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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSat, 19 Dec 2009 05:16:42 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/19/t12612250890532wbx0wpefswr.htm/, Retrieved Sat, 04 May 2024 00:12:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69544, Retrieved Sat, 04 May 2024 00:12:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact121

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [] [2009-11-27 14:46:03] [b98453cac15ba1066b407e146608df68]
-   PD    [(Partial) Autocorrelation Function] [WS9: ACF] [2009-12-04 17:46:09] [5c968c05ca472afa314d272082b56b09]
-   PD        [(Partial) Autocorrelation Function] [d=1 D=0 en lambda...] [2009-12-19 12:16:42] [91df150cd527c563f0151b3a845ecd72] [Current]
-   P           [(Partial) Autocorrelation Function] [d=0, D=1 en lambd...] [2009-12-19 12:25:49] [4d62210f0915d3a20cbf115865da7cd4]
-   P           [(Partial) Autocorrelation Function] [D=1, d=1 en lambd...] [2009-12-19 12:36:40] [4d62210f0915d3a20cbf115865da7cd4]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
113
110
107
103
98
98
137
148
147
139
130
128
127
123
118
114
108
111
151
159
158
148
138
137
136
133
126
120
114
116
153
162
161
149
139
135
130
127
122
117
112
113
149
157
157
147
137
132
125
123
117
114
111
112
144
150
149
134
123
116

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69544&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69544&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69544&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3383872.59920.005893
2-0.087573-0.67270.251895
3-0.344355-2.6450.005226
4-0.308417-2.3690.010565
5-0.099735-0.76610.223342
6-0.042922-0.32970.371401
7-0.049779-0.38240.351786
8-0.227948-1.75090.042581
9-0.240628-1.84830.034787
10-0.058289-0.44770.327996
110.2913682.2380.014503
120.8045716.180
130.2604472.00050.025026
14-0.084702-0.65060.258912
15-0.307088-2.35880.010833
16-0.262067-2.0130.024344
17-0.092858-0.71330.239249
18-0.02332-0.17910.429226
19-0.017242-0.13240.447545
20-0.15846-1.21720.114196
21-0.176237-1.35370.090498
22-0.044939-0.34520.365592
230.2112781.62290.054976
240.5937674.56081.3e-05
250.1992321.53030.06564
26-0.062223-0.47790.317229
27-0.240639-1.84840.03478
28-0.207476-1.59370.058179
29-0.092493-0.71050.24011
30-0.020334-0.15620.438209
310.0063830.0490.48053
32-0.086519-0.66460.25446
33-0.098795-0.75890.225478
34-0.027691-0.21270.416148
350.1315621.01050.15818
360.3798822.91790.00249

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.338387 & 2.5992 & 0.005893 \tabularnewline
2 & -0.087573 & -0.6727 & 0.251895 \tabularnewline
3 & -0.344355 & -2.645 & 0.005226 \tabularnewline
4 & -0.308417 & -2.369 & 0.010565 \tabularnewline
5 & -0.099735 & -0.7661 & 0.223342 \tabularnewline
6 & -0.042922 & -0.3297 & 0.371401 \tabularnewline
7 & -0.049779 & -0.3824 & 0.351786 \tabularnewline
8 & -0.227948 & -1.7509 & 0.042581 \tabularnewline
