/// <summary> /// compute the "a" factor of the linear function of design2 /// </summary> /// <param name="design1"></param> /// <param name="design2"></param> /// <returns></returns> public static double a(NuGenStatistics design1, NuGenStatistics design2) { try { return(cov(design1, design2) / (Math.Pow(design2.s(), 2))); } catch (Exception) { return(double.NaN); } }
/// <summary> /// compute the "a" factor of the linear function of design /// </summary> /// <param name="design"></param> /// <returns></returns> public double a(NuGenStatistics design) { try { return(this.cov(design) / (Math.Pow(design.s(), 2))); } catch (Exception) { return(double.NaN); } }
/// <summary> /// compute the correlation coefficient /// </summary> /// <param name="design1"></param> /// <param name="design2"></param> /// <returns></returns> public static double r(NuGenStatistics design1, NuGenStatistics design2) { try { return(cov(design1, design2) / (design1.s() * design2.s())); } catch (Exception) { return(double.NaN); } }
/// <summary> /// compute the correlation coefficient /// </summary> /// <param name="design"></param> /// <returns></returns> public double r(NuGenStatistics design) { try { return(this.cov(design) / (this.s() * design.s())); } catch (Exception) { return(double.NaN); } }
/// <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 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 "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 "a" factor of the linear function of design2 /// </summary> /// <param name="design1"></param> /// <param name="design2"></param> /// <returns></returns> public static double a(NuGenStatistics design1, NuGenStatistics design2) { try { return cov(design1, design2) / (Math.Pow(design2.s(), 2)); } catch (Exception) { return double.NaN; } }
/// <summary> /// compute the "a" factor of the linear function of design /// </summary> /// <param name="design"></param> /// <returns></returns> public double a(NuGenStatistics design) { try { return this.cov(design) / (Math.Pow(design.s(), 2)); } catch (Exception) { return double.NaN; } }
/// <summary> /// compute the correlation coefficient /// </summary> /// <param name="design1"></param> /// <param name="design2"></param> /// <returns></returns> public static double r(NuGenStatistics design1, NuGenStatistics design2) { try { return cov(design1, design2) / (design1.s() * design2.s()); } catch (Exception) { return double.NaN; } }
/// <summary> /// compute the correlation coefficient /// </summary> /// <param name="design"></param> /// <returns></returns> public double r(NuGenStatistics design) { try { return this.cov(design) / (this.s() * design.s()); } catch (Exception) { return double.NaN; } }
/// <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 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; } }
/// <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 "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()); }