blob: bfe4debdc4e9d18a861ff886fedc3bf97d8a0db1 (
plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
|
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.commons.math3.stat.descriptive;
import org.apache.commons.math3.linear.RealMatrix;
/**
* Reporting interface for basic multivariate statistics.
*
* @since 1.2
*/
public interface StatisticalMultivariateSummary {
/**
* Returns the dimension of the data
* @return The dimension of the data
*/
int getDimension();
/**
* Returns an array whose i<sup>th</sup> entry is the
* mean of the i<sup>th</sup> entries of the arrays
* that correspond to each multivariate sample
*
* @return the array of component means
*/
double[] getMean();
/**
* Returns the covariance of the available values.
* @return The covariance, null if no multivariate sample
* have been added or a zeroed matrix for a single value set.
*/
RealMatrix getCovariance();
/**
* Returns an array whose i<sup>th</sup> entry is the
* standard deviation of the i<sup>th</sup> entries of the arrays
* that correspond to each multivariate sample
*
* @return the array of component standard deviations
*/
double[] getStandardDeviation();
/**
* Returns an array whose i<sup>th</sup> entry is the
* maximum of the i<sup>th</sup> entries of the arrays
* that correspond to each multivariate sample
*
* @return the array of component maxima
*/
double[] getMax();
/**
* Returns an array whose i<sup>th</sup> entry is the
* minimum of the i<sup>th</sup> entries of the arrays
* that correspond to each multivariate sample
*
* @return the array of component minima
*/
double[] getMin();
/**
* Returns the number of available values
* @return The number of available values
*/
long getN();
/**
* Returns an array whose i<sup>th</sup> entry is the
* geometric mean of the i<sup>th</sup> entries of the arrays
* that correspond to each multivariate sample
*
* @return the array of component geometric means
*/
double[] getGeometricMean();
/**
* Returns an array whose i<sup>th</sup> entry is the
* sum of the i<sup>th</sup> entries of the arrays
* that correspond to each multivariate sample
*
* @return the array of component sums
*/
double[] getSum();
/**
* Returns an array whose i<sup>th</sup> entry is the
* sum of squares of the i<sup>th</sup> entries of the arrays
* that correspond to each multivariate sample
*
* @return the array of component sums of squares
*/
double[] getSumSq();
/**
* Returns an array whose i<sup>th</sup> entry is the
* sum of logs of the i<sup>th</sup> entries of the arrays
* that correspond to each multivariate sample
*
* @return the array of component log sums
*/
double[] getSumLog();
}
|
