Overload List
| # | Signature | Description |
|---|---|---|
| 1 | procedure JohnsonSBPDF(const X: TDenseMtxVec; gamma: Double; delta: Double; Lambda: Double; xi: Double; const Res: TDenseMtxVec); | Johnson bounded (SB) distribution PDF (vectorized). |
| 2 | function JohnsonSBPDF(x: Double; gamma: Double; delta: Double; Lambda: Double; xi: Double): Double; | Johnson bounded (S_B) probability density function (PDF). |
Overload 1: procedure JohnsonSBPDF(const X: TDenseMtxVec; gamma: Double; delta: Double; Lambda: Double; xi: Double; const Res: TDenseMtxVec);
Johnson bounded (SB) distribution PDF (vectorized).
| # | Name | Description |
|---|---|---|
| 1 | X | Defines distribution domain, vector or matrix with real values on closed interval [xi,xi+Lambda]. |
| 2 | gamma | Distribution shape parameter, real value. |
| 3 | delta | Distribution shape parameter, real positive value. |
| 4 | Lambda | Distribution scale parameter, real positive value. |
| 5 | xi | Distribution location parameter, real value. |
| 6 | Res | After calculation stores the PDF calculated from X, agmma, delta, Lambda and xi. Length and Complex properties of Res are adjusted automatically to match Length and Complex properties of X. |
Result: stored in self (calling object)
Overload 2: function JohnsonSBPDF(x: Double; gamma: Double; delta: Double; Lambda: Double; xi: Double): Double;
Johnson bounded (S_B) probability density function (PDF).
| # | Name | Description |
|---|---|---|
| 1 | x | Function domain, real value on the closed interval [xi, xi+Lambda]. |
| 2 | gamma | Distribution shape parameter, real value. |
| 3 | delta | Distribution shape parameter, real positive value (delta>0). |
| 4 | Lambda | Distribution scale parameter, real positive value (Lambda>0). |
| 5 | xi | Distribution location parameter, real value. |
Returns: Double - the Johnson bounded (S_B) PDF for shape parameters gamma, delta, scale Lambda and location xi. Returns NaN if Lambda<=0, delta<=0, or x outside [xi, xi+Lambda].
Remarks:
The Johnson S_B (bounded) density. With z=(x-xi)/lambda in (0,1),
PDF(x | gamma,delta,lambda,xi) = delta/(lambdasqrt(2pi) z(1-z)) exp[-1/2(gamma+deltaln[z/(1-z)])^2] , z=(x-xi)/lambda .
Equivalent to scipy.stats johnsonsb(a=gamma, b=delta, loc=xi, scale=Lambda). Returns NaN for Lambda<=0, delta<=0, or x outside [xi, xi+Lambda].