Gamma Type

Gamma distribution Sampling implementation based on: "A Simple Method for Generating Gamma Variables" - Marsaglia & Tsang ACM Transactions on Mathematical Software, Vol. 26, No. 3, September 2000, Pages 363-372.

Static members

Static member Description

Gamma.CDF(alpha) (beta) (x)

Full Usage: Gamma.CDF(alpha) (beta) (x)

Parameters:
    alpha : float
    beta : float
    x : float

Returns: float

Computes the cumulative distribution function.

alpha : float
beta : float
x : float
Returns: float

Gamma.Mean(alpha) (beta)

Full Usage: Gamma.Mean(alpha) (beta)

Parameters:
    alpha : float
    beta : float

Returns: float

Computes the mean.

alpha : float
beta : float
Returns: float

Gamma.PDF(alpha) (beta) (x)

Full Usage: Gamma.PDF(alpha) (beta) (x)

Parameters:
    alpha : float
    beta : float
    x : float

Returns: float

Computes the probability density function.

alpha : float
beta : float
x : float
Returns: float

Gamma.Sample(alpha) (beta)

Full Usage: Gamma.Sample(alpha) (beta)

Parameters:
    alpha : float
    beta : float

Returns: float

Produces a random sample using the current random number generator (from GetSampleGenerator()).

alpha : float
beta : float
Returns: float

Gamma.StandardDeviation(alpha) (beta)

Full Usage: Gamma.StandardDeviation(alpha) (beta)

Parameters:
    alpha : float
    beta : float

Returns: float

Computes the standard deviation.

alpha : float
beta : float
Returns: float

Gamma.Support(alpha) (beta)

Full Usage: Gamma.Support(alpha) (beta)

Parameters:
    alpha : float
    beta : float

Returns: float * float

Returns the support of the exponential distribution: [0, Positive Infinity).

alpha : float
beta : float
Returns: float * float

Gamma.Variance(alpha) (beta)

Full Usage: Gamma.Variance(alpha) (beta)

Parameters:
    alpha : float
    beta : float

Returns: float

Computes the variance.

alpha : float
beta : float
Returns: float