lin Regression - Android java.lang

Android examples for java.lang:Math

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Description

lin Regression

Demo Code


//package com.java2s;
import android.util.Log;

public class Main {
    private static String logtag = "MU";

    public static double[] linRegression(double[] dists, double[] concs) {
        int n = dists.length;

        if (dists.length != concs.length) {
            Log.e(logtag, "Both input arrays must be the same length.");
        }// w w w  . ja  v  a2s  .c om

        // first pass: read in data, compute xbar and ybar
        double sumx = 0.0, sumy = 0.0, sumx2 = 0.0, sumxy = 0.0;
        for (int i = 0; i < dists.length; i++) {
            sumx += concs[i];
            sumx2 += concs[i] * concs[i];
            sumy += dists[i];
            sumxy += dists[i] * concs[i];
        }

        Log.d(logtag, "sumx2=" + sumx2 + " sumy=" + sumy);

        double xbar = sumx / n;
        double ybar = sumy / n;

        // second pass: compute summary statistics
        double xxbar = 0.0, yybar = 0.0, xybar = 0.0;
        for (int i = 0; i < n; i++) {
            xxbar += (concs[i] - xbar) * (concs[i] - xbar);
            yybar += (dists[i] - ybar) * (dists[i] - ybar);
            xybar += (concs[i] - xbar) * (dists[i] - ybar);
        }

        Log.d(logtag, "xxbar=" + xxbar + " xybar=" + xybar + " yybar ="
                + yybar);

        double[] coeffs = new double[5];
        coeffs[0] = xybar / xxbar;
        coeffs[2] = ybar - coeffs[0] * xbar;

        // print results
        Log.d(logtag, "y   = " + coeffs[0] + " * x + " + coeffs[2]);

        // analyze results
        int df = n - 2;
        double rss = 0.0; // residual sum of squares
        double ssr = 0.0; // regression sum of squares
        for (int i = 0; i < n; i++) {
            double fit = coeffs[0] * concs[i] + coeffs[1];
            rss += (fit - dists[i]) * (fit - dists[i]);
            ssr += (fit - ybar) * (fit - ybar);
        }
        double R2 = ssr / yybar;
        coeffs[4] = R2;
        double svar = rss / df;
        double svar1 = svar / xxbar;
        coeffs[1] = svar1;
        double svar0 = svar / n + xbar * xbar * svar1;
        coeffs[3] = svar0;
        Log.d(logtag, "R^2                 = " + R2);
        Log.d(logtag, "std error of beta_1 = " + Math.sqrt(svar1));
        Log.d(logtag, "std error of beta_0 = " + Math.sqrt(svar0));
        svar0 = svar * sumx2 / (n * xxbar);
        Log.d(logtag, "std error of beta_0 = " + Math.sqrt(svar0));

        Log.d(logtag, "SSTO = " + yybar);
        Log.d(logtag, "SSE  = " + rss);
        Log.d(logtag, "SSR  = " + ssr);

        return coeffs;
    }
}

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