RSS POSTS: ##

RSS POSTS:

Conformalized TabICL: Prediction Intervals for a State-Of-The-Art Tabular Foundation Model in Python and R
Conformalized TabPFN: Prediction Intervals for a Pretrained Transformer for Tabular Data in Python and R
Leaflet attribution
More crochet/programming thoughts
Functions over Idioms - Writing R in Python with rfuns
Open Source Makes AI Better
nanotime 0.3.15 on CRAN: Coping
Deploying Quarto documents with GitLab
New release of mapsf: version 1.2.0
Vendor onboarding without the pain: standardising CRO and vendor handoff
From file drop to audit trail: event-driven ingestion for clinical data delivery
Validating your first Shiny app for GxP: a survival guide
Five tips for managing your R-universe 🚀
The Atlas-Learn Approach to the Manifold Hypothesis
blockr: Clinical Data Analysis without Code
Five Things (May 23, 2026): AI in life sciences
ctrlvee: Extract external R code and insert inline
CRANberries UPDATED:
{shinyOAuth} 0.5.0: Provider-Agnostic OAuth Authentication for ‘shiny’ Applications - diffify
{tsgarch} 1.0.4: Univariate GARCH Models - diffify
{RSQLite} 3.53.1: SQLite Interface for R - diffify
{rpymat} 0.1.9: Easy to Configure an Isolated ‘Python’ Environment - diffify
{readNSx} 0.0.7: Read ‘Blackrock-Microsystems’ Files (‘NEV’, ‘NSx’) - diffify
{rd2d} 0.2.0: Estimation and Inference for Boundary Discontinuity Designs - diffify
{ravetools} 0.2.5: Signal and Image Processing Toolbox for Analyzing Intracranial Electroencephalography Data - diffify
{maskedcauses} 0.10.0: Likelihood Models for Systems with Masked Component Cause of Failure - diffify
{flexhaz} 0.5.2: Dynamic Failure Rate Distributions for Survival Analysis - diffify
{filearray} 0.2.2: File-Backed Array for Out-of-Memory Computation - diffify
{elfgen} 2.3.5: Ecological Limit Function Model Generation and Analysis Toolkit - diffify
{dipsaus} 0.3.5: A Dipping Sauce for Data Analysis and Visualizations - diffify
{Compositional} 8.2: Compositional Data Analysis - diffify
{LBI} 0.2.4: Likelihood Based Inference - diffify
{multiSA} 0.2.0: Multi-Stock Assessment - diffify
{h3sdm} 0.1.2: Species Distribution Modeling with H3 Grids - diffify
{cdcanthro} 0.2.0: Sex- and Age-Standardized Metrics from the Centers for Disease Control and Prevention (CDC) Growth Charts - diffify
{familiar} 2.0.1: End-to-End Automated Machine Learning and Model Evaluation - diffify
{CDCPLACES} 1.2.1: Access the ‘CDC PLACES’ API - diffify
{ReliaGrowR} 0.7: Reliability Growth Analysis and Repairable Systems Modeling - diffify
{msPCA} 0.4.0: Sparse Principal Component Analysis with Multiple Principal Components - diffify
{meteo} 2.0-5: RFSI & STRK Interpolation for Meteo and Environmental Variables - diffify
{bigassertr} 0.2.0: Assertion and Message Functions - diffify
{harbinger} 2.0.757: A Unified Time Series Event Detection Framework - diffify
{daltoolboxdp} 1.3.747: Deep Python Extensions for ‘daltoolbox’ - diffify
{tspredit} 2.0.707: Time Series Prediction with Integrated Tuning - diffify
