readme.md

In cbrown5/BayeSens: Prior sensitivity analysis for Bayesian MCMC models

Tools for prior sensitivity analysis with Bayesian MCMC models

The package BayeSens provides functions for non-parametric calculation of the Hellinger distance, parametric calculation of the Hellinger distance; data cloning ; and calculating posterior shrinkage . Refer to the vignette for more help. (type once the package is loaded, type vignette('BayeSens') in R).

To install this package open R and type: install.packages("devtools") devtools::install_github("cbrown5/BayeSens")

Or if you want the vignettes:

devtools::install_github("cbrown5/BayeSens", build_vignettes = TRUE) (this option requires running a couple of mixing models, but they are short runs)

To get started check out the vignette: vignette("BayeSens")

If you want to apply this tool for isotope mixing models, then see vignette("isotope-mixing-example")

To cite this package please cite the paper "Quantifying learning in biotracer studies" (Brown,et al. Oecologia 2018), or see `citation("BayeSens").

cbrown5/BayeSens documentation built on April 26, 2020, 12:40 a.m.