Showing 6 of total 6 results (show query)
easystats
bayestestR:Understand and Describe Bayesian Models and Posterior Distributions
Provides utilities to describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion (Highest Density Interval - HDI; Kruschke, 2015 <doi:10.1016/C2012-0-00477-2>) and indices used for null-hypothesis testing (such as ROPE percentage, pd and Bayes factors). References: Makowski et al. (2021) <doi:10.21105/joss.01541>.
Maintained by Dominique Makowski. Last updated 9 hours ago.
bayes-factorsbayesfactorbayesianbayesian-frameworkcredible-intervaleasystatshacktoberfesthdimapposterior-distributionsrope
580 stars 16.85 score 2.2k scripts 83 dependents
mjskay
ggdist:Visualizations of Distributions and Uncertainty
Provides primitives for visualizing distributions using 'ggplot2' that are particularly tuned for visualizing uncertainty in either a frequentist or Bayesian mode. Both analytical distributions (such as frequentist confidence distributions or Bayesian priors) and distributions represented as samples (such as bootstrap distributions or Bayesian posterior samples) are easily visualized. Visualization primitives include but are not limited to: points with multiple uncertainty intervals, eye plots (Spiegelhalter D., 1999) <https://ideas.repec.org/a/bla/jorssa/v162y1999i1p45-58.html>, density plots, gradient plots, dot plots (Wilkinson L., 1999) <doi:10.1080/00031305.1999.10474474>, quantile dot plots (Kay M., Kola T., Hullman J., Munson S., 2016) <doi:10.1145/2858036.2858558>, complementary cumulative distribution function barplots (Fernandes M., Walls L., Munson S., Hullman J., Kay M., 2018) <doi:10.1145/3173574.3173718>, and fit curves with multiple uncertainty ribbons.
Maintained by Matthew Kay. Last updated 4 months ago.
ggplot2uncertaintyuncertainty-visualizationvisualizationcpp
859 stars 14.95 score 3.1k scripts 62 dependentsmjskay
tidybayes:Tidy Data and 'Geoms' for Bayesian Models
Compose data for and extract, manipulate, and visualize posterior draws from Bayesian models ('JAGS', 'Stan', 'rstanarm', 'brms', 'MCMCglmm', 'coda', ...) in a tidy data format. Functions are provided to help extract tidy data frames of draws from Bayesian models and that generate point summaries and intervals in a tidy format. In addition, 'ggplot2' 'geoms' and 'stats' are provided for common visualization primitives like points with multiple uncertainty intervals, eye plots (intervals plus densities), and fit curves with multiple, arbitrary uncertainty bands.
Maintained by Matthew Kay. Last updated 7 months ago.
bayesian-data-analysisbrmsggplot2jagsstantidy-datavisualization
733 stars 14.72 score 7.3k scripts 20 dependents
ngumbang
HDInterval:Highest (Posterior) Density Intervals
A generic function and a set of methods to calculate highest density intervals for a variety of classes of objects which can specify a probability density distribution, including MCMC output, fitted density objects, and functions.
Maintained by Ngumbang Juat. Last updated 2 years ago.
6.80 score 936 scripts 49 dependents
ropensci
fellingdater:Estimate, report and combine felling dates of historical tree-ring series
fellingdater is an R package that aims to facilitate the analysis and interpretation of tree-ring data from wooden cultural heritage objects and structures. The package standardizes the process of computing and combining felling date estimates, both for individual and groups of related tree-ring series.
Maintained by Kristof Haneca. Last updated 10 months ago.
dendrochronologysapwoodtree-rings
9 stars 4.91 score 7 scripts
meierluk
hdi:High-Dimensional Inference
Implementation of multiple approaches to perform inference in high-dimensional models.
Maintained by Lukas Meier. Last updated 4 years ago.
2 stars 4.47 score 139 scripts 7 dependents