Plots

plot_autocorr(data[, var_names, ...])	Bar plot of the autocorrelation function (ACF) for a sequence of data.
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.