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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 computationFri, 18 Dec 2009 04:02:34 -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/18/t1261134337srox6l59m5r6asb.htm/, Retrieved Sat, 27 Apr 2024 12:40:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69231, Retrieved Sat, 27 Apr 2024 12:40:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact241
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
-   PD        [Univariate Data Series] [Totaal Werkzoeken...] [2009-11-24 16:54:07] [ee7c2e7343f5b1451e62c5c16ec521f1]
-   P           [Univariate Data Series] [Totaal Werkzoeken...] [2009-11-24 17:23:40] [ee7c2e7343f5b1451e62c5c16ec521f1]
- RMPD            [(Partial) Autocorrelation Function] [] [2009-11-26 08:57:08] [5edbdb7a459c4059b6c3b063ba86821c]
-   P               [(Partial) Autocorrelation Function] [] [2009-11-26 10:12:32] [5edbdb7a459c4059b6c3b063ba86821c]
-    D                  [(Partial) Autocorrelation Function] [] [2009-12-18 11:02:34] [24029b2c7217429de6ff94b5379eb52c] [Current]
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Dataseries X:
80.2
74.8
77.8
73
72
75.8
72.6
71.9
74.8
72.9
72.9
79.9
74
76
69.6
77.3
75.2
75.8
77.6
76.7
77
77.9
76.7
71.9
73.4
72.5
73.7
69.5
74.7
72.5
72.1
70.7
71.4
69.5
73.5
72.4
74.5
72.2
73
73.3
71.3
73.6
71.3
71.2
81.4
76.1
71.1
75.7
70
68.5
56.7
57.9
58.8
59.3
61.3
62.9
61.4
64.5
63.8
61.6




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=69231&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=69231&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69231&T=0

As an alternative you can also use a 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
1-0.409873-3.14830.001288
20.1007540.77390.221038
30.0290230.22290.41218
4-0.0197-0.15130.440121
5-0.062612-0.48090.316171
6-0.042847-0.32910.371618
7-0.134587-1.03380.152729
80.0719240.55250.291361
9-0.065893-0.50610.307326
100.1084860.83330.204019
110.087560.67260.251926
12-0.307347-2.36080.01078
130.3373382.59110.006018
14-0.230707-1.77210.040771
150.0327470.25150.401138
16-0.041393-0.31790.375824
170.0421220.32350.373713
18-0.086787-0.66660.253805
190.1507691.15810.125749
20-0.076526-0.58780.279452
210.0615330.47260.319105
22-0.187412-1.43950.077642
230.2320521.78240.039912
24-0.071137-0.54640.29342
25-0.052122-0.40040.345171
260.1188440.91290.182517
27-0.01041-0.080.46827
28-0.013509-0.10380.458853
290.1003820.7710.221878
30-0.107791-0.8280.205515
31-0.031201-0.23970.405714
32-0.02677-0.20560.418898
330.0081760.06280.475069
340.0769670.59120.278324
35-0.277083-2.12830.018749
360.2870352.20480.015691

