make_bic_penalty#

make_bic_penalty(n_params: int, n: int, additional_cpts: int = 1) float[source][source]#

Create a Bayesian Information Criterion (BIC) penalty.

The BIC penalty is a constant penalty given by (n_params + additional_cpts) * log(n), where n is the sample size and n_params is the number of parameters per segment in the model across all variables, and additional_cpts is the number of additional change point parameters per segment. For change detection, this is 1.

Parameters:
n_paramsint

Number of model parameters per segment.

nint

Sample size.

additional_cpts: int, optional, default=1

Number of additional change point parameters per segment. For change detection, this is 1.

Returns:
float

The BIC penalty value.