void CalcEstimates()
{
int n = XMat.GetLength(0), k = XMat.GetLength(1) - 1;
// коэффициенты, необходимые далее
double Qost = CalculatedY.Zip(RealY, (a, b) => (a - b) * (a - b)).Sum();
double QR = Matrix.ScalarMul(CalculatedY, CalculatedY);
S2 = Qost / (n - k - 1);
// точечная оценка регресии
F = (QR / (k + 1)) / (Qost / (n - k - 1));
FCritical = FisherTable.GetValue(k + 1, n - k - 1);
// точечная оценка параметров регрессии
double[] Sb = Enumerable.Range(0, k + 1)
.Select(j => Math.Sqrt(S2 * XTXInvMat[j, j]))
.ToArray();
CoeffsT = Coeffs.Zip(Sb, (a, b) => Math.Abs(a / b)).ToArray();
TCritical = StudentTable.GetValue(n - k - 1);
// интервальная оценка регрессии
IntervalEstimates = new double[n];
for (int i = 0; i < n; i++)
{
var x0 = Enumerable.Range(0, XMat.GetLength(1)).Select(j => XMat[i, j]).ToArray();
IntervalEstimates[i] = TCritical *
Math.Sqrt(S2 * Matrix.ScalarMul(x0, Matrix.MulVect(XTXInvMat, x0)));
}
// интервальная оценка параметров регрессии
CoeffsIntervalEstimates = Sb.Select(s => Math.Abs(s * TCritical)).ToArray();
ApproximationError = RealY.Zip(CalculatedY, (a, b) => Math.Abs((a - b) / a)).Sum() / RealY.Length;
}
public DescriptiveStatistics(string name, double[] vals)
{
ParameterName = name;
Sum = vals.Sum();
Count = vals.Length;
Average = Sum / Count;
Dispersion = vals.Sum(e => Math.Pow(e - Average, 2)) / (Count - 1);
StandardDeviation = Math.Sqrt(Dispersion);
StandardError = StandardDeviation / Math.Sqrt(Count);
Min = vals.Min();
Max = vals.Max();
Interval = Max - Min;
Median = GetMedian(vals);
Mode = GetMode(vals);
Excess = GetExcess(vals, Average, StandardDeviation);
Asymmetry = GetAsymmetry(vals, Average, StandardDeviation);
double t = StudentTable.GetValue(Count - 1);
MarginalError = t * StandardError;
double neededError = 0.01;
RequiredSize = (int)(t * t * Dispersion / (neededError * neededError));
MarginalErrorWithRequiredSize = t * StandardDeviation / Math.Sqrt(RequiredSize);
}
public Correlations(Table tbl, DescriptiveStatistics[] dstats)
{
CalcCorrMatrix(tbl, dstats);
CalcPartialCorrMatrix(tbl);
CalcMultipleCorrelation(tbl);
MultipleDeterminationCoeffs = MultipleCorreletaionCoeffs.Select(a => a * a).ToArray();
CalcMultipleSignificance(tbl);
CalcSignificanceMatrix(tbl);
Critical = StudentTable.GetValue(tbl.RowsCount - 2);
}