How to calculate the Akaike Information Criterion (AIC) - General Discussion https://nm.dev/forums/nmdev-discussion/how-to-calculate-the-akaike-information-criterion-aic/ NM DEV Discussion Board en-US Fri, 10 Jul 2026 13:17:17 +0000 wpForo 60 How to calculate the Akaike Information Criterion (AIC) https://nm.dev/forums/nmdev-discussion/how-to-calculate-the-akaike-information-criterion-aic/#post-84 Tue, 30 Jul 2024 16:51:25 +0000 In below code I return the "pValue" in the "AugmentedDickeyFuller". 
Now we can use different LagOrder parameters where it is important to choose the "best" possible lagOrder to return as accurate "pValue" as possible.

Normally a good way to determine what LagOrder value to choose is by calculate the
Akaike Information Criterion (AIC).

Where the lowest found AIC would be a good pValue to choose.

I am not sure how to calculate the AIC with the library in this context?
Below line is just pseudo code and that function do not exist but show the intent.

Thank you!

CalculateAIC(statistic, lagOrder)
TrendType P_1 = TrendType.CONSTANT;
ADFDistribution dist = P_1.getDistribution(array_MSFT.Length);

double minAIC = double.MaxValue;
int bestLagOrder = 0;

int maxLagOrder = 20;
for (int lagOrder = 0; lagOrder <= maxLagOrder; lagOrder++) {
    AugmentedDickeyFuller ADFtest = new AugmentedDickeyFuller(array_MSFT, P_1, lagOrder, dist);
    double pValue = ADFtest.pValue();
    double statistic = ADFtest.statistics();

    //How to Implement AIC calculation? (Pseudo Code)
    double aic = CalculateAIC(statistic, lagOrder); 
    
    if (aic < minAIC) {
        minAIC = aic;
        bestLagOrder = lagOrder;
    }
}
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