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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 computationTue, 24 Nov 2009 09:08:51 -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/24/t1259079050pe1z0eh6xgh2jw6.htm/, Retrieved Sun, 16 Jun 2024 20:49:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59142, Retrieved Sun, 16 Jun 2024 20:49:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact224
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]
-   PD          [(Partial) Autocorrelation Function] [Workshop 7 - Meth...] [2009-11-24 16:08:51] [d904c6aa144b8c40108ebe5ec22fe1a0] [Current]
-   PD            [(Partial) Autocorrelation Function] [] [2009-11-28 01:06:43] [74be16979710d4c4e7c6647856088456]
-                 [(Partial) Autocorrelation Function] [workshop8/method ...] [2009-11-30 13:01:47] [24c4941ee50deadff4640c9c09cc70cb]
-                 [(Partial) Autocorrelation Function] [] [2009-11-30 16:47:53] [74be16979710d4c4e7c6647856088456]
-                   [(Partial) Autocorrelation Function] [] [2009-12-03 17:26:44] [74be16979710d4c4e7c6647856088456]
-                 [(Partial) Autocorrelation Function] [Workshop 7: Metho...] [2009-12-07 12:46:48] [24c4941ee50deadff4640c9c09cc70cb]
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Dataseries X:
269645
267037
258113
262813
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
295881




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=59142&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=59142&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59142&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
10.9237997.15570
20.8466366.5580
30.7506575.81460
40.6462425.00583e-06
50.542664.20344.4e-05
60.4348433.36830.000663
70.3400712.63420.005357
80.2536411.96470.027043
90.1718421.33110.094099
100.0977460.75710.225964
110.0433910.33610.368982
12-0.021354-0.16540.434589
13-0.069678-0.53970.295692
14-0.122877-0.95180.172509
15-0.184957-1.43270.078571
16-0.228008-1.76610.041229
17-0.274443-2.12580.018821
18-0.322382-2.49720.00764
19-0.36247-2.80770.003361
20-0.402384-3.11690.001402
21-0.442075-3.42430.000559
22-0.46022-3.56480.000361
23-0.473365-3.66670.000261
24-0.456423-3.53540.000396
25-0.446817-3.4610.000499
26-0.42149-3.26480.000906
27-0.383749-2.97250.002123
28-0.346633-2.6850.004682
29-0.319368-2.47380.008107
30-0.284497-2.20370.015697
31-0.25184-1.95070.027881
32-0.224837-1.74160.043353
33-0.181336-1.40460.082644
34-0.142129-1.10090.137663
35-0.104045-0.80590.211732
36-0.085752-0.66420.254543

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.923799 & 7.1557 & 0 \tabularnewline
2 & 0.846636 & 6.558 & 0 \tabularnewline
3 & 0.750657 & 5.8146 & 0 \tabularnewline
4 & 0.646242 & 5.0058 & 3e-06 \tabularnewline
5 & 0.54266 & 4.2034 & 4.4e-05 \tabularnewline
6 & 0.434843 & 3.3683 & 0.000663 \tabularnewline