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.409873 & -3.1483 & 0.001288 \tabularnewline
2 & 0.100754 & 0.7739 & 0.221038 \tabularnewline
3 & 0.029023 & 0.2229 & 0.41218 \tabularnewline
4 & -0.0197 & -0.1513 & 0.440121 \tabularnewline
5 & -0.062612 & -0.4809 & 0.316171 \tabularnewline
6 & -0.042847 & -0.3291 & 0.371618 \tabularnewline
7 & -0.134587 & -1.0338 & 0.152729 \tabularnewline
8 & 0.071924 & 0.5525 & 0.291361 \tabularnewline
9 & -0.065893 & -0.5061 & 0.307326 \tabularnewline
10 & 0.108486 & 0.8333 & 0.204019 \tabularnewline
11 & 0.08756 & 0.6726 & 0.251926 \tabularnewline
12 & -0.307347 & -2.3608 & 0.01078 \tabularnewline
13 & 0.337338 & 2.5911 & 0.006018 \tabularnewline
14 & -0.230707 & -1.7721 & 0.040771 \tabularnewline
15 & 0.032747 & 0.2515 & 0.401138 \tabularnewline
16 & -0.041393 & -0.3179 & 0.375824 \tabularnewline
17 & 0.042122 & 0.3235 & 0.373713 \tabularnewline
18 & -0.086787 & -0.6666 & 0.253805 \tabularnewline
19 & 0.150769 & 1.1581 & 0.125749 \tabularnewline
20 & -0.076526 & -0.5878 & 0.279452 \tabularnewline
21 & 0.061533 & 0.4726 & 0.319105 \tabularnewline
22 & -0.187412 & -1.4395 & 0.077642 \tabularnewline
23 & 0.232052 & 1.7824 & 0.039912 \tabularnewline
24 & -0.071137 & -0.5464 & 0.29342 \tabularnewline
25 & -0.052122 & -0.4004 & 0.345171 \tabularnewline
26 & 0.118844 & 0.9129 & 0.182517 \tabularnewline
27 & -0.01041 & -0.08 & 0.46827 \tabularnewline
28 & -0.013509 & -0.1038 & 0.458853 \tabularnewline
29 & 0.100382 & 0.771 & 0.221878 \tabularnewline
30 & -0.107791 & -0.828 & 0.205515 \tabularnewline
31 & -0.031201 & -0.2397 & 0.405714 \tabularnewline
32 & -0.02677 & -0.2056 & 0.418898 \tabularnewline
33 & 0.008176 & 0.0628 & 0.475069 \tabularnewline
34 & 0.076967 & 0.5912 & 0.278324 \tabularnewline
35 & -0.277083 & -2.1283 & 0.018749 \tabularnewline
36 & 0.287035 & 2.2048 & 0.015691 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69231&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]-0.409873[/C][C]-3.1483[/C][C]0.001288[/C][/ROW]
[ROW][C]2[/C][C]0.100754[/C][C]0.7739[/C][C]0.221038[/C][/ROW]
[ROW][C]3[/C][C]0.029023[/C][C]0.2229[/C][C]0.41218[/C][/ROW]
[ROW][C]4[/C][C]-0.0197[/C][C]-0.1513[/C][C]0.440121[/C][/ROW]
[ROW][C]5[/C][C]-0.062612[/C][C]-0.4809[/C][C]0.316171[/C][/ROW]
[ROW][C]6[/C][C]-0.042847[/C][C]-0.3291[/C][C]0.371618[/C][/ROW]
[ROW][C]7[/C][C]-0.134587[/C][C]-1.0338[/C][C]0.152729[/C][/ROW]
[ROW][C]8[/C][C]0.071924[/C][C]0.5525[/C][C]0.291361[/C][/ROW]
[ROW][C]9[/C][C]-0.065893[/C][C]-0.5061[/C][C]0.307326[/C][/ROW]
[ROW][C]10[/C][C]0.108486[/C][C]0.8333[/C][C]0.204019[/C][/ROW]
[ROW][C]11[/C][C]0.08756[/C][C]0.6726[/C][C]0.251926[/C][/ROW]
[ROW][C]12[/C][C]-0.307347[/C][C]-2.3608[/C][C]0.01078[/C][/ROW]
[ROW][C]13[/C][C]0.337338[/C][C]2.5911[/C][C]0.006018[/C][/ROW]
[ROW][C]14[/C][C]-0.230707[/C][C]-1.7721[/C][C]0.040771[/C][/ROW]
[ROW][C]15[/C][C]0.032747[/C][C]0.2515[/C][C]0.401138[/C][/ROW]
[ROW][C]16[/C][C]-0.041393[/C][C]-0.3179[/C][C]0.375824[/C][/ROW]
[ROW][C]17[/C][C]0.042122[/C][C]0.3235[/C][C]0.373713[/C][/ROW]
[ROW][C]18[/C][C]-0.086787[/C][C]-0.6666[/C][C]0.253805[/C][/ROW]
[ROW][C]19[/C][C]0.150769[/C][C]1.1581[/C][C]0.125749[/C][/ROW]
[ROW][C]20[/C][C]-0.076526[/C][C]-0.5878[/C][C]0.279452[/C][/ROW]
[ROW][C]21[/C][C]0.061533[/C][C]0.4726[/C][C]0.319105[/C][/ROW]
[ROW][C]22[/C][C]-0.187412[/C][C]-1.4395[/C][C]0.077642[/C][/ROW]
[ROW][C]23[/C][C]0.232052[/C][C]1.7824[/C][C]0.039912[/C][/ROW]
[ROW][C]24[/C][C]-0.071137[/C][C]-0.5464[/C][C]0.29342[/C][/ROW]
[ROW][C]25[/C][C]-0.052122[/C][C]-0.4004[/C][C]0.345171[/C][/ROW]
[ROW][C]26[/C][C]0.118844[/C][C]0.9129[/C][C]0.182517[/C][/ROW]
[ROW][C]27[/C][C]-0.01041[/C][C]-0.08[/C][C]0.46827[/C][/ROW]
[ROW][C]28[/C][C]-0.013509[/C][C]-0.1038[/C][C]0.458853[/C][/ROW]
[ROW][C]29[/C][C]0.100382[/C][C]0.771[/C][C]0.221878[/C][/ROW]
[ROW][C]30[/C][C]-0.107791[/C][C]-0.828[/C][C]0.205515[/C][/ROW]
[ROW][C]31[/C][C]-0.031201[/C][C]-0.2397[/C][C]0.405714[/C][/ROW]
[ROW][C]32[/C][C]-0.02677[/C][C]-0.2056[/C][C]0.418898[/C][/ROW]
[ROW][C]33[/C][C]0.008176[/C][C]0.0628[/C][C]0.475069[/C][/ROW]
[ROW][C]34[/C][C]0.076967[/C][C]0.5912[/C][C]0.278324[/C][/ROW]
[ROW][C]35[/C][C]-0.277083[/C][C]-2.1283[/C][C]0.018749[/C][/ROW]
[ROW][C]36[/C][C]0.287035[/C][C]2.2048[/C][C]0.015691[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69231&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69231&T=1

