Overload List
| # | Signature | Description |
|---|---|---|
| 1 | procedure ChiSquareCDF(const X: TDenseMtxVec; Nu: Integer; const Res: TDenseMtxVec); | Chi-Squared CDF (vectorized). |
| 2 | function ChiSquareCDF(x: Double; Nu: Integer): Double; | Chi-squared cumulative distribution function (CDF). |
Overload 1: procedure ChiSquareCDF(const X: TDenseMtxVec; Nu: Integer; const Res: TDenseMtxVec);
Chi-Squared CDF (vectorized).
| # | Name | Description |
|---|---|---|
| 1 | X | Defines distribution domain, real vector or matrix with positive values. |
| 2 | Nu | Defines distribution degrees of freedom. Nu must be a positive integer value. |
| 3 | Res | After calculation stores the CDF calculated from X, m and b. 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 ChiSquareCDF(x: Double; Nu: Integer): Double;
Chi-squared cumulative distribution function (CDF).
| # | Name | Description |
|---|---|---|
| 1 | x | Function domain, real value >= 0. |
| 2 | Nu | Degrees of freedom, integer > 0. |
Returns: Double - the chi-squared cumulative distribution function (CDF) at x with Nu degrees of freedom. Returns NAN when Nu <= 0.
Remarks:
Computes the chi-squared CDF
CDF(x|nu)=integral _0 ^x (t^((nu-2)/2)* exp(-t/2))/(2^(nu/2)*Gamma (nu /2)) dt = P(nu/2,x/2)
i.e. the regularized lower incomplete gamma function; the implementation computes it as GammaCDF(x, Nu/2, 2). The result is the probability that an observation falls in , lies in and is monotone non-decreasing. Domain: x >= 0, integer nu > 0. If nu <= 0 the result is NAN.