statsmodels.sandbox.distributions.extras.ACSkewT_gen

class statsmodels.sandbox.distributions.extras.ACSkewT_gen[source]

univariate Skew-T distribution of Azzalini

class follows scipy.stats.distributions pattern but with __init__

Methods

cdf(x, *args, **kwds)

Cumulative distribution function of the given RV.

entropy(*args, **kwds)

Differential entropy of the RV.

expect([func, args, loc, scale, lb, ub, …])

Calculate expected value of a function with respect to the distribution by numerical integration.

fit(data, *args, **kwds)

Return MLEs for shape (if applicable), location, and scale parameters from data.

fit_loc_scale(data, *args)

Estimate loc and scale parameters from data using 1st and 2nd moments.

freeze(*args, **kwds)

Freeze the distribution for the given arguments.

interval(alpha, *args, **kwds)

Confidence interval with equal areas around the median.

isf(q, *args, **kwds)

Inverse survival function (inverse of sf) at q of the given RV.

logcdf(x, *args, **kwds)

Log of the cumulative distribution function at x of the given RV.

logpdf(x, *args, **kwds)

Log of the probability density function at x of the given RV.

logsf(x, *args, **kwds)

Log of the survival function of the given RV.

mean(*args, **kwds)

Mean of the distribution.

median(*args, **kwds)

Median of the distribution.

moment(n, *args, **kwds)

n-th order non-central moment of distribution.

nnlf(theta, x)

Return negative loglikelihood function.

pdf(x, *args, **kwds)

Probability density function at x of the given RV.

ppf(q, *args, **kwds)

Percent point function (inverse of cdf) at q of the given RV.

rvs(*args, **kwds)

Random variates of given type.

sf(x, *args, **kwds)

Survival function (1 - cdf) at x of the given RV.

stats(*args, **kwds)

Some statistics of the given RV.

std(*args, **kwds)

Standard deviation of the distribution.

var(*args, **kwds)

Variance of the distribution.

Attributes

random_state

Get or set the RandomState object for generating random variates.