ggmcmc1.5.1.1 package

Tools for Analyzing MCMC Simulations from Bayesian Inference

ac

Calculate the autocorrelation of a single chain, for a specified amoun...

calc_bin

Calculate binwidths by parameter, based on the total number of bins.

ci

Calculate Credible Intervals (wide and narrow).

custom.sort

Auxiliary function that sorts Parameter names taking into account nume...

get_family

Subset a ggs object to get only the parameters with a given regular ex...

ggmcmc

Wrapper function that creates a single pdf file with all plots that gg...

ggs

Import MCMC samples into a ggs object than can be used by all ggs_* gr...

ggs_autocorrelation

Plot an autocorrelation matrix

ggs_caterpillar

Caterpillar plot with thick and thin CI

ggs_chain

Auxiliary function that extracts information from a single chain.

ggs_compare_partial

Density plots comparing the distribution of the whole chain with only ...

ggs_crosscorrelation

Plot the Cross-correlation between-chains

ggs_density

Density plots of the chains

ggs_diagnostics

Formal diagnostics of convergence and sampling quality

ggs_effective

Dotplot of the effective number of independent draws

ggs_geweke

Dotplot of the Geweke diagnostic, the standard Z-score

ggs_grb

Gelman-Rubin-Brooks plot (Rhat shrinkage)

ggs_histogram

Histograms of the paramters.

ggs_pairs

Create a plot matrix of posterior simulations

ggs_pcp

Plot for model fit of binary response variables: percent correctly pre...

ggs_ppmean

Posterior predictive plot comparing the outcome mean vs the distributi...

ggs_ppsd

Posterior predictive plot comparing the outcome standard deviation vs ...

ggs_Rhat

Dotplot of Potential Scale Reduction Factor (Rhat)

ggs_rocplot

Receiver-Operator Characteristic (ROC) plot for models with binary out...

ggs_running

Running means of the chains

ggs_separation

Separation plot for models with binary response variables

ggs_traceplot

Traceplot of the chains

gl_unq

Generate a factor with unequal number of repetitions.

plab

Generate a data frame suitable for matching parameter names with their...

roc_calc

Calculate the ROC curve for a set of observed outcomes and predicted p...

sde0f

Spectral Density Estimate at Zero Frequency.

Tools for assessing and diagnosing convergence of Markov Chain Monte Carlo simulations, as well as for graphically display results from full MCMC analysis. The package also facilitates the graphical interpretation of models by providing flexible functions to plot the results against observed variables, and functions to work with hierarchical/multilevel batches of parameters (Fernández-i-Marín, 2016 <doi:10.18637/jss.v070.i09>).

  • Maintainer: Xavier Fernández i Marín
  • License: GPL-2
  • Last published: 2021-02-10