Showing 10 of total 10 results (show query)
indrajeetpatil
ggstatsplot:'ggplot2' Based Plots with Statistical Details
Extension of 'ggplot2', 'ggstatsplot' creates graphics with details from statistical tests included in the plots themselves. It provides an easier syntax to generate information-rich plots for statistical analysis of continuous (violin plots, scatterplots, histograms, dot plots, dot-and-whisker plots) or categorical (pie and bar charts) data. Currently, it supports the most common types of statistical approaches and tests: parametric, nonparametric, robust, and Bayesian versions of t-test/ANOVA, correlation analyses, contingency table analysis, meta-analysis, and regression analyses. References: Patil (2021) <doi:10.21105/joss.03236>.
Maintained by Indrajeet Patil. Last updated 1 months ago.
bayes-factorsdatasciencedatavizeffect-sizeggplot-extensionhypothesis-testingnon-parametric-statisticsregression-modelsstatistical-analysis
2.1k stars 14.46 score 3.0k scripts 1 dependents
easystats
see:Model Visualisation Toolbox for 'easystats' and 'ggplot2'
Provides plotting utilities supporting packages in the 'easystats' ecosystem (<https://github.com/easystats/easystats>) and some extra themes, geoms, and scales for 'ggplot2'. Color scales are based on <https://materialui.co/>. References: Lüdecke et al. (2021) <doi:10.21105/joss.03393>.
Maintained by Indrajeet Patil. Last updated 20 days ago.
data-visualizationeasystatsggplot2hacktoberfestplottingseestatisticsvisualisationvisualization
902 stars 13.22 score 2.0k scripts 3 dependentseasystats
easystats:Framework for Easy Statistical Modeling, Visualization, and Reporting
A meta-package that installs and loads a set of packages from 'easystats' ecosystem in a single step. This collection of packages provide a unifying and consistent framework for statistical modeling, visualization, and reporting. Additionally, it provides articles targeted at instructors for teaching 'easystats', and a dashboard targeted at new R users for easily conducting statistical analysis by accessing summary results, model fit indices, and visualizations with minimal programming.
Maintained by Daniel Lüdecke. Last updated 27 days ago.
dataanalyticsdatascienceeasystatshacktoberfestmodelsperformance-metricsregression-modelsstatistics
1.1k stars 13.01 score 1.8k scripts 1 dependentsindrajeetpatil
statsExpressions:Tidy Dataframes and Expressions with Statistical Details
Utilities for producing dataframes with rich details for the most common types of statistical approaches and tests: parametric, nonparametric, robust, and Bayesian t-test, one-way ANOVA, correlation analyses, contingency table analyses, and meta-analyses. The functions are pipe-friendly and provide a consistent syntax to work with tidy data. These dataframes additionally contain expressions with statistical details, and can be used in graphing packages. This package also forms the statistical processing backend for 'ggstatsplot'. References: Patil (2021) <doi:10.21105/joss.03236>.
Maintained by Indrajeet Patil. Last updated 1 months ago.
bayesian-inferencebayesian-statisticscontingency-tablecorrelationeffectsizemeta-analysisparametricrobustrobust-statisticsstatistical-detailsstatistical-teststidy
312 stars 10.92 score 146 scripts 2 dependents
jinseob2kim
jsmodule:'RStudio' Addins and 'Shiny' Modules for Medical Research
'RStudio' addins and 'Shiny' modules for descriptive statistics, regression and survival analysis.
Maintained by Jinseob Kim. Last updated 14 days ago.
medicalrstudio-addinsshinyshiny-modulesstatistics
21 stars 8.69 score 61 scripts
ethan-young
multitool:Run Multiverse Style Analyses
Run the same analysis over a range of arbitrary data processing decisions. 'multitool' provides an interface for creating alternative analysis pipelines and turning them into a grid of all possible pipelines. Using this grid as a blueprint, you can model your data across all possible pipelines and summarize the results.
Maintained by Ethan Young. Last updated 4 months ago.
1 stars 5.63 score 71 scripts
allen-1242
TangledFeatures:Feature Selection in Highly Correlated Spaces
Feature selection algorithm that extracts features in highly correlated spaces. The extracted features are meant to be fed into simple explainable models such as linear or logistic regressions. The package is useful in the field of explainable modelling as a way to understand variable behavior.
Maintained by Allen Sunny. Last updated 1 years ago.
4.18 score 6 scripts
jgeller112
webgazeR:Tools for Processing Webcam Eye Tracking Data
A companion package to gazeR. Functions for reading and pre-processing webcam eye tracking data.
Maintained by Jason Geller. Last updated 6 days ago.
1 stars 3.25 score 21 scripts
cran
popstudy:Applied Techniques to Demographic and Time Series Analysis
The use of overparameterization is proposed with combinatorial analysis to test a broader spectrum of possible ARIMA models. In the selection of ARIMA models, the most traditional methods such as correlograms or others, do not usually cover many alternatives to define the number of coefficients to be estimated in the model, which represents an estimation method that is not the best. The popstudy package contains several tools for statistical analysis in demography and time series based in Shryock research (Shryock et. al. (1980) <https://books.google.co.cr/books?id=8Oo6AQAAMAAJ>).
Maintained by Cesar Gamboa-Sanabria. Last updated 1 years ago.
1.70 score