Log-Generalized Normal

greybox.distributions.dlgnorm(q, loc=0, scale=1, shape=1, log=False)

Log-Generalised Normal distribution density.

The density is obtained by transforming a Generalised Normal distribution through the exponential function with Jacobian adjustment.

Parameters:

• q (array_like) – Quantiles (must be positive).

• loc (float) – Location parameter.

• scale (float) – Scale parameter.

• shape (float) – Shape parameter.

• log (bool) – If True, return log-density.

Returns:

Density values.

Return type:

array

greybox.distributions.qlgnorm(p, loc=0, scale=1, shape=1)

Log-Generalised Normal distribution quantile function.

Quantiles are obtained by exponentiating Generalised Normal quantiles.

Parameters:

• p (array_like) – Probabilities.

• loc (float) – Location parameter.

• scale (float) – Scale parameter.

• shape (float) – Shape parameter.

Returns:

Quantile values.

Return type:

array