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EasyStat - Automated Statistical Analysis, Visualization and Multi-Format Narrative Reporting

Provides automated statistical analysis, rich visualization, and multi-format narrative reporting through a unified pipeline. Descriptive statistics are available via easy_describe() and easy_group_summary(). Inferential tests with plain-language narratives are provided by easy_regression(), easy_logistic_regression(), easy_ttest(), easy_anova(), easy_chisq(), easy_ztest(), easy_ftest(), easy_correlation(), easy_wilcox(), and easy_kruskal(). Publication-ready 'ggplot2' visualizations are produced by easy_histogram(), easy_boxplot(), easy_scatter(), easy_barplot(), easy_qqplot(), easy_density(), easy_correlation_heatmap(), easy_regression_diagnostics(), and easy_odds_ratio_plot(). The core Narrative Generator Module applies conditional logic to extracted p-values, effect sizes, and model-fit metrics to produce statistically sound, human-readable explanations automatically. Results render in the 'RStudio' Viewer (HTML), the console (ASCII), or export directly to Microsoft Word via 'flextable' and 'officer'.

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statistical-analysisstatistical-inferencestatistical-modelingstatistics

4.92 score 2 stars 28 scripts 506 downloads

ViewR - Advanced Interactive Data Tables and Data Explorer

An advanced, interactive data table and data explorer for R, delivered as a modern, self-contained 'htmlwidget' with a high-performance virtualized grid. ViewR renders 'Kaggle'-style micro-dashboard column headers complete with data-type badges, mini distribution spark-histograms, and data-completeness (missingness) bars. It provides hover metadata cards, a sliding Data Insights drawer with interactive histograms and 'Pareto' category charts, a multi-condition visual query builder (AND/OR), a column visibility picker, and a reproducible code generator that emits 'dplyr', base R, and 'SQL' that matches the active filter and column state. The interface is implemented entirely in dependency-free vanilla 'JavaScript' (no 'React' or build toolchain) and works in the 'RStudio'/'Positron' Viewer, inside 'Shiny' apps, in 'R Markdown'/'Quarto', or as a portable standalone 'HTML' file. A single call to viewr() opens the explorer; the legacy 'Shiny'-gadget ViewR() editor remains available.

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data-analysisdata-science

4.78 score 3 stars 10 scripts 447 downloads

ggnext - A Next-Generation Grammar of Graphics

An implementation of the Grammar of Graphics described by Wilkinson (2005, ISBN:978-0-387-24544-7), built on 'S7' classes. The familiar grammar vocabulary of aesthetics, geometries, statistics, scales, coordinates, facets and themes composed with '+' is preserved; every constructor that takes an argument also accepts a plot as the first argument of a native pipe ('|>') stage, so the two styles are interchangeable. The package is extended with built-in interactivity, animation, an exact-data export, a plot linter that flags common statistical-graphics mistakes before a figure ships, and a catalogue covering layout diagrams (Sankey, treemap, network, radar), machine-learning diagnostics (SHAP, receiver operating characteristic, calibration, partial dependence) and clinical reporting (Kaplan-Meier, forest, swimmer, CONSORT). Static output is written to Scalable Vector Graphics; interactive output is a self-contained 'HTML' document using a canvas element and vanilla 'JavaScript'. Both render targets consume the same computed-geometry buffer, giving a single source of truth for layer geometry. Layout and estimation algorithms follow their published descriptions, including Bruls, Huizing and van Wijk (2000) <doi:10.1007/978-3-7091-6783-0_4> for squarified treemaps, Fruchterman and Reingold (1991) <doi:10.1002/spe.4380211102> for force-directed graphs, and Kaplan and Meier (1958) <doi:10.1080/01621459.1958.10501452> for survival curves.

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datadata-analysisdata-analyticsdata-engineeringdata-sciencedata-visualizationdatasciencedatasetimageimage-analysisimage-generationimage-manipulationstatisticsvisualization

4.26 score 12 stars 392 downloads

BivLaplaceRL - Bivariate Laplace Transforms, Stochastic Orders, and Entropy Measures in Reliability

Implements methods for bivariate and univariate Laplace transforms of residual lives and reversed residual lives, associated stochastic ordering concepts, and entropy measures for reliability analysis. The package covers: (1) Bivariate Laplace transform of residual lives and stochastic comparisons based on the bivariate Laplace transform order of residual lives (BLt-rl), including weak bivariate hazard rate, mean residual life, and relative mean residual life orders, nonparametric estimation, and NBUHR/NWUHR aging class characterisation; Jayalekshmi, Rajesh, and Nair (2022) "Bivariate Laplace Transform of Residual Lives and Their Properties" <doi:10.1080/03610926.2022.2085874>; (2) Bivariate Laplace transform order of reversed residual lives (BLt-Rrl), reversed hazard gradient, reversed mean residual life, and the associated stochastic orders (weak bivariate reversed hazard rate, weak bivariate reversed mean residual life); Jayalekshmi, Rajesh, and Nair (2022) "Bivariate Laplace Transform Order and Ordering of Reversed Residual Lives" <doi:10.1142/S0218539322500061>; (3) Univariate Laplace transform of residual life, hazard rate, mean residual life, and the corresponding stochastic orders (Lt-rl order, hazard rate order, MRL order), together with a nonparametric estimator. Shannon entropy and Golomb's (1966) information generating function are also provided. Parametric families supported include the Gumbel bivariate exponential, Farlie-Gumbel-Morgenstern (FGM), bivariate power, and Schur-constant distributions. Plotting utilities and a simulation framework for evaluating estimator performance are also provided.

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statistics

4.18 score 324 downloads

RenyiExtropy - Entropy and Extropy Measures for Probability Distributions

Provides functions to compute Shannon entropy, Renyi entropy, Tsallis entropy, and related extropy measures for discrete probability distributions. Includes joint and conditional entropy, KL divergence, Jensen-Shannon divergence, cross-entropy, normalized entropy, and Renyi extropy (including the conditional and maximum forms). All measures use the natural logarithm (nats). Useful for information theory, statistics, and machine learning applications.

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4.18 score 261 downloads