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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 05:07:02 -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/t12611381076o9zs3cko1kp1bn.htm/, Retrieved Thu, 31 Oct 2024 23:07:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69266, Retrieved Thu, 31 Oct 2024 23:07:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144
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] [] [2009-11-26 09:48:27] [69400782d28359bd00f6a8e8fb9347a1]
-   P             [(Partial) Autocorrelation Function] [] [2009-12-18 12:07:02] [a1151e037da67acc5ce4bbcb8804d7f1] [Current]
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Dataseries X:
392
394
392
396
392
396
419
421
420
418
410
418
426
428
430
424
423
427
441
449
452
462
455
461
461
463
462
456
455
456
472
472
471
465
459
465
468
467
463
460
462
461
476
476
471
453
443
442
444
438
427
424
416
406
431
434
418
412
404
409
412




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=69266&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=69266&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69266&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
10.1665781.29030.100947
2-0.142563-1.10430.136939
3-0.169963-1.31650.096502
4-0.186503-1.44460.07688
50.2354171.82350.036602
60.2943672.28020.013083
70.2109011.63360.053786
8-0.119342-0.92440.179486
9-0.21667-1.67830.049244
10-0.100859-0.78130.218863
110.1417391.09790.138316
120.4811943.72730.000215
130.1053920.81640.208762
14-0.101948-0.78970.21641
15-0.172259-1.33430.093572
16-0.155424-1.20390.116676
170.1027140.79560.214696
180.168021.30150.099035
190.1339981.03790.15173
20-0.173377-1.3430.09217
21-0.15566-1.20570.116327
22-0.062011-0.48030.316369
230.0734890.56920.285659
240.2969272.30.012471
250.016040.12420.450769
26-0.198099-1.53450.065086
27-0.238654-1.84860.034722
28-0.139708-1.08220.141753
290.082230.63690.263291
300.0878510.68050.249406
310.0195710.15160.440005
32-0.217258-1.68290.048798
33-0.110366-0.85490.198007
34-0.031991-0.24780.402566
350.0052390.04060.483883
360.2008651.55590.062496

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.166578 & 1.2903 & 0.100947 \tabularnewline
2 & -0.142563 & -1.1043 & 0.136939 \tabularnewline
3 & -0.169963 & -1.3165 & 0.096502 \tabularnewline
4 & -0.186503 & -1.4446 & 0.07688 \tabularnewline
5 & 0.235417 & 1.8235 & 0.036602 \tabularnewline
6 & 0.294367 & 2.2802 & 0.013083 \tabularnewline
7 & 0.210901 & 1.6336 & 0.053786 \tabularnewline
8 & -0.119342 & -0.9244 & 0.179486 \tabularnewline
9 & -0.21667 & -1.6783 & 0.049244 \tabularnewline
10 & -0.100859 & -0.7813 & 0.218863 \tabularnewline
11 & 0.141739 & 1.0979 & 0.138316 \tabularnewline
12 & 0.481194 & 3.7273 & 0.000215 \tabularnewline
13 & 0.105392 & 0.8164 & 0.208762 \tabularnewline