As an alternative you can also use a QR Code:  

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

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.409873-3.14830.001288
20.1007540.77390.221038
30.0290230.22290.41218
4-0.0197-0.15130.440121
5-0.062612-0.48090.316171
6-0.042847-0.32910.371618
7-0.134587-1.03380.152729
80.0719240.55250.291361
9-0.065893-0.50610.307326
100.1084860.83330.204019
110.087560.67260.251926
12-0.307347-2.36080.01078
130.3373382.59110.006018
14-0.230707-1.77210.040771
150.0327470.25150.401138
16-0.041393-0.31790.375824
170.0421220.32350.373713
18-0.086787-0.66660.253805
190.1507691.15810.125749
20-0.076526-0.58780.279452
210.0615330.47260.319105
22-0.187412-1.43950.077642
230.2320521.78240.039912
24-0.071137-0.54640.29342
25-0.052122-0.40040.345171
260.1188440.91290.182517
27-0.01041-0.080.46827
28-0.013509-0.10380.458853
290.1003820.7710.221878
30-0.107791-0.8280.205515
31-0.031201-0.23970.405714
32-0.02677-0.20560.418898
330.0081760.06280.475069
340.0769670.59120.278324
35-0.277083-2.12830.018749
360.2870352.20480.015691







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.409873-3.14830.001288
2-0.080819-0.62080.268566
30.0490360.37660.353893
40.0231570.17790.429716
5-0.080183-0.61590.270167
6-0.127693-0.98080.165342
7-0.240945-1.85070.034608
8-0.083706-0.6430.261371
9-0.059105-0.4540.32575
100.092390.70970.240356
110.1976921.51850.067115
12-0.320499-2.46180.008383
130.0195720.15030.440506
14-0.154647-1.18790.119824
15-0.073847-0.56720.286356
16-0.046137-0.35440.362156
170.0466040.3580.360822
18-0.085873-0.65960.256038
190.0014810.01140.495482
20-0.012229-0.09390.462741
21-0.090653-0.69630.24448
22-0.242886-1.86560.033533
230.0932240.71610.238388
240.0105770.08120.467762
250.1073470.82450.206475
260.051830.39810.345993
270.0409480.31450.377114
28-0.097788-0.75110.227781
290.0876660.67340.251669
30-0.085913-0.65990.25594
310.0161110.12370.450968
32-0.069071-0.53050.298863
330.0620850.47690.317604
340.0498380.38280.351617
35-0.149611-1.14920.127558
36-0.020811-0.15990.436771

