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Description of Statistical Computation

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 computationWed, 02 Dec 2009 09:12:55 -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/02/t1259770434ro9pz9aec39zfyr.htm/, Retrieved Sat, 27 Apr 2024 21:20:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62413, Retrieved Sat, 27 Apr 2024 21:20:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact113

Tree of Dependent Computations

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]
- R PD          [(Partial) Autocorrelation Function] [] [2009-12-02 16:12:55] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-   P             [(Partial) Autocorrelation Function] [eerst gewoon diff...] [2009-12-03 15:02:43] [cd6314e7e707a6546bd4604c9d1f2b69]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
267413
267366
264777
258863
254844
254868
277267
285351
286602
283042
276687
277915
277128
277103
275037
270150
267140
264993
287259
291186
292300
288186
281477
282656
280190
280408
276836
275216
274352
271311
289802
290726
292300
278506
269826
265861
269034
264176
255198
253353
246057
235372
258556
260993
254663
250643
243422
247105
248541
245039
237080
237085
225554
226839
247934
248333
246969
245098
246263
255765
264319
268347
273046
273963
267430
271993
292710

Tables (Output of Computation)





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=62413&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=62413&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62413&T=0

As an alternative you can also use a QR Code:  
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
10.9174626.80410
20.8264096.12880
30.7228855.36111e-06
40.6104394.52711.6e-05
50.4849523.59650.000345
60.3832842.84250.003134
70.2871842.12980.018838
80.2043761.51570.067662
90.1263070.93670.176499
100.0619540.45950.323857
110.0075080.05570.477898
12-0.05557-0.41210.340927
13-0.113926-0.84490.200915
14-0.178618-1.32470.09538
15-0.220868-1.6380.053565
16-0.279313-2.07140.021511
17-0.331836-2.4610.008512
18-0.386843-2.86890.002916
19-0.429764-3.18720.001185
20-0.474145-3.51640.000442
21-0.495471-3.67450.000271
22-0.498509-3.6970.000252
23-0.476097-3.53080.000423
24-0.457462-3.39260.000645
25-0.429548-3.18560.00119
26-0.380831-2.82430.003294
27-0.341107-2.52970.007155
28-0.303871-2.25360.014115
29-0.255384-1.8940.031746
30-0.206639-1.53250.065569
31-0.167669-1.24350.109485
32-0.113898-0.84470.200971
33-0.063269-0.46920.320384
34-0.023254-0.17250.431856
35-0.002547-0.01890.492499
360.0139090.10310.45911