14 & -0.101948 & -0.7897 & 0.21641 \tabularnewline
15 & -0.172259 & -1.3343 & 0.093572 \tabularnewline
16 & -0.155424 & -1.2039 & 0.116676 \tabularnewline
17 & 0.102714 & 0.7956 & 0.214696 \tabularnewline
18 & 0.16802 & 1.3015 & 0.099035 \tabularnewline
19 & 0.133998 & 1.0379 & 0.15173 \tabularnewline
20 & -0.173377 & -1.343 & 0.09217 \tabularnewline
21 & -0.15566 & -1.2057 & 0.116327 \tabularnewline
22 & -0.062011 & -0.4803 & 0.316369 \tabularnewline
23 & 0.073489 & 0.5692 & 0.285659 \tabularnewline
24 & 0.296927 & 2.3 & 0.012471 \tabularnewline
25 & 0.01604 & 0.1242 & 0.450769 \tabularnewline
26 & -0.198099 & -1.5345 & 0.065086 \tabularnewline
27 & -0.238654 & -1.8486 & 0.034722 \tabularnewline
28 & -0.139708 & -1.0822 & 0.141753 \tabularnewline
29 & 0.08223 & 0.6369 & 0.263291 \tabularnewline
30 & 0.087851 & 0.6805 & 0.249406 \tabularnewline
31 & 0.019571 & 0.1516 & 0.440005 \tabularnewline
32 & -0.217258 & -1.6829 & 0.048798 \tabularnewline
33 & -0.110366 & -0.8549 & 0.198007 \tabularnewline
34 & -0.031991 & -0.2478 & 0.402566 \tabularnewline
35 & 0.005239 & 0.0406 & 0.483883 \tabularnewline
36 & 0.200865 & 1.5559 & 0.062496 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69266&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]0.166578[/C][C]1.2903[/C][C]0.100947[/C][/ROW]
[ROW][C]2[/C][C]-0.142563[/C][C]-1.1043[/C][C]0.136939[/C][/ROW]
[ROW][C]3[/C][C]-0.169963[/C][C]-1.3165[/C][C]0.096502[/C][/ROW]
[ROW][C]4[/C][C]-0.186503[/C][C]-1.4446[/C][C]0.07688[/C][/ROW]
[ROW][C]5[/C][C]0.235417[/C][C]1.8235[/C][C]0.036602[/C][/ROW]
[ROW][C]6[/C][C]0.294367[/C][C]2.2802[/C][C]0.013083[/C][/ROW]
[ROW][C]7[/C][C]0.210901[/C][C]1.6336[/C][C]0.053786[/C][/ROW]
[ROW][C]8[/C][C]-0.119342[/C][C]-0.9244[/C][C]0.179486[/C][/ROW]
[ROW][C]9[/C][C]-0.21667[/C][C]-1.6783[/C][C]0.049244[/C][/ROW]
[ROW][C]10[/C][C]-0.100859[/C][C]-0.7813[/C][C]0.218863[/C][/ROW]
[ROW][C]11[/C][C]0.141739[/C][C]1.0979[/C][C]0.138316[/C][/ROW]
[ROW][C]12[/C][C]0.481194[/C][C]3.7273[/C][C]0.000215[/C][/ROW]
[ROW][C]13[/C][C]0.105392[/C][C]0.8164[/C][C]0.208762[/C][/ROW]
[ROW][C]14[/C][C]-0.101948[/C][C]-0.7897[/C][C]0.21641[/C][/ROW]
[ROW][C]15[/C][C]-0.172259[/C][C]-1.3343[/C][C]0.093572[/C][/ROW]
[ROW][C]16[/C][C]-0.155424[/C][C]-1.2039[/C][C]0.116676[/C][/ROW]
[ROW][C]17[/C][C]0.102714[/C][C]0.7956[/C][C]0.214696[/C][/ROW]
[ROW][C]18[/C][C]0.16802[/C][C]1.3015[/C][C]0.099035[/C][/ROW]
[ROW][C]19[/C][C]0.133998[/C][C]1.0379[/C][C]0.15173[/C][/ROW]
[ROW][C]20[/C][C]-0.173377[/C][C]-1.343[/C][C]0.09217[/C][/ROW]
[ROW][C]21[/C][C]-0.15566[/C][C]-1.2057[/C][C]0.116327[/C][/ROW]
[ROW][C]22[/C][C]-0.062011[/C][C]-0.4803[/C][C]0.316369[/C][/ROW]
[ROW][C]23[/C][C]0.073489[/C][C]0.5692[/C][C]0.285659[/C][/ROW]
[ROW][C]24[/C][C]0.296927[/C][C]2.3[/C][C]0.012471[/C][/ROW]