7 & 0.340071 & 2.6342 & 0.005357 \tabularnewline
8 & 0.253641 & 1.9647 & 0.027043 \tabularnewline
9 & 0.171842 & 1.3311 & 0.094099 \tabularnewline
10 & 0.097746 & 0.7571 & 0.225964 \tabularnewline
11 & 0.043391 & 0.3361 & 0.368982 \tabularnewline
12 & -0.021354 & -0.1654 & 0.434589 \tabularnewline
13 & -0.069678 & -0.5397 & 0.295692 \tabularnewline
14 & -0.122877 & -0.9518 & 0.172509 \tabularnewline
15 & -0.184957 & -1.4327 & 0.078571 \tabularnewline
16 & -0.228008 & -1.7661 & 0.041229 \tabularnewline
17 & -0.274443 & -2.1258 & 0.018821 \tabularnewline
18 & -0.322382 & -2.4972 & 0.00764 \tabularnewline
19 & -0.36247 & -2.8077 & 0.003361 \tabularnewline
20 & -0.402384 & -3.1169 & 0.001402 \tabularnewline
21 & -0.442075 & -3.4243 & 0.000559 \tabularnewline
22 & -0.46022 & -3.5648 & 0.000361 \tabularnewline
23 & -0.473365 & -3.6667 & 0.000261 \tabularnewline
24 & -0.456423 & -3.5354 & 0.000396 \tabularnewline
25 & -0.446817 & -3.461 & 0.000499 \tabularnewline
26 & -0.42149 & -3.2648 & 0.000906 \tabularnewline
27 & -0.383749 & -2.9725 & 0.002123 \tabularnewline
28 & -0.346633 & -2.685 & 0.004682 \tabularnewline
29 & -0.319368 & -2.4738 & 0.008107 \tabularnewline
30 & -0.284497 & -2.2037 & 0.015697 \tabularnewline
31 & -0.25184 & -1.9507 & 0.027881 \tabularnewline
32 & -0.224837 & -1.7416 & 0.043353 \tabularnewline
33 & -0.181336 & -1.4046 & 0.082644 \tabularnewline
34 & -0.142129 & -1.1009 & 0.137663 \tabularnewline
35 & -0.104045 & -0.8059 & 0.211732 \tabularnewline
36 & -0.085752 & -0.6642 & 0.254543 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59142&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]0.923799[/C][C]7.1557[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.846636[/C][C]6.558[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.750657[/C][C]5.8146[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.646242[/C][C]5.0058[/C][C]3e-06[/C][/ROW]
[ROW][C]5[/C][C]0.54266[/C][C]4.2034[/C][C]4.4e-05[/C][/ROW]
[ROW][C]6[/C][C]0.434843[/C][C]3.3683[/C][C]0.000663[/C][/ROW]
[ROW][C]7[/C][C]0.340071[/C][C]2.6342[/C][C]0.005357[/C][/ROW]
[ROW][C]8[/C][C]0.253641[/C][C]1.9647[/C][C]0.027043[/C][/ROW]
[ROW][C]9[/C][C]0.171842[/C][C]1.3311[/C][C]0.094099[/C][/ROW]
[ROW][C]10[/C][C]0.097746[/C][C]0.7571[/C][C]0.225964[/C][/ROW]
[ROW][C]11[/C][C]0.043391[/C][C]0.3361[/C][C]0.368982[/C][/ROW]
[ROW][C]12[/C][C]-0.021354[/C][C]-0.1654[/C][C]0.434589[/C][/ROW]
[ROW][C]13[/C][C]-0.069678[/C][C]-0.5397[/C][C]0.295692[/C][/ROW]
[ROW][C]14[/C][C]-0.122877[/C][C]-0.9518[/C][C]0.172509[/C][/ROW]
[ROW][C]15[/C][C]-0.184957[/C][C]-1.4327[/C][C]0.078571[/C][/ROW]
[ROW][C]16[/C][C]-0.228008[/C][C]-1.7661[/C][C]0.041229[/C][/ROW]
[ROW][C]17[/C][C]-0.274443[/C][C]-2.1258[/C][C]0.018821[/C][/ROW]
[ROW][C]18[/C][C]-0.322382[/C][C]-2.4972[/C][C]0.00764[/C][/ROW]
[ROW][C]19[/C][C]-0.36247[/C][C]-2.8077[/C][C]0.003361[/C][/ROW]
