Example usage for org.apache.commons.math.stat.regression SimpleRegression getRSquare

Introduction

In this page you can find the example usage for org.apache.commons.math.stat.regression SimpleRegression getRSquare.

Prototype

public double getRSquare() 

Source Link

Document

Returns the <a href="http://www.xycoon.com/coefficient1.htm"> coefficient of determination</a>, usually denoted r-square.

Usage

From source file:com.discursive.jccook.math.SimpleRegressionExample.java

public static void main(String[] args) throws MathException {

    SimpleRegression sr = new SimpleRegression();

    // Add data points       
    sr.addData(0, 0);/*w  ww .  j a  va  2  s.com*/
    sr.addData(1, 1.2);
    sr.addData(2, 2.6);
    sr.addData(3, 3.2);
    sr.addData(4, 4);
    sr.addData(5, 5);

    NumberFormat format = NumberFormat.getInstance();

    // Print the value of y when line intersects the y axis
    System.out.println("Intercept: " + format.format(sr.getIntercept()));

    // Print the number of data points
    System.out.println("N: " + sr.getN());

    // Print the Slope and the Slop Confidence
    System.out.println("Slope: " + format.format(sr.getSlope()));
    System.out.println("Slope Confidence: " + format.format(sr.getSlopeConfidenceInterval()));

    // Print RSquare a measure of relatedness
    System.out.println("RSquare: " + format.format(sr.getRSquare()));

    sr.addData(400, 100);
    sr.addData(300, 105);
    sr.addData(350, 70);
    sr.addData(200, 50);
    sr.addData(150, 300);
    sr.addData(50, 500);

    System.out.println("Intercept: " + format.format(sr.getIntercept()));
    System.out.println("N: " + sr.getN());
    System.out.println("Slope: " + format.format(sr.getSlope()));
    System.out.println("Slope Confidence: " + format.format(sr.getSlopeConfidenceInterval()));
    System.out.println("RSquare: " + format.format(sr.getRSquare()));

}

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From source file:uk.ac.leeds.ccg.andyt.generic.visualisation.charts.Generic_ScatterPlotAndLinearRegression.java

/**
 * @param data double[2][] where: data[0][] are the y values data[1][] are
 * the x values/*w ww.  j a  v a 2 s.  c o m*/
 * @return double[] result where: <ul> <li>result[0] is the y axis
 * intercept;</li> <li>result[1] is the change in y relative to x (gradient
 * or slope);</li> <li>result[2] is the rank correlation coefficient
 * (RSquare);</li> <li>result[3] is data[0].length.</li> </ul>
 */
public static double[] getSimpleRegressionParameters(double[][] data) {
    double[] result = new double[4];
    // org.apache.commons.math.stat.regression.SimpleRegression;
    SimpleRegression a_SimpleRegression = new SimpleRegression();
    //System.out.println("data.length " + data[0].length);
    for (int i = 0; i < data[0].length; i++) {
        a_SimpleRegression.addData(data[1][i], data[0][i]);
        //aSimpleRegression.addData(data[0][i], data[1][i]);
    }
    result[0] = a_SimpleRegression.getIntercept();
    result[1] = a_SimpleRegression.getSlope();
    result[2] = a_SimpleRegression.getRSquare();
    result[3] = data[0].length;
    return result;
}

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From source file:uk.ac.leeds.ccg.andyt.projects.moses.process.RegressionReport.java

/**
 * data[0][] = observed  SAR/*from   w  w w  .  j  a  v  a2  s . c  om*/
 * data[1][] = expected  CAS
 *
 * @param data
 * @return 
 */
public static double[] printSimpleRegression(double[][] data) {
    double[] result = new double[3];
    // org.apache.commons.math.stat.regression.SimpleRegression;
    SimpleRegression aSimpleRegression = new SimpleRegression();
    System.out.println("data.length " + data[0].length);
    for (int i = 0; i < data[0].length; i++) {
        // aSimpleRegression.addData( data[1][i], data[0][i] );
        aSimpleRegression.addData(data[0][i], data[1][i]);
    }
    double _Intercept = aSimpleRegression.getIntercept();
    double _Slope = aSimpleRegression.getSlope();
    double _RSquare = aSimpleRegression.getRSquare();
    System.out.println(" y = " + _Slope + " * x + " + _Intercept);
    System.out.println(" RSquare " + _RSquare);
    result[0] = _Intercept;
    result[1] = _Slope;
    result[2] = _RSquare;
    return result;
}

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