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 computationFri, 04 Dec 2009 05:15:32 -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/04/t1259928986cc8no1z3vqzcead.htm/, Retrieved Sat, 27 Apr 2024 23:11:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63375, Retrieved Sat, 27 Apr 2024 23:11:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact125

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] [] [2009-11-23 15:21:31] [5d885a68c2332cc44f6191ec94766bfa]
-    D            [(Partial) Autocorrelation Function] [AC D=1] [2009-12-04 12:15:32] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
594

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=63375&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=63375&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63375&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
10.9394186.50850
20.8661646.0010
30.7802145.40551e-06
40.6811344.7191e-05
50.5721213.96380.000122
60.461013.1940.00124
70.3470182.40420.010058
80.2356231.63240.054565
90.1354370.93830.176384
100.0483030.33470.369672
11-0.025232-0.17480.430982
12-0.10007-0.69330.245729
13-0.153979-1.06680.1457
14-0.199665-1.38330.086483
15-0.244988-1.69730.048055
16-0.296525-2.05440.022703
17-0.348398-2.41380.009826
18-0.383787-2.6590.00531
19-0.41552-2.87880.002972
20-0.441641-3.05980.00181
21-0.461235-3.19550.001234
22-0.469418-3.25220.001049
23-0.472063-3.27050.000995
24-0.456495-3.16270.001355
25-0.427759-2.96360.002361
26-0.380564-2.63660.005624
27-0.344549-2.38710.010484
28-0.293736-2.03510.023693
29-0.229256-1.58830.059389
30-0.171108-1.18550.120833
31-0.12169-0.84310.201679
32-0.074272-0.51460.304607
33-0.029872-0.2070.41846
340.0079090.05480.478265
350.0516450.35780.361028
360.0838060.58060.282106

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.939418 & 6.5085 & 0 \tabularnewline
2 & 0.866164 & 6.001 & 0 \tabularnewline
3 & 0.780214 & 5.4055 & 1e-06 \tabularnewline
4 & 0.681134 & 4.719 & 1e-05 \tabularnewline
5 & 0.572121 & 3.9638 & 0.000122 \tabularnewline
6 & 0.46101 & 3.194 & 0.00124 \tabularnewline
7 & 0.347018 & 2.4042 & 0.010058 \tabularnewline
8 & 0.235623 & 1.6324 & 0.054565 \tabularnewline
9 & 0.135437 & 0.9383 & 0.176384 \tabularnewline
10 & 0.048303 & 0.3347 & 0.369672 \tabularnewline
11 & -0.025232 & -0.1748 & 0.430982 \tabularnewline
12 & -0.10007 & -0.6933 & 0.245729 \tabularnewline
13 & -0.153979 & -1.0668 & 0.1457 \tabularnewline
14 & -0.199665 & -1.3833 & 0.086483 \tabularnewline
15 & -0.244988 & -1.6973 & 0.048055 \tabularnewline
16 & -0.296525 & -2.0544 & 0.022703 \tabularnewline
17 & -0.348398 & -2.4138 & 0.009826 \tabularnewline
18 & -0.383787 & -2.659 & 0.00531 \tabularnewline
19 & -0.41552 & -2.8788 & 0.002972 \tabularnewline
20 & -0.441641 & -3.0598 & 0.00181 \tabularnewline
21 & -0.461235 & -3.1955 & 0.001234 \tabularnewline
22 & -0.469418 & -3.2522 & 0.001049 \tabularnewline
23 & -0.472063 & -3.2705 & 0.000995 \tabularnewline
