1 files changed, 103 insertions, 0 deletions
diff --git a/src/main/java/org/apache/commons/math/stat/inference/OneWayAnova.java b/src/main/java/org/apache/commons/math/stat/inference/OneWayAnova.java
new file mode 100644
index 0000000..a2cde47
--- /dev/null
+++ b/src/main/java/org/apache/commons/math/stat/inference/OneWayAnova.java
@@ -0,0 +1,103 @@
+/*
+ * 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;
+
+}