{SeroTrackR} 1.1.0: Serology-Based Data Analysis and Visualization - diffify
{fmpcloudr} 0.1.7: R Access to the ‘FMP Cloud’ and ‘Financial Modeling Prep’ API - diffify
{parglm} 0.1.10: Parallel GLM - diffify
{mathml} 1.8: Translate R Expressions to ‘MathML’ and ‘LaTeX’/’MathJax’ - diffify
{mlr3db} 0.7.2: Data Base Backend for ‘mlr3’ - diffify
{JMbdirect} 0.1.1: Joint Model for Longitudinal and Multiple Time to Events Data - diffify
{isoWater} 1.2.2: Discovery, Retrieval, and Analysis of Water Isotope Data - diffify
{doFuture} 1.2.2: Use Foreach to Parallelize via the Future Framework - diffify
{binsreg} 2.1: Binscatter Estimation and Inference - diffify
{spatstat.Knet} 3.1-3: Extension to ‘spatstat’ for Large Datasets on a Linear Network - diffify
{RGraphSpace} 1.3.0: A Lightweight Interface Between ‘igraph’ and ‘ggplot2’ Graphics - diffify
{copBasic} 2.2.14: General Bivariate Copula Theory and Many Utility Functions - diffify
{BeeBDC} 1.3.4: Occurrence Data Cleaning - diffify
{Bayesiangammareg} 0.1.1: Double Generalized Gamma Regression Models - diffify
{bonsai} 0.4.1: Model Wrappers for Tree-Based Models - diffify
{tidyclust} 0.3.0: A Common API to Clustering - diffify
{rlas} 1.9.2: Read and Write ‘las’ and ‘laz’ Binary File Formats Used for Remote Sensing Data - diffify
{autotab} 1.0.1: Variational Autoencoders for Heterogeneous Tabular Data - diffify
{StepReg} 1.6.5: Stepwise Regression Analysis - diffify
{rddensity} 3.0: Manipulation Testing Based on Density Discontinuity - diffify
{performance} 0.17.0: Assessment of Regression Models Performance - diffify
{modEvA} 3.45: Model Evaluation and Analysis - diffify
{mlr3fselect} 1.6.0: Feature Selection for ‘mlr3’ - diffify
{logging} 0.10-111: R Logging Package - diffify
{amadeus} 2.0.0: Accessing and Analyzing Large-Scale Environmental Data - diffify
{Spower} 0.6.3: Power Analyses using Monte Carlo Simulations - diffify
{fiodata} 0.2.0: Regional and Multi-Regional Input-Output Data - diffify
{LLMR} 0.6.4: Interface for Large Language Model APIs in R - diffify
{bioLeak} 0.3.8: Leakage-Safe Modeling and Auditing for Genomic and Clinical Data - diffify
{statgenHTP} 1.0.9.2: High Throughput Phenotyping (HTP) Data Analysis - diffify
{ROpenCVLite} 4.130.0: Helper Package for Installing ‘OpenCV’ - diffify
{mpactr} 0.3.3: Correction of Preprocessed MS Data - diffify
{ggpointless} 0.3.0: Extra Geometries and Stats for ‘ggplot2’ - diffify
{bayestestR} 0.18.0: Understand and Describe Bayesian Models and Posterior Distributions - diffify
{tufte} 0.15.0: Tufte’s Styles for R Markdown Documents - diffify
{DSIR} 0.7.0: Data Science Infrastructure for Global Health - diffify
{comexr} 0.3.0: Client for the Brazilian Foreign Trade Statistics API (‘ComexStat’) - diffify
{fuzzySim} 4.54: Fuzzy Similarity in Species Distributions - diffify
{ecorest} 2.0.3: Conducts Analyses Informing Ecosystem Restoration Decisions - diffify
{spant} 4.1.0: MR Spectroscopy Analysis Tools - diffify
{hanyupinyin} 0.1.3: Convert Chinese Characters into Hanyu Pinyin - diffify