24 & -0.456495 & -3.1627 & 0.001355 \tabularnewline
25 & -0.427759 & -2.9636 & 0.002361 \tabularnewline
26 & -0.380564 & -2.6366 & 0.005624 \tabularnewline
27 & -0.344549 & -2.3871 & 0.010484 \tabularnewline
28 & -0.293736 & -2.0351 & 0.023693 \tabularnewline
29 & -0.229256 & -1.5883 & 0.059389 \tabularnewline
30 & -0.171108 & -1.1855 & 0.120833 \tabularnewline
31 & -0.12169 & -0.8431 & 0.201679 \tabularnewline
32 & -0.074272 & -0.5146 & 0.304607 \tabularnewline
33 & -0.029872 & -0.207 & 0.41846 \tabularnewline
34 & 0.007909 & 0.0548 & 0.478265 \tabularnewline
35 & 0.051645 & 0.3578 & 0.361028 \tabularnewline
36 & 0.083806 & 0.5806 & 0.282106 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63375&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]0.939418[/C][C]6.5085[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.866164[/C][C]6.001[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.780214[/C][C]5.4055[/C][C]1e-06[/C][/ROW]
[ROW][C]4[/C][C]0.681134[/C][C]4.719[/C][C]1e-05[/C][/ROW]
[ROW][C]5[/C][C]0.572121[/C][C]3.9638[/C][C]0.000122[/C][/ROW]
[ROW][C]6[/C][C]0.46101[/C][C]3.194[/C][C]0.00124[/C][/ROW]
[ROW][C]7[/C][C]0.347018[/C][C]2.4042[/C][C]0.010058[/C][/ROW]
[ROW][C]8[/C][C]0.235623[/C][C]1.6324[/C][C]0.054565[/C][/ROW]
[ROW][C]9[/C][C]0.135437[/C][C]0.9383[/C][C]0.176384[/C][/ROW]
[ROW][C]10[/C][C]0.048303[/C][C]0.3347[/C][C]0.369672[/C][/ROW]
[ROW][C]11[/C][C]-0.025232[/C][C]-0.1748[/C][C]0.430982[/C][/ROW]
[ROW][C]12[/C][C]-0.10007[/C][C]-0.6933[/C][C]0.245729[/C][/ROW]
[ROW][C]13[/C][C]-0.153979[/C][C]-1.0668[/C][C]0.1457[/C][/ROW]
[ROW][C]14[/C][C]-0.199665[/C][C]-1.3833[/C][C]0.086483[/C][/ROW]
[ROW][C]15[/C][C]-0.244988[/C][C]-1.6973[/C][C]0.048055[/C][/ROW]
[ROW][C]16[/C][C]-0.296525[/C][C]-2.0544[/C][C]0.022703[/C][/ROW]
[ROW][C]17[/C][C]-0.348398[/C][C]-2.4138[/C][C]0.009826[/C][/ROW]
[ROW][C]18[/C][C]-0.383787[/C][C]-2.659[/C][C]0.00531[/C][/ROW]
[ROW][C]19[/C][C]-0.41552[/C][C]-2.8788[/C][C]0.002972[/C][/ROW]
[ROW][C]20[/C][C]-0.441641[/C][C]-3.0598[/C][C]0.00181[/C][/ROW]
[ROW][C]21[/C][C]-0.461235[/C][C]-3.1955[/C][C]0.001234[/C][/ROW]
[ROW][C]22[/C][C]-0.469418[/C][C]-3.2522[/C][C]0.001049[/C][/ROW]
[ROW][C]23[/C][C]-0.472063[/C][C]-3.2705[/C][C]0.000995[/C][/ROW]
[ROW][C]24[/C][C]-0.456495[/C][C]-3.1627[/C][C]0.001355[/C][/ROW]
[ROW][C]25[/C][C]-0.427759[/C][C]-2.9636[/C][C]0.002361[/C][/ROW]
[ROW][C]26[/C][C]-0.380564[/C][C]-2.6366[/C][C]0.005624[/C][/ROW]
[ROW][C]27[/C][C]-0.344549[/C][C]-2.3871[/C][C]0.010484[/C][/ROW]
[ROW][C]28[/C][C]-0.293736[/C][C]-2.0351[/C][C]0.023693[/C][/ROW]
[ROW][C]29[/C][C]-0.229256[/C][C]-1.5883[/C][C]0.059389[/C][/ROW]
[ROW][C]30[/C][C]-0.171108[/C][C]-1.1855[/C][C]0.120833[/C][/ROW]
[ROW][C]31[/C][C]-0.12169[/C][C]-0.8431[/C][C]0.201679[/C][/ROW]
[ROW][C]32[/C][C]-0.074272[/C][C]-0.5146[/C][C]0.304607[/C][/ROW]
[ROW][C]33[/C][C]-0.029872[/C][C]-0.207[/C][C]0.41846[/C][/ROW]
[ROW][C]34[/C][C]0.007909[/C][C]0.0548[/C][C]0.478265[/C][/ROW]