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.917462 & 6.8041 & 0 \tabularnewline
2 & 0.826409 & 6.1288 & 0 \tabularnewline
3 & 0.722885 & 5.3611 & 1e-06 \tabularnewline
4 & 0.610439 & 4.5271 & 1.6e-05 \tabularnewline
5 & 0.484952 & 3.5965 & 0.000345 \tabularnewline
6 & 0.383284 & 2.8425 & 0.003134 \tabularnewline
7 & 0.287184 & 2.1298 & 0.018838 \tabularnewline
8 & 0.204376 & 1.5157 & 0.067662 \tabularnewline
9 & 0.126307 & 0.9367 & 0.176499 \tabularnewline
10 & 0.061954 & 0.4595 & 0.323857 \tabularnewline
11 & 0.007508 & 0.0557 & 0.477898 \tabularnewline
12 & -0.05557 & -0.4121 & 0.340927 \tabularnewline
13 & -0.113926 & -0.8449 & 0.200915 \tabularnewline
14 & -0.178618 & -1.3247 & 0.09538 \tabularnewline
15 & -0.220868 & -1.638 & 0.053565 \tabularnewline
16 & -0.279313 & -2.0714 & 0.021511 \tabularnewline
17 & -0.331836 & -2.461 & 0.008512 \tabularnewline
18 & -0.386843 & -2.8689 & 0.002916 \tabularnewline
19 & -0.429764 & -3.1872 & 0.001185 \tabularnewline
20 & -0.474145 & -3.5164 & 0.000442 \tabularnewline
21 & -0.495471 & -3.6745 & 0.000271 \tabularnewline
22 & -0.498509 & -3.697 & 0.000252 \tabularnewline
23 & -0.476097 & -3.5308 & 0.000423 \tabularnewline
24 & -0.457462 & -3.3926 & 0.000645 \tabularnewline
25 & -0.429548 & -3.1856 & 0.00119 \tabularnewline
26 & -0.380831 & -2.8243 & 0.003294 \tabularnewline
27 & -0.341107 & -2.5297 & 0.007155 \tabularnewline
28 & -0.303871 & -2.2536 & 0.014115 \tabularnewline
29 & -0.255384 & -1.894 & 0.031746 \tabularnewline
30 & -0.206639 & -1.5325 & 0.065569 \tabularnewline
31 & -0.167669 & -1.2435 & 0.109485 \tabularnewline
32 & -0.113898 & -0.8447 & 0.200971 \tabularnewline
33 & -0.063269 & -0.4692 & 0.320384 \tabularnewline
34 & -0.023254 & -0.1725 & 0.431856 \tabularnewline
35 & -0.002547 & -0.0189 & 0.492499 \tabularnewline
36 & 0.013909 & 0.1031 & 0.45911 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62413&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]0.917462[/C][C]6.8041[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.826409[/C][C]6.1288[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.722885[/C][C]5.3611[/C][C]1e-06[/C][/ROW]
[ROW][C]4[/C][C]0.610439[/C][C]4.5271[/C][C]1.6e-05[/C][/ROW]
[ROW][C]5[/C][C]0.484952[/C][C]3.5965[/C][C]0.000345[/C][/ROW]
[ROW][C]6[/C][C]0.383284[/C][C]2.8425[/C][C]0.003134[/C][/ROW]
[ROW][C]7[/C][C]0.287184[/C][C]2.1298[/C][C]0.018838[/C][/ROW]
[ROW][C]8[/C][C]0.204376[/C][C]1.5157[/C][C]0.067662[/C][/ROW]
[ROW][C]9[/C][C]0.126307[/C][C]0.9367[/C][C]0.176499[/C][/ROW]
[ROW][C]10[/C][C]0.061954[/C][C]0.4595[/C][C]0.323857[/C][/ROW]
[ROW][C]11[/C][C]0.007508[/C][C]0.0557[/C][C]0.477898[/C][/ROW]
