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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 08:00:41 -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/t1259334160qee2bhz45gwk8qz.htm/, Retrieved Mon, 29 Apr 2024 04:38:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60869, Retrieved Mon, 29 Apr 2024 04:38:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact121
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 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [] [2009-11-27 15:00:41] [cb3e966d7bf80cd999a0432e97d174a7] [Current]
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Dataseries X:
103,5
104,6
118,6
106,3
110,7
121,6
107
107,6
125,6
113,5
129,2
130,9
104,7
115,2
124,5
112,3
127,5
120,6
117,5
117,7
120,4
125
131,6
121,1
114,2
112,1
127
116,8
112
129,7
113,6
115,7
119,5
125,8
129,6
128
112,8
101,6
123,9
118,8
109,1
130,6
112,4
111
116,2
119,8
117,2
127,3
107,7
97,5
120,1
110,6
111,3
119,8
105,5
108,7
128,7
119,5
121,1
128,4




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=60869&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=60869&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60869&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
10.0455080.35250.362849
2-0.137553-1.06550.145463
30.3023222.34180.011265
4-0.204869-1.58690.058895
50.0141180.10940.456641
60.4171453.23120.001002
7-0.138398-1.0720.144001
8-0.165745-1.28390.102064
90.1011040.78310.21831
10-0.286897-2.22230.015022
11-0.020425-0.15820.437409
120.4697963.6390.000286
13-0.010395-0.08050.468047
14-0.200811-1.55550.062546
15-0.006552-0.05080.479845
16-0.179444-1.390.084837
17-0.107684-0.83410.203762
180.1777751.3770.086808
19-0.085561-0.66280.255013
20-0.241312-1.86920.03324
21-0.014686-0.11380.454906
22-0.158771-1.22980.111779
23-0.088369-0.68450.248145
240.2765732.14230.018117
250.1108860.85890.196902
26-0.235807-1.82660.036371
27-0.00757-0.05860.476719
28-0.099537-0.7710.221862
29-0.198184-1.53510.065005
300.1274760.98740.163701
310.0077080.05970.476295
32-0.246041-1.90580.030733
33-0.038615-0.29910.382945
34-0.046979-0.36390.358606
35-0.145449-1.12660.13219
360.2116841.63970.053151

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.045508 & 0.3525 & 0.362849 \tabularnewline
2 & -0.137553 & -1.0655 & 0.145463 \tabularnewline
3 & 0.302322 & 2.3418 & 0.011265 \tabularnewline
4 & -0.204869 & -1.5869 & 0.058895 \tabularnewline
5 & 0.014118 & 0.1094 & 0.456641 \tabularnewline
6 & 0.417145 & 3.2312 & 0.001002 \tabularnewline
7 & -0.138398 & -1.072 & 0.144001 \tabularnewline
8 & -0.165745 & -1.2839 & 0.102064 \tabularnewline
9 & 0.101104 & 0.7831 & 0.21831 \tabularnewline
10 & -0.286897 & -2.2223 & 0.015022 \tabularnewline
11 & -0.020425 & -0.1582 & 0.437409 \tabularnewline
12 & 0.469796 & 3.639 & 0.000286 \tabularnewline
