Probabilities.LogNormalCDF Method

Overload List

#SignatureDescription
1procedure LogNormalCDF(const X: TDenseMtxVec; Mu: Double; sigma: Double; const Res: TDenseMtxVec);Log-Normal CDF (vectorized).
2function LogNormalCDF(x: Double; Mu: Double; sigma: Double): Double;Log-normal cumulative distribution function (CDF).

Overload 1: procedure LogNormalCDF(const X: TDenseMtxVec; Mu: Double; sigma: Double; const Res: TDenseMtxVec);

Log-Normal CDF (vectorized).

#NameDescription
1XDefines distribution domain, real vector or matrix with positive real values or zeros.
2MuDistribution location parameter, real value.
3sigmaDistribution scale parameter, real positive value.
4ResAfter calculation stores the CDF calculated from X, Mu and sigma. 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 LogNormalCDF(x: Double; Mu: Double; sigma: Double): Double;

Log-normal cumulative distribution function (CDF).

#NameDescription
1xFunction domain, real value > 0.
2MuLocation parameter: mean of ln(x), any real value.
3sigmaScale parameter: standard deviation of ln(x), real value > 0.

Returns: Double - the log-normal cumulative distribution function (CDF) at x. Returns NAN when sigma <= 0 or x <= 0.

Remarks:

Computes the log-normal CDF

CDF(x| mu,sigma )= 1/2[ 1+erf( (ln x - mu)/(sqrt(2) sigma))]

(clamped to at most 1). Domain: x > 0, sigma > 0; the result lies in [0,1][0,1] and is monotone non-decreasing. If x <= 0 or sigma <= 0 the result is NAN.

See Also: Probabilities.LogNormalPDF, Probabilities.LogNormalCDFInv