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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, 27 Nov 2009 15:11:12 -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/Nov/27/t1259360150npmtfkkiy31u5vv.htm/, Retrieved Sun, 28 Apr 2024 20:37:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61309, Retrieved Sun, 28 Apr 2024 20:37:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact97
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       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:19:56] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [Model 1 met d=0, ...] [2009-11-27 22:11:12] [7d2d29a9bcbcfc0ea3924e19a42d8563] [Current]
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Dataseries X:
104.08
103.86
107.47
111.1
117.33
119.04
123.68
125.9
124.54
119.39
118.8
114.81
117.9
120.53
125.15
126.49
131.85
127.4
131.08
122.37
124.34
119.61
119.97
116.46
117.03
120.96
124.71
127.08
131.91
137.69
142.46
144.32
138.06
124.45
126.71
121.83
122.51
125.48
127.77
128.03
132.84
133.41
139.99
138.53
136.12
124.75
122.88
121.46
118.4
122.45
128.94
133.25
137.94
140.04
130.74
131.55
129.47
125.45
127.87
124.68




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=61309&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=61309&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61309&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
10.7498125.19492e-06
20.5305293.67560.000299
30.2518541.74490.043701
40.1002850.69480.245267
50.0532980.36930.35678
60.0100340.06950.472434
7-0.056081-0.38850.349668
8-0.077412-0.53630.297106
9-0.156942-1.08730.141162
10-0.241936-1.67620.050103
11-0.216146-1.49750.070405
12-0.223482-1.54830.064056
13-0.034154-0.23660.406978
140.0427990.29650.384056
150.1337560.92670.179363
160.1920791.33080.094777
170.193921.34350.092711
180.1870581.2960.10059
190.1741151.20630.116807
200.1331940.92280.180365
210.123790.85760.197675
220.0867550.60110.275314
23-0.069785-0.48350.315475
24-0.128051-0.88720.189708
25-0.210644-1.45940.075487
26-0.157118-1.08850.140894
27-0.126362-0.87550.192842
28-0.114838-0.79560.215086
29-0.110085-0.76270.22469
30-0.114813-0.79540.215135
31-0.131917-0.91390.182657
32-0.133149-0.92250.180445
33-0.122387-0.84790.200345
34-0.104633-0.72490.236011
35-0.023708-0.16430.435111
36-0.032567-0.22560.411223

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.749812 & 5.1949 & 2e-06 \tabularnewline
2 & 0.530529 & 3.6756 & 0.000299 \tabularnewline
3 & 0.251854 & 1.7449 & 0.043701 \tabularnewline
4 & 0.100285 & 0.6948 & 0.245267 \tabularnewline
5 & 0.053298 & 0.3693 & 0.35678 \tabularnewline
6 & 0.010034 & 0.0695 & 0.472434 \tabularnewline
7 & -0.056081 & -0.3885 & 0.349668 \tabularnewline
8 & -0.077412 & -0.5363 & 0.297106 \tabularnewline
9 & -0.156942 & -1.0873 & 0.141162 \tabularnewline