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.409873 & -3.1483 & 0.001288 \tabularnewline
2 & -0.080819 & -0.6208 & 0.268566 \tabularnewline
3 & 0.049036 & 0.3766 & 0.353893 \tabularnewline
4 & 0.023157 & 0.1779 & 0.429716 \tabularnewline
5 & -0.080183 & -0.6159 & 0.270167 \tabularnewline
6 & -0.127693 & -0.9808 & 0.165342 \tabularnewline
7 & -0.240945 & -1.8507 & 0.034608 \tabularnewline
8 & -0.083706 & -0.643 & 0.261371 \tabularnewline
9 & -0.059105 & -0.454 & 0.32575 \tabularnewline
10 & 0.09239 & 0.7097 & 0.240356 \tabularnewline
11 & 0.197692 & 1.5185 & 0.067115 \tabularnewline
12 & -0.320499 & -2.4618 & 0.008383 \tabularnewline
13 & 0.019572 & 0.1503 & 0.440506 \tabularnewline
14 & -0.154647 & -1.1879 & 0.119824 \tabularnewline
15 & -0.073847 & -0.5672 & 0.286356 \tabularnewline
16 & -0.046137 & -0.3544 & 0.362156 \tabularnewline
17 & 0.046604 & 0.358 & 0.360822 \tabularnewline
18 & -0.085873 & -0.6596 & 0.256038 \tabularnewline
19 & 0.001481 & 0.0114 & 0.495482 \tabularnewline
20 & -0.012229 & -0.0939 & 0.462741 \tabularnewline
21 & -0.090653 & -0.6963 & 0.24448 \tabularnewline
22 & -0.242886 & -1.8656 & 0.033533 \tabularnewline
23 & 0.093224 & 0.7161 & 0.238388 \tabularnewline
24 & 0.010577 & 0.0812 & 0.467762 \tabularnewline
25 & 0.107347 & 0.8245 & 0.206475 \tabularnewline
26 & 0.05183 & 0.3981 & 0.345993 \tabularnewline
27 & 0.040948 & 0.3145 & 0.377114 \tabularnewline
28 & -0.097788 & -0.7511 & 0.227781 \tabularnewline
29 & 0.087666 & 0.6734 & 0.251669 \tabularnewline
30 & -0.085913 & -0.6599 & 0.25594 \tabularnewline
31 & 0.016111 & 0.1237 & 0.450968 \tabularnewline
32 & -0.069071 & -0.5305 & 0.298863 \tabularnewline
33 & 0.062085 & 0.4769 & 0.317604 \tabularnewline
34 & 0.049838 & 0.3828 & 0.351617 \tabularnewline
35 & -0.149611 & -1.1492 & 0.127558 \tabularnewline
36 & -0.020811 & -0.1599 & 0.436771 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69231&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]-0.409873[/C][C]-3.1483[/C][C]0.001288[/C][/ROW]
[ROW][C]2[/C][C]-0.080819[/C][C]-0.6208[/C][C]0.268566[/C][/ROW]
[ROW][C]3[/C][C]0.049036[/C][C]0.3766[/C][C]0.353893[/C][/ROW]
[ROW][C]4[/C][C]0.023157[/C][C]0.1779[/C][C]0.429716[/C][/ROW]
[ROW][C]5[/C][C]-0.080183[/C][C]-0.6159[/C][C]0.270167[/C][/ROW]
[ROW][C]6[/C][C]-0.127693[/C][C]-0.9808[/C][C]0.165342[/C][/ROW]
[ROW][C]7[/C][C]-0.240945[/C][C]-1.8507[/C][C]0.034608[/C][/ROW]
[ROW][C]8[/C][C]-0.083706[/C][C]-0.643[/C][C]0.261371[/C][/ROW]
[ROW][C]9[/C][C]-0.059105[/C][C]-0.454[/C][C]0.32575[/C][/ROW]
[ROW][C]10[/C][C]0.09239[/C][C]0.7097[/C][C]0.240356[/C][/ROW]
[ROW][C]11[/C][C]0.197692[/C][C]1.5185[/C][C]0.067115[/C][/ROW]
[ROW][C]12[/C][C]-0.320499[/C][C]-2.4618[/C][C]0.008383[/C][/ROW]
[ROW][C]13[/C][C]0.019572[/C][C]0.1503[/C][C]0.440506[/C][/ROW]
[ROW][C]14[/C][C]-0.154647[/C][C]-1.1879[/C][C]0.119824[/C][/ROW]
[ROW][C]15[/C][C]-0.073847[/C][C]-0.5672[/C][C]0.286356[/C][/ROW]
[ROW][C]16[/C][C]-0.046137[/C][C]-0.3544[/C][C]0.362156[/C][/ROW]
[ROW][C]17[/C][C]0.046604[/C][C]0.358[/C][C]0.360822[/C][/ROW]
[ROW][C]18[/C][C]-0.085873[/C][C]-0.6596[/C][C]0.256038[/C][/ROW]
[ROW][C]19[/C][C]0.001481[/C][C]0.0114[/C][C]0.495482[/C][/ROW]
[ROW][C]20[/C][C]-0.012229[/C][C]-0.0939[/C][C]0.462741[/C][/ROW]
[ROW][C]21[/C][C]-0.090653[/C][C]-0.6963[/C][C]0.24448[/C][/ROW]
[ROW][C]22[/C][C]-0.242886[/C][C]-1.8656[/C][C]0.033533[/C][/ROW]
[ROW][C]23[/C][C]0.093224[/C][C]0.7161[/C][C]0.238388[/C][/ROW]
[ROW][C]24[/C][C]0.010577[/C][C]0.0812[/C][C]0.467762[/C][/ROW]
[ROW][C]25[/C][C]0.107347[/C][C]0.8245[/C][C]0.206475[/C][/ROW]
[ROW][C]26[/C][C]0.05183[/C][C]0.3981[/C][C]0.345993[/C][/ROW]
[ROW][C]27[/C][C]0.040948[/C][C]0.3145[/C][C]0.377114[/C][/ROW]
[ROW][C]28[/C][C]-0.097788[/C][C]-0.7511[/C][C]0.227781[/C][/ROW]
[ROW][C]29[/C][C]0.087666[/C][C]0.6734[/C][C]0.251669[/C][/ROW]
[ROW][C]30[/C][C]-0.085913[/C][C]-0.6599[/C][C]0.25594[/C][/ROW]
[ROW][C]31[/C][C]0.016111[/C][C]0.1237[/C][C]0.450968[/C][/ROW]
[ROW][C]32[/C][C]-0.069071[/C][C]-0.5305[/C][C]0.298863[/C][/ROW]
[ROW][C]33[/C][C]0.062085[/C][C]0.4769[/C][C]0.317604[/C][/ROW]
[ROW][C]34[/C][C]0.049838[/C][C]0.3828[/C][C]0.351617[/C][/ROW]
[ROW][C]35[/C][C]-0.149611[/C][C]-1.1492[/C][C]0.127558[/C][/ROW]
[ROW][C]36[/C][C]-0.020811[/C][C]-0.1599[/C][C]0.436771[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69231&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69231&T=2

