copulas.univariate.gaussian_kde module

class copulas.univariate.gaussian_kde.GaussianKDE(*args, **kwargs)[source]

Bases: copulas.univariate.base.ScipyModel

A wrapper for gaussian Kernel density estimation implemented in scipy.stats toolbox. gaussian_kde is slower than statsmodels but allows more flexibility.

When a sample_size is provided the fit method will sample the data, and mask the real information. Also, ensure the number of entries will be always the value of sample_size.

Parameters

sample_size (int) – amount of parameters to sample

BOUNDED = 0
MODEL_CLASS

alias of scipy.stats.kde.gaussian_kde

PARAMETRIC = 0
cumulative_distribution(X)[source]

Compute the cumulative distribution value for each point in X.

Parameters

X (numpy.ndarray) – Values for which the cumulative distribution will be computed. It must have shape (n, 1).

Returns

Cumulative distribution values for points in X.

Return type

numpy.ndarray

Raises

NotFittedError – if the model is not fitted.

percent_point(U, method='chandrupatla')[source]

Compute the inverse cumulative distribution value for each point in U.

Parameters
  • U (numpy.ndarray) – Values for which the cumulative distribution will be computed. It must have shape (n, 1) and values must be in [0,1].

  • method (str) – Whether to use the chandrupatla or bisect solver.

Returns

Inverse cumulative distribution values for points in U.

Return type

numpy.ndarray

Raises

NotFittedError – if the model is not fitted.

probability_density(X)[source]

Compute the probability density for each point in X.

Parameters

X (numpy.ndarray) – Values for which the probability density will be computed. It must have shape (n, 1).

Returns

Probability density values for points in X.

Return type

numpy.ndarray

Raises

NotFittedError – if the model is not fitted.

sample(n_samples=1)[source]

Sample values from this model.

Argument:
n_samples (int):

Number of values to sample

Returns

Array of shape (n_samples, 1) with values randomly sampled from this model distribution.

Return type

numpy.ndarray

Raises

NotFittedError – if the model is not fitted.