[ROW][C]25[/C][C]0.01604[/C][C]0.1242[/C][C]0.450769[/C][/ROW]
[ROW][C]26[/C][C]-0.198099[/C][C]-1.5345[/C][C]0.065086[/C][/ROW]
[ROW][C]27[/C][C]-0.238654[/C][C]-1.8486[/C][C]0.034722[/C][/ROW]
[ROW][C]28[/C][C]-0.139708[/C][C]-1.0822[/C][C]0.141753[/C][/ROW]
[ROW][C]29[/C][C]0.08223[/C][C]0.6369[/C][C]0.263291[/C][/ROW]
[ROW][C]30[/C][C]0.087851[/C][C]0.6805[/C][C]0.249406[/C][/ROW]
[ROW][C]31[/C][C]0.019571[/C][C]0.1516[/C][C]0.440005[/C][/ROW]
[ROW][C]32[/C][C]-0.217258[/C][C]-1.6829[/C][C]0.048798[/C][/ROW]
[ROW][C]33[/C][C]-0.110366[/C][C]-0.8549[/C][C]0.198007[/C][/ROW]
[ROW][C]34[/C][C]-0.031991[/C][C]-0.2478[/C][C]0.402566[/C][/ROW]
[ROW][C]35[/C][C]0.005239[/C][C]0.0406[/C][C]0.483883[/C][/ROW]
[ROW][C]36[/C][C]0.200865[/C][C]1.5559[/C][C]0.062496[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69266&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69266&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
10.1665781.29030.100947
2-0.142563-1.10430.136939
3-0.169963-1.31650.096502
4-0.186503-1.44460.07688
50.2354171.82350.036602
60.2943672.28020.013083
70.2109011.63360.053786
8-0.119342-0.92440.179486
9-0.21667-1.67830.049244
10-0.100859-0.78130.218863
110.1417391.09790.138316
120.4811943.72730.000215
130.1053920.81640.208762
14-0.101948-0.78970.21641
15-0.172259-1.33430.093572
16-0.155424-1.20390.116676
170.1027140.79560.214696
180.168021.30150.099035
190.1339981.03790.15173
20-0.173377-1.3430.09217
21-0.15566-1.20570.116327
22-0.062011-0.48030.316369
230.0734890.56920.285659
240.2969272.30.012471
250.016040.12420.450769
26-0.198099-1.53450.065086
27-0.238654-1.84860.034722
28-0.139708-1.08220.141753
290.082230.63690.263291
300.0878510.68050.249406
310.0195710.15160.440005
32-0.217258-1.68290.048798
33-0.110366-0.85490.198007
34-0.031991-0.24780.402566
350.0052390.04060.483883
360.2008651.55590.062496







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1665781.29030.100947
2-0.175172-1.35690.089952
3-0.119772-0.92770.178627
4-0.170607-1.32150.095674
50.2767732.14390.018053
60.1620891.25550.107076
70.1997281.54710.063551
8-0.128799-0.99770.161222
9-0.012012-0.0930.463089
10-0.07438-0.57610.283336
110.1221690.94630.173892
120.3241222.51060.007382
13-0.042144-0.32640.372611
140.0182410.14130.444055
15-0.025671-0.19880.421528
16-0.014239-0.11030.456271
17-0.105669-0.81850.208153
18-0.060624-0.46960.320176
19-0.017108-0.13250.447508
20-0.138608-1.07360.143639
210.0605250.46880.320447
22-0.011517-0.08920.464605
230.0327890.2540.400188
240.0509940.3950.347123
25-0.029497-0.22850.410025
26-0.156597-1.2130.114942
27-0.123119-0.95370.172036
28-0.052189-0.40430.343732
29-0.029486-0.22840.410056
30-0.079266-0.6140.270771
31-0.042054-0.32570.372874
32-0.058044-0.44960.327306
