Java tutorial
/* * Copyright 2012 J. Patrick Meyer * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package com.itemanalysis.psychometrics.kernel; import org.apache.commons.math3.stat.descriptive.moment.StandardDeviation; import org.apache.commons.math3.stat.descriptive.rank.Percentile; /** * See Silverman (1986, p. 45). * * Silverman, B. W. (1986). Density estimation for statistics and data analysis. Boca Raton, FL: Chapman Hall. * */ public final class ScottsBandwidth implements Bandwidth { private double[] x = null; private double adjustmentFactor = 1.0; private Percentile pcntl = null; public ScottsBandwidth(double[] x) { this(x, 1.0); } public ScottsBandwidth(double[] x, double adjustmentFactor) { this.x = x; this.adjustmentFactor = adjustmentFactor; pcntl = new Percentile(); } public double value() { StandardDeviation sd = new StandardDeviation(); double q3 = pcntl.evaluate(x, 75.0); double q1 = pcntl.evaluate(x, 25.0); double IQR = (q3 - q1) / 1.34; double s = sd.evaluate(x); double N = (double) x.length; double m = Math.min(s, IQR); return 1.06 * m * Math.pow(N, -1.0 / 5.0) * adjustmentFactor; } public double getAdjustmentFactor() { return adjustmentFactor; } }