| ggmcmc-package | Wrapper function that creates a single pdf file with all plots that ggmcmc can produce. |
| ac | Calculate the autocorrelation of a single chain, for a specified amount of lags |
| binary | Simulated data for a binary logistic regression and its MCMC samples |
| 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 numeric values |
| get_family | Subset a ggs object to get only the parameters with a given regular expression. |
| ggmcmc | Wrapper function that creates a single pdf file with all plots that ggmcmc can produce. |
| ggs | Import MCMC samples into a ggs object than can be used by all ggs_* graphical functions. |
| 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 its last part. |
| 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 predicted |
| ggs_ppmean | Posterior predictive plot comparing the outcome mean vs the distribution of the predicted posterior means. |
| ggs_ppsd | Posterior predictive plot comparing the outcome standard deviation vs the distribution of the predicted posterior standard deviations. |
| ggs_Rhat | Dotplot of Potential Scale Reduction Factor (Rhat) |
| ggs_rocplot | Receiver-Operator Characteristic (ROC) plot for models with binary outcomes |
| 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. |
| linear | Simulated data for a continuous linear regression and its MCMC samples |
| plab | Generate a data frame suitable for matching parameter names with their labels |
| radon | Simulations of the parameters of a hierarchical model |
| roc_calc | Calculate the ROC curve for a set of observed outcomes and predicted probabilities |
| s | Simulations of the parameters of a simple linear regression with fake data. |
| s.binary | Simulations of the parameters of a simple linear regression with fake data. |
| s.y.rep | Simulations of the posterior predictive distribution of a simple linear regression with fake data. |
| sde0f | Spectral Density Estimate at Zero Frequency. |
| y | Values for the observed outcome of a simple linear regression with fake data. |
| y.binary | Values for the observed outcome of a binary logistic regression with fake data. |