Probabilities.FCDF Method

Overload List

#SignatureDescription
1procedure FCDF(const X: TDenseMtxVec; Nu1: Integer; Nu2: Integer; const Res: TDenseMtxVec);Fisher(F) CDF (vectorized).
2function FCDF(x: Double; Nu1: Integer; Nu2: Integer): Double;F (Fisher-Snedecor) cumulative distribution function (CDF).

Overload 1: procedure FCDF(const X: TDenseMtxVec; Nu1: Integer; Nu2: Integer; const Res: TDenseMtxVec);

Fisher(F) CDF (vectorized).

#NameDescription
1XDefines distribution domain, real vector or matrix with positive real values or zeros.
2Nu1Defines distribution degrees of freedom. Nu1 must be a positive integer.
3Nu2Defines distribution degrees of freedom. Nu2 must be a positive integer.
4ResAfter calculation stores the CDF calculated from X, Nu1 and Nu2. 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 FCDF(x: Double; Nu1: Integer; Nu2: Integer): Double;

F (Fisher-Snedecor) cumulative distribution function (CDF).

#NameDescription
1xDistribution domain, real value >= 0.
2Nu1Numerator degrees of freedom, integer > 0.
3Nu2Denominator degrees of freedom, integer > 0.

Returns: Double - the F cumulative distribution function (CDF) at x for degrees of freedom Nu1 and Nu2. Returns NAN when Nu1 <= 0, Nu2 <= 0 or x < 0.

Remarks:

Computes the F CDF via the regularized incomplete beta function. The implementation uses the identity

CDF(x|nu _1 , nu _2 )= 1 - I_(nu_2/(nu_2+nu_1 x))(nu_2/2,nu_1/2)

where I_z(a,b) is the regularized incomplete beta function. The result is the probability that an observation falls in [0,x][0,x], lies in [0,1][0,1] and is monotone non-decreasing. Domain: x >= 0, integer nu_1,nu_2 > 0. If either parameter is <= 0 or x < 0 the result is NAN.

See Also: Probabilities.FPDF, Probabilities.FCDFInv