9 & -0.240628 & -1.8483 & 0.034787 \tabularnewline
10 & -0.058289 & -0.4477 & 0.327996 \tabularnewline
11 & 0.291368 & 2.238 & 0.014503 \tabularnewline
12 & 0.804571 & 6.18 & 0 \tabularnewline
13 & 0.260447 & 2.0005 & 0.025026 \tabularnewline
14 & -0.084702 & -0.6506 & 0.258912 \tabularnewline
15 & -0.307088 & -2.3588 & 0.010833 \tabularnewline
16 & -0.262067 & -2.013 & 0.024344 \tabularnewline
17 & -0.092858 & -0.7133 & 0.239249 \tabularnewline
18 & -0.02332 & -0.1791 & 0.429226 \tabularnewline
19 & -0.017242 & -0.1324 & 0.447545 \tabularnewline
20 & -0.15846 & -1.2172 & 0.114196 \tabularnewline
21 & -0.176237 & -1.3537 & 0.090498 \tabularnewline
22 & -0.044939 & -0.3452 & 0.365592 \tabularnewline
23 & 0.211278 & 1.6229 & 0.054976 \tabularnewline
24 & 0.593767 & 4.5608 & 1.3e-05 \tabularnewline
25 & 0.199232 & 1.5303 & 0.06564 \tabularnewline
26 & -0.062223 & -0.4779 & 0.317229 \tabularnewline
27 & -0.240639 & -1.8484 & 0.03478 \tabularnewline
28 & -0.207476 & -1.5937 & 0.058179 \tabularnewline
29 & -0.092493 & -0.7105 & 0.24011 \tabularnewline
30 & -0.020334 & -0.1562 & 0.438209 \tabularnewline
31 & 0.006383 & 0.049 & 0.48053 \tabularnewline
32 & -0.086519 & -0.6646 & 0.25446 \tabularnewline
33 & -0.098795 & -0.7589 & 0.225478 \tabularnewline
34 & -0.027691 & -0.2127 & 0.416148 \tabularnewline
35 & 0.131562 & 1.0105 & 0.15818 \tabularnewline
36 & 0.379882 & 2.9179 & 0.00249 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69544&T=1

[TABLE]
[ROW][C]Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]ACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.338387[/C][C]2.5992[/C][C]0.005893[/C][/ROW]
[ROW][C]2[/C][C]-0.087573[/C][C]-0.6727[/C][C]0.251895[/C][/ROW]
[ROW][C]3[/C][C]-0.344355[/C][C]-2.645[/C][C]0.005226[/C][/ROW]
[ROW][C]4[/C][C]-0.308417[/C][C]-2.369[/C][C]0.010565[/C][/ROW]
[ROW][C]5[/C][C]-0.099735[/C][C]-0.7661[/C][C]0.223342[/C][/ROW]
[ROW][C]6[/C][C]-0.042922[/C][C]-0.3297[/C][C]0.371401[/C][/ROW]
[ROW][C]7[/C][C]-0.049779[/C][C]-0.3824[/C][C]0.351786[/C][/ROW]
[ROW][C]8[/C][C]-0.227948[/C][C]-1.7509[/C][C]0.042581[/C][/ROW]
[ROW][C]9[/C][C]-0.240628[/C][C]-1.8483[/C][C]0.034787[/C][/ROW]
[ROW][C]10[/C][C]-0.058289[/C][C]-0.4477[/C][C]0.327996[/C][/ROW]
[ROW][C]11[/C][C]0.291368[/C][C]2.238[/C][C]0.014503[/C][/ROW]
[ROW][C]12[/C][C]0.804571[/C][C]6.18[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.260447[/C][C]2.0005[/C][C]0.025026[/C][/ROW]
[ROW][C]14[/C][C]-0.084702[/C][C]-0.6506[/C][C]0.258912[/C][/ROW]
[ROW][C]15[/C][C]-0.307088[/C][C]-2.3588[/C][C]0.010833[/C][/ROW]
[ROW][C]16[/C][C]-0.262067[/C][C]-2.013[/C][C]0.024344[/C][/ROW]
[ROW][C]17[/C][C]-0.092858[/C][C]-0.7133[/C][C]0.239249[/C][/ROW]
[ROW][C]18[/C][C]-0.02332[/C][C]-0.1791[/C][C]0.429226[/C][/ROW]
[ROW][C]19[/C][C]-0.017242[/C][C]-0.1324[/C][C]0.447545[/C][/ROW]
[ROW][C]20[/C][C]-0.15846[/C][C]-1.2172[/C][C]0.114196[/C][/ROW]
