FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationTue, 15 Dec 2009 06:32:12 -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/15/t12608840153vm85669hbq6wjt.htm/, Retrieved Wed, 08 May 2024 07:53:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67896, Retrieved Wed, 08 May 2024 07:53:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100

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]
-    D          [(Partial) Autocorrelation Function] [] [2009-12-15 13:32:12] [cb3e966d7bf80cd999a0432e97d174a7] [Current]
-   P             [(Partial) Autocorrelation Function] [] [2009-12-18 15:06:49] [1c68450965e88b7c1ed117c35898acdf]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
558
564
581
597
587
536
524
537
536
533
528
516
502
506
518
534
528
478
469
490
493
508
517
514
510
527
542
565
555
499
511
526
532
549
561
557
566
588
620
626
620
573
573
574
580
590
593
597
595
612
628
629
621
569
567
573
584
589
591
595

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=67896&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=67896&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67896&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
10.88846.88150
20.7244915.61190
30.6148344.76256e-06
40.5723514.43342e-05
50.5760274.46191.8e-05
60.565864.38312.4e-05
70.5088643.94160.000107
80.41323.20060.001097
90.3521722.72790.004174
100.3490852.7040.00445
110.4003343.1010.001469
120.4104413.17930.001168
130.2685812.08040.020883
140.0981940.76060.224936
15-0.019332-0.14970.440734
16-0.073801-0.57170.284844
17-0.085607-0.66310.254901
18-0.106471-0.82470.206398
19-0.159959-1.2390.110078
20-0.243602-1.88690.032005
21-0.292432-2.26520.013563
22-0.289211-2.24020.014396
23-0.23785-1.84240.035181
24-0.215635-1.67030.050035
25-0.295867-2.29180.012722
26-0.391813-3.0350.001777
27-0.437655-3.39010.00062
28-0.433817-3.36030.000679
29-0.401522-3.11020.00143
30-0.371411-2.87690.002777
31-0.356623-2.76240.003803
32-0.370571-2.87040.002827
33-0.361048-2.79670.003464
34-0.310675-2.40650.009602
35-0.238869-1.85030.0346
36-0.191277-1.48160.071837

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.8884 & 6.8815 & 0 \tabularnewline
2 & 0.724491 & 5.6119 & 0 \tabularnewline
3 & 0.614834 & 4.7625 & 6e-06 \tabularnewline
4 & 0.572351 & 4.4334 & 2e-05 \tabularnewline
5 & 0.576027 & 4.4619 & 1.8e-05 \tabularnewline
6 & 0.56586 & 4.3831 & 2.4e-05 \tabularnewline
7 & 0.508864 & 3.9416 & 0.000107 \tabularnewline
8 & 0.4132 & 3.2006 & 0.001097 \tabularnewline
9 & 0.352172 & 2.7279 & 0.004174 \tabularnewline
10 & 0.349085 & 2.704 & 0.00445 \tabularnewline
11 & 0.400334 & 3.101 & 0.001469 \tabularnewline
12 & 0.410441 & 3.1793 & 0.001168 \tabularnewline
13 & 0.268581 & 2.0804 & 0.020883 \tabularnewline
14 & 0.098194 & 0.7606 & 0.224936 \tabularnewline