10 & -0.241936 & -1.6762 & 0.050103 \tabularnewline
11 & -0.216146 & -1.4975 & 0.070405 \tabularnewline
12 & -0.223482 & -1.5483 & 0.064056 \tabularnewline
13 & -0.034154 & -0.2366 & 0.406978 \tabularnewline
14 & 0.042799 & 0.2965 & 0.384056 \tabularnewline
15 & 0.133756 & 0.9267 & 0.179363 \tabularnewline
16 & 0.192079 & 1.3308 & 0.094777 \tabularnewline
17 & 0.19392 & 1.3435 & 0.092711 \tabularnewline
18 & 0.187058 & 1.296 & 0.10059 \tabularnewline
19 & 0.174115 & 1.2063 & 0.116807 \tabularnewline
20 & 0.133194 & 0.9228 & 0.180365 \tabularnewline
21 & 0.12379 & 0.8576 & 0.197675 \tabularnewline
22 & 0.086755 & 0.6011 & 0.275314 \tabularnewline
23 & -0.069785 & -0.4835 & 0.315475 \tabularnewline
24 & -0.128051 & -0.8872 & 0.189708 \tabularnewline
25 & -0.210644 & -1.4594 & 0.075487 \tabularnewline
26 & -0.157118 & -1.0885 & 0.140894 \tabularnewline
27 & -0.126362 & -0.8755 & 0.192842 \tabularnewline
28 & -0.114838 & -0.7956 & 0.215086 \tabularnewline
29 & -0.110085 & -0.7627 & 0.22469 \tabularnewline
30 & -0.114813 & -0.7954 & 0.215135 \tabularnewline
31 & -0.131917 & -0.9139 & 0.182657 \tabularnewline
32 & -0.133149 & -0.9225 & 0.180445 \tabularnewline
33 & -0.122387 & -0.8479 & 0.200345 \tabularnewline
34 & -0.104633 & -0.7249 & 0.236011 \tabularnewline
35 & -0.023708 & -0.1643 & 0.435111 \tabularnewline
36 & -0.032567 & -0.2256 & 0.411223 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61309&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]0.749812[/C][C]5.1949[/C][C]2e-06[/C][/ROW]
[ROW][C]2[/C][C]0.530529[/C][C]3.6756[/C][C]0.000299[/C][/ROW]
[ROW][C]3[/C][C]0.251854[/C][C]1.7449[/C][C]0.043701[/C][/ROW]
[ROW][C]4[/C][C]0.100285[/C][C]0.6948[/C][C]0.245267[/C][/ROW]
[ROW][C]5[/C][C]0.053298[/C][C]0.3693[/C][C]0.35678[/C][/ROW]
[ROW][C]6[/C][C]0.010034[/C][C]0.0695[/C][C]0.472434[/C][/ROW]
[ROW][C]7[/C][C]-0.056081[/C][C]-0.3885[/C][C]0.349668[/C][/ROW]
[ROW][C]8[/C][C]-0.077412[/C][C]-0.5363[/C][C]0.297106[/C][/ROW]
[ROW][C]9[/C][C]-0.156942[/C][C]-1.0873[/C][C]0.141162[/C][/ROW]
[ROW][C]10[/C][C]-0.241936[/C][C]-1.6762[/C][C]0.050103[/C][/ROW]
[ROW][C]11[/C][C]-0.216146[/C][C]-1.4975[/C][C]0.070405[/C][/ROW]
[ROW][C]12[/C][C]-0.223482[/C][C]-1.5483[/C][C]0.064056[/C][/ROW]
[ROW][C]13[/C][C]-0.034154[/C][C]-0.2366[/C][C]0.406978[/C][/ROW]
[ROW][C]14[/C][C]0.042799[/C][C]0.2965[/C][C]0.384056[/C][/ROW]
[ROW][C]15[/C][C]0.133756[/C][C]0.9267[/C][C]0.179363[/C][/ROW]
[ROW][C]16[/C][C]0.192079[/C][C]1.3308[/C][C]0.094777[/C][/ROW]
[ROW][C]17[/C][C]0.19392[/C][C]1.3435[/C][C]0.092711[/C][/ROW]
[ROW][C]18[/C][C]0.187058[/C][C]1.296[/C][C]0.10059[/C][/ROW]
[ROW][C]19[/C][C]0.174115[/C][C]1.2063[/C][C]0.116807[/C][/ROW]
[ROW][C]20[/C][C]0.133194[/C][C]0.9228[/C][C]0.180365[/C][/ROW]
[ROW][C]21[/C][C]0.12379[/C][C]0.8576[/C][C]0.197675[/C][/ROW]
