basetable - Fast and Memory-Efficient Base R Table Manipulation
A tabular data manipulation, exploration and validation toolkit with a base R-style interface (subset, transform, aggregate, merge, split) and no external computation dependency. Grouping, joins, ordering, filtering, reshaping and delimited-file reading run in a bundled 'C++' engine that uses multiple threads for the heavier operations. Grouped reducers accumulate in compiled code without materialising intermediate columns, so grouped aggregation and counting allocate close to nothing. Results are returned as an ordinary data frame with a light 'basetable' class.
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base-rcppdata-framedata-manipulationdata-tabledata-wranglingdataframehigh-performancemultithreadingrcpp-alternativetabular-datacpp
6.88 score 2 stars 5 dependents 1 scripts 248 downloadsfunctionals - Functional Programming with Parallelism and Progress Tracking
Provides functional tools such as fmap(), fwalk(), and fapply() to iterate over vectors, data frames, or grouped data with optional parallelism and real-time progress tracking. Progress updates reflect completed tasks across sequential, multicore, and cluster-backed execution. A uniform error policy keeps a run going when individual tasks fail, and optional per-task L'Ecuyer-CMRG random-number streams make parallel Monte Carlo work reproducible regardless of the number of cores. Designed for readable and reproducible workflows, including simulation and benchmarking.
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functional-programming
6.35 score 3 stars 5 dependents 410 downloadsdensemlp - Dense Neural Networks for Tabular Regression, Classification and Survival
Dense feed-forward neural networks (multilayer perceptrons) for tabular regression, classification and survival analysis, with a formula or x/y interface. Supports residual and gated hidden blocks, batch normalization, per-layer dropout, learned cross-feature interactions, exponential moving-average weights, learning-rate schedules, internal bootstrap ensembles and Adam optimization. Survival outcomes are trained with either a batch-wise Breslow-tie Cox partial likelihood or a discrete-time inverse-probability-of-censoring-weighted integrated Brier score. The numerical kernels are implemented natively in C++ via 'RcppArmadillo', with no external deep learning framework dependency (no 'torch' / 'libtorch'). Companion helpers provide k-fold cross-validation, hyperparameter search and task-aware evaluation metrics.
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classificationdeep-learningmlpregressiontabular-datatorchopenblascpp
5.86 score 2 stars 3 dependents 419 downloadstestflow - A Workflow for Statistical Testing and Interpretation
Provides a unified workflow for choosing, running, and interpreting common statistical tests, from group comparisons and analysis of variance to regression, survival analysis, and diagnostic and agreement statistics. The package combines assumption checks, test selection, effect sizes, formatted results, plain-language interpretation, and a sample-size planning module covering continuous, binary, survival, ordinal, bioequivalence, and precision-based designs. Implemented methods follow standard references including Casella and Berger (2002, ISBN:9780534243128), Hollander et al. (2013, ISBN:9781118553299), Agresti (2013, ISBN:9780470463635), Cohen (1988, ISBN:9780805802832), Hosmer, Lemeshow and Sturdivant (2013, ISBN:9780470582473), and Julious (2010, ISBN:9781584887393).
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data-analysisggplot2statistical-testsstatisticsteaching
5.70 score 2 stars 5 scripts 375 downloadsCEACT - Cost-Effectiveness Analysis Toolkit for Clinical Trials
Provides tools for trial-based economic evaluation of healthcare interventions. Computes and visualizes incremental cost-effectiveness ratios, cost-effectiveness acceptability curves, cost-effectiveness planes, net monetary benefit tables, and one-way deterministic sensitivity analyses. Supports cost-utility analyses using observed summaries and non-parametric bootstrap uncertainty.
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clinical-trialshealth-economic-evaluation
5.20 score 8 stars 302 downloadssurvdnn - Deep Neural Networks for Survival Analysis with R 'torch'
Provides deep learning models for right-censored survival data using the 'torch' backend. Supports multiple loss functions, including Cox partial likelihood, L2-penalized Cox, time-dependent Cox, and accelerated failure time (AFT) loss. Offers a formula-based interface, built-in support for cross-validation, hyperparameter tuning, survival curve plotting, and evaluation metrics such as the C-index, Brier score, and integrated Brier score. For methodological details, see Kvamme et al. (2019) <https://www.jmlr.org/papers/v20/18-424.html>. The package is described in El Badisy (2026) <doi:10.32614/RJ-2026-008>.
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deep-neural-networkssurvival-analysis
5.16 score 6 stars 1 dependents 3 scripts 353 downloadsmissknn - Fast Masked K-Nearest Neighbor Imputation
Fast masked KNN imputation for tabular data with support for single and multiple imputation.
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big-dataimputationknnmissing-datarcppparallelcpp
5.08 score 1 stars 1 dependents 319 downloadsunsurv - Unsupervised Clustering of Individualized Survival Curves
Tools for clustering individualized survival curves using the Partitioning Around Medoids (PAM) algorithm, with monotonic enforcement, optional smoothing, weighted distances (L1/L2), automatic K selection via silhouette width, prediction for new curves, basic stability checks, and plotting helpers. The method is described in El Badisy (2026) <doi:10.1093/bioadv/vbag218>.
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5.02 score 1 dependents 307 downloadsmcstatsim - Monte Carlo Statistical Simulation Tools Using a Functional Approach
A lightweight toolkit for Monte Carlo simulation studies built around a higher-order, functional-style interface: the simulation is expressed as a function of its parameters and mapped over a grid of conditions by a single driver function, which handles iteration, parallelism, reproducible per-replication random-number streams, error capture and result assembly. Also provides ready-to-use performance measures with Monte Carlo standard errors, a summary layer, and diagnostic plots.
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biostatisticsfunctional-programmingmonte-carloparallel-computingreproducible-researchsimulationsimulation-modelingsimulation-studiesstatistical-computingstatistics
4.75 score 2 stars 14 scripts 242 downloadsphynotype - Clustering and Consensus Meta-Clustering
Tools for clustering, consensus meta-clustering, validation, exploratory interpretation, cluster prediction, and plotting. The package provides a clustering workflow with consensus clustering following Strehl and Ghosh (2002) <https://www.jmlr.org/papers/v3/strehl02a.html>.
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bioinformaticsclusteringconsensus-clusteringmachine-learningmeta-clusteringphenotypingvalidation
4.65 score 247 downloadsmimar - Compact Multiple Imputation, Assessment, and Reporting
Provides compact tools for missing-data analysis, including artificial amputation, chained single and multiple imputation, statistical and machine-learning-based imputation methods, diagnostic evaluation, and post-imputation pooling.
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data-analysisimputationmachine-learningmissing-datamultiple-imputationstatistics
4.60 score 1 stars 241 downloads