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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 computationThu, 26 Nov 2009 08:43:41 -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/t12592504039jgbzycoofadvk5.htm/, Retrieved Mon, 29 Apr 2024 05:10:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60120, Retrieved Mon, 29 Apr 2024 05:10:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134

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 12:19:56] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [] [2009-11-26 15:43:41] [27b6e36591879260e4dc6bb7e89a38fd] [Current]
-   P             [(Partial) Autocorrelation Function] [] [2009-12-18 11:26:25] [e149fd9094b67af26551857fa83a9d9d]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
613
611
594
595
591
589
584
573
567
569
621
629
628
612
595
597
593
590
580
574
573
573
620
626
620
588
566
557
561
549
532
526
511
499
555
565
542
527
510
514
517
508
493
490
469
478
528
534
518
506
502
516
528
533
536
537
524
536
587
597
581

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=60120&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=60120&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60120&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
10.9239956.4680
20.8457815.92050
30.758515.30961e-06
40.65364.57521.6e-05
50.5390563.77340.000218
60.4279472.99560.002144
70.3137822.19650.01641
80.2156151.50930.068822
90.1217940.85260.199027
100.0360890.25260.400809
11-0.033418-0.23390.408007
12-0.104499-0.73150.233982
13-0.165979-1.16190.125461
14-0.211121-1.47780.072924
15-0.265907-1.86130.03435
16-0.325001-2.2750.013659
17-0.362811-2.53970.007159
18-0.408949-2.86260.003082
19-0.441747-3.09220.001637
20-0.474918-3.32440.000842
21-0.494935-3.46450.000557
22-0.499377-3.49560.000507
23-0.489641-3.42750.000621
24-0.470603-3.29420.000919
25-0.413423-2.8940.002832
26-0.375571-2.6290.005704
27-0.327327-2.29130.013143
28-0.263137-1.8420.035769
29-0.204948-1.43460.078871
30-0.155902-1.09130.140235
31-0.102989-0.72090.237192
32-0.057775-0.40440.34383
33-0.012311-0.08620.465837
340.033090.23160.408895
350.0680540.47640.31796
360.1006490.70450.242214

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.923995 & 6.468 & 0 \tabularnewline
2 & 0.845781 & 5.9205 & 0 \tabularnewline
3 & 0.75851 & 5.3096 & 1e-06 \tabularnewline
4 & 0.6536 & 4.5752 & 1.6e-05 \tabularnewline
5 & 0.539056 & 3.7734 & 0.000218 \tabularnewline
6 & 0.427947 & 2.9956 & 0.002144 \tabularnewline
7 & 0.313782 & 2.1965 & 0.01641 \tabularnewline
8 & 0.215615 & 1.5093 & 0.068822 \tabularnewline
9 & 0.121794 & 0.8526 & 0.199027 \tabularnewline
10 & 0.036089 & 0.2526 & 0.400809 \tabularnewline
11 & -0.033418 & -0.2339 & 0.408007 \tabularnewline
12 & -0.104499 & -0.7315 & 0.233982 \tabularnewline