[ROW][C]22[/C][C]0.086755[/C][C]0.6011[/C][C]0.275314[/C][/ROW]
[ROW][C]23[/C][C]-0.069785[/C][C]-0.4835[/C][C]0.315475[/C][/ROW]
[ROW][C]24[/C][C]-0.128051[/C][C]-0.8872[/C][C]0.189708[/C][/ROW]
[ROW][C]25[/C][C]-0.210644[/C][C]-1.4594[/C][C]0.075487[/C][/ROW]
[ROW][C]26[/C][C]-0.157118[/C][C]-1.0885[/C][C]0.140894[/C][/ROW]
[ROW][C]27[/C][C]-0.126362[/C][C]-0.8755[/C][C]0.192842[/C][/ROW]
[ROW][C]28[/C][C]-0.114838[/C][C]-0.7956[/C][C]0.215086[/C][/ROW]
[ROW][C]29[/C][C]-0.110085[/C][C]-0.7627[/C][C]0.22469[/C][/ROW]
[ROW][C]30[/C][C]-0.114813[/C][C]-0.7954[/C][C]0.215135[/C][/ROW]
[ROW][C]31[/C][C]-0.131917[/C][C]-0.9139[/C][C]0.182657[/C][/ROW]
[ROW][C]32[/C][C]-0.133149[/C][C]-0.9225[/C][C]0.180445[/C][/ROW]
[ROW][C]33[/C][C]-0.122387[/C][C]-0.8479[/C][C]0.200345[/C][/ROW]
[ROW][C]34[/C][C]-0.104633[/C][C]-0.7249[/C][C]0.236011[/C][/ROW]
[ROW][C]35[/C][C]-0.023708[/C][C]-0.1643[/C][C]0.435111[/C][/ROW]
[ROW][C]36[/C][C]-0.032567[/C][C]-0.2256[/C][C]0.411223[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61309&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61309&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
10.7498125.19492e-06
20.5305293.67560.000299
30.2518541.74490.043701
40.1002850.69480.245267
50.0532980.36930.35678
60.0100340.06950.472434
7-0.056081-0.38850.349668
8-0.077412-0.53630.297106
9-0.156942-1.08730.141162
10-0.241936-1.67620.050103
11-0.216146-1.49750.070405
12-0.223482-1.54830.064056
13-0.034154-0.23660.406978
140.0427990.29650.384056
150.1337560.92670.179363
160.1920791.33080.094777
170.193921.34350.092711
180.1870581.2960.10059
190.1741151.20630.116807
200.1331940.92280.180365
210.123790.85760.197675
220.0867550.60110.275314
23-0.069785-0.48350.315475
24-0.128051-0.88720.189708
25-0.210644-1.45940.075487
26-0.157118-1.08850.140894
27-0.126362-0.87550.192842
28-0.114838-0.79560.215086
29-0.110085-0.76270.22469
30-0.114813-0.79540.215135
31-0.131917-0.91390.182657
32-0.133149-0.92250.180445
33-0.122387-0.84790.200345
34-0.104633-0.72490.236011
35-0.023708-0.16430.435111
36-0.032567-0.22560.411223







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7498125.19492e-06
2-0.072386-0.50150.309153
3-0.276612-1.91640.030638
40.0761490.52760.300113
50.1474991.02190.155975
6-0.126029-0.87320.193463
7-0.170866-1.18380.121162
80.1235250.85580.198179
9-0.142329-0.98610.164518
10-0.253837-1.75860.042507
110.2680061.85680.034741
12-0.071269-0.49380.311863
130.231511.60390.057643
14-0.095973-0.66490.254643
150.0776840.53820.29646
160.1576661.09230.140068
17-0.09755-0.67580.251192
180.016060.11130.455934
190.0024470.0170.493271
200.0465850.32280.374142
21-0.058473-0.40510.343597
22-0.100784-0.69830.244194
23-0.168909-1.17020.123841
240.0758260.52530.300884
250.1347050.93330.177677
26-0.036118-0.25020.401738
27-0.090973-0.63030.26575
280.0628470.43540.332607