15 & -0.019332 & -0.1497 & 0.440734 \tabularnewline
16 & -0.073801 & -0.5717 & 0.284844 \tabularnewline
17 & -0.085607 & -0.6631 & 0.254901 \tabularnewline
18 & -0.106471 & -0.8247 & 0.206398 \tabularnewline
19 & -0.159959 & -1.239 & 0.110078 \tabularnewline
20 & -0.243602 & -1.8869 & 0.032005 \tabularnewline
21 & -0.292432 & -2.2652 & 0.013563 \tabularnewline
22 & -0.289211 & -2.2402 & 0.014396 \tabularnewline
23 & -0.23785 & -1.8424 & 0.035181 \tabularnewline
24 & -0.215635 & -1.6703 & 0.050035 \tabularnewline
25 & -0.295867 & -2.2918 & 0.012722 \tabularnewline
26 & -0.391813 & -3.035 & 0.001777 \tabularnewline
27 & -0.437655 & -3.3901 & 0.00062 \tabularnewline
28 & -0.433817 & -3.3603 & 0.000679 \tabularnewline
29 & -0.401522 & -3.1102 & 0.00143 \tabularnewline
30 & -0.371411 & -2.8769 & 0.002777 \tabularnewline
31 & -0.356623 & -2.7624 & 0.003803 \tabularnewline
32 & -0.370571 & -2.8704 & 0.002827 \tabularnewline
33 & -0.361048 & -2.7967 & 0.003464 \tabularnewline
34 & -0.310675 & -2.4065 & 0.009602 \tabularnewline
35 & -0.238869 & -1.8503 & 0.0346 \tabularnewline
36 & -0.191277 & -1.4816 & 0.071837 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67896&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]0.8884[/C][C]6.8815[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.724491[/C][C]5.6119[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.614834[/C][C]4.7625[/C][C]6e-06[/C][/ROW]
[ROW][C]4[/C][C]0.572351[/C][C]4.4334[/C][C]2e-05[/C][/ROW]
[ROW][C]5[/C][C]0.576027[/C][C]4.4619[/C][C]1.8e-05[/C][/ROW]
[ROW][C]6[/C][C]0.56586[/C][C]4.3831[/C][C]2.4e-05[/C][/ROW]
[ROW][C]7[/C][C]0.508864[/C][C]3.9416[/C][C]0.000107[/C][/ROW]
[ROW][C]8[/C][C]0.4132[/C][C]3.2006[/C][C]0.001097[/C][/ROW]
[ROW][C]9[/C][C]0.352172[/C][C]2.7279[/C][C]0.004174[/C][/ROW]
[ROW][C]10[/C][C]0.349085[/C][C]2.704[/C][C]0.00445[/C][/ROW]
[ROW][C]11[/C][C]0.400334[/C][C]3.101[/C][C]0.001469[/C][/ROW]
[ROW][C]12[/C][C]0.410441[/C][C]3.1793[/C][C]0.001168[/C][/ROW]
[ROW][C]13[/C][C]0.268581[/C][C]2.0804[/C][C]0.020883[/C][/ROW]
[ROW][C]14[/C][C]0.098194[/C][C]0.7606[/C][C]0.224936[/C][/ROW]
[ROW][C]15[/C][C]-0.019332[/C][C]-0.1497[/C][C]0.440734[/C][/ROW]
[ROW][C]16[/C][C]-0.073801[/C][C]-0.5717[/C][C]0.284844[/C][/ROW]
[ROW][C]17[/C][C]-0.085607[/C][C]-0.6631[/C][C]0.254901[/C][/ROW]
[ROW][C]18[/C][C]-0.106471[/C][C]-0.8247[/C][C]0.206398[/C][/ROW]
[ROW][C]19[/C][C]-0.159959[/C][C]-1.239[/C][C]0.110078[/C][/ROW]
[ROW][C]20[/C][C]-0.243602[/C][C]-1.8869[/C][C]0.032005[/C][/ROW]
[ROW][C]21[/C][C]-0.292432[/C][C]-2.2652[/C][C]0.013563[/C][/ROW]
[ROW][C]22[/C][C]-0.289211[/C][C]-2.2402[/C][C]0.014396[/C][/ROW]
[ROW][C]23[/C][C]-0.23785[/C][C]-1.8424[/C][C]0.035181[/C][/ROW]
[ROW][C]24[/C][C]-0.215635[/C][C]-1.6703[/C][C]0.050035[/C][/ROW]