{tidyBdE} 0.6.1: Retrieve Data from ‘Banco de España’ - diffify
{nanotime} 0.3.15: Nanosecond-Resolution Time Support for R - diffify
{lpcde} 1.0.0: Boundary Adaptive Local Polynomial Conditional Density Estimator - diffify
{rasterpic} 0.5.0: Convert Digital Images into ‘SpatRaster’ Objects - diffify
{CalibrateSSB} 1.4.0: Weighting and Estimation for Panel Data with Non-Response - diffify
{seminrExtras} 1.0.1: Conduct Additional Modeling and Analysis for ‘seminr’ - diffify
{rtpcr} 2.1.8: qPCR Data Analysis - diffify
{morpheus} 1.0-5: Estimate Parameters of Mixtures of Logistic Regressions - diffify
{MMRcaseselection} 0.2.0: Case Classification and Selection Based on Regression Results - diffify
{insight} 1.5.1: Easy Access to Model Information for Various Model Objects - diffify
{cvcqv} 1.0.3: Coefficient of Variation (CV) with Confidence Intervals (CI) - diffify
{admiralonco} 1.4.1: Oncology Extension Package for ADaM in ‘R’ Asset Library - diffify
{yahoofinancer} 0.5.0: Fetch Data from Yahoo Finance API - diffify
{ksformat} 0.7.1: ‘SAS’-Style ‘PROC FORMAT’ for R - diffify
{EDOtrans} 0.3.5: Euclidean Distance-Optimized Data Transformation - diffify
{SEQTaRget} 1.4.2: Sequential Trial Emulation - diffify
{scf} 1.0.10: Analyzing the Survey of Consumer Finances - diffify
{retroharmonize} 0.2.8: Ex Post Survey Data Harmonization - diffify
{rerddapUtils} 1.0.1: Miscellaneous Utilities for ‘rerddap’ - diffify
{multimediate} 0.1.6: Causal Mediation Analysis in Presence of Multiple Mediators Uncausally Related - diffify
{lpdensity} 3.0: Local Polynomial Density Estimation and Inference - diffify
{htrSPRanalysis} 0.1.3: Analysis of Surface Plasmon Resonance Data - diffify
{ETDQualitizer} 1.0.0: Automated Eye Tracking Data Quality Determination for Screen-Based Eye Trackers - diffify
{bayesianETAS} 2.0.0: Bayesian Estimation of the Temporal and Spatio-Temporal ETAS Models for Earthquake Occurrences - diffify
{automatedRecLin} 1.1.1: Record Linkage Based on an Entropy-Maximizing Classifier - diffify
{bmgarch} 2.1.0: Bayesian Multivariate GARCH Models - diffify
{spatstat.sparse} 3.2-0: Sparse Three-Dimensional Arrays and Linear Algebra Utilities - diffify
{ISwR} 2.0-12: Introductory Statistics with R - diffify
{gkwdist} 1.1.3: Generalized Kumaraswamy Distribution Family - diffify
{dplR} 1.7.9: Dendrochronology Program Library in R - diffify
{plotbb} 0.1.2: Grammar of Graphics for ‘base’ Plot - diffify
{pandemonium} 1.0.0: High Dimensional Analysis in Linked Spaces - diffify
{LikertMakeR} 2.3.0: Synthesise and Correlate Likert Scale and Rating-Scale Data Based on Summary Statistics - diffify
{lme4breeding} 1.1.2: Breeding-Related Mixed-Effects Models - diffify
{tokenizers.bpe} 0.1.5: Byte Pair Encoding Text Tokenization - diffify
{statuser} 0.3.0: Statistical Tools Designed for End Users - diffify
{gctsc} 0.2.4: Gaussian and Student-t Copula Models for Count Time Series - diffify
{backbone} 3.0.4: Extracts the Backbone from Networks - diffify
