Plots

plot_autocorr(data[, var_names, ...])

Bar plot of the autocorrelation function for a sequence of data.

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_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, ...])

Plot quantile, local or evolution of effective sample sizes (ESS).

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 for diagnosing convergence.

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, filter_vars, ...])

Plot posterior of traces as violin plot.