Java org.apache.commons.math.stat.regression SimpleRegression fields, constructors, methods, implement or subclass

Example usage for Java org.apache.commons.math.stat.regression SimpleRegression fields, constructors, methods, implement or subclass

Introduction

In this page you can find the methods, fields and constructors for org.apache.commons.math.stat.regression SimpleRegression.

The text is from its open source code.

org.apache.commons.math.stat.regression.SimpleRegression has subclasses.
Click this link to see all its subclasses.

	SimpleRegression() Create an empty SimpleRegression instance

void	addData(double x, double y) Adds the observation (x,y) to the regression data set.
void	addData(double[][] data) Adds the observations represented by the elements in `data`.
void	clear() Clears all data from the model.
double	getIntercept() Returns the intercept of the estimated regression line.
double	getMeanSquareError() Returns the sum of squared errors divided by the degrees of freedom, usually abbreviated MSE.
long	getN() Returns the number of observations that have been added to the model.
double	getR() Returns Pearson's product moment correlation coefficient, usually denoted r.
double	getRSquare() Returns the coefficient of determination, usually denoted r-square.
double	getSlope() Returns the slope of the estimated regression line.
double	getSlopeConfidenceInterval() Returns the half-width of a 95% confidence interval for the slope estimate.
double	getSlopeStdErr() Returns the standard error of the slope estimate, usually denoted s(b1).
double	predict(double x) Returns the "predicted" `y` value associated with the supplied `x` value, based on the data that has been added to the model when this method is activated.