{dendroTools} 1.2.16: Linear and Nonlinear Methods for Analyzing Daily and Monthly Dendroclimatological Data - diffify
{maestro} 1.1.1: Orchestration of Data Pipelines - diffify
{fastei} 0.0.19: Methods for ‘‘A Fast Alternative for the R x C Ecological Inference Case’’ - diffify
{f1pits} 1.3.1: F1 Pit Stop Datasets - diffify
{treestats} 1.70.11: Phylogenetic Tree Statistics - diffify
{NonlinearDiD} 0.2.0: Staggered Difference-in-Differences with Nonlinear Outcomes - diffify
{ggpicrust2} 2.5.16: Make ‘PICRUSt2’ Output Analysis and Visualization Easier - diffify
{dendRoAnalyst} 0.1.6: A Tool for Processing and Analyzing Dendrometer Data - diffify
{ipeaplot} 0.5.2: Add Ipea Editorial Standards to ‘ggplot2’ Graphics - diffify
{openairmaps} 0.10.1: Create Maps of Air Pollution Data - diffify
{geobr} 2.0.0: Download Official Spatial Data Sets of Brazil - diffify
{r.proxy} 0.1.4: Set Proxy in R Console - diffify
{predictsr} 0.2.1: Access the ‘PREDICTS’ Biodiversity Database - diffify
{openair} 3.1.0: Tools for the Analysis of Air Pollution Data - diffify
{getCRUCLdata} 2.0.0: ‘CRU’ ‘CL’ v. 2.0 Climatology Client - diffify
{rym} 1.1.2: R Interface to Yandex Metrica API - diffify
{extraoperators} 0.4.0: Extra Binary Relational and Logical Operators - diffify
{bcp} 4.0.4: Bayesian Analysis of Change Point Problems - diffify
{ngme2} 0.9.8: Linear Latent Non-Gaussian Models with Flexible Distributions - diffify
{CVglasso} 1.0.1: Lasso Penalized Precision Matrix Estimation - diffify
{climatol} 4.5-0: Climate Tools (Series Homogenization and Derived Products) - diffify
{spatialEco} 2.0-5: Spatial Analysis and Modelling Utilities - diffify
{ryandexdirect} 3.6.6: Load Data From ‘Yandex Direct’ - diffify
{r5r} 2.4.0: Rapid Realistic Routing with ‘R5’ - diffify
{mrgsolve} 2.0.1: Simulate from ODE-Based Models - diffify
{gtfsio} 1.2.1: Read and Write General Transit Feed Specification (GTFS) Files - diffify
{fuseMLR} 0.0.4: Fusing Machine Learning in R - diffify
{ECoL} 0.4.4: Complexity Measures for Supervised Problems - diffify
{brickster} 0.2.13: R Toolkit for ‘Databricks’ - diffify
{BRCore} 2.0.7: A Unified Framework for Identification and Ecological Interpretation of Microbial Data from Bioenergy Research Centers - diffify
{bage} 0.10.9: Bayesian Estimation and Forecasting of Age-Specific Rates - diffify
{armadillo4r} 0.9.0: An ‘Armadillo’ Interface - diffify
{ggforestplotR} 0.2.0: Publication-Ready Forest Plots with ‘ggplot2’ - diffify
{fsdaR} 0.9-1: Robust Data Analysis Through Monitoring and Dynamic Visualization - diffify
{vismeteor} 3.0.1: Analysis of Visual Meteor Data - diffify
{verdadecu} 1.0.1: Data from the Ecuador Truth Commission - diffify
{spicy} 0.12.0: Descriptive Statistics, Summary Tables, and Data Management Tools - diffify
{owd} 1.0-7: Open Working Directory - diffify
{osmclass} 0.1.5: Classify Open Street Map Features - diffify
{nhanesdiva} 1.0.1: NHANES Data Search, Preview, and Download Tools - diffify
{groupedHyperframe} 0.4.1: Grouped Hyper Data Frame - diffify
{GeoTox} 1.0.0: Spatiotemporal Mixture Risk Assessment - diffify