13 & -0.165979 & -1.1619 & 0.125461 \tabularnewline
14 & -0.211121 & -1.4778 & 0.072924 \tabularnewline
15 & -0.265907 & -1.8613 & 0.03435 \tabularnewline
16 & -0.325001 & -2.275 & 0.013659 \tabularnewline
17 & -0.362811 & -2.5397 & 0.007159 \tabularnewline
18 & -0.408949 & -2.8626 & 0.003082 \tabularnewline
19 & -0.441747 & -3.0922 & 0.001637 \tabularnewline
20 & -0.474918 & -3.3244 & 0.000842 \tabularnewline
21 & -0.494935 & -3.4645 & 0.000557 \tabularnewline
22 & -0.499377 & -3.4956 & 0.000507 \tabularnewline
23 & -0.489641 & -3.4275 & 0.000621 \tabularnewline
24 & -0.470603 & -3.2942 & 0.000919 \tabularnewline
25 & -0.413423 & -2.894 & 0.002832 \tabularnewline
26 & -0.375571 & -2.629 & 0.005704 \tabularnewline
27 & -0.327327 & -2.2913 & 0.013143 \tabularnewline
28 & -0.263137 & -1.842 & 0.035769 \tabularnewline
29 & -0.204948 & -1.4346 & 0.078871 \tabularnewline
30 & -0.155902 & -1.0913 & 0.140235 \tabularnewline
31 & -0.102989 & -0.7209 & 0.237192 \tabularnewline
32 & -0.057775 & -0.4044 & 0.34383 \tabularnewline
33 & -0.012311 & -0.0862 & 0.465837 \tabularnewline
34 & 0.03309 & 0.2316 & 0.408895 \tabularnewline
35 & 0.068054 & 0.4764 & 0.31796 \tabularnewline
36 & 0.100649 & 0.7045 & 0.242214 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60120&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]0.923995[/C][C]6.468[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.845781[/C][C]5.9205[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.75851[/C][C]5.3096[/C][C]1e-06[/C][/ROW]
[ROW][C]4[/C][C]0.6536[/C][C]4.5752[/C][C]1.6e-05[/C][/ROW]
[ROW][C]5[/C][C]0.539056[/C][C]3.7734[/C][C]0.000218[/C][/ROW]
[ROW][C]6[/C][C]0.427947[/C][C]2.9956[/C][C]0.002144[/C][/ROW]
[ROW][C]7[/C][C]0.313782[/C][C]2.1965[/C][C]0.01641[/C][/ROW]
[ROW][C]8[/C][C]0.215615[/C][C]1.5093[/C][C]0.068822[/C][/ROW]
[ROW][C]9[/C][C]0.121794[/C][C]0.8526[/C][C]0.199027[/C][/ROW]
[ROW][C]10[/C][C]0.036089[/C][C]0.2526[/C][C]0.400809[/C][/ROW]
[ROW][C]11[/C][C]-0.033418[/C][C]-0.2339[/C][C]0.408007[/C][/ROW]
[ROW][C]12[/C][C]-0.104499[/C][C]-0.7315[/C][C]0.233982[/C][/ROW]
[ROW][C]13[/C][C]-0.165979[/C][C]-1.1619[/C][C]0.125461[/C][/ROW]
[ROW][C]14[/C][C]-0.211121[/C][C]-1.4778[/C][C]0.072924[/C][/ROW]
[ROW][C]15[/C][C]-0.265907[/C][C]-1.8613[/C][C]0.03435[/C][/ROW]
[ROW][C]16[/C][C]-0.325001[/C][C]-2.275[/C][C]0.013659[/C][/ROW]
[ROW][C]17[/C][C]-0.362811[/C][C]-2.5397[/C][C]0.007159[/C][/ROW]
[ROW][C]18[/C][C]-0.408949[/C][C]-2.8626[/C][C]0.003082[/C][/ROW]
[ROW][C]19[/C][C]-0.441747[/C][C]-3.0922[/C][C]0.001637[/C][/ROW]
[ROW][C]20[/C][C]-0.474918[/C][C]-3.3244[/C][C]0.000842[/C][/ROW]
[ROW][C]21[/C][C]-0.494935[/C][C]-3.4645[/C][C]0.000557[/C][/ROW]
[ROW][C]22[/C][C]-0.499377[/C][C]-3.4956[/C][C]0.000507[/C][/ROW]