[ROW][C]21[/C][C]-0.176237[/C][C]-1.3537[/C][C]0.090498[/C][/ROW]
[ROW][C]22[/C][C]-0.044939[/C][C]-0.3452[/C][C]0.365592[/C][/ROW]
[ROW][C]23[/C][C]0.211278[/C][C]1.6229[/C][C]0.054976[/C][/ROW]
[ROW][C]24[/C][C]0.593767[/C][C]4.5608[/C][C]1.3e-05[/C][/ROW]
[ROW][C]25[/C][C]0.199232[/C][C]1.5303[/C][C]0.06564[/C][/ROW]
[ROW][C]26[/C][C]-0.062223[/C][C]-0.4779[/C][C]0.317229[/C][/ROW]
[ROW][C]27[/C][C]-0.240639[/C][C]-1.8484[/C][C]0.03478[/C][/ROW]
[ROW][C]28[/C][C]-0.207476[/C][C]-1.5937[/C][C]0.058179[/C][/ROW]
[ROW][C]29[/C][C]-0.092493[/C][C]-0.7105[/C][C]0.24011[/C][/ROW]
[ROW][C]30[/C][C]-0.020334[/C][C]-0.1562[/C][C]0.438209[/C][/ROW]
[ROW][C]31[/C][C]0.006383[/C][C]0.049[/C][C]0.48053[/C][/ROW]
[ROW][C]32[/C][C]-0.086519[/C][C]-0.6646[/C][C]0.25446[/C][/ROW]
[ROW][C]33[/C][C]-0.098795[/C][C]-0.7589[/C][C]0.225478[/C][/ROW]
[ROW][C]34[/C][C]-0.027691[/C][C]-0.2127[/C][C]0.416148[/C][/ROW]
[ROW][C]35[/C][C]0.131562[/C][C]1.0105[/C][C]0.15818[/C][/ROW]
[ROW][C]36[/C][C]0.379882[/C][C]2.9179[/C][C]0.00249[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69544&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69544&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3383872.59920.005893
2-0.087573-0.67270.251895
3-0.344355-2.6450.005226
4-0.308417-2.3690.010565
5-0.099735-0.76610.223342
6-0.042922-0.32970.371401
7-0.049779-0.38240.351786
8-0.227948-1.75090.042581
9-0.240628-1.84830.034787
10-0.058289-0.44770.327996
110.2913682.2380.014503
120.8045716.180
130.2604472.00050.025026
14-0.084702-0.65060.258912
15-0.307088-2.35880.010833
16-0.262067-2.0130.024344
17-0.092858-0.71330.239249
18-0.02332-0.17910.429226
19-0.017242-0.13240.447545
20-0.15846-1.21720.114196
21-0.176237-1.35370.090498
22-0.044939-0.34520.365592
230.2112781.62290.054976
240.5937674.56081.3e-05
250.1992321.53030.06564
26-0.062223-0.47790.317229
27-0.240639-1.84840.03478
28-0.207476-1.59370.058179
29-0.092493-0.71050.24011
30-0.020334-0.15620.438209
310.0063830.0490.48053
32-0.086519-0.66460.25446
33-0.098795-0.75890.225478
34-0.027691-0.21270.416148
350.1315621.01050.15818
360.3798822.91790.00249






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3383872.59920.005893
2-0.22821-1.75290.042406
3-0.274889-2.11150.019489
4-0.133851-1.02810.154042
5-0.028068-0.21560.415024
6-0.176882-1.35870.089714
7-0.169906-1.30510.098467
8-0.368384-2.82960.00318
9-0.352603-2.70840.004417
10-0.335816-2.57950.006204
11-0.150591-1.15670.126026
120.6158184.73027e-06
13-0.336309-2.58320.006143
140.0574170.4410.330403
150.1488311.14320.128788
160.0655570.50360.308225
170.0057580.04420.482437
180.1013710.77860.219651
190.0581580.44670.328358
200.1070460.82220.207126
210.0149630.11490.454445
220.0849130.65220.258392
23-0.063702-0.48930.31322
24-0.091584-0.70350.242266
250.0744120.57160.284893
26-0.035356-0.27160.393448
27-0.043767-0.33620.368963
28-0.030489-0.23420.407823
29-0.072468-0.55660.289939