13 & -0.010395 & -0.0805 & 0.468047 \tabularnewline
14 & -0.200811 & -1.5555 & 0.062546 \tabularnewline
15 & -0.006552 & -0.0508 & 0.479845 \tabularnewline
16 & -0.179444 & -1.39 & 0.084837 \tabularnewline
17 & -0.107684 & -0.8341 & 0.203762 \tabularnewline
18 & 0.177775 & 1.377 & 0.086808 \tabularnewline
19 & -0.085561 & -0.6628 & 0.255013 \tabularnewline
20 & -0.241312 & -1.8692 & 0.03324 \tabularnewline
21 & -0.014686 & -0.1138 & 0.454906 \tabularnewline
22 & -0.158771 & -1.2298 & 0.111779 \tabularnewline
23 & -0.088369 & -0.6845 & 0.248145 \tabularnewline
24 & 0.276573 & 2.1423 & 0.018117 \tabularnewline
25 & 0.110886 & 0.8589 & 0.196902 \tabularnewline
26 & -0.235807 & -1.8266 & 0.036371 \tabularnewline
27 & -0.00757 & -0.0586 & 0.476719 \tabularnewline
28 & -0.099537 & -0.771 & 0.221862 \tabularnewline
29 & -0.198184 & -1.5351 & 0.065005 \tabularnewline
30 & 0.127476 & 0.9874 & 0.163701 \tabularnewline
31 & 0.007708 & 0.0597 & 0.476295 \tabularnewline
32 & -0.246041 & -1.9058 & 0.030733 \tabularnewline
33 & -0.038615 & -0.2991 & 0.382945 \tabularnewline
34 & -0.046979 & -0.3639 & 0.358606 \tabularnewline
35 & -0.145449 & -1.1266 & 0.13219 \tabularnewline
36 & 0.211684 & 1.6397 & 0.053151 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60869&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]0.045508[/C][C]0.3525[/C][C]0.362849[/C][/ROW]
[ROW][C]2[/C][C]-0.137553[/C][C]-1.0655[/C][C]0.145463[/C][/ROW]
[ROW][C]3[/C][C]0.302322[/C][C]2.3418[/C][C]0.011265[/C][/ROW]
[ROW][C]4[/C][C]-0.204869[/C][C]-1.5869[/C][C]0.058895[/C][/ROW]
[ROW][C]5[/C][C]0.014118[/C][C]0.1094[/C][C]0.456641[/C][/ROW]
[ROW][C]6[/C][C]0.417145[/C][C]3.2312[/C][C]0.001002[/C][/ROW]
[ROW][C]7[/C][C]-0.138398[/C][C]-1.072[/C][C]0.144001[/C][/ROW]
[ROW][C]8[/C][C]-0.165745[/C][C]-1.2839[/C][C]0.102064[/C][/ROW]
[ROW][C]9[/C][C]0.101104[/C][C]0.7831[/C][C]0.21831[/C][/ROW]
[ROW][C]10[/C][C]-0.286897[/C][C]-2.2223[/C][C]0.015022[/C][/ROW]
[ROW][C]11[/C][C]-0.020425[/C][C]-0.1582[/C][C]0.437409[/C][/ROW]
[ROW][C]12[/C][C]0.469796[/C][C]3.639[/C][C]0.000286[/C][/ROW]
[ROW][C]13[/C][C]-0.010395[/C][C]-0.0805[/C][C]0.468047[/C][/ROW]
[ROW][C]14[/C][C]-0.200811[/C][C]-1.5555[/C][C]0.062546[/C][/ROW]
[ROW][C]15[/C][C]-0.006552[/C][C]-0.0508[/C][C]0.479845[/C][/ROW]
[ROW][C]16[/C][C]-0.179444[/C][C]-1.39[/C][C]0.084837[/C][/ROW]
[ROW][C]17[/C][C]-0.107684[/C][C]-0.8341[/C][C]0.203762[/C][/ROW]
[ROW][C]18[/C][C]0.177775[/C][C]1.377[/C][C]0.086808[/C][/ROW]
[ROW][C]19[/C][C]-0.085561[/C][C]-0.6628[/C][C]0.255013[/C][/ROW]
[ROW][C]20[/C][C]-0.241312[/C][C]-1.8692[/C][C]0.03324[/C][/ROW]
[ROW][C]21[/C][C]-0.014686[/C][C]-0.1138[/C][C]0.454906[/C][/ROW]
[ROW][C]22[/C][C]-0.158771[/C][C]-1.2298[/C][C]0.111779[/C][/ROW]
[ROW][C]23[/C][C]-0.088369[/C][C]-0.6845[/C][C]0.248145[/C][/ROW]
[ROW][C]24[/C][C]0.276573[/C][C]2.1423[/C][C]0.018117[/C][/ROW]
[ROW][C]25[/C][C]0.110886[/C][C]0.8589[/C][C]0.196902[/C][/ROW]
[ROW][C]26[/C][C]-0.235807[/C][C]-1.8266[/C][C]0.036371[/C][/ROW]
[ROW][C]27[/C][C]-0.00757[/C][C]-0.0586[/C][C]0.476719[/C][/ROW]
[ROW][C]28[/C][C]-0.099537[/C][C]-0.771[/C][C]0.221862[/C][/ROW]
[ROW][C]29[/C][C]-0.198184[/C][C]-1.5351[/C][C]0.065005[/C][/ROW]
[ROW][C]30[/C][C]0.127476[/C][C]0.9874[/C][C]0.163701[/C][/ROW]
[ROW][C]31[/C][C]0.007708[/C][C]0.0597[/C][C]0.476295[/C][/ROW]
[ROW][C]32[/C][C]-0.246041[/C][C]-1.9058[/C][C]0.030733[/C][/ROW]
[ROW][C]33[/C][C]-0.038615[/C][C]-0.2991[/C][C]0.382945[/C][/ROW]
[ROW][C]34[/C][C]-0.046979[/C][C]-0.3639[/C][C]0.358606[/C][/ROW]
[ROW][C]35[/C][C]-0.145449[/C][C]-1.1266[/C][C]0.13219[/C][/ROW]
[ROW][C]36[/C][C]0.211684[/C][C]1.6397[/C][C]0.053151[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60869&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60869&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
10.0455080.35250.362849
2-0.137553-1.06550.145463
30.3023222.34180.011265
4-0.204869-1.58690.058895
50.0141180.10940.456641
60.4171453.23120.001002
7-0.138398-1.0720.144001
8-0.165745-1.28390.102064
90.1011040.78310.21831
10-0.286897-2.22230.015022
11-0.020425-0.15820.437409
120.4697963.6390.000286
13-0.010395-0.08050.468047
14-0.200811-1.55550.062546
15-0.006552-0.05080.479845
16-0.179444-1.390.084837
17-0.107684-0.83410.203762
180.1777751.3770.086808
19-0.085561-0.66280.255013
20-0.241312-1.86920.03324
21-0.014686-0.11380.454906
22-0.158771-1.22980.111779
23-0.088369-0.68450.248145
240.2765732.14230.018117
250.1108860.85890.196902
26-0.235807-1.82660.036371
27-0.00757-0.05860.476719
28-0.099537-0.7710.221862
29-0.198184-1.53510.065005
300.1274760.98740.163701
310.0077080.05970.476295
32-0.246041-1.90580.030733
33-0.038615-0.29910.382945
34-0.046979-0.36390.358606
35-0.145449-1.12660.13219
360.2116841.63970.053151







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0455080.35250.362849
2-0.139914-1.08380.141401
30.3227992.50040.007578
4-0.30857-2.39020.009999
50.2256561.74790.042797
60.2333681.80770.037837
7-0.089216-0.69110.246095
8-0.166142-1.28690.101531
9-0.047066-0.36460.358357
10-0.179867-1.39320.084343
110.0654630.50710.306981
120.3562062.75920.003836
130.1325891.0270.154265
14-0.245904-1.90480.030804
15-0.261882-2.02850.023476
160.0230850.17880.429344
17-0.146801-1.13710.130006
18-0.111924-0.8670.19471
190.0067060.05190.479372
200.0062980.04880.480627
210.0215880.16720.433879
220.0435610.33740.368489
230.0411870.3190.375406
24-0.070167-0.54350.294395
250.0481830.37320.355148
26-0.168351-1.3040.0986
270.0133810.10370.458896
28-0.18487-1.4320.078667
29-0.103183-0.79930.213649
30-0.139229-1.07850.142572
310.1052120.8150.209157
32-0.011469-0.08880.464752
33-0.047208-0.36570.357948
340.0373320.28920.386722
35-0.05078-0.39330.347731
36-0.072461-0.56130.288349

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.045508 & 0.3525 & 0.362849 \tabularnewline
2 & -0.139914 & -1.0838 & 0.141401 \tabularnewline
3 & 0.322799 & 2.5004 & 0.007578 \tabularnewline
4 & -0.30857 & -2.3902 & 0.009999 \tabularnewline
5 & 0.225656 & 1.7479 & 0.042797 \tabularnewline
6 & 0.233368 & 1.8077 & 0.037837 \tabularnewline
7 & -0.089216 & -0.6911 & 0.246095 \tabularnewline
8 & -0.166142 & -1.2869 & 0.101531 \tabularnewline
9 & -0.047066 & -0.3646 & 0.358357 \tabularnewline
10 & -0.179867 & -1.3932 & 0.084343 \tabularnewline
11 & 0.065463 & 0.5071 & 0.306981 \tabularnewline
12 & 0.356206 & 2.7592 & 0.003836 \tabularnewline
13 & 0.132589 & 1.027 & 0.154265 \tabularnewline
14 & -0.245904 & -1.9048 & 0.030804 \tabularnewline
15 & -0.261882 & -2.0285 & 0.023476 \tabularnewline
16 & 0.023085 & 0.1788 & 0.429344 \tabularnewline
17 & -0.146801 & -1.1371 & 0.130006 \tabularnewline
18 & -0.111924 & -0.867 & 0.19471 \tabularnewline
19 & 0.006706 & 0.0519 & 0.479372 \tabularnewline
20 & 0.006298 & 0.0488 & 0.480627 \tabularnewline
21 & 0.021588 & 0.1672 & 0.433879 \tabularnewline
22 & 0.043561 & 0.3374 & 0.368489 \tabularnewline
23 & 0.041187 & 0.319 & 0.375406 \tabularnewline
24 & -0.070167 & -0.5435 & 0.294395 \tabularnewline
25 & 0.048183 & 0.3732 & 0.355148 \tabularnewline
26 & -0.168351 & -1.304 & 0.0986 \tabularnewline
27 & 0.013381 & 0.1037 & 0.458896 \tabularnewline
28 & -0.18487 & -1.432 & 0.078667 \tabularnewline
29 & -0.103183 & -0.7993 & 0.213649 \tabularnewline
30 & -0.139229 & -1.0785 & 0.142572 \tabularnewline
31 & 0.105212 & 0.815 & 0.209157 \tabularnewline
32 & -0.011469 & -0.0888 & 0.464752 \tabularnewline
33 & -0.047208 & -0.3657 & 0.357948 \tabularnewline
34 & 0.037332 & 0.2892 & 0.386722 \tabularnewline
35 & -0.05078 & -0.3933 & 0.347731 \tabularnewline
36 & -0.072461 & -0.5613 & 0.288349 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60869&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]0.045508[/C][C]0.3525[/C][C]0.362849[/C][/ROW]
[ROW][C]2[/C][C]-0.139914[/C][C]-1.0838[/C][C]0.141401[/C][/ROW]
[ROW][C]3[/C][C]0.322799[/C][C]2.5004[/C][C]0.007578[/C][/ROW]
[ROW][C]4[/C][C]-0.30857[/C][C]-2.3902[/C][C]0.009999[/C][/ROW]
[ROW][C]5[/C][C]0.225656[/C][C]1.7479[/C][C]0.042797[/C][/ROW]
[ROW][C]6[/C][C]0.233368[/C][C]1.8077[/C][C]0.037837[/C][/ROW]
[ROW][C]7[/C][C]-0.089216[/C][C]-0.6911[/C][C]0.246095[/C][/ROW]
[ROW][C]8[/C][C]-0.166142[/C][C]-1.2869[/C][C]0.101531[/C][/ROW]
[ROW][C]9[/C][C]-0.047066[/C][C]-0.3646[/C][C]0.358357[/C][/ROW]
[ROW][C]10[/C][C]-0.179867[/C][C]-1.3932[/C][C]0.084343[/C][/ROW]
[ROW][C]11[/C][C]0.065463[/C][C]0.5071[/C][C]0.306981[/C][/ROW]
[ROW][C]12[/C][C]0.356206[/C][C]2.7592[/C][C]0.003836[/C][/ROW]
[ROW][C]13[/C][C]0.132589[/C][C]1.027[/C][C]0.154265[/C][/ROW]
[ROW][C]14[/C][C]-0.245904[/C][C]-1.9048[/C][C]0.030804[/C][/ROW]
[ROW][C]15[/C][C]-0.261882[/C][C]-2.0285[/C][C]0.023476[/C][/ROW]
[ROW][C]16[/C][C]0.023085[/C][C]0.1788[/C][C]0.429344[/C][/ROW]
[ROW][C]17[/C][C]-0.146801[/C][C]-1.1371[/C][C]0.130006[/C][/ROW]
[ROW][C]18[/C][C]-0.111924[/C][C]-0.867[/C][C]0.19471[/C][/ROW]
[ROW][C]19[/C][C]0.006706[/C][C]0.0519[/C][C]0.479372[/C][/ROW]
[ROW][C]20[/C][C]0.006298[/C][C]0.0488[/C][C]0.480627[/C][/ROW]
[ROW][C]21[/C][C]0.021588[/C][C]0.1672[/C][C]0.433879[/C][/ROW]
[ROW][C]22[/C][C]0.043561[/C][C]0.3374[/C][C]0.368489[/C][/ROW]
[ROW][C]23[/C][C]0.041187[/C][C]0.319[/C][C]0.375406[/C][/ROW]
[ROW][C]24[/C][C]-0.070167[/C][C]-0.5435[/C][C]0.294395[/C][/ROW]
[ROW][C]25[/C][C]0.048183[/C][C]0.3732[/C][C]0.355148[/C][/ROW]
[ROW][C]26[/C][C]-0.168351[/C][C]-1.304[/C][C]0.0986[/C][/ROW]
[ROW][C]27[/C][C]0.013381[/C][C]0.1037[/C][C]0.458896[/C][/ROW]
[ROW][C]28[/C][C]-0.18487[/C][C]-1.432[/C][C]0.078667[/C][/ROW]
[ROW][C]29[/C][C]-0.103183[/C][C]-0.7993[/C][C]0.213649[/C][/ROW]
[ROW][C]30[/C][C]-0.139229[/C][C]-1.0785[/C][C]0.142572[/C][/ROW]
[ROW][C]31[/C][C]0.105212[/C][C]0.815[/C][C]0.209157[/C][/ROW]
[ROW][C]32[/C][C]-0.011469[/C][C]-0.0888[/C][C]0.464752[/C][/ROW]
[ROW][C]33[/C][C]-0.047208[/C][C]-0.3657[/C][C]0.357948[/C][/ROW]
[ROW][C]34[/C][C]0.037332[/C][C]0.2892[/C][C]0.386722[/C][/ROW]
[ROW][C]35[/C][C]-0.05078[/C][C]-0.3933[/C][C]0.347731[/C][/ROW]
[ROW][C]36[/C][C]-0.072461[/C][C]-0.5613[/C][C]0.288349[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60869&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60869&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
10.0455080.35250.362849
2-0.139914-1.08380.141401
30.3227992.50040.007578
4-0.30857-2.39020.009999
50.2256561.74790.042797
60.2333681.80770.037837
7-0.089216-0.69110.246095
8-0.166142-1.28690.101531
9-0.047066-0.36460.358357
10-0.179867-1.39320.084343
110.0654630.50710.306981
120.3562062.75920.003836
130.1325891.0270.154265
14-0.245904-1.90480.030804
15-0.261882-2.02850.023476
160.0230850.17880.429344
17-0.146801-1.13710.130006
18-0.111924-0.8670.19471
190.0067060.05190.479372
200.0062980.04880.480627
210.0215880.16720.433879
220.0435610.33740.368489
230.0411870.3190.375406
24-0.070167-0.54350.294395
250.0481830.37320.355148
26-0.168351-1.3040.0986
270.0133810.10370.458896
28-0.18487-1.4320.078667
29-0.103183-0.79930.213649
30-0.139229-1.07850.142572
310.1052120.8150.209157
32-0.011469-0.08880.464752
33-0.047208-0.36570.357948
340.0373320.28920.386722
35-0.05078-0.39330.347731
36-0.072461-0.56130.288349



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