1 /* 2 * Licensed to the Apache Software Foundation (ASF) under one or more 3 * contributor license agreements. See the NOTICE file distributed with 4 * this work for additional information regarding copyright ownership. 5 * The ASF licenses this file to You under the Apache License, Version 2.0 6 * (the "License"); you may not use this file except in compliance with 7 * the License. You may obtain a copy of the License at 8 * 9 * http://www.apache.org/licenses/LICENSE-2.0 10 * 11 * Unless required by applicable law or agreed to in writing, software 12 * distributed under the License is distributed on an "AS IS" BASIS, 13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 * See the License for the specific language governing permissions and 15 * limitations under the License. 16 */ 17 package org.apache.commons.math.stat.descriptive; 18 19 import org.apache.commons.math.linear.RealMatrix; 20 21 /** 22 * Reporting interface for basic multivariate statistics. 23 * 24 * @since 1.2 25 * @version $Revision: 670469 $ $Date: 2008-06-23 04:01:38 -0400 (Mon, 23 Jun 2008) $ 26 */ 27 public interface StatisticalMultivariateSummary { 28 /** 29 * Returns the dimension of the data 30 * @return The dimension of the data 31 */ 32 public int getDimension(); 33 /** 34 * Returns an array whose i<sup>th</sup> entry is the 35 * mean of the i<sup>th</sup> entries of the arrays 36 * that correspond to each multivariate sample 37 * 38 * @return the array of component means 39 */ 40 public abstract double[] getMean(); 41 /** 42 * Returns the covariance of the available values. 43 * @return The covariance, null if no multivariate sample 44 * have been added or a zeroed matrix for a single value set. 45 */ 46 public abstract RealMatrix getCovariance(); 47 /** 48 * Returns an array whose i<sup>th</sup> entry is the 49 * standard deviation of the i<sup>th</sup> entries of the arrays 50 * that correspond to each multivariate sample 51 * 52 * @return the array of component standard deviations 53 */ 54 public abstract double[] getStandardDeviation(); 55 /** 56 * Returns an array whose i<sup>th</sup> entry is the 57 * maximum of the i<sup>th</sup> entries of the arrays 58 * that correspond to each multivariate sample 59 * 60 * @return the array of component maxima 61 */ 62 public abstract double[] getMax(); 63 /** 64 * Returns an array whose i<sup>th</sup> entry is the 65 * minimum of the i<sup>th</sup> entries of the arrays 66 * that correspond to each multivariate sample 67 * 68 * @return the array of component minima 69 */ 70 public abstract double[] getMin(); 71 /** 72 * Returns the number of available values 73 * @return The number of available values 74 */ 75 public abstract long getN(); 76 /** 77 * Returns an array whose i<sup>th</sup> entry is the 78 * geometric mean of the i<sup>th</sup> entries of the arrays 79 * that correspond to each multivariate sample 80 * 81 * @return the array of component geometric means 82 */ 83 public double[] getGeometricMean(); 84 /** 85 * Returns an array whose i<sup>th</sup> entry is the 86 * sum of the i<sup>th</sup> entries of the arrays 87 * that correspond to each multivariate sample 88 * 89 * @return the array of component sums 90 */ 91 public abstract double[] getSum(); 92 /** 93 * Returns an array whose i<sup>th</sup> entry is the 94 * sum of squares of the i<sup>th</sup> entries of the arrays 95 * that correspond to each multivariate sample 96 * 97 * @return the array of component sums of squares 98 */ 99 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 }