/// <summary>
/// compute the "b" factor of the linear function of design2
/// </summary>
/// <param name="design1"></param>
/// <param name="design2"></param>
/// <returns></returns>
public static double b(NuGenStatistics design1, NuGenStatistics design2)
{
return design1.mean() - a(design1, design2) * design2.mean();
}
/// <summary>
/// compute the covariance
/// </summary>
/// <param name="s1"></param>
/// <param name="s2"></param>
/// <returns></returns>
public static double cov(NuGenStatistics s1, NuGenStatistics s2)
{
try
{
if (s1.length() != s2.length()) return double.NaN;
int len = s1.length();
double sum_mul = 0;
for (int i = 0; i <= len - 1; i++)
sum_mul += (s1.list[i] * s2.list[i]);
return (sum_mul - len * s1.mean() * s2.mean()) / (len - 1);
}
catch (Exception)
{
return double.NaN;
}
}
/// <summary>
/// compute the "b" factor of the linear function of design
/// </summary>
/// <param name="design"></param>
/// <returns></returns>
public double b(NuGenStatistics design)
{
return this.mean() - this.a(design) * design.mean();
}
/// <summary>
/// compute the covariance
/// </summary>
/// <param name="s"></param>
/// <returns></returns>
public double cov(NuGenStatistics s)
{
try
{
if (this.length() != s.length()) return double.NaN;
int len = this.length();
double sum_mul = 0;
for (int i = 0; i <= len - 1; i++)
sum_mul += (this.list[i] * s.list[i]);
return (sum_mul - len * this.mean() * s.mean()) / (len - 1);
}
catch (Exception)
{
return double.NaN;
}
}