private SortedDictionary <double, double> GetMeanFrequencies(int sampleSize, int numberOfSamples, int minValue, int maxValue)
{
var clt = new CentralLimitTheorem(sampleSize, numberOfSamples, minValue, maxValue);
SortedDictionary <double, double> meanFrequencies = clt.GetFrequencyOfMeans();
return(meanFrequencies);
}
public void GetMeanSampleTest()
{
int minNumber = 1;
int maxNumber = 6;
int sampleSize = 4;
int numberOfSamples = 1000;
var clt = new CentralLimitTheorem(sampleSize, numberOfSamples, minNumber, maxNumber);
double[] samples = clt.GetMeanSamples();
Assert.Equals(numberOfSamples, samples.Length);
}
public void GetRandomNumberTest()
{
int minNumber = 1;
int maxNumber = 6;
int sampleSize = 4;
int numberOfSamples = 1000;
var clt = new CentralLimitTheorem(sampleSize, numberOfSamples, minNumber, maxNumber);
double randomNumber = clt.GetRandomNumber();
Assert.Greater(randomNumber, minNumber);
Assert.Less(randomNumber, maxNumber);
}
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}";
}
