The methods of the Correlation class are listed below. For a complete list of Correlation class members, see the Correlation Members topic.
Public Instance Methods
 CoefficientOfDetermination |
Calculates the coefficient of determination (denoted R-squared or R2) for the set of pairs of points: (xValues[0], yValues[0]), (xValues[1], yValues[1]),..., (xValues[n], yValues[n]).
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| Covariance | Evaluates the covariance the two (ordered) discrete variables. |
| CovarianceMatrixRealized | Calculates the covariance matrix for a collection of (ordered) discrete variables. |
| Equals (inherited from Object) | Determines whether the specified Object is equal to the current Object. |
| EstimateX |
Estimates the value of the X variable when the Y variable is known using the regression line of X on Y, which can be evaluated using LeastSquaresRegressionLineX.
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| EstimateY |
Estimates the value of the Y variable when the X variable is known using the regression line of Y on X, which can be evaluated using LeastSquaresRegressionLineY.
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| GetHashCode (inherited from Object) | Serves as a hash function for a particular type, suitable for use in hashing algorithms and data structures like a hash table. |
| GetType (inherited from Object) | Gets the Type of the current instance. |
| KendallCorrelationCoefficient |
Calculates Kendall's correlation coefficient of a set of pairs of points: (xValues[0], yValues[0]), (xValues[1], yValues[1]),... ,(xValues[n], yValues[n]).
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| LeastSquaresRegressionLineX |
Constructs the regression line of X on Y using the method of least squares, for the set of pairs of points: (xValues[0], yValues[0]), (xValues[1], yValues[1]),... , (xValues[n], yValues[n]).
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| LeastSquaresRegressionLineY |
Constructs the regression line of Y on X using the method of least squares, for the set of pairs of points: (xValues[0], yValues[0]), (xValues[1], yValues[1]),... , (xValues[n], yValues[n]).
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| Mean | Calculates the arithmetic mean of the a set of doubles. |
| PearsonCorrelation |
Calculates Pearson's correlation coefficient of a set of pairs of points: (xValues[0], yValues[0]), (xValues[1], yValues[1]),... , (xValues[n], yValues[n]).
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| Residuals |
Determines the residual for a given pair of points from the set of pairs of points: (xValues[0], yValues[0]), (xValues[1], yValues[1]),... , (xValues[n], yValues[n]); in accordance with the regression line constructed using LeastSquaresRegressionLineX.
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| ResidualsAverage |
Determines the arithmetic average of the residuals for all pairs of points from the set of pairs of points: (xValues[0], yValues[0]), (xValues[1], yValues[1]),... , (xValues[n], yValues[n]); in accordance with the regression line constructed using LeastSquaresRegressionLineX.
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| SampleVariance | Calculates the sample variance of a given numerical data set. |
| Significance |
Calculates the significance test of a Correlation coefficient (either Pearson's or Spearman's) for a set of pairs of points: (xValues[0], yValues[0]), (xValues[1], yValues[1]),... , (xValues[n], yValues[n]).
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| SpearmanRankTest |
Calculates Spearson's Rank correlation coefficient of a set of pairs of points: (xValues[0], yValues[0]), (xValues[1], yValues[1]),... , (xValues[n], yValues[n]).
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| ToString (inherited from Object) | Returns a String that represents the current Object. |
Protected Instance Methods
 Finalize (inherited from Object) | Allows an Object to attempt to free resources and perform other cleanup operations before the Object is reclaimed by garbage collection. |
| MemberwiseClone (inherited from Object) | Creates a shallow copy of the current Object. |
See Also
Correlation Class | Correlation Namespace