Summary
Hypergeometric cumulative distribution function (CDF).Unit
Probabilities
Declaration
Function HypGeometricCDF(x: Integer; M, K, N: Integer): TSample;
Result
the hypergeometric cumulative distribution function (CDF) for value x using the integer parameters M (total number of elements), K (number of elements with a certain trait) and N (number of samples drawn). Value x must be greater of equal than zero, all the parameters M, K N must be greater or equal than zero, M >= N, M >= K, N >= X, K >= x. If not all of these conditions are met, the result is NAN. The hypergeometric cumulative distribution function is defined by the following equation:
The result of HypGeometricCDF is the probability of drawing up to x elements of a possible K in N drawings without replacement from a group of M elements.
Categories
Discrete probabilities| See Also |
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| HypGeometricPDF |
| HypGeometricCDFInv |
Declaration
Procedure HypGeometricCDF(X: TDenseMtxVec; M, K, N: Integer; Res: TDenseMtxVec);
Description
Calculates the HyperGeometric CDF for vector X using the parameters M, K and N. 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 |