[ROW][C]20[/C][C]-0.402384[/C][C]-3.1169[/C][C]0.001402[/C][/ROW]
[ROW][C]21[/C][C]-0.442075[/C][C]-3.4243[/C][C]0.000559[/C][/ROW]
[ROW][C]22[/C][C]-0.46022[/C][C]-3.5648[/C][C]0.000361[/C][/ROW]
[ROW][C]23[/C][C]-0.473365[/C][C]-3.6667[/C][C]0.000261[/C][/ROW]
[ROW][C]24[/C][C]-0.456423[/C][C]-3.5354[/C][C]0.000396[/C][/ROW]
[ROW][C]25[/C][C]-0.446817[/C][C]-3.461[/C][C]0.000499[/C][/ROW]
[ROW][C]26[/C][C]-0.42149[/C][C]-3.2648[/C][C]0.000906[/C][/ROW]
[ROW][C]27[/C][C]-0.383749[/C][C]-2.9725[/C][C]0.002123[/C][/ROW]
[ROW][C]28[/C][C]-0.346633[/C][C]-2.685[/C][C]0.004682[/C][/ROW]
[ROW][C]29[/C][C]-0.319368[/C][C]-2.4738[/C][C]0.008107[/C][/ROW]
[ROW][C]30[/C][C]-0.284497[/C][C]-2.2037[/C][C]0.015697[/C][/ROW]
[ROW][C]31[/C][C]-0.25184[/C][C]-1.9507[/C][C]0.027881[/C][/ROW]
[ROW][C]32[/C][C]-0.224837[/C][C]-1.7416[/C][C]0.043353[/C][/ROW]
[ROW][C]33[/C][C]-0.181336[/C][C]-1.4046[/C][C]0.082644[/C][/ROW]
[ROW][C]34[/C][C]-0.142129[/C][C]-1.1009[/C][C]0.137663[/C][/ROW]
[ROW][C]35[/C][C]-0.104045[/C][C]-0.8059[/C][C]0.211732[/C][/ROW]
[ROW][C]36[/C][C]-0.085752[/C][C]-0.6642[/C][C]0.254543[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59142&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59142&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
10.9237997.15570
20.8466366.5580
30.7506575.81460
40.6462425.00583e-06
50.542664.20344.4e-05
60.4348433.36830.000663
70.3400712.63420.005357
80.2536411.96470.027043
90.1718421.33110.094099
100.0977460.75710.225964
110.0433910.33610.368982
12-0.021354-0.16540.434589
13-0.069678-0.53970.295692
14-0.122877-0.95180.172509
15-0.184957-1.43270.078571
16-0.228008-1.76610.041229
17-0.274443-2.12580.018821
18-0.322382-2.49720.00764
19-0.36247-2.80770.003361
20-0.402384-3.11690.001402
21-0.442075-3.42430.000559
22-0.46022-3.56480.000361
23-0.473365-3.66670.000261
24-0.456423-3.53540.000396
25-0.446817-3.4610.000499
26-0.42149-3.26480.000906
27-0.383749-2.97250.002123
28-0.346633-2.6850.004682
29-0.319368-2.47380.008107
30-0.284497-2.20370.015697
31-0.25184-1.95070.027881
32-0.224837-1.74160.043353
33-0.181336-1.40460.082644
34-0.142129-1.10090.137663
35-0.104045-0.80590.211732
36-0.085752-0.66420.254543







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9237997.15570
2-0.046177-0.35770.360917
3-0.170373-1.31970.095974
4-0.114407-0.88620.189526
5-0.044626-0.34570.365398
6-0.08452-0.65470.257584
70.0170930.13240.447556
8-0.004607-0.03570.485826
9-0.052018-0.40290.344215
10-0.03839-0.29740.383607
110.0637890.49410.311518
12-0.14708-1.13930.129558
130.0161050.12480.450569
14-0.085496-0.66220.255174
15-0.148302-1.14870.12761
160.0531210.41150.341095
17-0.048011-0.37190.355641
18-0.123603-0.95740.171097
19-0.020795-0.16110.436286
20-0.063074-0.48860.313464
21-0.11834-0.91670.181496
220.0694360.53780.296336
23-0.00518-0.04010.484064
240.0770340.59670.276477
25-0.118167-0.91530.181845