[ROW][C]12[/C][C]-0.05557[/C][C]-0.4121[/C][C]0.340927[/C][/ROW]
[ROW][C]13[/C][C]-0.113926[/C][C]-0.8449[/C][C]0.200915[/C][/ROW]
[ROW][C]14[/C][C]-0.178618[/C][C]-1.3247[/C][C]0.09538[/C][/ROW]
[ROW][C]15[/C][C]-0.220868[/C][C]-1.638[/C][C]0.053565[/C][/ROW]
[ROW][C]16[/C][C]-0.279313[/C][C]-2.0714[/C][C]0.021511[/C][/ROW]
[ROW][C]17[/C][C]-0.331836[/C][C]-2.461[/C][C]0.008512[/C][/ROW]
[ROW][C]18[/C][C]-0.386843[/C][C]-2.8689[/C][C]0.002916[/C][/ROW]
[ROW][C]19[/C][C]-0.429764[/C][C]-3.1872[/C][C]0.001185[/C][/ROW]
[ROW][C]20[/C][C]-0.474145[/C][C]-3.5164[/C][C]0.000442[/C][/ROW]
[ROW][C]21[/C][C]-0.495471[/C][C]-3.6745[/C][C]0.000271[/C][/ROW]
[ROW][C]22[/C][C]-0.498509[/C][C]-3.697[/C][C]0.000252[/C][/ROW]
[ROW][C]23[/C][C]-0.476097[/C][C]-3.5308[/C][C]0.000423[/C][/ROW]
[ROW][C]24[/C][C]-0.457462[/C][C]-3.3926[/C][C]0.000645[/C][/ROW]
[ROW][C]25[/C][C]-0.429548[/C][C]-3.1856[/C][C]0.00119[/C][/ROW]
[ROW][C]26[/C][C]-0.380831[/C][C]-2.8243[/C][C]0.003294[/C][/ROW]
[ROW][C]27[/C][C]-0.341107[/C][C]-2.5297[/C][C]0.007155[/C][/ROW]
[ROW][C]28[/C][C]-0.303871[/C][C]-2.2536[/C][C]0.014115[/C][/ROW]
[ROW][C]29[/C][C]-0.255384[/C][C]-1.894[/C][C]0.031746[/C][/ROW]
[ROW][C]30[/C][C]-0.206639[/C][C]-1.5325[/C][C]0.065569[/C][/ROW]
[ROW][C]31[/C][C]-0.167669[/C][C]-1.2435[/C][C]0.109485[/C][/ROW]
[ROW][C]32[/C][C]-0.113898[/C][C]-0.8447[/C][C]0.200971[/C][/ROW]
[ROW][C]33[/C][C]-0.063269[/C][C]-0.4692[/C][C]0.320384[/C][/ROW]
[ROW][C]34[/C][C]-0.023254[/C][C]-0.1725[/C][C]0.431856[/C][/ROW]
[ROW][C]35[/C][C]-0.002547[/C][C]-0.0189[/C][C]0.492499[/C][/ROW]
[ROW][C]36[/C][C]0.013909[/C][C]0.1031[/C][C]0.45911[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62413&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62413&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9174626.80410
20.8264096.12880
30.7228855.36111e-06
40.6104394.52711.6e-05
50.4849523.59650.000345
60.3832842.84250.003134
70.2871842.12980.018838
80.2043761.51570.067662
90.1263070.93670.176499
100.0619540.45950.323857
110.0075080.05570.477898
12-0.05557-0.41210.340927
13-0.113926-0.84490.200915
14-0.178618-1.32470.09538
15-0.220868-1.6380.053565
16-0.279313-2.07140.021511
17-0.331836-2.4610.008512
18-0.386843-2.86890.002916
19-0.429764-3.18720.001185
20-0.474145-3.51640.000442
21-0.495471-3.67450.000271
22-0.498509-3.6970.000252
23-0.476097-3.53080.000423
24-0.457462-3.39260.000645
25-0.429548-3.18560.00119
26-0.380831-2.82430.003294
27-0.341107-2.52970.007155
28-0.303871-2.25360.014115
29-0.255384-1.8940.031746
30-0.206639-1.53250.065569
31-0.167669-1.24350.109485
32-0.113898-0.84470.200971
33-0.063269-0.46920.320384
34-0.023254-0.17250.431856
35-0.002547-0.01890.492499
360.0139090.10310.45911