[ROW][C]23[/C][C]-0.489641[/C][C]-3.4275[/C][C]0.000621[/C][/ROW]
[ROW][C]24[/C][C]-0.470603[/C][C]-3.2942[/C][C]0.000919[/C][/ROW]
[ROW][C]25[/C][C]-0.413423[/C][C]-2.894[/C][C]0.002832[/C][/ROW]
[ROW][C]26[/C][C]-0.375571[/C][C]-2.629[/C][C]0.005704[/C][/ROW]
[ROW][C]27[/C][C]-0.327327[/C][C]-2.2913[/C][C]0.013143[/C][/ROW]
[ROW][C]28[/C][C]-0.263137[/C][C]-1.842[/C][C]0.035769[/C][/ROW]
[ROW][C]29[/C][C]-0.204948[/C][C]-1.4346[/C][C]0.078871[/C][/ROW]
[ROW][C]30[/C][C]-0.155902[/C][C]-1.0913[/C][C]0.140235[/C][/ROW]
[ROW][C]31[/C][C]-0.102989[/C][C]-0.7209[/C][C]0.237192[/C][/ROW]
[ROW][C]32[/C][C]-0.057775[/C][C]-0.4044[/C][C]0.34383[/C][/ROW]
[ROW][C]33[/C][C]-0.012311[/C][C]-0.0862[/C][C]0.465837[/C][/ROW]
[ROW][C]34[/C][C]0.03309[/C][C]0.2316[/C][C]0.408895[/C][/ROW]
[ROW][C]35[/C][C]0.068054[/C][C]0.4764[/C][C]0.31796[/C][/ROW]
[ROW][C]36[/C][C]0.100649[/C][C]0.7045[/C][C]0.242214[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60120&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60120&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
10.9239956.4680
20.8457815.92050
30.758515.30961e-06
40.65364.57521.6e-05
50.5390563.77340.000218
60.4279472.99560.002144
70.3137822.19650.01641
80.2156151.50930.068822
90.1217940.85260.199027
100.0360890.25260.400809
11-0.033418-0.23390.408007
12-0.104499-0.73150.233982
13-0.165979-1.16190.125461
14-0.211121-1.47780.072924
15-0.265907-1.86130.03435
16-0.325001-2.2750.013659
17-0.362811-2.53970.007159
18-0.408949-2.86260.003082
19-0.441747-3.09220.001637
20-0.474918-3.32440.000842
21-0.494935-3.46450.000557
22-0.499377-3.49560.000507
23-0.489641-3.42750.000621
24-0.470603-3.29420.000919
25-0.413423-2.8940.002832
26-0.375571-2.6290.005704
27-0.327327-2.29130.013143
28-0.263137-1.8420.035769
29-0.204948-1.43460.078871
30-0.155902-1.09130.140235
31-0.102989-0.72090.237192
32-0.057775-0.40440.34383
33-0.012311-0.08620.465837
340.033090.23160.408895
350.0680540.47640.31796
360.1006490.70450.242214






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9239956.4680
2-0.054612-0.38230.351953
3-0.104295-0.73010.234414
4-0.170684-1.19480.118961
5-0.129799-0.90860.184006
6-0.04157-0.2910.386145
7-0.082323-0.57630.283537
80.0393570.27550.392045
9-0.047102-0.32970.371512
10-0.033524-0.23470.407723
110.0114270.080.468287
12-0.11153-0.78070.219364
13-0.031823-0.22280.412325
140.0097880.06850.472828
15-0.144606-1.01220.158197
16-0.134217-0.93950.176036
170.0372910.2610.39758
18-0.122548-0.85780.19758
190.0056240.03940.484378
20-0.106529-0.74570.229705
210.0048430.03390.486546
220.0102840.0720.471452
230.0036050.02520.489986
240.0111720.07820.468992
250.1663641.16450.12492
26-0.187643-1.31350.097566
270.0165030.11550.454253
280.0281990.19740.42217
29-0.040747-0.28520.388335
30-0.039569-0.2770.391478
