public static (double[], double[]) Calculate(double[] Y, decimal alpha, decimal beta, decimal gamma, int p, int s)
{
WintersHelper.Init(Y, s, alpha, beta, gamma);
(double[], double[])calculated = WintersHelper.Calculate(p, s);
double mad = MeanAbsoluteDeviation.Calculation(Y, calculated.Item1);
if (!double.IsNaN(mad) && mad < SmallestError)
{
SmallestError = mad;
BestAlpha = alpha;
BestBeta = beta;
BestGamma = gamma;
BestResult = calculated;
}
return(calculated);
}
public static (double[], double[]) Calculate(
double[] inputValue, int amountOfPeriodsToCalculate, decimal dataSmoothingFactor, decimal trendSmoothingFactor)
{
SmallestError = double.MaxValue;
double initalSmoothedValue = inputValue[0];
(List <double>, List <double>)auxValues = HoltHelper.CalculteSmoothedAndTrendValues(
inputValue.Select(d => (decimal)d).ToList(), dataSmoothingFactor, trendSmoothingFactor, new List <decimal>(), new List <decimal>());
//Calculate forecast for periods which already have real values
double[] full =
HoltHelper.Calculate(auxValues.Item1, auxValues.Item2, inputValue.Take(1).ToList()).ToArray <double>();
(double[], double[])calculated = ArrayBased.Split(full, amountOfPeriodsToCalculate);
double mad = MeanAbsoluteDeviation.Calculation(inputValue, calculated.Item1);
if (!double.IsNaN(mad) && mad < SmallestError)
{
SmallestError = mad;
BestDataSmoothing = (double)dataSmoothingFactor;
BestTrendSmoothing = (double)trendSmoothingFactor;
BestResult = calculated;
}
return(calculated);
}