[ROW][C]35[/C][C]0.051645[/C][C]0.3578[/C][C]0.361028[/C][/ROW]
[ROW][C]36[/C][C]0.083806[/C][C]0.5806[/C][C]0.282106[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63375&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63375&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
10.9394186.50850
20.8661646.0010
30.7802145.40551e-06
40.6811344.7191e-05
50.5721213.96380.000122
60.461013.1940.00124
70.3470182.40420.010058
80.2356231.63240.054565
90.1354370.93830.176384
100.0483030.33470.369672
11-0.025232-0.17480.430982
12-0.10007-0.69330.245729
13-0.153979-1.06680.1457
14-0.199665-1.38330.086483
15-0.244988-1.69730.048055
16-0.296525-2.05440.022703
17-0.348398-2.41380.009826
18-0.383787-2.6590.00531
19-0.41552-2.87880.002972
20-0.441641-3.05980.00181
21-0.461235-3.19550.001234
22-0.469418-3.25220.001049
23-0.472063-3.27050.000995
24-0.456495-3.16270.001355
25-0.427759-2.96360.002361
26-0.380564-2.63660.005624
27-0.344549-2.38710.010484
28-0.293736-2.03510.023693
29-0.229256-1.58830.059389
30-0.171108-1.18550.120833
31-0.12169-0.84310.201679
32-0.074272-0.51460.304607
33-0.029872-0.2070.41846
340.0079090.05480.478265
350.0516450.35780.361028
360.0838060.58060.282106






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9394186.50850
2-0.139099-0.96370.170012
3-0.13876-0.96140.170595
4-0.145869-1.01060.158635
5-0.124366-0.86160.196587
6-0.064016-0.44350.329693
7-0.084492-0.58540.280517
8-0.049031-0.33970.367785
90.0151840.10520.45833
100.0200340.13880.445096
110.0148960.10320.459116
12-0.135882-0.94140.175602
130.0678850.47030.320128
14-0.045739-0.31690.376351
15-0.111424-0.7720.221959
16-0.17166-1.18930.120086
17-0.116362-0.80620.212058
180.0837290.58010.282283
19-0.041839-0.28990.386581
20-0.040667-0.28180.389673
21-0.033296-0.23070.409272
220.0213030.14760.44164
23-0.020467-0.14180.443916
240.0224520.15560.438519
250.0157470.10910.45679
260.1009970.69970.243738
27-0.182349-1.26330.106283
280.0631130.43730.331942
290.0567840.39340.34788
30-0.035842-0.24830.402472
31-0.078455-0.54360.294632
32-0.024521-0.16990.432908
330.0045340.03140.487536
34-0.001153-0.0080.49683
350.0927210.64240.261838
36-0.067979-0.4710.319897

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.939418 & 6.5085 & 0 \tabularnewline
2 & -0.139099 & -0.9637 & 0.170012 \tabularnewline
3 & -0.13876 & -0.9614 & 0.170595 \tabularnewline
4 & -0.145869 & -1.0106 & 0.158635 \tabularnewline
5 & -0.124366 & -0.8616 & 0.196587 \tabularnewline
6 & -0.064016 & -0.4435 & 0.329693 \tabularnewline
7 & -0.084492 & -0.5854 & 0.280517 \tabularnewline
8 & -0.049031 & -0.3397 & 0.367785 \tabularnewline
9 & 0.015184 & 0.1052 & 0.45833 \tabularnewline
10 & 0.020034 & 0.1388 & 0.445096 \tabularnewline
11 & 0.014896 & 0.1032 & 0.459116 \tabularnewline
12 & -0.135882 & -0.9414 & 0.175602 \tabularnewline
13 & 0.067885 & 0.4703 & 0.320128 \tabularnewline
14 & -0.045739 & -0.3169 & 0.376351 \tabularnewline
15 & -0.111424 & -0.772 & 0.221959 \tabularnewline
16 & -0.17166 & -1.1893 & 0.120086 \tabularnewline
