Overload List
| # | Signature | Description |
|---|---|---|
| 1 | procedure GumbelCDFInv(const P: TDenseMtxVec; Mu: Double; beta: Double; minimum: Boolean; const Res: TDenseMtxVec); | Gumbel distribution PPF (vectorized). |
| 2 | function GumbelCDFInv(p: Double; Mu: Double; beta: Double; minimum: Boolean): Double; | Gumbel distribution point percent function (PPF). |
Overload 1: procedure GumbelCDFInv(const P: TDenseMtxVec; Mu: Double; beta: Double; minimum: Boolean; const Res: TDenseMtxVec);
Gumbel distribution PPF (vectorized).
| # | Name | Description |
|---|---|---|
| 1 | P | Defines distribution probabilities, real vector or matrix with values within closed interval [0,1]. |
| 2 | Mu | Defines the location parameter. |
| 3 | beta | Defines the scale parameter, positive real value. |
| 4 | minimum | Defines maximum or minimum Gumbel distrubution. If true, the routine calculates minimum Gumbel PDF. |
| 5 | Res | After calculation stores the PPF calculated from P, Mu and beta. Length and Complex properties of Res are adjusted automatically to match Length and Complex properties of P. |
Result: stored in self (calling object)
Overload 2: function GumbelCDFInv(p: Double; Mu: Double; beta: Double; minimum: Boolean): Double;
Gumbel distribution point percent function (PPF).
| # | Name | Description |
|---|---|---|
| 1 | p | Probability, real value on closed interval [0,1]. |
| 2 | Mu | Location parameter, real value. |
| 3 | beta | Scale parameter, positive real value. |
| 4 | minimum | Selects the distribution sign. If true, the minimum (left) Gumbel PPF is computed |
| 5 | if false, the maximum (right) Gumbel PPF. |
Returns: Double - the Gumbel distribution point percent function (PPF) for probability p using the parameters Mu and beta. For p outside [0,1] or beta <= 0 the result is NAN.
Remarks:
The inverse Gumbel cumulative distribution function (quantile) is
CDF^(-1)(p| mu,beta)={ mu+beta ln(ln1/(1-p)), if amp; minimum
{ [4pt] mu-beta ln(ln1/p), if amp; maximum
Domain: probability p in [0,1], Mu any real value, scale beta > 0. For p < 0, p > 1, or beta <= 0 the result is NAN.
See Also: Probabilities.GumbelPDF, Probabilities.GumbelCDF