LogNormalFit Routines

Summary

Calculate parameters for log-normaly distributed values.

Declaration

Procedure LogNormalFit(X: TVec; out mu, sigma: TSample; out PCIMu, PCISigma: TTwoElmReal; alpha: TSample = 0.05);

Parameter	Description
X	Stores data which is assumed to be log-normaly distributed.
Mu,Sigma	Return log-normal distribution parameter estimators.
PCIMu,PCISigma	Mu and Sigma (1-Alpha)*100 percent confidence intervals.
Alpha	Confidence interval percentage.

Description

Calculate parameters for log-normally distributed values.

See Also
NormalFit
RandomLogNormal

Example 1

The following example generates 100 random log-normally distributed values and then uses NormalFit routine to extract used Mu and Sigma parameters:

  Uses StatRandom, Statistics, MtxExpr;
  procecure Example;
    var Data :Vector;
    mu,sigma: TSample;
    MuCI, SigmaCI : TTwoElmReal;
  begin
    Data.Size(100);
    RandomLogNormal(3,0.2,Data);
    LogNormalFit(Data,mu,sigma,MuCI,SigmaCI);
    // mu approx 3.0
    // sigma approx 0.2
  end;

  #include "StatRandom.hpp"
  #include "MtxVecCpp.h"
  #include "Statistics.hpp"
  void __fastcall Example();
  {
    Vector Data;
    Data->Size(100,false);
    RandomLogNormal(3,0.2,Data);
    double mu, sigma;
    double MuCI[2];
    double SigmaCI[2];
    LogNormalFit(Data,mu,sigma,MuCI,SigmaCI,0.05);
    // mu approx 3.0
    // sigma approx 0.2
  }

  using Dew.Math;
  using Dew.Stats;
  using Dew.Stats.Units;
  namespace Dew.Examples;
  {
    private void Example()
    {
      Vector Data = new Vector(0);
      Data.Size(100,false);
      StatRandom.RandomLogNormal(3,0.2,Data);
      double mu, sigma;
      double[2] MuCI;
      double[2] SigmaCI;
      Statistics.LogNormalFit(Data,out mu,out sigma,out MuCI,out SigmaCI,0.05);
      // mu approx 3.0
      // sigma approx 0.2
    }
  }

Declaration

Procedure LogNormalFit(X: TVec; out mu, sigma: TSample);