2.1.11.10 ocmath_AIC

1 Description
2 Syntax
3 Parameters
4 Return
5 Examples
6 Remark
7 See Also
8 Header to Include
9 Reference

Description

Function to compute Akaike's Information Criterion (AIC)

Syntax

double ocmath_AIC( const int nSize, const int nParam, const double dSSE, int * iFault = NULL )

Parameters

nSize: [input] the number of data points
nParam: [input] the number of parameters fit by the regression.
dSSE: [input] the sum of square of residuals
iFault: [output] error code returned. is equal to STATS_NO_ERROR on successful exit

Return

Value of Akaike's Information Criterion

Examples

Before compile this example please run run.LoadOC(Originlab\stats_utils.c, 16); in Command Window to load all depentence source files.

#include <stats_utils.h>

void ocmath_AIC_ex1()
{
    vector vX={3,4,4.5,5,5.5, 6};
    vector vY={4,3,3.5,3, 4.2,5};
    
    vector vW;                        
    vW.SetSize(vX.GetSize());
    vW = 1;

    //parameters required by stats_polynomial_fit
    LROptions sLROptions;    
    RegStats sRegStats;    
    RegANOVA sRegANOVA;
    matrix mCov,mCorr;
    FitParameter sFitParameter[3];  
    
    sLROptions.Confidence = 0.95;    
    
    int nOrder = 2;        
    
    int nParam;
    nParam = (sLROptions.FixIntercept) ? nOrder : nOrder + 1;
    
            
    int nRet = stats_polynomial_fit(vX,vY,vW,nOrder,sLROptions,sFitParameter,nParam,&sRegStats,&sRegANOVA,mCov,mCorr);
    if (nRet != STATS_NO_ERROR)
        return;
    
    int ifault;
    double dAIC = ocmath_AIC(vX.GetSize(), nParam, sRegStats.SSR, &ifault);//dAIC = 31.23                
}