Summary
Gamma probability density function (PDF).Unit
Probabilities
Declaration
Function GammaPDF(x, a, b: TSample): TSample;
| Parameter | Description |
|---|---|
| x | Defines distribution parameter, valid on [0,INF) interval. |
| a | Defines distribution scale parameter. a must be a positive scalar. |
| b | Defines distribution shape parameter. b must be a positive scalar. |
Result
the Gamma probability density function (PDF) for value x using the parameters a and b. Both parameters a and b must be positive, otherwise the result is NAN.Description
Calculates the Gamma distribution probability density function, defined by the equation:
where G is the Gamma function.
The Gamma distribution is especially important in that it allows us to define two families of random variables, the exponential and chi-squared, that are used extensively in applied statistics. Gamma probability density function can be useful in reliability models of lifetimes.The gamma distribution is more flexible than the exponential in that the probability of surviving an additional period may depend on age. Parameters:
- a: (0,INF)
- b: (0,INF)
Categories
Continuous probabilities| See Also |
|---|
| GammaCDF |
| GammaCDFInv |
Declaration
Procedure GammaPDF(X: TDenseMtxVec; A, B: TSample; Res: TDenseMtxVec);
Description
Calculates the Gamma PDF for vector X using the parameters A and B. The results are stored in vector Res. The Res Length and Complex properties are adjusted automatically. If vector X is complex, an exception is raised.| Copyright 2008 Dew Research |