public Mean Copy()
{
Mean result = new Mean();
Copy(this, result);
return(result);
}
public double GetCovarianve(double[] xArray, double[] yArray, bool biasCorrected) //throws MathIllegalArgumentException
{
Mean mean = new Mean();
double result = 0.0D;
int length = xArray.Length;
if (length != yArray.Length)
{
// throw new MathIllegalArgumentException(LocalizedFormats.DIMENSIONS_MISMATCH_SIMPLE, new Object[] { Integer.valueOf(length), Integer.valueOf(yArray.length)
}
if (length < 2)
{
//throw new MathIllegalArgumentException(LocalizedFormats.INSUFFICIENT_OBSERVED_POINTS_IN_SAMPLE, new Object[] { Integer.valueOf(length), Integer.valueOf(2) });
}
double xMean = mean.Evaluate(xArray);
double yMean = mean.Evaluate(yArray);
for (int i = 0; i < length; i++)
{
double xDev = xArray[i] - xMean;
double yDev = yArray[i] - yMean;
result += (xDev * yDev - result) / (i + 1);
}
return(biasCorrected ? result * (length / (length - 1)) : result);
}
public static void Copy(Mean source, Mean dest)
{
MathUtils.checkNotNull(source);
MathUtils.checkNotNull(dest);
dest.SetData(source.GetDataRef());
dest.incMoment = source.incMoment;
dest.moment = source.moment.Copy();
}
public double Evaluate(double[] values, int begin, int length) //throws MathIllegalArgumentException
{
double var = Double.NaN;
if (Test(values, begin, length))
{
Clear();
if (length == 1)
{
var = 0.0D;
}
else if (length > 1)
{
Mean mean = new Mean();
double m = mean.Evaluate(values, begin, length);
var = Evaluate(values, m, begin, length);
}
}
return(var);
}
public Mean(Mean original)
{
Copy(original, this);
}