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 * https://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
18 /*
19 * This is not the original file distributed by the Apache Software Foundation
20 * It has been modified by the Hipparchus project
21 */
22 package org.hipparchus.stat.descriptive;
23
24 import org.hipparchus.linear.RealMatrix;
25
26 /**
27 * Reporting interface for basic multivariate statistics.
28 */
29 public interface StatisticalMultivariateSummary {
30
31 /**
32 * Returns the dimension of the data
33 * @return The dimension of the data
34 */
35 int getDimension();
36
37 /**
38 * Returns an array whose i<sup>th</sup> entry is the
39 * mean of the i<sup>th</sup> entries of the arrays
40 * that correspond to each multivariate sample
41 *
42 * @return the array of component means
43 */
44 double[] getMean();
45
46 /**
47 * Returns the covariance of the available values.
48 * @return The covariance, null if no multivariate sample
49 * have been added or a zeroed matrix for a single value set.
50 */
51 RealMatrix getCovariance();
52
53 /**
54 * Returns an array whose i<sup>th</sup> entry is the
55 * standard deviation of the i<sup>th</sup> entries of the arrays
56 * that correspond to each multivariate sample
57 *
58 * @return the array of component standard deviations
59 */
60 double[] getStandardDeviation();
61
62 /**
63 * Returns an array whose i<sup>th</sup> entry is the
64 * maximum of the i<sup>th</sup> entries of the arrays
65 * that correspond to each multivariate sample
66 *
67 * @return the array of component maxima
68 */
69 double[] getMax();
70
71 /**
72 * Returns an array whose i<sup>th</sup> entry is the
73 * minimum of the i<sup>th</sup> entries of the arrays
74 * that correspond to each multivariate sample
75 *
76 * @return the array of component minima
77 */
78 double[] getMin();
79
80 /**
81 * Returns the number of available values
82 * @return The number of available values
83 */
84 long getN();
85
86 /**
87 * Returns an array whose i<sup>th</sup> entry is the
88 * geometric mean of the i<sup>th</sup> entries of the arrays
89 * that correspond to each multivariate sample
90 *
91 * @return the array of component geometric means
92 */
93 double[] getGeometricMean();
94
95 /**
96 * Returns an array whose i<sup>th</sup> entry is the
97 * sum of the i<sup>th</sup> entries of the arrays
98 * that correspond to each multivariate sample
99 *
100 * @return the array of component sums
101 */
102 double[] getSum();
103
104 /**
105 * Returns an array whose i<sup>th</sup> entry is the
106 * sum of squares of the i<sup>th</sup> entries of the arrays
107 * that correspond to each multivariate sample
108 *
109 * @return the array of component sums of squares
110 */
111 double[] getSumSq();
112
113 /**
114 * Returns an array whose i<sup>th</sup> entry is the
115 * sum of logs of the i<sup>th</sup> entries of the arrays
116 * that correspond to each multivariate sample
117 *
118 * @return the array of component log sums
119 */
120 double[] getSumLog();
121
122 }