330.1124990.87140.193502
34-0.000405-0.00310.498754
35-0.070888-0.54910.292488
360.0160220.12410.450825

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.166578 & 1.2903 & 0.100947 \tabularnewline
2 & -0.175172 & -1.3569 & 0.089952 \tabularnewline
3 & -0.119772 & -0.9277 & 0.178627 \tabularnewline
4 & -0.170607 & -1.3215 & 0.095674 \tabularnewline
5 & 0.276773 & 2.1439 & 0.018053 \tabularnewline
6 & 0.162089 & 1.2555 & 0.107076 \tabularnewline
7 & 0.199728 & 1.5471 & 0.063551 \tabularnewline
8 & -0.128799 & -0.9977 & 0.161222 \tabularnewline
9 & -0.012012 & -0.093 & 0.463089 \tabularnewline
10 & -0.07438 & -0.5761 & 0.283336 \tabularnewline
11 & 0.122169 & 0.9463 & 0.173892 \tabularnewline
12 & 0.324122 & 2.5106 & 0.007382 \tabularnewline
13 & -0.042144 & -0.3264 & 0.372611 \tabularnewline
14 & 0.018241 & 0.1413 & 0.444055 \tabularnewline
15 & -0.025671 & -0.1988 & 0.421528 \tabularnewline
16 & -0.014239 & -0.1103 & 0.456271 \tabularnewline
17 & -0.105669 & -0.8185 & 0.208153 \tabularnewline
18 & -0.060624 & -0.4696 & 0.320176 \tabularnewline
19 & -0.017108 & -0.1325 & 0.447508 \tabularnewline
20 & -0.138608 & -1.0736 & 0.143639 \tabularnewline
21 & 0.060525 & 0.4688 & 0.320447 \tabularnewline
22 & -0.011517 & -0.0892 & 0.464605 \tabularnewline
23 & 0.032789 & 0.254 & 0.400188 \tabularnewline
24 & 0.050994 & 0.395 & 0.347123 \tabularnewline
25 & -0.029497 & -0.2285 & 0.410025 \tabularnewline
26 & -0.156597 & -1.213 & 0.114942 \tabularnewline
27 & -0.123119 & -0.9537 & 0.172036 \tabularnewline
28 & -0.052189 & -0.4043 & 0.343732 \tabularnewline
29 & -0.029486 & -0.2284 & 0.410056 \tabularnewline
30 & -0.079266 & -0.614 & 0.270771 \tabularnewline
31 & -0.042054 & -0.3257 & 0.372874 \tabularnewline
32 & -0.058044 & -0.4496 & 0.327306 \tabularnewline
33 & 0.112499 & 0.8714 & 0.193502 \tabularnewline
34 & -0.000405 & -0.0031 & 0.498754 \tabularnewline
35 & -0.070888 & -0.5491 & 0.292488 \tabularnewline
36 & 0.016022 & 0.1241 & 0.450825 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69266&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]0.166578[/C][C]1.2903[/C][C]0.100947[/C][/ROW]
[ROW][C]2[/C][C]-0.175172[/C][C]-1.3569[/C][C]0.089952[/C][/ROW]
[ROW][C]3[/C][C]-0.119772[/C][C]-0.9277[/C][C]0.178627[/C][/ROW]
[ROW][C]4[/C][C]-0.170607[/C][C]-1.3215[/C][C]0.095674[/C][/ROW]
[ROW][C]5[/C][C]0.276773[/C][C]2.1439[/C][C]0.018053[/C][/ROW]
[ROW][C]6[/C][C]0.162089[/C][C]1.2555[/C][C]0.107076[/C][/ROW]
[ROW][C]7[/C][C]0.199728[/C][C]1.5471[/C][C]0.063551[/C][/ROW]
[ROW][C]8[/C][C]-0.128799[/C][C]-0.9977[/C][C]0.161222[/C][/ROW]
[ROW][C]9[/C][C]-0.012012[/C][C]-0.093[/C][C]0.463089[/C][/ROW]
[ROW][C]10[/C][C]-0.07438[/C][C]-0.5761[/C][C]0.283336[/C][/ROW]
[ROW][C]11[/C][C]0.122169[/C][C]0.9463[/C][C]0.173892[/C][/ROW]
