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.descriptive;
018    
019    import org.apache.commons.math.linear.RealMatrix;
020    
021    /**
022     *  Reporting interface for basic multivariate statistics.
023     *
024     * @since 1.2
025     * @version $Revision: 670469 $ $Date: 2008-06-23 04:01:38 -0400 (Mon, 23 Jun 2008) $
026     */
027    public interface StatisticalMultivariateSummary {
028        /** 
029         * Returns the dimension of the data
030         * @return The dimension of the data
031         */
032        public int getDimension();
033        /**
034         * Returns an array whose i<sup>th</sup> entry is the
035         * mean of the i<sup>th</sup> entries of the arrays
036         * that correspond to each multivariate sample
037         * 
038         * @return the array of component means
039         */
040        public abstract double[] getMean();
041        /** 
042         * Returns the covariance of the available values.
043         * @return The covariance, null if no multivariate sample
044         * have been added or a zeroed matrix for a single value set.  
045         */
046        public abstract RealMatrix getCovariance();
047        /**
048         * Returns an array whose i<sup>th</sup> entry is the
049         * standard deviation of the i<sup>th</sup> entries of the arrays
050         * that correspond to each multivariate sample
051         * 
052         * @return the array of component standard deviations
053         */
054        public abstract double[] getStandardDeviation();
055        /**
056         * Returns an array whose i<sup>th</sup> entry is the
057         * maximum of the i<sup>th</sup> entries of the arrays
058         * that correspond to each multivariate sample
059         * 
060         * @return the array of component maxima
061         */
062        public abstract double[] getMax();
063        /**
064         * Returns an array whose i<sup>th</sup> entry is the
065         * minimum of the i<sup>th</sup> entries of the arrays
066         * that correspond to each multivariate sample
067         * 
068         * @return the array of component minima
069         */
070        public abstract double[] getMin();
071        /** 
072         * Returns the number of available values
073         * @return The number of available values
074         */
075        public abstract long getN();
076        /**
077         * Returns an array whose i<sup>th</sup> entry is the
078         * geometric mean of the i<sup>th</sup> entries of the arrays
079         * that correspond to each multivariate sample
080         * 
081         * @return the array of component geometric means
082         */
083        public double[] getGeometricMean();
084        /**
085         * Returns an array whose i<sup>th</sup> entry is the
086         * sum of the i<sup>th</sup> entries of the arrays
087         * that correspond to each multivariate sample
088         * 
089         * @return the array of component sums
090         */
091        public abstract double[] getSum();
092        /**
093         * Returns an array whose i<sup>th</sup> entry is the
094         * sum of squares of the i<sup>th</sup> entries of the arrays
095         * that correspond to each multivariate sample
096         * 
097         * @return the array of component sums of squares
098         */
099        public abstract double[] getSumSq();
100        /**
101         * Returns an array whose i<sup>th</sup> entry is the
102         * sum of logs of the i<sup>th</sup> entries of the arrays
103         * that correspond to each multivariate sample
104         * 
105         * @return the array of component log sums
106         */
107        public abstract double[] getSumLog();
108    }