[ROW][C]25[/C][C]-0.295867[/C][C]-2.2918[/C][C]0.012722[/C][/ROW]
[ROW][C]26[/C][C]-0.391813[/C][C]-3.035[/C][C]0.001777[/C][/ROW]
[ROW][C]27[/C][C]-0.437655[/C][C]-3.3901[/C][C]0.00062[/C][/ROW]
[ROW][C]28[/C][C]-0.433817[/C][C]-3.3603[/C][C]0.000679[/C][/ROW]
[ROW][C]29[/C][C]-0.401522[/C][C]-3.1102[/C][C]0.00143[/C][/ROW]
[ROW][C]30[/C][C]-0.371411[/C][C]-2.8769[/C][C]0.002777[/C][/ROW]
[ROW][C]31[/C][C]-0.356623[/C][C]-2.7624[/C][C]0.003803[/C][/ROW]
[ROW][C]32[/C][C]-0.370571[/C][C]-2.8704[/C][C]0.002827[/C][/ROW]
[ROW][C]33[/C][C]-0.361048[/C][C]-2.7967[/C][C]0.003464[/C][/ROW]
[ROW][C]34[/C][C]-0.310675[/C][C]-2.4065[/C][C]0.009602[/C][/ROW]
[ROW][C]35[/C][C]-0.238869[/C][C]-1.8503[/C][C]0.0346[/C][/ROW]
[ROW][C]36[/C][C]-0.191277[/C][C]-1.4816[/C][C]0.071837[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67896&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67896&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
10.88846.88150
20.7244915.61190
30.6148344.76256e-06
40.5723514.43342e-05
50.5760274.46191.8e-05
60.565864.38312.4e-05
70.5088643.94160.000107
80.41323.20060.001097
90.3521722.72790.004174
100.3490852.7040.00445
110.4003343.1010.001469
120.4104413.17930.001168
130.2685812.08040.020883
140.0981940.76060.224936
15-0.019332-0.14970.440734
16-0.073801-0.57170.284844
17-0.085607-0.66310.254901
18-0.106471-0.82470.206398
19-0.159959-1.2390.110078
20-0.243602-1.88690.032005
21-0.292432-2.26520.013563
22-0.289211-2.24020.014396
23-0.23785-1.84240.035181
24-0.215635-1.67030.050035
25-0.295867-2.29180.012722
26-0.391813-3.0350.001777
27-0.437655-3.39010.00062
28-0.433817-3.36030.000679
29-0.401522-3.11020.00143
30-0.371411-2.87690.002777
31-0.356623-2.76240.003803
32-0.370571-2.87040.002827
33-0.361048-2.79670.003464
34-0.310675-2.40650.009602
35-0.238869-1.85030.0346
36-0.191277-1.48160.071837






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.88846.88150
2-0.30731-2.38040.010243
30.2432011.88380.032218
40.1311261.01570.156926
50.1505751.16640.124044
6-0.06308-0.48860.313448
7-0.087407-0.67710.250487
8-0.116957-0.90590.184294
90.1603691.24220.109496
100.0606780.470.320027
110.2085761.61560.055711
12-0.251267-1.94630.028153
13-0.591153-4.57911.2e-05
140.1399011.08370.141423
15-0.044175-0.34220.366707
16-0.082816-0.64150.261825
17-0.078253-0.60610.273351
18-0.125042-0.96860.168323
190.1201630.93080.17785
200.0213750.16560.434526
21-0.005742-0.04450.482335
22-0.039177-0.30350.381295
23-0.003528-0.02730.489143
240.0589060.45630.324916
250.0225360.17460.431006
26-0.054239-0.42010.337946
270.0551630.42730.335349
28-0.082353-0.63790.262983
290.0085290.06610.473773
300.0605830.46930.320286
310.0773930.59950.275554
32-0.069183-0.53590.297008
33-0.000874-0.00680.49731
