/// <summary>
/// 변량으로부터 대표적 통계 값들을 계산합니다.
/// </summary>
/// <param name="source"></param>
private void Compute(IEnumerable <double?> source)
{
Mean = source.Mean();
double variance = 0;
double correction = 0;
double skewness = 0;
double kurtosis = 0;
double minimum = Double.PositiveInfinity;
double maximum = Double.NegativeInfinity;
int n = 0;
foreach (var xi in source)
{
if (xi.HasValue)
{
double diff = xi.Value - Mean;
double tmp = diff * diff;
correction += diff;
variance += tmp;
tmp *= diff;
skewness += tmp;
tmp *= diff;
kurtosis += tmp;
if (minimum > xi)
{
minimum = xi.Value;
}
if (maximum < xi)
{
maximum = xi.Value;
}
n++;
}
}
Count = n;
if (n > 0)
{
Minimum = minimum;
Maximum = maximum;
Variance = (variance - (correction * correction / n)) / (n - 1);
StandardDeviation = System.Math.Sqrt(Variance);
if (Variance.ApproximateEqual(0.0) == false)
{
if (n > 2)
{
Skewness = (double)n / ((n - 1) * (n - 2)) * (skewness / (Variance * StandardDeviation));
}
if (n > 3)
{
Kurtosis = (((double)n * (n + 1))
/ ((n - 1) * (n - 2) * (n - 3))
* (kurtosis / (Variance * Variance)))
- ((3.0 * (n - 1) * (n - 1)) / ((n - 2) * (n - 3)));
}
}
}
}
/// <summary>
/// 변량으로부터 대표적 통계 값들을 계산합니다.
/// </summary>
/// <param name="source"></param>
private void ComputeHighAccuracy(IEnumerable <double> source)
{
Mean = source.Mean();
decimal mean = (decimal)Mean;
decimal variance = 0;
decimal correction = 0;
decimal skewness = 0;
decimal kurtosis = 0;
decimal minimum = Decimal.MaxValue;
decimal maximum = Decimal.MinValue;
int n = 0;
foreach (decimal xi in source)
{
decimal diff = xi - mean;
decimal tmp = diff * diff;
correction += diff;
variance += tmp;
tmp *= diff;
skewness += tmp;
tmp *= diff;
kurtosis += tmp;
if (minimum > xi)
{
minimum = xi;
}
if (maximum < xi)
{
maximum = xi;
}
n++;
}
Count = n;
Minimum = (double)minimum;
Maximum = (double)maximum;
Variance = (double)(variance - (correction * correction / n)) / (n - 1);
StandardDeviation = Math.Sqrt(Variance);
if (Variance.ApproximateEqual(0.0) == false)
{
if (n > 2)
{
Skewness = (double)n / ((n - 1) * (n - 2)) * ((double)skewness / (Variance * StandardDeviation));
}
if (n > 3)
{
Kurtosis = (((double)n * (n + 1))
/ ((n - 1) * (n - 2) * (n - 3))
* ((double)kurtosis / (Variance * Variance)))
- ((3.0 * (n - 1) * (n - 1)) / ((n - 2) * (n - 3)));
}
}
}
