interpret.plot_predictions
interpret.plot_predictions(model, idata, covariates, target='mean', sample_new_groups=False, pps=False, use_hdi=True, prob=None, transforms=None, legend=True, ax=None, fig_kwargs=None, subplot_kwargs=None)
Plot Conditional Adjusted Predictions
Parameters
model |
bambi.Model |
The model for which we want to plot the predictions. |
required |
idata |
arviz.InferenceData |
The InferenceData object that contains the samples from the posterior distribution of the model. |
required |
covariates |
list or dict |
A sequence of between one and three names of variables in the model. |
required |
target |
str |
Which model parameter to plot. Defaults to ‘mean’. Passing a parameter into target only works when pps is False as the target may not be available in the posterior predictive distribution. |
'mean' |
sample_new_groups |
bool |
If the model contains group-level effects, and data is passed for unseen groups, whether to sample from the new groups. Defaults to False . |
False |
pps |
bool |
Whether to plot the posterior predictive samples. Defaults to False . |
False |
use_hdi |
bool |
Whether to compute the highest density interval (defaults to True) or the quantiles. |
True |
prob |
float |
The probability for the credibility intervals. Must be between 0 and 1. Defaults to 0.94. Changing the global variable az.rcParam["stats.hdi_prob"] affects this default. |
None |
legend |
bool |
Whether to automatically include a legend in the plot. Defaults to True . |
True |
transforms |
dict |
Transformations that are applied to each of the variables being plotted. The keys are the name of the variables, and the values are functions to be applied. Defaults to None . |
None |
ax |
matplotlib.axes._subplots.AxesSubplot |
A matplotlib axes object or a sequence of them. If None, this function instantiates a new axes object. Defaults to None . |
None |
fig_kwargs |
optional |
Keyword arguments passed to the matplotlib figure function as a dict. For example, fig_kwargs=dict(figsize=(11, 8)), sharey=True would make the figure 11 inches wide by 8 inches high and would share the y-axis values. |
None |
subplot_kwargs |
optional |
Keyword arguments used to determine the covariates used for the horizontal, group, and panel axes. For example, subplot_kwargs=dict(main="x", group="y", panel="z") would plot the horizontal axis as x , the color (hue) as y , and the panel axis as z . |
None |
Returns
(matplotlib.figure.Figure, matplotlib.axes._subplots.AxesSubplot) |
A tuple with the figure and the axes. |
Raises
ValueError |
When level is not within 0 and 1. When the main covariate is not numeric or categoric. |
TypeError |
When covariates is not a string or a list of strings. |