340.0155220.12020.452349
35-0.089908-0.69640.244427
360.0649320.5030.308418

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.8884 & 6.8815 & 0 \tabularnewline
2 & -0.30731 & -2.3804 & 0.010243 \tabularnewline
3 & 0.243201 & 1.8838 & 0.032218 \tabularnewline
4 & 0.131126 & 1.0157 & 0.156926 \tabularnewline
5 & 0.150575 & 1.1664 & 0.124044 \tabularnewline
6 & -0.06308 & -0.4886 & 0.313448 \tabularnewline
7 & -0.087407 & -0.6771 & 0.250487 \tabularnewline
8 & -0.116957 & -0.9059 & 0.184294 \tabularnewline
9 & 0.160369 & 1.2422 & 0.109496 \tabularnewline
10 & 0.060678 & 0.47 & 0.320027 \tabularnewline
11 & 0.208576 & 1.6156 & 0.055711 \tabularnewline
12 & -0.251267 & -1.9463 & 0.028153 \tabularnewline
13 & -0.591153 & -4.5791 & 1.2e-05 \tabularnewline
14 & 0.139901 & 1.0837 & 0.141423 \tabularnewline
15 & -0.044175 & -0.3422 & 0.366707 \tabularnewline
16 & -0.082816 & -0.6415 & 0.261825 \tabularnewline
17 & -0.078253 & -0.6061 & 0.273351 \tabularnewline
18 & -0.125042 & -0.9686 & 0.168323 \tabularnewline
19 & 0.120163 & 0.9308 & 0.17785 \tabularnewline
20 & 0.021375 & 0.1656 & 0.434526 \tabularnewline
21 & -0.005742 & -0.0445 & 0.482335 \tabularnewline
22 & -0.039177 & -0.3035 & 0.381295 \tabularnewline
23 & -0.003528 & -0.0273 & 0.489143 \tabularnewline
24 & 0.058906 & 0.4563 & 0.324916 \tabularnewline
25 & 0.022536 & 0.1746 & 0.431006 \tabularnewline
26 & -0.054239 & -0.4201 & 0.337946 \tabularnewline
27 & 0.055163 & 0.4273 & 0.335349 \tabularnewline
28 & -0.082353 & -0.6379 & 0.262983 \tabularnewline
29 & 0.008529 & 0.0661 & 0.473773 \tabularnewline
30 & 0.060583 & 0.4693 & 0.320286 \tabularnewline
31 & 0.077393 & 0.5995 & 0.275554 \tabularnewline
32 & -0.069183 & -0.5359 & 0.297008 \tabularnewline
33 & -0.000874 & -0.0068 & 0.49731 \tabularnewline
34 & 0.015522 & 0.1202 & 0.452349 \tabularnewline
35 & -0.089908 & -0.6964 & 0.244427 \tabularnewline
36 & 0.064932 & 0.503 & 0.308418 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67896&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]0.8884[/C][C]6.8815[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.30731[/C][C]-2.3804[/C][C]0.010243[/C][/ROW]
[ROW][C]3[/C][C]0.243201[/C][C]1.8838[/C][C]0.032218[/C][/ROW]
[ROW][C]4[/C][C]0.131126[/C][C]1.0157[/C][C]0.156926[/C][/ROW]
[ROW][C]5[/C][C]0.150575[/C][C]1.1664[/C][C]0.124044[/C][/ROW]
[ROW][C]6[/C][C]-0.06308[/C][C]-0.4886[/C][C]0.313448[/C][/ROW]
[ROW][C]7[/C][C]-0.087407[/C][C]-0.6771[/C][C]0.250487[/C][/ROW]
[ROW][C]8[/C][C]-0.116957[/C][C]-0.9059[/C][C]0.184294[/C][/ROW]
[ROW][C]9[/C][C]0.160369[/C][C]1.2422[/C][C]0.109496[/C][/ROW]
[ROW][C]10[/C][C]0.060678[/C][C]0.47[/C][C]0.320027[/C][/ROW]
[ROW][C]11[/C][C]0.208576[/C][C]1.6156[/C][C]0.055711[/C][/ROW]
[ROW][C]12[/C][C]-0.251267[/C][C]-1.9463[/C][C]0.028153[/C][/ROW]