29-0.013606-0.09430.462645
30-0.132445-0.91760.181706
31-0.041609-0.28830.387189
32-0.030553-0.21170.416629
33-0.029997-0.20780.418121
34-0.107662-0.74590.229682
350.0049180.03410.486479
360.0483690.33510.369501

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.749812 & 5.1949 & 2e-06 \tabularnewline
2 & -0.072386 & -0.5015 & 0.309153 \tabularnewline
3 & -0.276612 & -1.9164 & 0.030638 \tabularnewline
4 & 0.076149 & 0.5276 & 0.300113 \tabularnewline
5 & 0.147499 & 1.0219 & 0.155975 \tabularnewline
6 & -0.126029 & -0.8732 & 0.193463 \tabularnewline
7 & -0.170866 & -1.1838 & 0.121162 \tabularnewline
8 & 0.123525 & 0.8558 & 0.198179 \tabularnewline
9 & -0.142329 & -0.9861 & 0.164518 \tabularnewline
10 & -0.253837 & -1.7586 & 0.042507 \tabularnewline
11 & 0.268006 & 1.8568 & 0.034741 \tabularnewline
12 & -0.071269 & -0.4938 & 0.311863 \tabularnewline
13 & 0.23151 & 1.6039 & 0.057643 \tabularnewline
14 & -0.095973 & -0.6649 & 0.254643 \tabularnewline
15 & 0.077684 & 0.5382 & 0.29646 \tabularnewline
16 & 0.157666 & 1.0923 & 0.140068 \tabularnewline
17 & -0.09755 & -0.6758 & 0.251192 \tabularnewline
18 & 0.01606 & 0.1113 & 0.455934 \tabularnewline
19 & 0.002447 & 0.017 & 0.493271 \tabularnewline
20 & 0.046585 & 0.3228 & 0.374142 \tabularnewline
21 & -0.058473 & -0.4051 & 0.343597 \tabularnewline
22 & -0.100784 & -0.6983 & 0.244194 \tabularnewline
23 & -0.168909 & -1.1702 & 0.123841 \tabularnewline
24 & 0.075826 & 0.5253 & 0.300884 \tabularnewline
25 & 0.134705 & 0.9333 & 0.177677 \tabularnewline
26 & -0.036118 & -0.2502 & 0.401738 \tabularnewline
27 & -0.090973 & -0.6303 & 0.26575 \tabularnewline
28 & 0.062847 & 0.4354 & 0.332607 \tabularnewline
29 & -0.013606 & -0.0943 & 0.462645 \tabularnewline
30 & -0.132445 & -0.9176 & 0.181706 \tabularnewline
31 & -0.041609 & -0.2883 & 0.387189 \tabularnewline
32 & -0.030553 & -0.2117 & 0.416629 \tabularnewline
33 & -0.029997 & -0.2078 & 0.418121 \tabularnewline
34 & -0.107662 & -0.7459 & 0.229682 \tabularnewline
35 & 0.004918 & 0.0341 & 0.486479 \tabularnewline
36 & 0.048369 & 0.3351 & 0.369501 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61309&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]0.749812[/C][C]5.1949[/C][C]2e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.072386[/C][C]-0.5015[/C][C]0.309153[/C][/ROW]
[ROW][C]3[/C][C]-0.276612[/C][C]-1.9164[/C][C]0.030638[/C][/ROW]
[ROW][C]4[/C][C]0.076149[/C][C]0.5276[/C][C]0.300113[/C][/ROW]
[ROW][C]5[/C][C]0.147499[/C][C]1.0219[/C][C]0.155975[/C][/ROW]
[ROW][C]6[/C][C]-0.126029[/C][C]-0.8732[/C][C]0.193463[/C][/ROW]
[ROW][C]7[/C][C]-0.170866[/C][C]-1.1838[/C][C]0.121162[/C][/ROW]
[ROW][C]8[/C][C]0.123525[/C][C]0.8558[/C][C]0.198179[/C][/ROW]
[ROW][C]9[/C][C]-0.142329[/C][C]-0.9861[/C][C]0.164518[/C][/ROW]
[ROW][C]10[/C][C]-0.253837[/C][C]-1.7586[/C][C]0.042507[/C][/ROW]
