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: 811786 $ $Date: 2009-09-06 11:36:08 +0200 (dim. 06 sept. 2009) $ 026 */ 027 public interface StatisticalMultivariateSummary { 028 029 /** 030 * Returns the dimension of the data 031 * @return The dimension of the data 032 */ 033 int getDimension(); 034 035 /** 036 * Returns an array whose i<sup>th</sup> entry is the 037 * mean of the i<sup>th</sup> entries of the arrays 038 * that correspond to each multivariate sample 039 * 040 * @return the array of component means 041 */ 042 double[] getMean(); 043 044 /** 045 * Returns the covariance of the available values. 046 * @return The covariance, null if no multivariate sample 047 * have been added or a zeroed matrix for a single value set. 048 */ 049 RealMatrix getCovariance(); 050 051 /** 052 * Returns an array whose i<sup>th</sup> entry is the 053 * standard deviation of the i<sup>th</sup> entries of the arrays 054 * that correspond to each multivariate sample 055 * 056 * @return the array of component standard deviations 057 */ 058 double[] getStandardDeviation(); 059 060 /** 061 * Returns an array whose i<sup>th</sup> entry is the 062 * maximum of the i<sup>th</sup> entries of the arrays 063 * that correspond to each multivariate sample 064 * 065 * @return the array of component maxima 066 */ 067 double[] getMax(); 068 069 /** 070 * Returns an array whose i<sup>th</sup> entry is the 071 * minimum of the i<sup>th</sup> entries of the arrays 072 * that correspond to each multivariate sample 073 * 074 * @return the array of component minima 075 */ 076 double[] getMin(); 077 078 /** 079 * Returns the number of available values 080 * @return The number of available values 081 */ 082 long getN(); 083 084 /** 085 * Returns an array whose i<sup>th</sup> entry is the 086 * geometric mean of the i<sup>th</sup> entries of the arrays 087 * that correspond to each multivariate sample 088 * 089 * @return the array of component geometric means 090 */ 091 double[] getGeometricMean(); 092 093 /** 094 * Returns an array whose i<sup>th</sup> entry is the 095 * sum of the i<sup>th</sup> entries of the arrays 096 * that correspond to each multivariate sample 097 * 098 * @return the array of component sums 099 */ 100 double[] getSum(); 101 102 /** 103 * Returns an array whose i<sup>th</sup> entry is the 104 * sum of squares of the i<sup>th</sup> entries of the arrays 105 * that correspond to each multivariate sample 106 * 107 * @return the array of component sums of squares 108 */ 109 double[] getSumSq(); 110 111 /** 112 * Returns an array whose i<sup>th</sup> entry is the 113 * sum of logs of the i<sup>th</sup> entries of the arrays 114 * that correspond to each multivariate sample 115 * 116 * @return the array of component log sums 117 */ 118 double[] getSumLog(); 119 120 }