/*
 * 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 $Revision$ $Date$
 */
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.
	 */
	public 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.
	 */
	public 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.
	 */
	public boolean anovaTest(Collection<double[]> categoryData, double alpha)
			throws IllegalArgumentException, MathException;

}