pystra.distributions.distribution.StdNormal#

Use it: User guide · Worked example · Theory

class StdNormal[source]#

Bases: object

Standard normal distribution (mean 0, standard deviation 1).

A lightweight implementation using scipy.special error functions, avoiding the overhead of a full scipy.stats distribution object. This class is used internally by the Nataf transformation and by the marginal distribution mappings (x_to_u / u_to_x).

Methods

cdf

Cumulative distribution function of the standard normal.

pdf

Probability density function of the standard normal.

ppf

Percent-point (inverse CDF) of the standard normal.
static pdf(u)[source]#

Probability density function of the standard normal.

Parameters:

u (float | ndarray) – Quantile(s) in standard normal space.

Returns:

Density value(s).

Return type:

float | ndarray

static cdf(u)[source]#

Cumulative distribution function of the standard normal.

Parameters:

u (ArrayLike) – Quantile(s) in standard normal space.

Returns:

Probability value(s) in [0, 1].

Return type:

float | ndarray

static ppf(p)[source]#

Percent-point (inverse CDF) of the standard normal.

Parameters:

p (ArrayLike) – Probability value(s) in (0, 1).

Returns:

Quantile(s) in standard normal space.

Return type:

float | ndarray