30-0.045503-0.34950.363974
31-0.016811-0.12910.448847
320.0105520.08110.467837
330.0527160.40490.343501
34-0.026602-0.20430.419399
350.0035320.02710.489225
36-0.108948-0.83680.203029

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.338387 & 2.5992 & 0.005893 \tabularnewline
2 & -0.22821 & -1.7529 & 0.042406 \tabularnewline
3 & -0.274889 & -2.1115 & 0.019489 \tabularnewline
4 & -0.133851 & -1.0281 & 0.154042 \tabularnewline
5 & -0.028068 & -0.2156 & 0.415024 \tabularnewline
6 & -0.176882 & -1.3587 & 0.089714 \tabularnewline
7 & -0.169906 & -1.3051 & 0.098467 \tabularnewline
8 & -0.368384 & -2.8296 & 0.00318 \tabularnewline
9 & -0.352603 & -2.7084 & 0.004417 \tabularnewline
10 & -0.335816 & -2.5795 & 0.006204 \tabularnewline
11 & -0.150591 & -1.1567 & 0.126026 \tabularnewline
12 & 0.615818 & 4.7302 & 7e-06 \tabularnewline
13 & -0.336309 & -2.5832 & 0.006143 \tabularnewline
14 & 0.057417 & 0.441 & 0.330403 \tabularnewline
15 & 0.148831 & 1.1432 & 0.128788 \tabularnewline
16 & 0.065557 & 0.5036 & 0.308225 \tabularnewline
17 & 0.005758 & 0.0442 & 0.482437 \tabularnewline
18 & 0.101371 & 0.7786 & 0.219651 \tabularnewline
19 & 0.058158 & 0.4467 & 0.328358 \tabularnewline
20 & 0.107046 & 0.8222 & 0.207126 \tabularnewline
21 & 0.014963 & 0.1149 & 0.454445 \tabularnewline
22 & 0.084913 & 0.6522 & 0.258392 \tabularnewline
23 & -0.063702 & -0.4893 & 0.31322 \tabularnewline
24 & -0.091584 & -0.7035 & 0.242266 \tabularnewline
25 & 0.074412 & 0.5716 & 0.284893 \tabularnewline
26 & -0.035356 & -0.2716 & 0.393448 \tabularnewline
27 & -0.043767 & -0.3362 & 0.368963 \tabularnewline
28 & -0.030489 & -0.2342 & 0.407823 \tabularnewline
29 & -0.072468 & -0.5566 & 0.289939 \tabularnewline
30 & -0.045503 & -0.3495 & 0.363974 \tabularnewline
31 & -0.016811 & -0.1291 & 0.448847 \tabularnewline
32 & 0.010552 & 0.0811 & 0.467837 \tabularnewline
33 & 0.052716 & 0.4049 & 0.343501 \tabularnewline
34 & -0.026602 & -0.2043 & 0.419399 \tabularnewline
35 & 0.003532 & 0.0271 & 0.489225 \tabularnewline
36 & -0.108948 & -0.8368 & 0.203029 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69544&T=2

[TABLE]
[ROW][C]Partial Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]PACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.338387[/C][C]2.5992[/C][C]0.005893[/C][/ROW]
[ROW][C]2[/C][C]-0.22821[/C][C]-1.7529[/C][C]0.042406[/C][/ROW]
[ROW][C]3[/C][C]-0.274889[/C][C]-2.1115[/C][C]0.019489[/C][/ROW]
[ROW][C]4[/C][C]-0.133851[/C][C]-1.0281[/C][C]0.154042[/C][/ROW]
[ROW][C]5[/C][C]-0.028068[/C][C]-0.2156[/C][C]0.415024[/C][/ROW]
[ROW][C]6[/C][C]-0.176882[/C][C]-1.3587[/C][C]0.089714[/C][/ROW]
[ROW][C]7[/C][C]-0.169906[/C][C]-1.3051[/C][C]0.098467[/C][/ROW]
[ROW][C]8[/C][C]-0.368384[/C][C]-2.8296[/C][C]0.00318[/C][/ROW]
[ROW][C]9[/C][C]-0.352603[/C][C]-2.7084[/C][C]0.004417[/C][/ROW]
[ROW][C]10[/C][C]-0.335816[/C][C]-2.5795[/C][C]0.006204[/C][/ROW]
[ROW][C]11[/C][C]-0.150591[/C][C]-1.1567[/C][C]0.126026[/C][/ROW]