{DeductiveR} 2.0.0: Deductive Rational Method - diffify
{eAnalytics} 0.4: Dynamic Web-Based Analytics for the Energy Industry - diffify
{leidenbase} 0.1.37: R and C/C++ Wrappers to Run the Leiden find_partition() Function - diffify
{TKCat} 1.2.1: Tailored Knowledge Catalog - diffify
{PHENTHAUproc} 1.1.2: Phenology Modelling of Thaumetopoea Processionea - diffify
{tidypopgen} 0.4.4: Tidy Population Genetics - diffify
{mlr3resampling} 2026.5.19: Resampling Algorithms for ‘mlr3’ Framework - diffify
{contentanalysis} 1.1.0: Scientific Content and Citation Analysis from PDF Documents - diffify
{OmicFlow} 1.6.0: Fast and Efficient (Automated) Analysis of Sparse Omics Data - diffify
{somhca} 0.4.0: Self-Organising Maps Coupled with Hierarchical Cluster Analysis - diffify
{MSCMT} 1.4.2: Multivariate Synthetic Control Method Using Time Series - diffify
{joinpointR} 0.6.0: Tidy Tools for Joinpoint Regression Models - diffify
{akin} 0.3.3: Functional Utilities for Data Processing - diffify
{shortr} 1.0.3: Develop Concise but Comprehensive Shortened Versions of Psychometric Instruments - diffify
{tidycensus} 1.8.0: Load US Census Boundary and Attribute Data as ‘tidyverse’ and ‘sf’-Ready Data Frames - diffify
{PEAXAI} 1.0.1: Probabilistic Efficiency Analysis Using Explainable Artificial Intelligence - diffify
{tweedie} 3.1.0: Evaluation of Tweedie Exponential Family Models - diffify
{tidylearn} 0.3.1: A Unified Tidy Interface to R’s Machine Learning Ecosystem - diffify
{groupedHyperframe.random} 0.3.0: Simulated Point-Pattern via Vectorized Parameterization - diffify
{bit64} 4.8.2: A S3 Class for Vectors of 64bit Integers - diffify
{TwoStepSDFM} 0.2.2: Estimate a Sparse Mixed Frequency Gaussian Factor Model Using a Two-Step Procedure - diffify
{ProduceR} 1.2: Concise and Efficient Tools for Everyday Statistical Production - diffify
{pensar} 0.6.3: LLM Wiki Engine - diffify
{RMX} 0.1-7: Rasch Models – eXtensions - diffify
{rixpress} 0.12.3: Build Reproducible Analytical Pipelines with ‘Nix’ - diffify
{LatentBMA} 0.1.3: Bayesian Model Averaging for Univariate Link Latent Gaussian Models - diffify
{DiscreteTests} 0.4.0: Vectorised Computation of P-Values and Their Supports for Several Discrete Statistical Tests - diffify
{SpaDES.core} 3.1.0: Core Utilities for Developing and Running Spatially Explicit Discrete Event Models - diffify
{ReDaMoR} 1.0.0: Relational Data Modeler - diffify
{pool} 1.0.5: Object Pooling - diffify
{nprobust} 1.0.0: Kernel Density and Local Polynomial Regression Methods - diffify
{DiceView} 3.2: Methods for Visualization of Computer Experiments Design and Surrogate - diffify
{collapse} 2.1.7: Advanced and Fast Data Transformation - diffify
{cjoint} 2.1.3: AMCE Estimator for Conjoint Experiments - diffify
{CUSUMdesign} 1.1.8: Compute Decision Interval and Average Run Length for CUSUM Charts - diffify
{tinyVAST} 1.6.0: Multivariate Spatio-Temporal Models using Structural Equations - diffify
{couplr} 1.4.0: Optimal Pairing and Matching via Linear Assignment - diffify
