org.jfree.data.statistics
Class Regression
public abstract
class
Regression
extends Object
A utility class for fitting regression curves to data.
Method Summary |
static double[] | getOLSRegression(double[][] data)
Returns the parameters 'a' and 'b' for an equation y = a + bx, fitted to
the data using ordinary least squares regression. |
static double[] | getOLSRegression(XYDataset data, int series)
Returns the parameters 'a' and 'b' for an equation y = a + bx, fitted to
the data using ordinary least squares regression. |
static double[] | getPowerRegression(double[][] data)
Returns the parameters 'a' and 'b' for an equation y = ax^b, fitted to
the data using a power regression equation. |
static double[] | getPowerRegression(XYDataset data, int series)
Returns the parameters 'a' and 'b' for an equation y = ax^b, fitted to
the data using a power regression equation. |
public static double[] getOLSRegression(double[][] data)
Returns the parameters 'a' and 'b' for an equation y = a + bx, fitted to
the data using ordinary least squares regression. The result is
returned as a double[], where result[0] --> a, and result[1] --> b.
Parameters: data the data.
Returns: The parameters.
public static double[] getOLSRegression(
XYDataset data, int series)
Returns the parameters 'a' and 'b' for an equation y = a + bx, fitted to
the data using ordinary least squares regression. The result is returned
as a double[], where result[0] --> a, and result[1] --> b.
Parameters: data the data. series the series (zero-based index).
Returns: The parameters.
public static double[] getPowerRegression(double[][] data)
Returns the parameters 'a' and 'b' for an equation y = ax^b, fitted to
the data using a power regression equation. The result is returned as
an array, where double[0] --> a, and double[1] --> b.
Parameters: data the data.
Returns: The parameters.
public static double[] getPowerRegression(
XYDataset data, int series)
Returns the parameters 'a' and 'b' for an equation y = ax^b, fitted to
the data using a power regression equation. The result is returned as
an array, where double[0] --> a, and double[1] --> b.
Parameters: data the data. series the series to fit the regression line against.
Returns: The parameters.
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