| /* |
| * Licensed to the Apache Software Foundation (ASF) under one or more |
| * contributor license agreements. See the NOTICE file distributed with |
| * this work for additional information regarding copyright ownership. |
| * The ASF licenses this file to You 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 org.apache.commons.math.stat.inference; |
| |
| import org.apache.commons.math.MathException; |
| import java.util.Collection; |
| |
| /** |
| * An interface for one-way ANOVA (analysis of variance). |
| * |
| * <p> Tests for differences between two or more categories of univariate data |
| * (for example, the body mass index of accountants, lawyers, doctors and |
| * computer programmers). When two categories are given, this is equivalent to |
| * the {@link org.apache.commons.math.stat.inference.TTest}. |
| * </p> |
| * |
| * @since 1.2 |
| * @version $Revision: 811786 $ $Date: 2009-09-06 11:36:08 +0200 (dim. 06 sept. 2009) $ |
| */ |
| public interface OneWayAnova { |
| |
| /** |
| * Computes the ANOVA F-value for a collection of <code>double[]</code> |
| * arrays. |
| * |
| * <p><strong>Preconditions</strong>: <ul> |
| * <li>The categoryData <code>Collection</code> must contain |
| * <code>double[]</code> arrays.</li> |
| * <li> There must be at least two <code>double[]</code> arrays in the |
| * <code>categoryData</code> collection and each of these arrays must |
| * contain at least two values.</li></ul></p> |
| * |
| * @param categoryData <code>Collection</code> of <code>double[]</code> |
| * arrays each containing data for one category |
| * @return Fvalue |
| * @throws IllegalArgumentException if the preconditions are not met |
| * @throws MathException if the statistic can not be computed do to a |
| * convergence or other numerical error. |
| */ |
| double anovaFValue(Collection<double[]> categoryData) |
| throws IllegalArgumentException, MathException; |
| |
| /** |
| * Computes the ANOVA P-value for a collection of <code>double[]</code> |
| * arrays. |
| * |
| * <p><strong>Preconditions</strong>: <ul> |
| * <li>The categoryData <code>Collection</code> must contain |
| * <code>double[]</code> arrays.</li> |
| * <li> There must be at least two <code>double[]</code> arrays in the |
| * <code>categoryData</code> collection and each of these arrays must |
| * contain at least two values.</li></ul></p> |
| * |
| * @param categoryData <code>Collection</code> of <code>double[]</code> |
| * arrays each containing data for one category |
| * @return Pvalue |
| * @throws IllegalArgumentException if the preconditions are not met |
| * @throws MathException if the statistic can not be computed do to a |
| * convergence or other numerical error. |
| */ |
| double anovaPValue(Collection<double[]> categoryData) |
| throws IllegalArgumentException, MathException; |
| |
| /** |
| * Performs an ANOVA test, evaluating the null hypothesis that there |
| * is no difference among the means of the data categories. |
| * |
| * <p><strong>Preconditions</strong>: <ul> |
| * <li>The categoryData <code>Collection</code> must contain |
| * <code>double[]</code> arrays.</li> |
| * <li> There must be at least two <code>double[]</code> arrays in the |
| * <code>categoryData</code> collection and each of these arrays must |
| * contain at least two values.</li> |
| * <li>alpha must be strictly greater than 0 and less than or equal to 0.5. |
| * </li></ul></p> |
| * |
| * @param categoryData <code>Collection</code> of <code>double[]</code> |
| * arrays each containing data for one category |
| * @param alpha significance level of the test |
| * @return true if the null hypothesis can be rejected with |
| * confidence 1 - alpha |
| * @throws IllegalArgumentException if the preconditions are not met |
| * @throws MathException if the statistic can not be computed do to a |
| * convergence or other numerical error. |
| */ |
| boolean anovaTest(Collection<double[]> categoryData, double alpha) |
| throws IllegalArgumentException, MathException; |
| |
| } |