[ROW][C]13[/C][C]-0.591153[/C][C]-4.5791[/C][C]1.2e-05[/C][/ROW]
[ROW][C]14[/C][C]0.139901[/C][C]1.0837[/C][C]0.141423[/C][/ROW]
[ROW][C]15[/C][C]-0.044175[/C][C]-0.3422[/C][C]0.366707[/C][/ROW]
[ROW][C]16[/C][C]-0.082816[/C][C]-0.6415[/C][C]0.261825[/C][/ROW]
[ROW][C]17[/C][C]-0.078253[/C][C]-0.6061[/C][C]0.273351[/C][/ROW]
[ROW][C]18[/C][C]-0.125042[/C][C]-0.9686[/C][C]0.168323[/C][/ROW]
[ROW][C]19[/C][C]0.120163[/C][C]0.9308[/C][C]0.17785[/C][/ROW]
[ROW][C]20[/C][C]0.021375[/C][C]0.1656[/C][C]0.434526[/C][/ROW]
[ROW][C]21[/C][C]-0.005742[/C][C]-0.0445[/C][C]0.482335[/C][/ROW]
[ROW][C]22[/C][C]-0.039177[/C][C]-0.3035[/C][C]0.381295[/C][/ROW]
[ROW][C]23[/C][C]-0.003528[/C][C]-0.0273[/C][C]0.489143[/C][/ROW]
[ROW][C]24[/C][C]0.058906[/C][C]0.4563[/C][C]0.324916[/C][/ROW]
[ROW][C]25[/C][C]0.022536[/C][C]0.1746[/C][C]0.431006[/C][/ROW]
[ROW][C]26[/C][C]-0.054239[/C][C]-0.4201[/C][C]0.337946[/C][/ROW]
[ROW][C]27[/C][C]0.055163[/C][C]0.4273[/C][C]0.335349[/C][/ROW]
[ROW][C]28[/C][C]-0.082353[/C][C]-0.6379[/C][C]0.262983[/C][/ROW]
[ROW][C]29[/C][C]0.008529[/C][C]0.0661[/C][C]0.473773[/C][/ROW]
[ROW][C]30[/C][C]0.060583[/C][C]0.4693[/C][C]0.320286[/C][/ROW]
[ROW][C]31[/C][C]0.077393[/C][C]0.5995[/C][C]0.275554[/C][/ROW]
[ROW][C]32[/C][C]-0.069183[/C][C]-0.5359[/C][C]0.297008[/C][/ROW]
[ROW][C]33[/C][C]-0.000874[/C][C]-0.0068[/C][C]0.49731[/C][/ROW]
[ROW][C]34[/C][C]0.015522[/C][C]0.1202[/C][C]0.452349[/C][/ROW]
[ROW][C]35[/C][C]-0.089908[/C][C]-0.6964[/C][C]0.244427[/C][/ROW]
[ROW][C]36[/C][C]0.064932[/C][C]0.503[/C][C]0.308418[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67896&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67896&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
10.88846.88150
2-0.30731-2.38040.010243
30.2432011.88380.032218
40.1311261.01570.156926
50.1505751.16640.124044
6-0.06308-0.48860.313448
7-0.087407-0.67710.250487
8-0.116957-0.90590.184294
90.1603691.24220.109496
100.0606780.470.320027
110.2085761.61560.055711
12-0.251267-1.94630.028153
13-0.591153-4.57911.2e-05
140.1399011.08370.141423
15-0.044175-0.34220.366707
16-0.082816-0.64150.261825
17-0.078253-0.60610.273351
18-0.125042-0.96860.168323
190.1201630.93080.17785
200.0213750.16560.434526
21-0.005742-0.04450.482335
22-0.039177-0.30350.381295
23-0.003528-0.02730.489143
240.0589060.45630.324916
250.0225360.17460.431006
26-0.054239-0.42010.337946
270.0551630.42730.335349
28-0.082353-0.63790.262983
290.0085290.06610.473773
300.0605830.46930.320286
310.0773930.59950.275554
32-0.069183-0.53590.297008
33-0.000874-0.00680.49731
340.0155220.12020.452349
35-0.089908-0.69640.244427
360.0649320.5030.308418


Figures (Output of Computation)

Input Parameters & R Code

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')