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9174626.80410
2-0.096856-0.71830.237805
3-0.126853-0.94080.175469
4-0.111541-0.82720.205846
5-0.147175-1.09150.13991
60.0839840.62280.267982
7-0.034405-0.25520.399776
8-0.000172-0.00130.499492
9-0.058646-0.43490.332659
10-0.020749-0.15390.439135
110.0001330.0010.499608
12-0.141956-1.05280.148524
13-0.035503-0.26330.396653
14-0.126556-0.93860.17603
150.0895860.66440.254608
16-0.165311-1.2260.112715
17-0.06637-0.49220.312264
18-0.103027-0.76410.224046
19-0.053742-0.39860.345879
20-0.050112-0.37160.355795
210.0035440.02630.489564
220.0424570.31490.377026
230.0485310.35990.360144
24-0.101482-0.75260.227446
25-0.039175-0.29050.386253
260.0612290.45410.325777
27-0.080323-0.59570.276912
28-0.030403-0.22550.411222
290.0727130.53930.295944
30-0.041673-0.30910.379225
31-0.018356-0.13610.446107
320.063930.47410.318648
33-0.019635-0.14560.442379
34-0.104086-0.77190.221732
35-0.099479-0.73780.231899
36-0.057069-0.42320.336887

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.917462 & 6.8041 & 0 \tabularnewline
2 & -0.096856 & -0.7183 & 0.237805 \tabularnewline
3 & -0.126853 & -0.9408 & 0.175469 \tabularnewline
4 & -0.111541 & -0.8272 & 0.205846 \tabularnewline
5 & -0.147175 & -1.0915 & 0.13991 \tabularnewline
6 & 0.083984 & 0.6228 & 0.267982 \tabularnewline
7 & -0.034405 & -0.2552 & 0.399776 \tabularnewline
8 & -0.000172 & -0.0013 & 0.499492 \tabularnewline
9 & -0.058646 & -0.4349 & 0.332659 \tabularnewline
10 & -0.020749 & -0.1539 & 0.439135 \tabularnewline
11 & 0.000133 & 0.001 & 0.499608 \tabularnewline
12 & -0.141956 & -1.0528 & 0.148524 \tabularnewline
13 & -0.035503 & -0.2633 & 0.396653 \tabularnewline
14 & -0.126556 & -0.9386 & 0.17603 \tabularnewline
15 & 0.089586 & 0.6644 & 0.254608 \tabularnewline
16 & -0.165311 & -1.226 & 0.112715 \tabularnewline
17 & -0.06637 & -0.4922 & 0.312264 \tabularnewline
18 & -0.103027 & -0.7641 & 0.224046 \tabularnewline
19 & -0.053742 & -0.3986 & 0.345879 \tabularnewline
20 & -0.050112 & -0.3716 & 0.355795 \tabularnewline
21 & 0.003544 & 0.0263 & 0.489564 \tabularnewline
22 & 0.042457 & 0.3149 & 0.377026 \tabularnewline
23 & 0.048531 & 0.3599 & 0.360144 \tabularnewline
24 & -0.101482 & -0.7526 & 0.227446 \tabularnewline
25 & -0.039175 & -0.2905 & 0.386253 \tabularnewline
26 & 0.061229 & 0.4541 & 0.325777 \tabularnewline
27 & -0.080323 & -0.5957 & 0.276912 \tabularnewline
28 & -0.030403 & -0.2255 & 0.411222 \tabularnewline
29 & 0.072713 & 0.5393 & 0.295944 \tabularnewline
30 & -0.041673 & -0.3091 & 0.379225 \tabularnewline
31 & -0.018356 & -0.1361 & 0.446107 \tabularnewline
32 & 0.06393 & 0.4741 & 0.318648 \tabularnewline
33 & -0.019635 & -0.1456 & 0.442379 \tabularnewline
34 & -0.104086 & -0.7719 & 0.221732 \tabularnewline
35 & -0.099479 & -0.7378 & 0.231899 \tabularnewline
36 & -0.057069 & -0.4232 & 0.336887 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62413&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]0.917462[/C][C]6.8041[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.096856[/C][C]-0.7183[/C][C]0.237805[/C][/ROW]
[ROW][C]3[/C][C]-0.126853[/C][C]-0.9408[/C][C]0.175469[/C][/ROW]
[ROW][C]4[/C][C]-0.111541[/C][C]-0.8272[/C][C]0.205846[/C][/ROW]
[ROW][C]5[/C][C]-0.147175[/C][C]-1.0915[/C][C]0.13991[/C][/ROW]
