    001    /*
    002     * Licensed to the Apache Software Foundation (ASF) under one or more
    003     * contributor license agreements.  See the NOTICE file distributed with
    004     * this work for additional information regarding copyright ownership.
    005     * The ASF licenses this file to You under the Apache License, Version 2.0
    006     * (the "License"); you may not use this file except in compliance with
    007     * the License.  You may obtain a copy of the License at
    008     *
    009     *      http://www.apache.org/licenses/LICENSE-2.0
    010     *
    011     * Unless required by applicable law or agreed to in writing, software
    012     * distributed under the License is distributed on an "AS IS" BASIS,
    013     * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    014     * See the License for the specific language governing permissions and
    015     * limitations under the License.
    016     */
    017    package org.apache.commons.math.stat.inference;
    018
    019    import org.apache.commons.math.MathException;
    020    import java.util.Collection;
    021
    022    /**
    023     * An interface for one-way ANOVA (analysis of variance).
    024     *
    025     * <p> Tests for differences between two or more categories of univariate data
    026     * (for example, the body mass index of accountants, lawyers, doctors and
    027     * computer programmers).  When two categories are given, this is equivalent to
    028     * the {@link org.apache.commons.math.stat.inference.TTest}.
    029     * </p>
    030     *
    031     * @since 1.2
    032     * @version $Revision: 811786 $ $Date: 2009-09-06 11:36:08 +0200 (dim. 06 sept. 2009) $
    033     */
    034    public interface OneWayAnova {
    035
    036        /**
    037         * Computes the ANOVA F-value for a collection of <code>double[]</code>
    038         * arrays.
    039         *
    040         * <p><strong>Preconditions</strong>: <ul>
    041         * <li>The categoryData <code>Collection</code> must contain
    042         * <code>double[]</code> arrays.</li>
    043         * <li> There must be at least two <code>double[]</code> arrays in the
    044         * <code>categoryData</code> collection and each of these arrays must
    045         * contain at least two values.</li></ul></p>
    046         *
    047         * @param categoryData <code>Collection</code> of <code>double[]</code>
    048         * arrays each containing data for one category
    049         * @return Fvalue
    050         * @throws IllegalArgumentException if the preconditions are not met
    051         * @throws MathException if the statistic can not be computed do to a
    052         *         convergence or other numerical error.
    053         */
    054        double anovaFValue(Collection<double[]> categoryData)
    055            throws IllegalArgumentException, MathException;
    056
    057        /**
    058         * Computes the ANOVA P-value for a collection of <code>double[]</code>
    059         * arrays.
    060         *
    061         * <p><strong>Preconditions</strong>: <ul>
    062         * <li>The categoryData <code>Collection</code> must contain
    063         * <code>double[]</code> arrays.</li>
    064         * <li> There must be at least two <code>double[]</code> arrays in the
    065         * <code>categoryData</code> collection and each of these arrays must
    066         * contain at least two values.</li></ul></p>
    067         *
    068         * @param categoryData <code>Collection</code> of <code>double[]</code>
    069         * arrays each containing data for one category
    070         * @return Pvalue
    071         * @throws IllegalArgumentException if the preconditions are not met
    072         * @throws MathException if the statistic can not be computed do to a
    073         *         convergence or other numerical error.
    074         */
    075        double anovaPValue(Collection<double[]> categoryData)
    076            throws IllegalArgumentException, MathException;
    077
    078        /**
    079         * Performs an ANOVA test, evaluating the null hypothesis that there
    080         * is no difference among the means of the data categories.
    081         *
    082         * <p><strong>Preconditions</strong>: <ul>
    083         * <li>The categoryData <code>Collection</code> must contain
    084         * <code>double[]</code> arrays.</li>
    085         * <li> There must be at least two <code>double[]</code> arrays in the
    086         * <code>categoryData</code> collection and each of these arrays must
    087         * contain at least two values.</li>
    088         * <li>alpha must be strictly greater than 0 and less than or equal to 0.5.
    089         * </li></ul></p>
    090         *
    091         * @param categoryData <code>Collection</code> of <code>double[]</code>
    092         * arrays each containing data for one category
    093         * @param alpha significance level of the test
    094         * @return true if the null hypothesis can be rejected with
    095         * confidence 1 - alpha
    096         * @throws IllegalArgumentException if the preconditions are not met
    097         * @throws MathException if the statistic can not be computed do to a
    098         *         convergence or other numerical error.
    099         */
    100        boolean anovaTest(Collection<double[]> categoryData, double alpha)
    101            throws IllegalArgumentException, MathException;
    102
    103    }