[ROW][C]11[/C][C]0.268006[/C][C]1.8568[/C][C]0.034741[/C][/ROW]
[ROW][C]12[/C][C]-0.071269[/C][C]-0.4938[/C][C]0.311863[/C][/ROW]
[ROW][C]13[/C][C]0.23151[/C][C]1.6039[/C][C]0.057643[/C][/ROW]
[ROW][C]14[/C][C]-0.095973[/C][C]-0.6649[/C][C]0.254643[/C][/ROW]
[ROW][C]15[/C][C]0.077684[/C][C]0.5382[/C][C]0.29646[/C][/ROW]
[ROW][C]16[/C][C]0.157666[/C][C]1.0923[/C][C]0.140068[/C][/ROW]
[ROW][C]17[/C][C]-0.09755[/C][C]-0.6758[/C][C]0.251192[/C][/ROW]
[ROW][C]18[/C][C]0.01606[/C][C]0.1113[/C][C]0.455934[/C][/ROW]
[ROW][C]19[/C][C]0.002447[/C][C]0.017[/C][C]0.493271[/C][/ROW]
[ROW][C]20[/C][C]0.046585[/C][C]0.3228[/C][C]0.374142[/C][/ROW]
[ROW][C]21[/C][C]-0.058473[/C][C]-0.4051[/C][C]0.343597[/C][/ROW]
[ROW][C]22[/C][C]-0.100784[/C][C]-0.6983[/C][C]0.244194[/C][/ROW]
[ROW][C]23[/C][C]-0.168909[/C][C]-1.1702[/C][C]0.123841[/C][/ROW]
[ROW][C]24[/C][C]0.075826[/C][C]0.5253[/C][C]0.300884[/C][/ROW]
[ROW][C]25[/C][C]0.134705[/C][C]0.9333[/C][C]0.177677[/C][/ROW]
[ROW][C]26[/C][C]-0.036118[/C][C]-0.2502[/C][C]0.401738[/C][/ROW]
[ROW][C]27[/C][C]-0.090973[/C][C]-0.6303[/C][C]0.26575[/C][/ROW]
[ROW][C]28[/C][C]0.062847[/C][C]0.4354[/C][C]0.332607[/C][/ROW]
[ROW][C]29[/C][C]-0.013606[/C][C]-0.0943[/C][C]0.462645[/C][/ROW]
[ROW][C]30[/C][C]-0.132445[/C][C]-0.9176[/C][C]0.181706[/C][/ROW]
[ROW][C]31[/C][C]-0.041609[/C][C]-0.2883[/C][C]0.387189[/C][/ROW]
[ROW][C]32[/C][C]-0.030553[/C][C]-0.2117[/C][C]0.416629[/C][/ROW]
[ROW][C]33[/C][C]-0.029997[/C][C]-0.2078[/C][C]0.418121[/C][/ROW]
[ROW][C]34[/C][C]-0.107662[/C][C]-0.7459[/C][C]0.229682[/C][/ROW]
[ROW][C]35[/C][C]0.004918[/C][C]0.0341[/C][C]0.486479[/C][/ROW]
[ROW][C]36[/C][C]0.048369[/C][C]0.3351[/C][C]0.369501[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61309&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61309&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
10.7498125.19492e-06
2-0.072386-0.50150.309153
3-0.276612-1.91640.030638
40.0761490.52760.300113
50.1474991.02190.155975
6-0.126029-0.87320.193463
7-0.170866-1.18380.121162
80.1235250.85580.198179
9-0.142329-0.98610.164518
10-0.253837-1.75860.042507
110.2680061.85680.034741
12-0.071269-0.49380.311863
130.231511.60390.057643
14-0.095973-0.66490.254643
150.0776840.53820.29646
160.1576661.09230.140068
17-0.09755-0.67580.251192
180.016060.11130.455934
190.0024470.0170.493271
200.0465850.32280.374142
21-0.058473-0.40510.343597
22-0.100784-0.69830.244194
23-0.168909-1.17020.123841
240.0758260.52530.300884
250.1347050.93330.177677
26-0.036118-0.25020.401738
27-0.090973-0.63030.26575
280.0628470.43540.332607
29-0.013606-0.09430.462645
30-0.132445-0.91760.181706
31-0.041609-0.28830.387189
32-0.030553-0.21170.416629
33-0.029997-0.20780.418121
34-0.107662-0.74590.229682
350.0049180.03410.486479
360.0483690.33510.369501



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