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 }