Confidence Interval
- {stacks} 0.1.0: Tidy Model Stacking
- {ppmSuite} 0.1.1: A Collection of Models that Employ a Prior Distribution on Partitions
- {pda} 1.0: Privacy-Preserving Distributed Algorithms
- {M2SMJF} 1.0: Multi-Modal Similarity Matrix Joint Factorization
- {fctbases} 1.0.0: Functional Bases
- {WRI} 0.1.0: Wasserstein Regression Inference
- {healthyR.data} 1.0.0: Data Only Package to ‘healthyR’
- {EcotoneFinder} 0.2.2: Characterising and Locating Ecotones and Communities
- {GWmodel} 2.2-2: Geographically-Weighted Models
- {kofdata} 0.1.4: Get Data from the ‘KOF Datenservice’ API
- {modmarg} 0.9.6: Calculating Marginal Effects and Levels with Errors
GitHub or Bitbucket
- convo, Enables conversations and contracts through controlled vocabulary naming conventions
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postcards, Create simple, beautiful personal websites and landing pages using only R Markdown.
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docsifier, Use docsify.js and Markdown files to create the documentation for your R package.
Updated Packages
Videos and Podcasts
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“Become an R-package developer!”, R-Ladies Bergen with Maëlle Salmon
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Processing Data in Chunks in R using iotools (Option for Big Data Analysis)
Shiny Apps
R Internationally
- {propre.rpls}, le package pour réaliser les publications sur le parc locatif social en France, premier livrable de la démarche PROPRE (PROcessus de Publications REproductibles).
Tutorials
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A latent threshold model to dichotomize a continuous predictor
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The ‘circular random walk’ puzzle: tidy simulation of stochastic processes in R
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Select Columns in R by Name, Index, Letters, & Certain Words with dplyr
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Continuous integration for R projects: from Travis CI to GitHub actions step by step
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Use case from “Engineering Production-Grade Shiny Apps” - Building an App, from Start to Finish
Upcoming Events in 3 Months
Events in 3 Months:
Call for Participation
Quotes of the Week
I’m working with these folks on the accessibility of the conference, the website, and related materials. Please give us your feedback and let us know how we can do better. https://t.co/CTr7u00bqv
— Liz Hare PhD STILL at home (@DogGeneticsLLC) November 26, 2020
Don't gather() and spread()
— Romain François 👨👧👧 (@romain_francois) November 25, 2020