31-0.009531-0.06670.473538
32-0.009573-0.0670.473424
330.0221580.15510.438688
340.0165260.11570.454188
35-0.00014-0.0010.499612
36-0.061608-0.43130.334087

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.923995 & 6.468 & 0 \tabularnewline
2 & -0.054612 & -0.3823 & 0.351953 \tabularnewline
3 & -0.104295 & -0.7301 & 0.234414 \tabularnewline
4 & -0.170684 & -1.1948 & 0.118961 \tabularnewline
5 & -0.129799 & -0.9086 & 0.184006 \tabularnewline
6 & -0.04157 & -0.291 & 0.386145 \tabularnewline
7 & -0.082323 & -0.5763 & 0.283537 \tabularnewline
8 & 0.039357 & 0.2755 & 0.392045 \tabularnewline
9 & -0.047102 & -0.3297 & 0.371512 \tabularnewline
10 & -0.033524 & -0.2347 & 0.407723 \tabularnewline
11 & 0.011427 & 0.08 & 0.468287 \tabularnewline
12 & -0.11153 & -0.7807 & 0.219364 \tabularnewline
13 & -0.031823 & -0.2228 & 0.412325 \tabularnewline
14 & 0.009788 & 0.0685 & 0.472828 \tabularnewline
15 & -0.144606 & -1.0122 & 0.158197 \tabularnewline
16 & -0.134217 & -0.9395 & 0.176036 \tabularnewline
17 & 0.037291 & 0.261 & 0.39758 \tabularnewline
18 & -0.122548 & -0.8578 & 0.19758 \tabularnewline
19 & 0.005624 & 0.0394 & 0.484378 \tabularnewline
20 & -0.106529 & -0.7457 & 0.229705 \tabularnewline
21 & 0.004843 & 0.0339 & 0.486546 \tabularnewline
22 & 0.010284 & 0.072 & 0.471452 \tabularnewline
23 & 0.003605 & 0.0252 & 0.489986 \tabularnewline
24 & 0.011172 & 0.0782 & 0.468992 \tabularnewline
25 & 0.166364 & 1.1645 & 0.12492 \tabularnewline
26 & -0.187643 & -1.3135 & 0.097566 \tabularnewline
27 & 0.016503 & 0.1155 & 0.454253 \tabularnewline
28 & 0.028199 & 0.1974 & 0.42217 \tabularnewline
29 & -0.040747 & -0.2852 & 0.388335 \tabularnewline
30 & -0.039569 & -0.277 & 0.391478 \tabularnewline
31 & -0.009531 & -0.0667 & 0.473538 \tabularnewline
32 & -0.009573 & -0.067 & 0.473424 \tabularnewline
33 & 0.022158 & 0.1551 & 0.438688 \tabularnewline
34 & 0.016526 & 0.1157 & 0.454188 \tabularnewline
35 & -0.00014 & -0.001 & 0.499612 \tabularnewline
36 & -0.061608 & -0.4313 & 0.334087 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60120&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]0.923995[/C][C]6.468[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.054612[/C][C]-0.3823[/C][C]0.351953[/C][/ROW]
[ROW][C]3[/C][C]-0.104295[/C][C]-0.7301[/C][C]0.234414[/C][/ROW]
[ROW][C]4[/C][C]-0.170684[/C][C]-1.1948[/C][C]0.118961[/C][/ROW]
[ROW][C]5[/C][C]-0.129799[/C][C]-0.9086[/C][C]0.184006[/C][/ROW]
[ROW][C]6[/C][C]-0.04157[/C][C]-0.291[/C][C]0.386145[/C][/ROW]
[ROW][C]7[/C][C]-0.082323[/C][C]-0.5763[/C][C]0.283537[/C][/ROW]
[ROW][C]8[/C][C]0.039357[/C][C]0.2755[/C][C]0.392045[/C][/ROW]
[ROW][C]9[/C][C]-0.047102[/C][C]-0.3297[/C][C]0.371512[/C][/ROW]
[ROW][C]10[/C][C]-0.033524[/C][C]-0.2347[/C][C]0.407723[/C][/ROW]
[ROW][C]11[/C][C]0.011427[/C][C]0.08[/C][C]0.468287[/C][/ROW]