260.0519860.40270.344306
27-0.009963-0.07720.46937
28-0.019004-0.14720.441732
29-0.123049-0.95310.172173
300.0148930.11540.454274
31-0.015733-0.12190.451707
32-0.036809-0.28510.388265
330.0912560.70690.241192
340.030380.23530.407379
35-0.10733-0.83140.204528
36-0.150683-1.16720.123877

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.923799 & 7.1557 & 0 \tabularnewline
2 & -0.046177 & -0.3577 & 0.360917 \tabularnewline
3 & -0.170373 & -1.3197 & 0.095974 \tabularnewline
4 & -0.114407 & -0.8862 & 0.189526 \tabularnewline
5 & -0.044626 & -0.3457 & 0.365398 \tabularnewline
6 & -0.08452 & -0.6547 & 0.257584 \tabularnewline
7 & 0.017093 & 0.1324 & 0.447556 \tabularnewline
8 & -0.004607 & -0.0357 & 0.485826 \tabularnewline
9 & -0.052018 & -0.4029 & 0.344215 \tabularnewline
10 & -0.03839 & -0.2974 & 0.383607 \tabularnewline
11 & 0.063789 & 0.4941 & 0.311518 \tabularnewline
12 & -0.14708 & -1.1393 & 0.129558 \tabularnewline
13 & 0.016105 & 0.1248 & 0.450569 \tabularnewline
14 & -0.085496 & -0.6622 & 0.255174 \tabularnewline
15 & -0.148302 & -1.1487 & 0.12761 \tabularnewline
16 & 0.053121 & 0.4115 & 0.341095 \tabularnewline
17 & -0.048011 & -0.3719 & 0.355641 \tabularnewline
18 & -0.123603 & -0.9574 & 0.171097 \tabularnewline
19 & -0.020795 & -0.1611 & 0.436286 \tabularnewline
20 & -0.063074 & -0.4886 & 0.313464 \tabularnewline
21 & -0.11834 & -0.9167 & 0.181496 \tabularnewline
22 & 0.069436 & 0.5378 & 0.296336 \tabularnewline
23 & -0.00518 & -0.0401 & 0.484064 \tabularnewline
24 & 0.077034 & 0.5967 & 0.276477 \tabularnewline
25 & -0.118167 & -0.9153 & 0.181845 \tabularnewline
26 & 0.051986 & 0.4027 & 0.344306 \tabularnewline
27 & -0.009963 & -0.0772 & 0.46937 \tabularnewline
28 & -0.019004 & -0.1472 & 0.441732 \tabularnewline
29 & -0.123049 & -0.9531 & 0.172173 \tabularnewline
30 & 0.014893 & 0.1154 & 0.454274 \tabularnewline
31 & -0.015733 & -0.1219 & 0.451707 \tabularnewline
32 & -0.036809 & -0.2851 & 0.388265 \tabularnewline
33 & 0.091256 & 0.7069 & 0.241192 \tabularnewline
34 & 0.03038 & 0.2353 & 0.407379 \tabularnewline
35 & -0.10733 & -0.8314 & 0.204528 \tabularnewline
36 & -0.150683 & -1.1672 & 0.123877 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59142&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]0.923799[/C][C]7.1557[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.046177[/C][C]-0.3577[/C][C]0.360917[/C][/ROW]
[ROW][C]3[/C][C]-0.170373[/C][C]-1.3197[/C][C]0.095974[/C][/ROW]
[ROW][C]4[/C][C]-0.114407[/C][C]-0.8862[/C][C]0.189526[/C][/ROW]
[ROW][C]5[/C][C]-0.044626[/C][C]-0.3457[/C][C]0.365398[/C][/ROW]
[ROW][C]6[/C][C]-0.08452[/C][C]-0.6547[/C][C]0.257584[/C][/ROW]
[ROW][C]7[/C][C]0.017093[/C][C]0.1324[/C][C]0.447556[/C][/ROW]
[ROW][C]8[/C][C]-0.004607[/C][C]-0.0357[/C][C]0.485826[/C][/ROW]
[ROW][C]9[/C][C]-0.052018[/C][C]-0.4029[/C][C]0.344215[/C][/ROW]
[ROW][C]10[/C][C]-0.03839[/C][C]-0.2974[/C][C]0.383607[/C][/ROW]