{h5lite} 2.1.1.1: Simplified ‘HDF5’ Interface - diffify
{emburden} 0.6.2: Energy Burden Analysis Using Net Energy Return Methodology - diffify
{cmAnalysis} 1.0.3: Process and Visualise Concept Mapping Data - diffify
{evoper} 0.7.0: Evolutionary Parameter Estimation for ‘Repast Simphony’ Models - diffify
{corrgram} 1.15: Plot a Correlogram - diffify
{RcamelsCL} 0.2-0: Easy Handling of the CAMELS-CL Dataset - diffify
{portfolioBacktest} 0.4.2: Automated Backtesting of Portfolios over Multiple Datasets - diffify
{essentialstools} 0.1.4: Datasets and Utilities for Essentials of Statistics for the Behavioral Sciences - diffify
{bedrockbio} 1.3.1: Open-Access Computational Biology Datasets - diffify
{poissonsuperlearner} 0.2.0: Poisson Super Learner - diffify
{changepointGA} 0.1.5: Changepoint Detection via Modified Genetic Algorithms - diffify
{umx} 4.65.0: Structural Equation Modeling and Twin Modeling in R - diffify
{ClickHouseHTTP} 1.0.0: A Simple HTTP Database Interface to ‘ClickHouse’ - diffify
{statgenMPP} 1.0.5: QTL Mapping for Multi Parent Populations - diffify
{RastaRocket} 1.1.5: Rocket-Fast Clinical Research Reporting - diffify
CRANberries NEW:
{snapr} 0.1.0: Convenient Snapshot Testing Functions for Packages
{BioUtils} 0.1.3: Biological Data Analysis and Visualization
{tsitter} 0.1.0: Tree-Sitter Parsing Tools
{megatrees} 1.0.0: Subsets of Randomly Selected Phylogenies from Existing Mega-Phylogenies
{free1way.docreg} 1.0-0: Additional Documentation and Regression Tests for ‘stats::free1way()’
{demor} 1.0.10: Methods for Demographic Analysis
{BSET} 1.0: A Bayesian Surrogate Evaluation Test
{scindex} 0.1.0: Strategic Convergence Index for Inter-Rater Reliability
{hespdiv} 1.2.10: Hierarchical Spatial Data Subdivision into Topologically Contiguous Units
{venny} 0.0.2: Venn Diagram
{smriti} 0.1.0: Automated Routing Engine for Longitudinal Missing Data
{REDCapSync} 0.1.0: Encapsulated ‘REDCap’ Projects for Synchronized Data Pipelines
{rollshap} 1.0.1: Rolling Shapley Values
{rextor} 1.1.0: Prepare ‘WEXTOR’ Data
{CopernicusDataspace} 0.0.1: Search Download and Handle Data from the Copernicus Data Space Ecosystem
{VOWR} 0.1.0: Vital Operational Waiting Risk for Healthcare Systems
{choicer} 0.1.0: Discrete Choice Models for Economic Applications
{bibnets} 0.4.4: Importing, Constructing, and Exporting Bibliometric Networks
{TrackTrap} 0.1.0: Model Cumulative Growing Degree-Days for Pest Monitoring
{Romney} 0.1.0: Classical Cultural Consensus Analysis
{prakriti} 0.1.4: Color Palettes Inspired by India’s Natural Landscapes
{personnelSelectionUtility} 1.0.2: Utility Analysis Methods for Personnel Selection
{mlumr} 0.1.0: Multilevel Unanchored Meta-Regression for Indirect Treatment Comparisons
{epiDeaths} 1.1.8: Functions for Calculating Mortality Indicators
{BetaDanish} 0.1.0: The Beta-Danish Distribution for Lifetime Data Analysis
{wjake} 1.0.0: Personal Themes and Formatting Preferences
{dqcheckr} 0.1.2: Automated Data Quality Checks for Recurring Dataset Deliveries
