1 /* 2 * Licensed to the Apache Software Foundation (ASF) under one or more 3 * contributor license agreements. See the NOTICE file distributed with 4 * this work for additional information regarding copyright ownership. 5 * The ASF licenses this file to You under the Apache License, Version 2.0 6 * (the "License"); you may not use this file except in compliance with 7 * the License. You may obtain a copy of the License at 8 * 9 * http://www.apache.org/licenses/LICENSE-2.0 10 * 11 * Unless required by applicable law or agreed to in writing, software 12 * distributed under the License is distributed on an "AS IS" BASIS, 13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 * See the License for the specific language governing permissions and 15 * limitations under the License. 16 */ 17 package org.apache.commons.math.stat.inference; 18 19 import org.apache.commons.math.MathException; 20 import java.util.Collection; 21 22 /** 23 * An interface for one-way ANOVA (analysis of variance). 24 * 25 * <p> Tests for differences between two or more categories of univariate data 26 * (for example, the body mass index of accountants, lawyers, doctors and 27 * computer programmers). When two categories are given, this is equivalent to 28 * the {@link org.apache.commons.math.stat.inference.TTest}. 29 * </p> 30 * 31 * @since 1.2 32 * @version $Revision: 811786 $ $Date: 2009-09-06 11:36:08 +0200 (dim. 06 sept. 2009) $ 33 */ 34 public interface OneWayAnova { 35 36 /** 37 * Computes the ANOVA F-value for a collection of <code>double[]</code> 38 * arrays. 39 * 40 * <p><strong>Preconditions</strong>: <ul> 41 * <li>The categoryData <code>Collection</code> must contain 42 * <code>double[]</code> arrays.</li> 43 * <li> There must be at least two <code>double[]</code> arrays in the 44 * <code>categoryData</code> collection and each of these arrays must 45 * contain at least two values.</li></ul></p> 46 * 47 * @param categoryData <code>Collection</code> of <code>double[]</code> 48 * arrays each containing data for one category 49 * @return Fvalue 50 * @throws IllegalArgumentException if the preconditions are not met 51 * @throws MathException if the statistic can not be computed do to a 52 * convergence or other numerical error. 53 */ 54 double anovaFValue(Collection<double[]> categoryData) 55 throws IllegalArgumentException, MathException; 56 57 /** 58 * Computes the ANOVA P-value for a collection of <code>double[]</code> 59 * arrays. 60 * 61 * <p><strong>Preconditions</strong>: <ul> 62 * <li>The categoryData <code>Collection</code> must contain 63 * <code>double[]</code> arrays.</li> 64 * <li> There must be at least two <code>double[]</code> arrays in the 65 * <code>categoryData</code> collection and each of these arrays must 66 * contain at least two values.</li></ul></p> 67 * 68 * @param categoryData <code>Collection</code> of <code>double[]</code> 69 * arrays each containing data for one category 70 * @return Pvalue 71 * @throws IllegalArgumentException if the preconditions are not met 72 * @throws MathException if the statistic can not be computed do to a 73 * convergence or other numerical error. 74 */ 75 double anovaPValue(Collection<double[]> categoryData) 76 throws IllegalArgumentException, MathException; 77 78 /** 79 * Performs an ANOVA test, evaluating the null hypothesis that there 80 * is no difference among the means of the data categories. 81 * 82 * <p><strong>Preconditions</strong>: <ul> 83 * <li>The categoryData <code>Collection</code> must contain 84 * <code>double[]</code> arrays.</li> 85 * <li> There must be at least two <code>double[]</code> arrays in the 86 * <code>categoryData</code> collection and each of these arrays must 87 * contain at least two values.</li> 88 * <li>alpha must be strictly greater than 0 and less than or equal to 0.5. 89 * </li></ul></p> 90 * 91 * @param categoryData <code>Collection</code> of <code>double[]</code> 92 * arrays each containing data for one category 93 * @param alpha significance level of the test 94 * @return true if the null hypothesis can be rejected with 95 * confidence 1 - alpha 96 * @throws IllegalArgumentException if the preconditions are not met 97 * @throws MathException if the statistic can not be computed do to a 98 * convergence or other numerical error. 99 */ 100 boolean anovaTest(Collection<double[]> categoryData, double alpha) 101 throws IllegalArgumentException, MathException; 102 103 } 104