[ROW][C]11[/C][C]0.063789[/C][C]0.4941[/C][C]0.311518[/C][/ROW]
[ROW][C]12[/C][C]-0.14708[/C][C]-1.1393[/C][C]0.129558[/C][/ROW]
[ROW][C]13[/C][C]0.016105[/C][C]0.1248[/C][C]0.450569[/C][/ROW]
[ROW][C]14[/C][C]-0.085496[/C][C]-0.6622[/C][C]0.255174[/C][/ROW]
[ROW][C]15[/C][C]-0.148302[/C][C]-1.1487[/C][C]0.12761[/C][/ROW]
[ROW][C]16[/C][C]0.053121[/C][C]0.4115[/C][C]0.341095[/C][/ROW]
[ROW][C]17[/C][C]-0.048011[/C][C]-0.3719[/C][C]0.355641[/C][/ROW]
[ROW][C]18[/C][C]-0.123603[/C][C]-0.9574[/C][C]0.171097[/C][/ROW]
[ROW][C]19[/C][C]-0.020795[/C][C]-0.1611[/C][C]0.436286[/C][/ROW]
[ROW][C]20[/C][C]-0.063074[/C][C]-0.4886[/C][C]0.313464[/C][/ROW]
[ROW][C]21[/C][C]-0.11834[/C][C]-0.9167[/C][C]0.181496[/C][/ROW]
[ROW][C]22[/C][C]0.069436[/C][C]0.5378[/C][C]0.296336[/C][/ROW]
[ROW][C]23[/C][C]-0.00518[/C][C]-0.0401[/C][C]0.484064[/C][/ROW]
[ROW][C]24[/C][C]0.077034[/C][C]0.5967[/C][C]0.276477[/C][/ROW]
[ROW][C]25[/C][C]-0.118167[/C][C]-0.9153[/C][C]0.181845[/C][/ROW]
[ROW][C]26[/C][C]0.051986[/C][C]0.4027[/C][C]0.344306[/C][/ROW]
[ROW][C]27[/C][C]-0.009963[/C][C]-0.0772[/C][C]0.46937[/C][/ROW]
[ROW][C]28[/C][C]-0.019004[/C][C]-0.1472[/C][C]0.441732[/C][/ROW]
[ROW][C]29[/C][C]-0.123049[/C][C]-0.9531[/C][C]0.172173[/C][/ROW]
[ROW][C]30[/C][C]0.014893[/C][C]0.1154[/C][C]0.454274[/C][/ROW]
[ROW][C]31[/C][C]-0.015733[/C][C]-0.1219[/C][C]0.451707[/C][/ROW]
[ROW][C]32[/C][C]-0.036809[/C][C]-0.2851[/C][C]0.388265[/C][/ROW]
[ROW][C]33[/C][C]0.091256[/C][C]0.7069[/C][C]0.241192[/C][/ROW]
[ROW][C]34[/C][C]0.03038[/C][C]0.2353[/C][C]0.407379[/C][/ROW]
[ROW][C]35[/C][C]-0.10733[/C][C]-0.8314[/C][C]0.204528[/C][/ROW]
[ROW][C]36[/C][C]-0.150683[/C][C]-1.1672[/C][C]0.123877[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59142&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59142&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
10.9237997.15570
2-0.046177-0.35770.360917
3-0.170373-1.31970.095974
4-0.114407-0.88620.189526
5-0.044626-0.34570.365398
6-0.08452-0.65470.257584
70.0170930.13240.447556
8-0.004607-0.03570.485826
9-0.052018-0.40290.344215
10-0.03839-0.29740.383607
110.0637890.49410.311518
12-0.14708-1.13930.129558
130.0161050.12480.450569
14-0.085496-0.66220.255174
15-0.148302-1.14870.12761
160.0531210.41150.341095
17-0.048011-0.37190.355641
18-0.123603-0.95740.171097
19-0.020795-0.16110.436286
20-0.063074-0.48860.313464
21-0.11834-0.91670.181496
220.0694360.53780.296336
23-0.00518-0.04010.484064
240.0770340.59670.276477
25-0.118167-0.91530.181845
260.0519860.40270.344306
27-0.009963-0.07720.46937
28-0.019004-0.14720.441732
29-0.123049-0.95310.172173
300.0148930.11540.454274
31-0.015733-0.12190.451707
32-0.036809-0.28510.388265
330.0912560.70690.241192
340.030380.23530.407379
35-0.10733-0.83140.204528
36-0.150683-1.16720.123877



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')