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
|
/* ----------------------------------------------------------------------------
* This file was automatically generated by SWIG (http://www.swig.org).
* Version 1.3.29
*
* Do not make changes to this file unless you know what you are doing--modify
* the SWIG interface file instead.
* ----------------------------------------------------------------------------- */
package org.quantlib;
public class MultipleStatistics {
private long swigCPtr;
protected boolean swigCMemOwn;
protected MultipleStatistics(long cPtr, boolean cMemoryOwn) {
swigCMemOwn = cMemoryOwn;
swigCPtr = cPtr;
}
protected static long getCPtr(MultipleStatistics obj) {
return (obj == null) ? 0 : obj.swigCPtr;
}
protected void finalize() {
delete();
}
public void delete() {
if(swigCPtr != 0 && swigCMemOwn) {
swigCMemOwn = false;
QuantLibJNI.delete_MultipleStatistics(swigCPtr);
}
swigCPtr = 0;
}
public MultipleStatistics(long dimension) {
this(QuantLibJNI.new_MultipleStatistics(dimension), true);
}
public long size() {
return QuantLibJNI.MultipleStatistics_size(swigCPtr);
}
public long samples() {
return QuantLibJNI.MultipleStatistics_samples(swigCPtr);
}
public double weightSum() {
return QuantLibJNI.MultipleStatistics_weightSum(swigCPtr);
}
public DoubleVector mean() {
return new DoubleVector(QuantLibJNI.MultipleStatistics_mean(swigCPtr), true);
}
public DoubleVector variance() {
return new DoubleVector(QuantLibJNI.MultipleStatistics_variance(swigCPtr), true);
}
public DoubleVector standardDeviation() {
return new DoubleVector(QuantLibJNI.MultipleStatistics_standardDeviation(swigCPtr), true);
}
public DoubleVector errorEstimate() {
return new DoubleVector(QuantLibJNI.MultipleStatistics_errorEstimate(swigCPtr), true);
}
public DoubleVector skewness() {
return new DoubleVector(QuantLibJNI.MultipleStatistics_skewness(swigCPtr), true);
}
public DoubleVector kurtosis() {
return new DoubleVector(QuantLibJNI.MultipleStatistics_kurtosis(swigCPtr), true);
}
public DoubleVector min() {
return new DoubleVector(QuantLibJNI.MultipleStatistics_min(swigCPtr), true);
}
public DoubleVector max() {
return new DoubleVector(QuantLibJNI.MultipleStatistics_max(swigCPtr), true);
}
public Matrix covariance() {
return new Matrix(QuantLibJNI.MultipleStatistics_covariance(swigCPtr), true);
}
public Matrix correlation() {
return new Matrix(QuantLibJNI.MultipleStatistics_correlation(swigCPtr), true);
}
public void reset() {
QuantLibJNI.MultipleStatistics_reset(swigCPtr);
}
public void add(DoubleVector value, double weight) {
QuantLibJNI.MultipleStatistics_add__SWIG_0(swigCPtr, DoubleVector.getCPtr(value), weight);
}
public void add(DoubleVector value) {
QuantLibJNI.MultipleStatistics_add__SWIG_1(swigCPtr, DoubleVector.getCPtr(value));
}
public void add(Array value, double weight) {
QuantLibJNI.MultipleStatistics_add__SWIG_2(swigCPtr, Array.getCPtr(value), weight);
}
public void add(Array value) {
QuantLibJNI.MultipleStatistics_add__SWIG_3(swigCPtr, Array.getCPtr(value));
}
}
|
