public ForecastingModel calculateTrend()
        {
            this.Trend = new List <double>();
            List <Tuple <double, double> > LeastSquaresSerie = new List <Tuple <double, double> >();

            for (int i = 0; i < this.SeasonallyAdjustedData.Count; i++)
            {
                LeastSquaresSerie.Add(new Tuple <double, double>(i + 1, this.SeasonallyAdjustedData.ElementAt(i)));
            }
            //y = mx + b
            LeastSquaresParameters = StatisticsModel.LeastSquares(LeastSquaresSerie);
            for (int i = 0; i < this.Serie.Count; i++)
            {
                this.Trend.Add((i + 1) * LeastSquaresParameters.M + LeastSquaresParameters.B);
            }
            return(this);
        }
        public ForecastingModel findSeasonality(Boolean isPearson)
        {
            double[] arrSource;
            double[] arrSource2;

            if (isPearson)
            {
                arrSource = this.Serie.ToArray();
            }
            else
            {
                arrSource2 = this.Serie.ToArray();
                arrSource  = new double[arrSource2.Length - 1];
                for (int i = 0; i < arrSource2.Length; i++)
                {
                    arrSource2[i] = Math.Log(arrSource2[i]);
                    if (i >= 1)
                    {
                        arrSource[i - 1] = arrSource2[i] - arrSource2[i - 1];
                    }
                }
            }
            double pearson;
            double max = -1;

            for (int shifts = 1; shifts <= 19; shifts++)
            {
                double[] arr = new double[arrSource.Length];
                Array.Copy(arrSource, 0, arr, shifts, arr.Length - shifts);
                if (isPearson)
                {
                    pearson = StatisticsModel.Pearson(arrSource, arr);
                }
                else
                {
                    pearson = RankCorrelation.ComputeRankCorrelation(arrSource, arr);
                }
                if (pearson > max)
                {
                    seasonalityRate = shifts;
                    max             = pearson;
                }
            }
            Console.WriteLine("pearson: " + max + " seasonalityRate: " + seasonalityRate);
            return(this);
        }
Пример #3
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        public ForecastingModel findSeasonality()
        {
            double[] arrSource = this.Serie.ToArray();
            double   pearson;
            double   max = -1;

            for (int shifts = 1; shifts <= 20; shifts++)
            {
                double[] arr = new double[arrSource.Length];
                Array.Copy(arrSource, 0, arr, shifts, arr.Length - shifts);
                pearson = StatisticsModel.Pearson(arrSource, arr);

                if (pearson > max)
                {
                    seasonalityRate = shifts;
                    max             = pearson;
                }
            }
            Console.WriteLine("pearson: " + max + " seasonalityRate: " + seasonalityRate);
            return(this);
        }