interpret.plot_slopes

interpret.plot_slopes(
    model,
    idata,
    wrt,
    conditional=None,
    average_by=None,
    eps=0.0001,
    slope='dydx',
    target='mean',
    pps=False,
    use_hdi=True,
    prob=az.rcParams['stats.ci_prob'],
    transforms=None,
    sample_new_groups=False,
    fig_kwargs=None,
    subplot_kwargs=None,
)

Plot conditional adjusted slopes.

Parameters

model : Model

The fitted Bambi model.

idata : InferenceData

InferenceData object containing the posterior samples.

wrt : str or dict

The predictor variable to compute the slope with respect to.

conditional : ConditionalParam = None

Variables to condition on for slopes.

average_by : str or list or bool or None = None

Variables to average slopes over.

eps : float = 0.0001

Perturbation size for finite differencing. Default is 1e-4.

slope : str or SlopeFunc = 'dydx'

The type of slope to compute. Default is ‘dydx’.

target : str = 'mean'

The target parameter to compute slopes for. Default is “mean”.

pps : bool = False

Whether to use posterior predictive samples. Default is False.

use_hdi : bool = True

Whether to use highest density interval. Default is True.

prob : float or list[float] = az.rcParams['stats.ci_prob']

Probability or list of probabilities for credible intervals. Default is from arviz rcParams. When a list is provided, nested bands with decreasing opacity are drawn.

transforms : dict or None = None

Dictionary of transformations to apply to predictions before differencing.

sample_new_groups : bool = False

Whether to sample new group levels. Default is False.

fig_kwargs : dict or None = None

Additional keyword arguments for figure customization.

subplot_kwargs : Mapping[str, str] or None = None

Overrides default plotting sequence (main, group, panel).

Returns

: Plot

A Seaborn objects Plot. In Jupyter notebooks, the plot automatically displays. In scripts, call .show() to display. The returned Plot object can be customized before displaying using method chaining (e.g., .label(), .theme()).

Raises

ValueError

If more than 3 conditional variables are provided without averaging.