[ROW][C]6[/C][C]0.083984[/C][C]0.6228[/C][C]0.267982[/C][/ROW]
[ROW][C]7[/C][C]-0.034405[/C][C]-0.2552[/C][C]0.399776[/C][/ROW]
[ROW][C]8[/C][C]-0.000172[/C][C]-0.0013[/C][C]0.499492[/C][/ROW]
[ROW][C]9[/C][C]-0.058646[/C][C]-0.4349[/C][C]0.332659[/C][/ROW]
[ROW][C]10[/C][C]-0.020749[/C][C]-0.1539[/C][C]0.439135[/C][/ROW]
[ROW][C]11[/C][C]0.000133[/C][C]0.001[/C][C]0.499608[/C][/ROW]
[ROW][C]12[/C][C]-0.141956[/C][C]-1.0528[/C][C]0.148524[/C][/ROW]
[ROW][C]13[/C][C]-0.035503[/C][C]-0.2633[/C][C]0.396653[/C][/ROW]
[ROW][C]14[/C][C]-0.126556[/C][C]-0.9386[/C][C]0.17603[/C][/ROW]
[ROW][C]15[/C][C]0.089586[/C][C]0.6644[/C][C]0.254608[/C][/ROW]
[ROW][C]16[/C][C]-0.165311[/C][C]-1.226[/C][C]0.112715[/C][/ROW]
[ROW][C]17[/C][C]-0.06637[/C][C]-0.4922[/C][C]0.312264[/C][/ROW]
[ROW][C]18[/C][C]-0.103027[/C][C]-0.7641[/C][C]0.224046[/C][/ROW]
[ROW][C]19[/C][C]-0.053742[/C][C]-0.3986[/C][C]0.345879[/C][/ROW]
[ROW][C]20[/C][C]-0.050112[/C][C]-0.3716[/C][C]0.355795[/C][/ROW]
[ROW][C]21[/C][C]0.003544[/C][C]0.0263[/C][C]0.489564[/C][/ROW]
[ROW][C]22[/C][C]0.042457[/C][C]0.3149[/C][C]0.377026[/C][/ROW]
[ROW][C]23[/C][C]0.048531[/C][C]0.3599[/C][C]0.360144[/C][/ROW]
[ROW][C]24[/C][C]-0.101482[/C][C]-0.7526[/C][C]0.227446[/C][/ROW]
[ROW][C]25[/C][C]-0.039175[/C][C]-0.2905[/C][C]0.386253[/C][/ROW]
[ROW][C]26[/C][C]0.061229[/C][C]0.4541[/C][C]0.325777[/C][/ROW]
[ROW][C]27[/C][C]-0.080323[/C][C]-0.5957[/C][C]0.276912[/C][/ROW]
[ROW][C]28[/C][C]-0.030403[/C][C]-0.2255[/C][C]0.411222[/C][/ROW]
[ROW][C]29[/C][C]0.072713[/C][C]0.5393[/C][C]0.295944[/C][/ROW]
[ROW][C]30[/C][C]-0.041673[/C][C]-0.3091[/C][C]0.379225[/C][/ROW]
[ROW][C]31[/C][C]-0.018356[/C][C]-0.1361[/C][C]0.446107[/C][/ROW]
[ROW][C]32[/C][C]0.06393[/C][C]0.4741[/C][C]0.318648[/C][/ROW]
[ROW][C]33[/C][C]-0.019635[/C][C]-0.1456[/C][C]0.442379[/C][/ROW]
[ROW][C]34[/C][C]-0.104086[/C][C]-0.7719[/C][C]0.221732[/C][/ROW]
[ROW][C]35[/C][C]-0.099479[/C][C]-0.7378[/C][C]0.231899[/C][/ROW]
[ROW][C]36[/C][C]-0.057069[/C][C]-0.4232[/C][C]0.336887[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62413&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62413&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9174626.80410
2-0.096856-0.71830.237805
3-0.126853-0.94080.175469
4-0.111541-0.82720.205846
5-0.147175-1.09150.13991
60.0839840.62280.267982
7-0.034405-0.25520.399776
8-0.000172-0.00130.499492
9-0.058646-0.43490.332659
10-0.020749-0.15390.439135
110.0001330.0010.499608
12-0.141956-1.05280.148524
13-0.035503-0.26330.396653
14-0.126556-0.93860.17603
150.0895860.66440.254608
16-0.165311-1.2260.112715
17-0.06637-0.49220.312264
18-0.103027-0.76410.224046
19-0.053742-0.39860.345879
20-0.050112-0.37160.355795
210.0035440.02630.489564
220.0424570.31490.377026
230.0485310.35990.360144
24-0.101482-0.75260.227446
25-0.039175-0.29050.386253
260.0612290.45410.325777
27-0.080323-0.59570.276912
28-0.030403-0.22550.411222
290.0727130.53930.295944
30-0.041673-0.30910.379225
31-0.018356-0.13610.446107
320.063930.47410.318648
33-0.019635-0.14560.442379
34-0.104086-0.77190.221732
35-0.099479-0.73780.231899
36-0.057069-0.42320.336887


Figures (Output of Computation)

Input Parameters & R Code

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')