private void CalculateBoxAndMahlerMethod()
{
BoxAndMahlerMethod rnd = new BoxAndMahlerMethod();
double[] randomValues = rnd.Random(sampleSize, m, dpow2);
double step = (double)rightXBorder / intervalsCount;
ConstructBoxAndMahlerfrequencies(randomValues, step);
ConstructBoxAndMahlerDistributionFunc(randomValues, step);
double mx = StatisticData.CalculateMathExpectation(randomValues);
double dx = StatisticData.CalculateDispersoin(randomValues, mx);
label3.Text = "M(X) = " + mx + " D(X) = " + dx;
//вычисление критерия Колмагорова
double kolmogorovCriterionLambdaValue = KolmogorovCriterion.GetLambda(randomValues, sampleSize);
double kolmogorovCriterionValue = KolmogorovCriterion.Calculate(randomValues, sampleSize);
label4.Text = $"Лямбда по критерию Колмогорова равна {Math.Round(kolmogorovCriterionLambdaValue, 3)}; \nОценка генератора " +
$"случайных чисел равна {kolmogorovCriterionValue}";
}
private void CalculateCentralLimitTheorem()
{
CentralLimitTheorem rnd = new CentralLimitTheorem();
double[] randomValues = rnd.Random(sampleSize, m, dpow2);
double step = (double)rightXBorder / intervalsCount;
ConstructFrequencyHistogram(randomValues, step);
ConstructStatisticalDistributionFunction(randomValues, step);
double mx = StatisticData.CalculateMathExpectation(randomValues);
double dx = StatisticData.CalculateDispersoin(randomValues, mx);
label1.Text = "M(X) = " + mx + " D(X) = " + dx;
//вычисление критерия Колмагорова
double kolmogorovCriterionLambdaValue = KolmogorovCriterion.GetLambda(randomValues, sampleSize);
double kolmogorovCriterionValue = KolmogorovCriterion.Calculate(randomValues, sampleSize);
label2.Text = $"Лямбда по критерию Колмогорова равна {Math.Round(kolmogorovCriterionLambdaValue, 3)}; \nОценка генератора " +
$"случайных чисел равна {kolmogorovCriterionValue}";
}