Overload List
| # | Signature | Description |
|---|---|---|
| 1 | procedure PoissonPDF(const X: TMtxVecInt; Lambda: Double; const Res: TDenseMtxVec); | Poisson distribution PDF (vectorized). |
| 2 | function PoissonPDF(x: Integer; Lambda: Double): Double; | Poisson probability mass function (PMF). |
Overload 1: procedure PoissonPDF(const X: TMtxVecInt; Lambda: Double; const Res: TDenseMtxVec);
Poisson distribution PDF (vectorized).
| # | Name | Description |
|---|---|---|
| 1 | X | Distribution domain, positive integer values or zeros. |
| 2 | Lambda | Distribution parameter, real positive value. |
| 3 | Res | After calculation stores the PDF calculated from X, alpha and beta. 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 PoissonPDF(x: Integer; Lambda: Double): Double;
Poisson probability mass function (PMF).
| # | Name | Description |
|---|---|---|
| 1 | x | Function domain, non-negative integer. |
| 2 | Lambda | Rate parameter, real positive value. |
Returns: Double - the Poisson probability mass function (PMF) at x using parameter Lambda. Returns NAN when Lambda<=0.
Remarks:
Computes the Poisson PMF, the probability of x events when the mean rate is Lambda:
PMF(x|lambda)=e^(-lambda) lambda^x/x!, x=0,1,2,...
Domain: x >= 0, lambda>0. For lambda <= 0 the result is NaN.
The Poisson distribution approximates the binomial when N is large and p small (good for N >= 20, p <= 0.05; very good for N >= 100, Np <= 10), so it is often called the distribution of "rare" events.