[ROW][C]12[/C][C]-0.11153[/C][C]-0.7807[/C][C]0.219364[/C][/ROW]
[ROW][C]13[/C][C]-0.031823[/C][C]-0.2228[/C][C]0.412325[/C][/ROW]
[ROW][C]14[/C][C]0.009788[/C][C]0.0685[/C][C]0.472828[/C][/ROW]
[ROW][C]15[/C][C]-0.144606[/C][C]-1.0122[/C][C]0.158197[/C][/ROW]
[ROW][C]16[/C][C]-0.134217[/C][C]-0.9395[/C][C]0.176036[/C][/ROW]
[ROW][C]17[/C][C]0.037291[/C][C]0.261[/C][C]0.39758[/C][/ROW]
[ROW][C]18[/C][C]-0.122548[/C][C]-0.8578[/C][C]0.19758[/C][/ROW]
[ROW][C]19[/C][C]0.005624[/C][C]0.0394[/C][C]0.484378[/C][/ROW]
[ROW][C]20[/C][C]-0.106529[/C][C]-0.7457[/C][C]0.229705[/C][/ROW]
[ROW][C]21[/C][C]0.004843[/C][C]0.0339[/C][C]0.486546[/C][/ROW]
[ROW][C]22[/C][C]0.010284[/C][C]0.072[/C][C]0.471452[/C][/ROW]
[ROW][C]23[/C][C]0.003605[/C][C]0.0252[/C][C]0.489986[/C][/ROW]
[ROW][C]24[/C][C]0.011172[/C][C]0.0782[/C][C]0.468992[/C][/ROW]
[ROW][C]25[/C][C]0.166364[/C][C]1.1645[/C][C]0.12492[/C][/ROW]
[ROW][C]26[/C][C]-0.187643[/C][C]-1.3135[/C][C]0.097566[/C][/ROW]
[ROW][C]27[/C][C]0.016503[/C][C]0.1155[/C][C]0.454253[/C][/ROW]
[ROW][C]28[/C][C]0.028199[/C][C]0.1974[/C][C]0.42217[/C][/ROW]
[ROW][C]29[/C][C]-0.040747[/C][C]-0.2852[/C][C]0.388335[/C][/ROW]
[ROW][C]30[/C][C]-0.039569[/C][C]-0.277[/C][C]0.391478[/C][/ROW]
[ROW][C]31[/C][C]-0.009531[/C][C]-0.0667[/C][C]0.473538[/C][/ROW]
[ROW][C]32[/C][C]-0.009573[/C][C]-0.067[/C][C]0.473424[/C][/ROW]
[ROW][C]33[/C][C]0.022158[/C][C]0.1551[/C][C]0.438688[/C][/ROW]
[ROW][C]34[/C][C]0.016526[/C][C]0.1157[/C][C]0.454188[/C][/ROW]
[ROW][C]35[/C][C]-0.00014[/C][C]-0.001[/C][C]0.499612[/C][/ROW]
[ROW][C]36[/C][C]-0.061608[/C][C]-0.4313[/C][C]0.334087[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60120&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60120&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
10.9239956.4680
2-0.054612-0.38230.351953
3-0.104295-0.73010.234414
4-0.170684-1.19480.118961
5-0.129799-0.90860.184006
6-0.04157-0.2910.386145
7-0.082323-0.57630.283537
80.0393570.27550.392045
9-0.047102-0.32970.371512
10-0.033524-0.23470.407723
110.0114270.080.468287
12-0.11153-0.78070.219364
13-0.031823-0.22280.412325
140.0097880.06850.472828
15-0.144606-1.01220.158197
16-0.134217-0.93950.176036
170.0372910.2610.39758
18-0.122548-0.85780.19758
190.0056240.03940.484378
20-0.106529-0.74570.229705
210.0048430.03390.486546
220.0102840.0720.471452
230.0036050.02520.489986
240.0111720.07820.468992
250.1663641.16450.12492
26-0.187643-1.31350.097566
270.0165030.11550.454253
280.0281990.19740.42217
29-0.040747-0.28520.388335
30-0.039569-0.2770.391478
31-0.009531-0.06670.473538
32-0.009573-0.0670.473424
330.0221580.15510.438688
340.0165260.11570.454188
35-0.00014-0.0010.499612
36-0.061608-0.43130.334087


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')