[ROW][C]12[/C][C]0.324122[/C][C]2.5106[/C][C]0.007382[/C][/ROW]
[ROW][C]13[/C][C]-0.042144[/C][C]-0.3264[/C][C]0.372611[/C][/ROW]
[ROW][C]14[/C][C]0.018241[/C][C]0.1413[/C][C]0.444055[/C][/ROW]
[ROW][C]15[/C][C]-0.025671[/C][C]-0.1988[/C][C]0.421528[/C][/ROW]
[ROW][C]16[/C][C]-0.014239[/C][C]-0.1103[/C][C]0.456271[/C][/ROW]
[ROW][C]17[/C][C]-0.105669[/C][C]-0.8185[/C][C]0.208153[/C][/ROW]
[ROW][C]18[/C][C]-0.060624[/C][C]-0.4696[/C][C]0.320176[/C][/ROW]
[ROW][C]19[/C][C]-0.017108[/C][C]-0.1325[/C][C]0.447508[/C][/ROW]
[ROW][C]20[/C][C]-0.138608[/C][C]-1.0736[/C][C]0.143639[/C][/ROW]
[ROW][C]21[/C][C]0.060525[/C][C]0.4688[/C][C]0.320447[/C][/ROW]
[ROW][C]22[/C][C]-0.011517[/C][C]-0.0892[/C][C]0.464605[/C][/ROW]
[ROW][C]23[/C][C]0.032789[/C][C]0.254[/C][C]0.400188[/C][/ROW]
[ROW][C]24[/C][C]0.050994[/C][C]0.395[/C][C]0.347123[/C][/ROW]
[ROW][C]25[/C][C]-0.029497[/C][C]-0.2285[/C][C]0.410025[/C][/ROW]
[ROW][C]26[/C][C]-0.156597[/C][C]-1.213[/C][C]0.114942[/C][/ROW]
[ROW][C]27[/C][C]-0.123119[/C][C]-0.9537[/C][C]0.172036[/C][/ROW]
[ROW][C]28[/C][C]-0.052189[/C][C]-0.4043[/C][C]0.343732[/C][/ROW]
[ROW][C]29[/C][C]-0.029486[/C][C]-0.2284[/C][C]0.410056[/C][/ROW]
[ROW][C]30[/C][C]-0.079266[/C][C]-0.614[/C][C]0.270771[/C][/ROW]
[ROW][C]31[/C][C]-0.042054[/C][C]-0.3257[/C][C]0.372874[/C][/ROW]
[ROW][C]32[/C][C]-0.058044[/C][C]-0.4496[/C][C]0.327306[/C][/ROW]
[ROW][C]33[/C][C]0.112499[/C][C]0.8714[/C][C]0.193502[/C][/ROW]
[ROW][C]34[/C][C]-0.000405[/C][C]-0.0031[/C][C]0.498754[/C][/ROW]
[ROW][C]35[/C][C]-0.070888[/C][C]-0.5491[/C][C]0.292488[/C][/ROW]
[ROW][C]36[/C][C]0.016022[/C][C]0.1241[/C][C]0.450825[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69266&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69266&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
10.1665781.29030.100947
2-0.175172-1.35690.089952
3-0.119772-0.92770.178627
4-0.170607-1.32150.095674
50.2767732.14390.018053
60.1620891.25550.107076
70.1997281.54710.063551
8-0.128799-0.99770.161222
9-0.012012-0.0930.463089
10-0.07438-0.57610.283336
110.1221690.94630.173892
120.3241222.51060.007382
13-0.042144-0.32640.372611
140.0182410.14130.444055
15-0.025671-0.19880.421528
16-0.014239-0.11030.456271
17-0.105669-0.81850.208153
18-0.060624-0.46960.320176
19-0.017108-0.13250.447508
20-0.138608-1.07360.143639
210.0605250.46880.320447
22-0.011517-0.08920.464605
230.0327890.2540.400188
240.0509940.3950.347123
25-0.029497-0.22850.410025
26-0.156597-1.2130.114942
27-0.123119-0.95370.172036
28-0.052189-0.40430.343732
29-0.029486-0.22840.410056
30-0.079266-0.6140.270771
31-0.042054-0.32570.372874
32-0.058044-0.44960.327306
330.1124990.87140.193502
34-0.000405-0.00310.498754
35-0.070888-0.54910.292488
360.0160220.12410.450825



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')