private void CalcRegressionCoefficients()
{
var transpMatrix = MatrixFunction.TransposeMatrix(dataMatrix);
int parametersCount = dataMatrix[0].Length, measuresCount = dataMatrix.Length;
double[] resultParameter = transpMatrix[resultParameterNumber];
List <double>[] withoutResultParameter = new List <double> [measuresCount];
for (int i = 0; i < measuresCount; i++)
{
withoutResultParameter[i] = new List <double>();
withoutResultParameter[i].Add(1);
for (int j = 0; j < parametersCount; ++j)
{
if (j != resultParameterNumber)
{
withoutResultParameter[i].Add(dataMatrix[i][j]);
}
}
}
xMatrix = withoutResultParameter.Select(o => o.ToArray()).ToArray();
var transpWithoutMatrix = MatrixFunction.TransposeMatrix(xMatrix);
RegressionCoefficients = MatrixFunction.MatrixVectorMultiplication(MatrixFunction.MultiplicateMatrix(MatrixFunction.InverseMatrix(MatrixFunction.MultiplicateMatrix(transpWithoutMatrix, xMatrix)), transpWithoutMatrix), resultParameter);
RegressionCoefficients = RegressionCoefficients.Take(parametersCount).ToArray();
}
private void CalcDispersion()
{
var yWithWave = MatrixFunction.MatrixVectorMultiplication(xMatrix, RegressionCoefficients);
var averageY = yWithWave.Average();
var devivationsYSum = yWithWave.Select(y => Math.Pow(y - averageY, 2)).Sum();
ExplicatedDispersion = devivationsYSum / parametersCount;
ResidualDispersion = devivationsYSum / (measuresCount - parametersCount - 1);
}