Calculate Credible Intervals (wide and narrow).
Subset a ggs object to get only the parameters with a given regular expression.
Caterpillar plot with thick and thin CI
Plot an autocorrelation matrix
Wrapper function that creates a single pdf file with all plots that ggmcmc can produce.
Calculate the autocorrelation of a single chain, for a specified amount of lags
Auxiliary function that extracts information from a single chain.
Calculate binwidths by parameter, based on the total number of bins.
Density plots comparing the distribution of the whole chain with only its last part.
Auxiliary function that sorts Parameter names taking into account numeric values
Histograms of the paramters.
Dotplot of the Geweke diagnostic, the standard Z-score
Receiver-Operator Characteristic (ROC) plot for models with binary outcomes
Create a plot matrix of posterior simulations
Posterior predictive plot comparing the outcome standard deviation vs the distribution of the predicted posterior standard deviations.
Running means of the chains
Posterior predictive plot comparing the outcome mean vs the distribution of the predicted posterior means.
Spectral Density Estimate at Zero Frequency.
Simulations of the parameters of a hierarchical model using the radon example in Gelman & Hill (2007).
Simulations of the posterior predictive distribution of a simple linear regression with fake data.
Simulations of the parameters of a simple linear regression with fake data.
Simulations of the parameters of a simple linear regression with fake data.
Generate a factor with unequal number of repetitions.
Density plots of the chains
Calculate the ROC curve for a set of observed outcomes and predicted probabilities
Values for the observed outcome of a binary logistic regression with fake data.
Plot the Cross-correlation between-chains
Values for the observed outcome of a simple linear regression with fake data.
Import MCMC samples into a ggs object than can be used by all ggs_* graphical functions.
Traceplot of the chains
Dotplot of Potential Scale Reduction Factor (Rhat)
Separation plot for models with binary response variables