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Java example source code file (StatisticalMultivariateSummary.java)

This example Java source code file (StatisticalMultivariateSummary.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

realmatrix, statisticalmultivariatesummary

The StatisticalMultivariateSummary.java Java example source code

/*
 * 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.math3.stat.descriptive;

import org.apache.commons.math3.linear.RealMatrix;

/**
 *  Reporting interface for basic multivariate statistics.
 *
 * @since 1.2
 */
public interface StatisticalMultivariateSummary {

    /**
     * Returns the dimension of the data
     * @return The dimension of the data
     */
    int getDimension();

    /**
     * Returns an array whose i<sup>th entry is the
     * mean of the i<sup>th entries of the arrays
     * that correspond to each multivariate sample
     *
     * @return the array of component means
     */
    double[] getMean();

    /**
     * Returns the covariance of the available values.
     * @return The covariance, null if no multivariate sample
     * have been added or a zeroed matrix for a single value set.
     */
    RealMatrix getCovariance();

    /**
     * Returns an array whose i<sup>th entry is the
     * standard deviation of the i<sup>th entries of the arrays
     * that correspond to each multivariate sample
     *
     * @return the array of component standard deviations
     */
    double[] getStandardDeviation();

    /**
     * Returns an array whose i<sup>th entry is the
     * maximum of the i<sup>th entries of the arrays
     * that correspond to each multivariate sample
     *
     * @return the array of component maxima
     */
    double[] getMax();

    /**
     * Returns an array whose i<sup>th entry is the
     * minimum of the i<sup>th entries of the arrays
     * that correspond to each multivariate sample
     *
     * @return the array of component minima
     */
    double[] getMin();

    /**
     * Returns the number of available values
     * @return The number of available values
     */
    long getN();

    /**
     * Returns an array whose i<sup>th entry is the
     * geometric mean of the i<sup>th entries of the arrays
     * that correspond to each multivariate sample
     *
     * @return the array of component geometric means
     */
    double[] getGeometricMean();

    /**
     * Returns an array whose i<sup>th entry is the
     * sum of the i<sup>th entries of the arrays
     * that correspond to each multivariate sample
     *
     * @return the array of component sums
     */
    double[] getSum();

    /**
     * Returns an array whose i<sup>th entry is the
     * sum of squares of the i<sup>th entries of the arrays
     * that correspond to each multivariate sample
     *
     * @return the array of component sums of squares
     */
    double[] getSumSq();

    /**
     * Returns an array whose i<sup>th entry is the
     * sum of logs of the i<sup>th entries of the arrays
     * that correspond to each multivariate sample
     *
     * @return the array of component log sums
     */
    double[] getSumLog();

}

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