SST Class

class sstudentt.SST(mu, sigma, nu, tau)[source]

Creates an Instance of the Skewed Student T Distribution. In this parameterization the expectation equals mu and standard deviation equals sigma.

Parameters
  • mu (scalar or array_like) – mu parameter

  • sigma (scalar or array_like) – sigma parameter

  • nu (scalar or array_like) – nu parameter

  • tau (scalar or array_like) – tau parameter

SST Methods

SST.d(y)[source]

Density Function

Parameters

y (scalar or array_like) – distribution values

Returns

density at the specified y values

Return type

array

SST.p(q)[source]

Distribution Function

Parameters

q (scalar or array_like) – value

Returns

The probability that the SST distributed variable will take

a value less than or equal to q. :rtype: array

SST.q(p)[source]

Quantile Function / Inverse CDF / Percent Point Function

Parameters

p (scalar or array_like) – probabilities

Returns

Quantile values corresponding to the specified probabilities.

Return type

array

SST.r(n=1)[source]

Draws Random Numbers which Follow the SST Distribution

Parameters

n (int or tuple of return shape, optional) – sample size

Returns

random sample drawn from the SST distribution

Return type

array

Note

n is ignored if the distribution parameters are provided as arrays. In that case, a sample with the shape of the provided arrays will be drawn. i.e. n = 1.