SpikeAndSlabPrior._tracked_label#

SpikeAndSlabPrior._tracked_label()[source]#

What the averaged diagnostic is.

The result’s shrinkage_label; it contains "inclusion", which is how inclusion_probabilities() knows the diagnostic is a probability rather than a scale.

Return type:

str

Returns:

The label.

Example

>>> SpikeAndSlabPrior()._tracked_label()
'posterior inclusion probability'