{rerddapUtils} 1.0.1: Miscellaneous Utilities for ‘rerddap’
{VARcheck} 0.1.0: Visual Diagnostic Checks for Vector Autoregressive Models
{teal.picks} 0.1.0: Dataset and Variable Picker and Merge Module for ‘teal’ Applications
{soilKey} 0.9.97: Automated Soil Profile Classification per ‘WRB’ 2022, ‘SiBCS’ 5 and ‘USDA’ Soil Taxonomy 13
{SimuRg} 0.2.0: Building, Fitting and Evaluating PK/PD Modeles
{seqwrap} 0.7.0: Item-by-Item Iterative Model Fitting
{SDI} 0.1.0: Slow Digestibility Index
{REFT} 0.1.4: Root Exudate Feature Toolkit
{quaqcr} 1.0.4: Quick ATAC-Seq QC
{mvnma} 0.1-0: Multivariate Network Meta-Analysis using Bayesian Methods
{grumpy} 0.1.1: Read ‘NumPy’ ‘.npy’ and ‘.npz’ Files
{ewens} 0.1.0: Ewens Distribution
{smsncut} 0.1.0: Optimal Diagnostic Cutoff Selection under Scale Mixtures of Skew-Normal Distributions
{newmark} 1.1.0: Uncertainty Analysis in Dynamic Site and Slope Response
{JM4QTN} 1.0.0: Joint Mapping for Quantitative Trait Loci
{ImmuneSigR} 0.1.0: Immune Cell Signature Retrieval and Single-Cell Scoring
{dbMatrix} 0.1.0: Database-Backed Matrix Classes and Operations
{conforest} 2.0.1: Conformal Random Forests for Response Surface Emulation
{surveytidy} 0.6.0: Tidy ‘dplyr’/’tidyr’ Verbs for Survey Design Objects
{submitr} 0.1.0: Scaffold and Submit Computational Jobs to HTC Schedulers
{sparseVCBART} 1.0.0: Sparse Varying Coefficient BART with Global-Local Priors”
{pairscale} 1.0: Pairwise Rescaling of Numeric Matrices
{mixtime} 0.1.0: Mixed Temporal Vectors and Operations
{llrem} 0.1.1: LLM Relational Event Models
{HealthMarkers} 0.1.2: Toolkit for Clinical, Metabolic, and Cardiovascular Biomarker Calculations
{gedi2} 2.3.4: Gene Expression Decomposition and Integration
{DrData} 0.2.0: Interactive Statistical Analysis and Machine Learning Platform
{diffcp} 0.1.0: Differentiating Through Cone Programs
{nhanesdiva} 1.0.1: NHANES Data Search, Preview, and Download Tools
{marsearth} 0.0.0: Portable Mars Runtime Replay
{vennDiagramLab} 2.0.5: Headless Venn Diagram Analysis and Rendering
{staat1cho} 0.1.0: Study Indicators Based on Dutch Higher Education Data (1CHO)
{sobol} 1.0.0: Quasi-Monte Carlo Sobol Sequence Generator
{rxode2mrgsolvebridge} 0.1.0: Convert Models Between ‘rxode2’ and ‘mrgsolve’
{roundr} 1.0.0: Incorporate Rounding for Discrete Data Modeling
{orisma} 0.1.0: Occupational Risk Integrated Systematic Mapping and Analysis
{maxentcpp} 1.0.0: Maximum Entropy Species Distribution Modeling (‘C++’ Implementation)
{leadeR} 0.1.0: Profiling Leaders at a Distance
{gendercoder} 0.1.1: Recodes Sex/Gender Descriptions into a Standard Set
{cclustr} 0.1.1: Consensus Clustering Methods for Multiple Imputed Data
{bolder} 0.1.1: ‘RStudio’ Add-Ins for Formatted Section Titles
{binxr} 0.1.1: ‘Binance’ REST API Client
{BFM} 0.2.11: Beta Factor Model
{BayesPPR} 0.1.0: Bayesian Projection Pursuit Regression
{AutoNN} 0.1.0: Automatic Neural Network Modeling for Time Series Forecasting

RSS POSTS: ##

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CRANberries UPDATED:

CRANberries NEW: