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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 computationThu, 26 Nov 2009 11:56:06 -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/26/t12592620985xaagewxzho9j7q.htm/, Retrieved Sun, 28 Apr 2024 23:01:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60289, Retrieved Sun, 28 Apr 2024 23:01:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact105
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] [] [2009-11-26 18:56:06] [aa8eb70c35ea8a87edcd21d6427e653e] [Current]
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Dataseries X:
2849,27
2921,44
2981,85
3080,58
3106,22
3119,31
3061,26
3097,31
3161,69
3257,16
3277,01
3295,32
3363,99
3494,17
3667,03
3813,06
3917,96
3895,51
3801,06
3570,12
3701,61
3862,27
3970,1
4138,52
4199,75
4290,89
4443,91
4502,64
4356,98
4591,27
4696,96
4621,4
4562,84
4202,52
4296,49
4435,23
4105,18
4116,68
3844,49
3720,98
3674,4
3857,62
3801,06
3504,37
3032,6
3047,03
2962,34
2197,82
2014,45
1862,83
1905,41
1810,99
1670,07
1864,44
2052,02
2029,6
2070,83
2293,41
2443,27
2513,17




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=60289&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=60289&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60289&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
10.9582766.63910
20.9115196.31520
30.8594065.95410
40.7943995.50381e-06
50.7285935.04783e-06
60.6461034.47632.3e-05
70.559363.87540.000161
80.4869913.3740.000737
90.4067942.81840.003496
100.3226582.23540.015038
110.242851.68250.049482
120.150231.04080.151585
130.0871550.60380.2744
140.0229230.15880.437241
15-0.053439-0.37020.356418
16-0.116936-0.81020.210925
17-0.176844-1.22520.113237
18-0.230108-1.59420.058724
19-0.275036-1.90550.031357
20-0.325807-2.25730.01429
21-0.364582-2.52590.007447
22-0.386699-2.67910.00504
23-0.404462-2.80220.003649
24-0.409281-2.83560.003338
25-0.407906-2.82610.003424
26-0.406688-2.81760.003502
27-0.39019-2.70330.004733
28-0.376067-2.60550.006091
29-0.370388-2.56610.00673
30-0.363964-2.52160.007528
31-0.35577-2.46480.008668
32-0.334978-2.32080.012296
33-0.309577-2.14480.018529
34-0.290177-2.01040.025012
35-0.269487-1.86710.034004
36-0.237148-1.6430.053458

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.958276 & 6.6391 & 0 \tabularnewline
2 & 0.911519 & 6.3152 & 0 \tabularnewline
3 & 0.859406 & 5.9541 & 0 \tabularnewline
4 & 0.794399 & 5.5038 & 1e-06 \tabularnewline
5 & 0.728593 & 5.0478 & 3e-06 \tabularnewline
6 & 0.646103 & 4.4763 & 2.3e-05 \tabularnewline
7 & 0.55936 & 3.8754 & 0.000161 \tabularnewline
8 & 0.486991 & 3.374 & 0.000737 \tabularnewline
9 & 0.406794 & 2.8184 & 0.003496 \tabularnewline
10 & 0.322658 & 2.2354 & 0.015038 \tabularnewline
11 & 0.24285 & 1.6825 & 0.049482 \tabularnewline
12 & 0.15023 & 1.0408 & 0.151585 \tabularnewline
13 & 0.087155 & 0.6038 & 0.2744 \tabularnewline
14 & 0.022923 & 0.1588 & 0.437241 \tabularnewline
15 & -0.053439 & -0.3702 & 0.356418 \tabularnewline
16 & -0.116936 & -0.8102 & 0.210925 \tabularnewline
17 & -0.176844 & -1.2252 & 0.113237 \tabularnewline
18 & -0.230108 & -1.5942 & 0.058724 \tabularnewline
19 & -0.275036 & -1.9055 & 0.031357 \tabularnewline
20 & -0.325807 & -2.2573 & 0.01429 \tabularnewline
21 & -0.364582 & -2.5259 & 0.007447 \tabularnewline
22 & -0.386699 & -2.6791 & 0.00504 \tabularnewline
23 & -0.404462 & -2.8022 & 0.003649 \tabularnewline
24 & -0.409281 & -2.8356 & 0.003338 \tabularnewline
25 & -0.407906 & -2.8261 & 0.003424 \tabularnewline
26 & -0.406688 & -2.8176 & 0.003502 \tabularnewline
27 & -0.39019 & -2.7033 & 0.004733 \tabularnewline
28 & -0.376067 & -2.6055 & 0.006091 \tabularnewline
29 & -0.370388 & -2.5661 & 0.00673 \tabularnewline
30 & -0.363964 & -2.5216 & 0.007528 \tabularnewline
31 & -0.35577 & -2.4648 & 0.008668 \tabularnewline
32 & -0.334978 & -2.3208 & 0.012296 \tabularnewline
33 & -0.309577 & -2.1448 & 0.018529 \tabularnewline
34 & -0.290177 & -2.0104 & 0.025012 \tabularnewline
35 & -0.269487 & -1.8671 & 0.034004 \tabularnewline
36 & -0.237148 & -1.643 & 0.053458 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60289&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]0.958276[/C][C]6.6391[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.911519[/C][C]6.3152[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.859406[/C][C]5.9541[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.794399[/C][C]5.5038[/C][C]1e-06[/C][/ROW]
[ROW][C]5[/C][C]0.728593[/C][C]5.0478[/C][C]3e-06[/C][/ROW]
[ROW][C]6[/C][C]0.646103[/C][C]4.4763[/C][C]2.3e-05[/C][/ROW]
[ROW][C]7[/C][C]0.55936[/C][C]3.8754[/C][C]0.000161[/C][/ROW]
[ROW][C]8[/C][C]0.486991[/C][C]3.374[/C][C]0.000737[/C][/ROW]
[ROW][C]9[/C][C]0.406794[/C][C]2.8184[/C][C]0.003496[/C][/ROW]
[ROW][C]10[/C][C]0.322658[/C][C]2.2354[/C][C]0.015038[/C][/ROW]
[ROW][C]11[/C][C]0.24285[/C][C]1.6825[/C][C]0.049482[/C][/ROW]
[ROW][C]12[/C][C]0.15023[/C][C]1.0408[/C][C]0.151585[/C][/ROW]
[ROW][C]13[/C][C]0.087155[/C][C]0.6038[/C][C]0.2744[/C][/ROW]
[ROW][C]14[/C][C]0.022923[/C][C]0.1588[/C][C]0.437241[/C][/ROW]
[ROW][C]15[/C][C]-0.053439[/C][C]-0.3702[/C][C]0.356418[/C][/ROW]
[ROW][C]16[/C][C]-0.116936[/C][C]-0.8102[/C][C]0.210925[/C][/ROW]
[ROW][C]17[/C][C]-0.176844[/C][C]-1.2252[/C][C]0.113237[/C][/ROW]
[ROW][C]18[/C][C]-0.230108[/C][C]-1.5942[/C][C]0.058724[/C][/ROW]
[ROW][C]19[/C][C]-0.275036[/C][C]-1.9055[/C][C]0.031357[/C][/ROW]
[ROW][C]20[/C][C]-0.325807[/C][C]-2.2573[/C][C]0.01429[/C][/ROW]
[ROW][C]21[/C][C]-0.364582[/C][C]-2.5259[/C][C]0.007447[/C][/ROW]
[ROW][C]22[/C][C]-0.386699[/C][C]-2.6791[/C][C]0.00504[/C][/ROW]
[ROW][C]23[/C][C]-0.404462[/C][C]-2.8022[/C][C]0.003649[/C][/ROW]
[ROW][C]24[/C][C]-0.409281[/C][C]-2.8356[/C][C]0.003338[/C][/ROW]
[ROW][C]25[/C][C]-0.407906[/C][C]-2.8261[/C][C]0.003424[/C][/ROW]
[ROW][C]26[/C][C]-0.406688[/C][C]-2.8176[/C][C]0.003502[/C][/ROW]
[ROW][C]27[/C][C]-0.39019[/C][C]-2.7033[/C][C]0.004733[/C][/ROW]
[ROW][C]28[/C][C]-0.376067[/C][C]-2.6055[/C][C]0.006091[/C][/ROW]
[ROW][C]29[/C][C]-0.370388[/C][C]-2.5661[/C][C]0.00673[/C][/ROW]
[ROW][C]30[/C][C]-0.363964[/C][C]-2.5216[/C][C]0.007528[/C][/ROW]
[ROW][C]31[/C][C]-0.35577[/C][C]-2.4648[/C][C]0.008668[/C][/ROW]
[ROW][C]32[/C][C]-0.334978[/C][C]-2.3208[/C][C]0.012296[/C][/ROW]
[ROW][C]33[/C][C]-0.309577[/C][C]-2.1448[/C][C]0.018529[/C][/ROW]
[ROW][C]34[/C][C]-0.290177[/C][C]-2.0104[/C][C]0.025012[/C][/ROW]
[ROW][C]35[/C][C]-0.269487[/C][C]-1.8671[/C][C]0.034004[/C][/ROW]
[ROW][C]36[/C][C]-0.237148[/C][C]-1.643[/C][C]0.053458[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60289&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60289&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
10.9582766.63910
20.9115196.31520
30.8594065.95410
40.7943995.50381e-06
50.7285935.04783e-06
60.6461034.47632.3e-05
70.559363.87540.000161
80.4869913.3740.000737
90.4067942.81840.003496
100.3226582.23540.015038
110.242851.68250.049482
120.150231.04080.151585
130.0871550.60380.2744
140.0229230.15880.437241
15-0.053439-0.37020.356418
16-0.116936-0.81020.210925
17-0.176844-1.22520.113237
18-0.230108-1.59420.058724
19-0.275036-1.90550.031357
20-0.325807-2.25730.01429
21-0.364582-2.52590.007447
22-0.386699-2.67910.00504
23-0.404462-2.80220.003649
24-0.409281-2.83560.003338
25-0.407906-2.82610.003424
26-0.406688-2.81760.003502
27-0.39019-2.70330.004733
28-0.376067-2.60550.006091
29-0.370388-2.56610.00673
30-0.363964-2.52160.007528
31-0.35577-2.46480.008668
32-0.334978-2.32080.012296
33-0.309577-2.14480.018529
34-0.290177-2.01040.025012
35-0.269487-1.86710.034004
36-0.237148-1.6430.053458







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9582766.63910
2-0.082908-0.57440.284188
3-0.086886-0.6020.275015
4-0.181172-1.25520.107741
5-0.029313-0.20310.419962
6-0.236457-1.63820.053957
7-0.073855-0.51170.305609
80.1483251.02760.154639
9-0.111073-0.76950.222673
10-0.116084-0.80430.212607
11-0.006182-0.04280.483006
12-0.21257-1.47270.073676
130.289972.0090.025091
14-0.116176-0.80490.212426
15-0.179273-1.2420.110128
160.0191690.13280.447449
170.0070790.0490.480544
18-0.066452-0.46040.323656
19-0.043234-0.29950.382912
20-0.000444-0.00310.498779
210.0189310.13120.448099
220.0228330.15820.437486
230.0836610.57960.282442
24-0.05716-0.3960.346924
250.1383160.95830.171362
26-0.11286-0.78190.219052
27-0.054763-0.37940.35303
28-0.026707-0.1850.426992
29-0.150511-1.04280.15114
30-0.107089-0.74190.230871
310.0604040.41850.338727
320.1139960.78980.216768
330.0252850.17520.430838
34-0.026217-0.18160.428315
35-0.03783-0.26210.397185
360.0782570.54220.295102

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.958276 & 6.6391 & 0 \tabularnewline
2 & -0.082908 & -0.5744 & 0.284188 \tabularnewline
3 & -0.086886 & -0.602 & 0.275015 \tabularnewline
4 & -0.181172 & -1.2552 & 0.107741 \tabularnewline
5 & -0.029313 & -0.2031 & 0.419962 \tabularnewline
6 & -0.236457 & -1.6382 & 0.053957 \tabularnewline
7 & -0.073855 & -0.5117 & 0.305609 \tabularnewline
8 & 0.148325 & 1.0276 & 0.154639 \tabularnewline
9 & -0.111073 & -0.7695 & 0.222673 \tabularnewline
10 & -0.116084 & -0.8043 & 0.212607 \tabularnewline
11 & -0.006182 & -0.0428 & 0.483006 \tabularnewline
12 & -0.21257 & -1.4727 & 0.073676 \tabularnewline
13 & 0.28997 & 2.009 & 0.025091 \tabularnewline
14 & -0.116176 & -0.8049 & 0.212426 \tabularnewline
15 & -0.179273 & -1.242 & 0.110128 \tabularnewline
16 & 0.019169 & 0.1328 & 0.447449 \tabularnewline
17 & 0.007079 & 0.049 & 0.480544 \tabularnewline
18 & -0.066452 & -0.4604 & 0.323656 \tabularnewline
19 & -0.043234 & -0.2995 & 0.382912 \tabularnewline
20 & -0.000444 & -0.0031 & 0.498779 \tabularnewline
21 & 0.018931 & 0.1312 & 0.448099 \tabularnewline
22 & 0.022833 & 0.1582 & 0.437486 \tabularnewline
23 & 0.083661 & 0.5796 & 0.282442 \tabularnewline
24 & -0.05716 & -0.396 & 0.346924 \tabularnewline
25 & 0.138316 & 0.9583 & 0.171362 \tabularnewline
26 & -0.11286 & -0.7819 & 0.219052 \tabularnewline
27 & -0.054763 & -0.3794 & 0.35303 \tabularnewline
28 & -0.026707 & -0.185 & 0.426992 \tabularnewline
29 & -0.150511 & -1.0428 & 0.15114 \tabularnewline
30 & -0.107089 & -0.7419 & 0.230871 \tabularnewline
31 & 0.060404 & 0.4185 & 0.338727 \tabularnewline
32 & 0.113996 & 0.7898 & 0.216768 \tabularnewline
33 & 0.025285 & 0.1752 & 0.430838 \tabularnewline
34 & -0.026217 & -0.1816 & 0.428315 \tabularnewline
35 & -0.03783 & -0.2621 & 0.397185 \tabularnewline
36 & 0.078257 & 0.5422 & 0.295102 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60289&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]0.958276[/C][C]6.6391[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.082908[/C][C]-0.5744[/C][C]0.284188[/C][/ROW]
[ROW][C]3[/C][C]-0.086886[/C][C]-0.602[/C][C]0.275015[/C][/ROW]
[ROW][C]4[/C][C]-0.181172[/C][C]-1.2552[/C][C]0.107741[/C][/ROW]
[ROW][C]5[/C][C]-0.029313[/C][C]-0.2031[/C][C]0.419962[/C][/ROW]
[ROW][C]6[/C][C]-0.236457[/C][C]-1.6382[/C][C]0.053957[/C][/ROW]
[ROW][C]7[/C][C]-0.073855[/C][C]-0.5117[/C][C]0.305609[/C][/ROW]
[ROW][C]8[/C][C]0.148325[/C][C]1.0276[/C][C]0.154639[/C][/ROW]
[ROW][C]9[/C][C]-0.111073[/C][C]-0.7695[/C][C]0.222673[/C][/ROW]
[ROW][C]10[/C][C]-0.116084[/C][C]-0.8043[/C][C]0.212607[/C][/ROW]
[ROW][C]11[/C][C]-0.006182[/C][C]-0.0428[/C][C]0.483006[/C][/ROW]
[ROW][C]12[/C][C]-0.21257[/C][C]-1.4727[/C][C]0.073676[/C][/ROW]
[ROW][C]13[/C][C]0.28997[/C][C]2.009[/C][C]0.025091[/C][/ROW]
[ROW][C]14[/C][C]-0.116176[/C][C]-0.8049[/C][C]0.212426[/C][/ROW]
[ROW][C]15[/C][C]-0.179273[/C][C]-1.242[/C][C]0.110128[/C][/ROW]
[ROW][C]16[/C][C]0.019169[/C][C]0.1328[/C][C]0.447449[/C][/ROW]
[ROW][C]17[/C][C]0.007079[/C][C]0.049[/C][C]0.480544[/C][/ROW]
[ROW][C]18[/C][C]-0.066452[/C][C]-0.4604[/C][C]0.323656[/C][/ROW]
[ROW][C]19[/C][C]-0.043234[/C][C]-0.2995[/C][C]0.382912[/C][/ROW]
[ROW][C]20[/C][C]-0.000444[/C][C]-0.0031[/C][C]0.498779[/C][/ROW]
[ROW][C]21[/C][C]0.018931[/C][C]0.1312[/C][C]0.448099[/C][/ROW]
[ROW][C]22[/C][C]0.022833[/C][C]0.1582[/C][C]0.437486[/C][/ROW]
[ROW][C]23[/C][C]0.083661[/C][C]0.5796[/C][C]0.282442[/C][/ROW]
[ROW][C]24[/C][C]-0.05716[/C][C]-0.396[/C][C]0.346924[/C][/ROW]
[ROW][C]25[/C][C]0.138316[/C][C]0.9583[/C][C]0.171362[/C][/ROW]
[ROW][C]26[/C][C]-0.11286[/C][C]-0.7819[/C][C]0.219052[/C][/ROW]
[ROW][C]27[/C][C]-0.054763[/C][C]-0.3794[/C][C]0.35303[/C][/ROW]
[ROW][C]28[/C][C]-0.026707[/C][C]-0.185[/C][C]0.426992[/C][/ROW]
[ROW][C]29[/C][C]-0.150511[/C][C]-1.0428[/C][C]0.15114[/C][/ROW]
[ROW][C]30[/C][C]-0.107089[/C][C]-0.7419[/C][C]0.230871[/C][/ROW]
[ROW][C]31[/C][C]0.060404[/C][C]0.4185[/C][C]0.338727[/C][/ROW]
[ROW][C]32[/C][C]0.113996[/C][C]0.7898[/C][C]0.216768[/C][/ROW]
[ROW][C]33[/C][C]0.025285[/C][C]0.1752[/C][C]0.430838[/C][/ROW]
[ROW][C]34[/C][C]-0.026217[/C][C]-0.1816[/C][C]0.428315[/C][/ROW]
[ROW][C]35[/C][C]-0.03783[/C][C]-0.2621[/C][C]0.397185[/C][/ROW]
[ROW][C]36[/C][C]0.078257[/C][C]0.5422[/C][C]0.295102[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60289&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60289&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
10.9582766.63910
2-0.082908-0.57440.284188
3-0.086886-0.6020.275015
4-0.181172-1.25520.107741
5-0.029313-0.20310.419962
6-0.236457-1.63820.053957
7-0.073855-0.51170.305609
80.1483251.02760.154639
9-0.111073-0.76950.222673
10-0.116084-0.80430.212607
11-0.006182-0.04280.483006
12-0.21257-1.47270.073676
130.289972.0090.025091
14-0.116176-0.80490.212426
15-0.179273-1.2420.110128
160.0191690.13280.447449
170.0070790.0490.480544
18-0.066452-0.46040.323656
19-0.043234-0.29950.382912
20-0.000444-0.00310.498779
210.0189310.13120.448099
220.0228330.15820.437486
230.0836610.57960.282442
24-0.05716-0.3960.346924
250.1383160.95830.171362
26-0.11286-0.78190.219052
27-0.054763-0.37940.35303
28-0.026707-0.1850.426992
29-0.150511-1.04280.15114
30-0.107089-0.74190.230871
310.0604040.41850.338727
320.1139960.78980.216768
330.0252850.17520.430838
34-0.026217-0.18160.428315
35-0.03783-0.26210.397185
360.0782570.54220.295102



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')