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
|
#! /usr/bin/env python
from __future__ import print_function
from openturns import *
TESTPREAMBLE()
RandomGenerator.SetSeed(0)
try:
# 2 D case
RandomGenerator.SetSeed(0)
# Matrices of the process
dim = 2
squareMatrix1 = SquareMatrix(dim)
squareMatrix1[0, 0] = 0.2
squareMatrix1[1, 0] = 0.3
squareMatrix1[0, 1] = 0.7
squareMatrix1[1, 1] = 0.4
# Second matrix to add to the ARMACoefficients
squareMatrix2 = SquareMatrix(dim)
squareMatrix2[0, 0] = 0.1
squareMatrix2[1, 0] = 0.
squareMatrix2[0, 1] = 0.
squareMatrix2[1, 1] = 0.5
# ARMA(p, q)
p = 1
q = 1
# AR coefficients
coefficientsP = ARMACoefficients(p, dim)
coefficientsP[0] = squareMatrix1
# MA coefficients
coefficientsQ = ARMACoefficients(p, dim)
coefficientsQ[0] = squareMatrix2
print("coefficientsP = ", repr(coefficientsP))
print("coefficientsQ = ", repr(coefficientsQ))
# Time grid creation and White Noise
Tmin = 0.0
deltaT = 0.1
steps = 11
# Initialization of the TimeGrid timeGrid1
timeGrid = RegularGrid(Tmin, deltaT, steps)
# Distributions for the choice
dist1 = Distribution(Normal(0.0, 0.01))
dist2 = Distribution(Normal(0.0, 0.02))
# Create a collection of distribution
aCollection = DistributionCollection()
aCollection.add(dist1)
aCollection.add(dist2)
dist = Distribution(ComposedDistribution(aCollection))
print("dist = ", dist)
epsilon = WhiteNoise(dist)
# Setting the timeGrid
epsilon.setTimeGrid(timeGrid)
# Last coefficients values
lastValues = NumericalSample(p, dim)
lastNoiseValues = NumericalSample(q, dim)
#
for j in range(dim):
# Fill the AR-part (the last p-coefficients X_{-1}, X{-2},..., X_{-p})
for i in range(p):
lastValues[i, j] = RandomGenerator.Generate()
# Fill the MA-part (the last p-coefficients \epsilon_{-1},
# \epsilon_{-2},..., \epsilon_{-p})
for i in range(q):
lastNoiseValues[i, j] = RandomGenerator.Generate()
# Print the initial state of the ARMA : coefficients
print("Last values of the process = ", lastValues)
print("Last innovations of the process = ", lastNoiseValues)
# ARMAState creation
# instanciation of timeGrid
state = ARMAState(lastValues, lastNoiseValues)
process = Process(ARMA(coefficientsP, coefficientsQ, epsilon))
process2 = ARMA(coefficientsP, coefficientsQ, epsilon)
process3 = ARMA(coefficientsP, coefficientsQ, epsilon, state)
print("process = ", process)
print("ARMA process = ", process2)
print("ARMA process with ARMAstate = ", process3)
# Test realization
print("One realization=", process2.getRealization())
# Some steps further
stepNumber = 4
print("One future=", process2.getFuture(stepNumber))
size = 3
print("Some futures=", process2.getFuture(stepNumber, size))
except:
import sys
print("t_ARMA_std.py", sys.exc_info()[0], sys.exc_info()[1])
|