[ROW][C]12[/C][C]0.615818[/C][C]4.7302[/C][C]7e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.336309[/C][C]-2.5832[/C][C]0.006143[/C][/ROW]
[ROW][C]14[/C][C]0.057417[/C][C]0.441[/C][C]0.330403[/C][/ROW]
[ROW][C]15[/C][C]0.148831[/C][C]1.1432[/C][C]0.128788[/C][/ROW]
[ROW][C]16[/C][C]0.065557[/C][C]0.5036[/C][C]0.308225[/C][/ROW]
[ROW][C]17[/C][C]0.005758[/C][C]0.0442[/C][C]0.482437[/C][/ROW]
[ROW][C]18[/C][C]0.101371[/C][C]0.7786[/C][C]0.219651[/C][/ROW]
[ROW][C]19[/C][C]0.058158[/C][C]0.4467[/C][C]0.328358[/C][/ROW]
[ROW][C]20[/C][C]0.107046[/C][C]0.8222[/C][C]0.207126[/C][/ROW]
[ROW][C]21[/C][C]0.014963[/C][C]0.1149[/C][C]0.454445[/C][/ROW]
[ROW][C]22[/C][C]0.084913[/C][C]0.6522[/C][C]0.258392[/C][/ROW]
[ROW][C]23[/C][C]-0.063702[/C][C]-0.4893[/C][C]0.31322[/C][/ROW]
[ROW][C]24[/C][C]-0.091584[/C][C]-0.7035[/C][C]0.242266[/C][/ROW]
[ROW][C]25[/C][C]0.074412[/C][C]0.5716[/C][C]0.284893[/C][/ROW]
[ROW][C]26[/C][C]-0.035356[/C][C]-0.2716[/C][C]0.393448[/C][/ROW]
[ROW][C]27[/C][C]-0.043767[/C][C]-0.3362[/C][C]0.368963[/C][/ROW]
[ROW][C]28[/C][C]-0.030489[/C][C]-0.2342[/C][C]0.407823[/C][/ROW]
[ROW][C]29[/C][C]-0.072468[/C][C]-0.5566[/C][C]0.289939[/C][/ROW]
[ROW][C]30[/C][C]-0.045503[/C][C]-0.3495[/C][C]0.363974[/C][/ROW]
[ROW][C]31[/C][C]-0.016811[/C][C]-0.1291[/C][C]0.448847[/C][/ROW]
[ROW][C]32[/C][C]0.010552[/C][C]0.0811[/C][C]0.467837[/C][/ROW]
[ROW][C]33[/C][C]0.052716[/C][C]0.4049[/C][C]0.343501[/C][/ROW]
[ROW][C]34[/C][C]-0.026602[/C][C]-0.2043[/C][C]0.419399[/C][/ROW]
[ROW][C]35[/C][C]0.003532[/C][C]0.0271[/C][C]0.489225[/C][/ROW]
[ROW][C]36[/C][C]-0.108948[/C][C]-0.8368[/C][C]0.203029[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69544&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69544&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3383872.59920.005893
2-0.22821-1.75290.042406
3-0.274889-2.11150.019489
4-0.133851-1.02810.154042
5-0.028068-0.21560.415024
6-0.176882-1.35870.089714
7-0.169906-1.30510.098467
8-0.368384-2.82960.00318
9-0.352603-2.70840.004417
10-0.335816-2.57950.006204
11-0.150591-1.15670.126026
120.6158184.73027e-06
13-0.336309-2.58320.006143
140.0574170.4410.330403
150.1488311.14320.128788
160.0655570.50360.308225
170.0057580.04420.482437
180.1013710.77860.219651
190.0581580.44670.328358
200.1070460.82220.207126
210.0149630.11490.454445
220.0849130.65220.258392
23-0.063702-0.48930.31322
24-0.091584-0.70350.242266
250.0744120.57160.284893
26-0.035356-0.27160.393448
27-0.043767-0.33620.368963
28-0.030489-0.23420.407823
29-0.072468-0.55660.289939
30-0.045503-0.34950.363974
31-0.016811-0.12910.448847
320.0105520.08110.467837
330.0527160.40490.343501
34-0.026602-0.20430.419399
350.0035320.02710.489225
36-0.108948-0.83680.203029


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1.3 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1.3 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')