Overload List
| # | Signature | Description |
|---|---|---|
| 1 | procedure NormalCDFInv(const P: TDenseMtxVec; Mu: Double; sigma: Double; const Res: TDenseMtxVec); | Normal distribution PPF (vectorized). |
| 2 | function NormalCDFInv(p: Double; Mu: Double; sigma: Double): Double; | Normal distribution inverse CDF (quantile / point percent function, PPF). |
Overload 1: procedure NormalCDFInv(const P: TDenseMtxVec; Mu: Double; sigma: Double; const Res: TDenseMtxVec);
Normal distribution PPF (vectorized).
| # | Name | Description |
|---|---|---|
| 1 | P | Defines distribution probabilities, real vector or matrix with values within closed interval [0,1]. |
| 2 | Mu | Distribution location parameter, real value. |
| 3 | sigma | Distribution scale parameter, real positive value. |
| 4 | Res | After calculation stores the PPF calculated from P, Mu and sigma. Length and Complex properties of Res are adjusted automatically to match Length and Complex properties of P. |
Result: stored in self (calling object)
Overload 2: function NormalCDFInv(p: Double; Mu: Double; sigma: Double): Double;
Normal distribution inverse CDF (quantile / point percent function, PPF).
| # | Name | Description |
|---|---|---|
| 1 | p | Probability, real value on the closed interval [0,1]. |
| 2 | Mu | Distribution location parameter (mean), any real value. |
| 3 | sigma | Distribution scale parameter (standard deviation), real value > 0. |
Returns: Double - the value x such that NormalCDF(x,Mu,sigma)=p. Returns NAN when p < 0, p > 1 or sigma <= 0; returns +INF at both p=0 and p=1.
Computes the inverse of the normal CDF (the quantile function)
inverse CDF(p| mu,sigma ) = F^(-1)(p| mu,sigma) = mu + sigma Phi^(-1)(p) , p(x)=CDF(x|mu,sigma)
where Phi^(-1) is the standard-normal quantile. The implementation evaluates Phi^(-1) with the AS 241 (PPND16) rational approximation (accurate to about 1 part in 10^(16)). Domain: p in [0,1], sigma > 0. Behaviour: for interior p in (0,1) the finite quantile is returned; at the boundaries p=0 and p=1 the result is +inf; if p not in [0,1] or sigma <= 0 the result is NAN.