hyperfine.distributions.modified_beta_2_mean

hyperfine.distributions.modified_beta_2_mean(alpha_1: Annotated[float, slice(0, None, None)], beta_1: Annotated[float, slice(0, None, None)], z_max_1: Annotated[float, slice(0, None, None)], fraction_1: Annotated[float, slice(0, 1, None)], alpha_2: Annotated[float, slice(0, None, None)], beta_2: Annotated[float, slice(0, None, None)], z_max_2: Annotated[float, slice(0, None, None)]) → float

Mean position of a weighted sum of two modified beta distributions.

Parameters:

• alpha_1 – First shape parameter of the first component.

• beta_1 – Second shape parameter of the first component.

• z_max_1 – Upper bounds of the domain of the first component.

• fraction_1 – Fractional weight of the first component.

• alpha_2 – First shape parameter of the second component.

• beta_2 – Second shape parameter of the second component.

• z_max_2 – Upper bounds of the domain of the second component.

Returns:

The mean position of the distribution.