As an alternative you can also use a QR Code:  

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

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.409873-3.14830.001288
2-0.080819-0.62080.268566
30.0490360.37660.353893
40.0231570.17790.429716
5-0.080183-0.61590.270167
6-0.127693-0.98080.165342
7-0.240945-1.85070.034608
8-0.083706-0.6430.261371
9-0.059105-0.4540.32575
100.092390.70970.240356
110.1976921.51850.067115
12-0.320499-2.46180.008383
130.0195720.15030.440506
14-0.154647-1.18790.119824
15-0.073847-0.56720.286356
16-0.046137-0.35440.362156
170.0466040.3580.360822
18-0.085873-0.65960.256038
190.0014810.01140.495482
20-0.012229-0.09390.462741
21-0.090653-0.69630.24448
22-0.242886-1.86560.033533
230.0932240.71610.238388
240.0105770.08120.467762
250.1073470.82450.206475
260.051830.39810.345993
270.0409480.31450.377114
28-0.097788-0.75110.227781
290.0876660.67340.251669
30-0.085913-0.65990.25594
310.0161110.12370.450968
32-0.069071-0.53050.298863
330.0620850.47690.317604
340.0498380.38280.351617
35-0.149611-1.14920.127558
36-0.020811-0.15990.436771



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; 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')