Main.java Source code

Introduction

Here is the source code for Main.java

Source

//package com.java2s;

public class Main {
    /**
     * result linear coef with coef[0]=a and coef[1]=b in a*x+b*/
    static public double[] regress(double[] y, double[] x) {
        double[] coefs = new double[2];

        // first pass: read in data, compute xbar and ybar
        double sumx = 0.0, sumy = 0.0, sumx2 = 0.0;
        int offset = 0;
        int length = x.length;
        double R2 = 0;
        while (R2 < 0.50) {
            for (int i = offset; i < length; i++) {
                if (x[i] != Integer.MIN_VALUE && y[i] != Integer.MIN_VALUE) {
                    sumx += x[i];
                    sumx2 += x[i] * x[i];
                    sumy += y[i];
                }
            }
            double xbar = sumx / length;
            double ybar = sumy / length;

            // second pass: compute summary statistics
            double xxbar = 0.0, yybar = 0.0, xybar = 0.0;
            for (int i = offset; i < length; i++) {
                if (x[i] != Integer.MIN_VALUE && y[i] != Integer.MIN_VALUE) {
                    xxbar += (x[i] - xbar) * (x[i] - xbar);
                    yybar += (y[i] - ybar) * (y[i] - ybar);
                    xybar += (x[i] - xbar) * (y[i] - ybar);
                }
            }
            double a = xybar / xxbar;
            double b = ybar - a * xbar;

            coefs[0] = a;
            coefs[1] = b;

            // analyze results

            int df = length - 2;
            double rss = 0.0; // residual sum of squares
            double ssr = 0.0; // regression sum of squares
            for (int i = offset; i < length; i++) {
                if (x[i] != Integer.MIN_VALUE && y[i] != Integer.MIN_VALUE) {
                    double fit = a * x[i] + b;
                    rss += (fit - y[i]) * (fit - y[i]);
                    ssr += (fit - ybar) * (fit - ybar);
                }
            }
            R2 = ssr / yybar;
            double svar = rss / df;
            double svar1 = svar / xxbar;
            double svar0 = svar / length + xbar * xbar * svar1;
            svar0 = svar * sumx2 / (length * xxbar);
            //Log.v("BORDER", "Coefficient of correlation : " + R2);
            offset++;
        }
        return coefs;
    }
}