| plot_bf(idata, var_name[, prior, ref_val, ...]) |
Approximated Bayes Factor for comparing hypothesis of two nested models. |
| plot_bpv(data[, kind, t_stat, bpv, ...]) |
Plot Bayesian p-value for observed data and Posterior/Prior predictive. |
| plot_compare(comp_df[, insample_dev, ...]) |
Summary plot for model comparison. |
| plot_density(data[, group, data_labels, ...]) |
Generate KDE plots for continuous variables and histograms for discrete ones. |
| plot_dist(values[, values2, color, kind, ...]) |
Plot distribution as histogram or kernel density estimates. |
| plot_dist_comparison(data[, kind, figsize, ...]) |
Plot to compare fitted and unfitted distributions. |
| plot_dot(values[, binwidth, dotsize, ...]) |
Plot distribution as dot plot or quantile dot plot. |
| plot_ecdf(values[, values2, eval_points, ...]) |
Plot ECDF or ECDF-Difference Plot with Confidence bands. |
| plot_elpd(compare_dict[, color, xlabels, ...]) |
Plot pointwise elpd differences between two or more models. |
| plot_energy(data[, kind, bfmi, figsize, ...]) |
Plot energy transition distribution and marginal energy distribution in HMC algorithms. |
| plot_ess(idata[, var_names, filter_vars, ...]) |
Generate quantile, local, or evolution ESS plots. |
| plot_forest(data[, kind, model_names, ...]) |
Forest plot to compare HDI intervals from a number of distributions. |
| plot_hdi(x[, y, hdi_prob, hdi_data, color, ...]) |
Plot HDI intervals for regression data. |
| plot_kde(values[, values2, cumulative, rug, ...]) |
1D or 2D KDE plot taking into account boundary conditions. |
| plot_khat(khats[, color, xlabels, ...]) |
Plot Pareto tail indices \(\hat{k}\) for diagnosing convergence in PSIS-LOO. |
| plot_loo_pit([idata, y, y_hat, log_weights, ...]) |
Plot Leave-One-Out (LOO) probability integral transformation (PIT) predictive checks. |
| plot_lm(y[, idata, x, y_model, y_hat, ...]) |
Posterior predictive and mean plots for regression-like data. |
| plot_mcse(idata[, var_names, filter_vars, ...]) |
Plot quantile or local Monte Carlo Standard Error. |
| plot_pair(data[, group, var_names, ...]) |
Plot a scatter, kde and/or hexbin matrix with (optional) marginals on the diagonal. |
| plot_parallel(data[, var_names, ...]) |
Plot parallel coordinates plot showing posterior points with and without divergences. |
| plot_posterior(data[, var_names, ...]) |
Plot Posterior densities in the style of John K. |
| plot_ppc(data[, kind, alpha, mean, ...]) |
Plot for posterior/prior predictive checks. |
| plot_rank(data[, var_names, filter_vars, ...]) |
Plot rank order statistics of chains. |
| plot_separation([idata, y, y_hat, ...]) |
Separation plot for binary outcome models. |
| plot_trace(data[, var_names, filter_vars, ...]) |
Plot distribution (histogram or kernel density estimates) and sampled values or rank plot. |
| plot_ts(idata, y[, x, y_hat, y_holdout, ...]) |
Plot timeseries data. |
| plot_violin(data[, var_names, combine_dims, ...]) |
Plot posterior of traces as violin plot. |