17 & -0.116362 & -0.8062 & 0.212058 \tabularnewline
18 & 0.083729 & 0.5801 & 0.282283 \tabularnewline
19 & -0.041839 & -0.2899 & 0.386581 \tabularnewline
20 & -0.040667 & -0.2818 & 0.389673 \tabularnewline
21 & -0.033296 & -0.2307 & 0.409272 \tabularnewline
22 & 0.021303 & 0.1476 & 0.44164 \tabularnewline
23 & -0.020467 & -0.1418 & 0.443916 \tabularnewline
24 & 0.022452 & 0.1556 & 0.438519 \tabularnewline
25 & 0.015747 & 0.1091 & 0.45679 \tabularnewline
26 & 0.100997 & 0.6997 & 0.243738 \tabularnewline
27 & -0.182349 & -1.2633 & 0.106283 \tabularnewline
28 & 0.063113 & 0.4373 & 0.331942 \tabularnewline
29 & 0.056784 & 0.3934 & 0.34788 \tabularnewline
30 & -0.035842 & -0.2483 & 0.402472 \tabularnewline
31 & -0.078455 & -0.5436 & 0.294632 \tabularnewline
32 & -0.024521 & -0.1699 & 0.432908 \tabularnewline
33 & 0.004534 & 0.0314 & 0.487536 \tabularnewline
34 & -0.001153 & -0.008 & 0.49683 \tabularnewline
35 & 0.092721 & 0.6424 & 0.261838 \tabularnewline
36 & -0.067979 & -0.471 & 0.319897 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63375&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]0.939418[/C][C]6.5085[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.139099[/C][C]-0.9637[/C][C]0.170012[/C][/ROW]
[ROW][C]3[/C][C]-0.13876[/C][C]-0.9614[/C][C]0.170595[/C][/ROW]
[ROW][C]4[/C][C]-0.145869[/C][C]-1.0106[/C][C]0.158635[/C][/ROW]
[ROW][C]5[/C][C]-0.124366[/C][C]-0.8616[/C][C]0.196587[/C][/ROW]
[ROW][C]6[/C][C]-0.064016[/C][C]-0.4435[/C][C]0.329693[/C][/ROW]
[ROW][C]7[/C][C]-0.084492[/C][C]-0.5854[/C][C]0.280517[/C][/ROW]
[ROW][C]8[/C][C]-0.049031[/C][C]-0.3397[/C][C]0.367785[/C][/ROW]
[ROW][C]9[/C][C]0.015184[/C][C]0.1052[/C][C]0.45833[/C][/ROW]
[ROW][C]10[/C][C]0.020034[/C][C]0.1388[/C][C]0.445096[/C][/ROW]
[ROW][C]11[/C][C]0.014896[/C][C]0.1032[/C][C]0.459116[/C][/ROW]
[ROW][C]12[/C][C]-0.135882[/C][C]-0.9414[/C][C]0.175602[/C][/ROW]
[ROW][C]13[/C][C]0.067885[/C][C]0.4703[/C][C]0.320128[/C][/ROW]
[ROW][C]14[/C][C]-0.045739[/C][C]-0.3169[/C][C]0.376351[/C][/ROW]
[ROW][C]15[/C][C]-0.111424[/C][C]-0.772[/C][C]0.221959[/C][/ROW]
[ROW][C]16[/C][C]-0.17166[/C][C]-1.1893[/C][C]0.120086[/C][/ROW]
[ROW][C]17[/C][C]-0.116362[/C][C]-0.8062[/C][C]0.212058[/C][/ROW]
[ROW][C]18[/C][C]0.083729[/C][C]0.5801[/C][C]0.282283[/C][/ROW]
[ROW][C]19[/C][C]-0.041839[/C][C]-0.2899[/C][C]0.386581[/C][/ROW]
[ROW][C]20[/C][C]-0.040667[/C][C]-0.2818[/C][C]0.389673[/C][/ROW]
[ROW][C]21[/C][C]-0.033296[/C][C]-0.2307[/C][C]0.409272[/C][/ROW]
[ROW][C]22[/C][C]0.021303[/C][C]0.1476[/C][C]0.44164[/C][/ROW]
[ROW][C]23[/C][C]-0.020467[/C][C]-0.1418[/C][C]0.443916[/C][/ROW]
[ROW][C]24[/C][C]0.022452[/C][C]0.1556[/C][C]0.438519[/C][/ROW]
[ROW][C]25[/C][C]0.015747[/C][C]0.1091[/C][C]0.45679[/C][/ROW]
[ROW][C]26[/C][C]0.100997[/C][C]0.6997[/C][C]0.243738[/C][/ROW]
[ROW][C]27[/C][C]-0.182349[/C][C]-1.2633[/C][C]0.106283[/C][/ROW]
[ROW][C]28[/C][C]0.063113[/C][C]0.4373[/C][C]0.331942[/C][/ROW]
[ROW][C]29[/C][C]0.056784[/C][C]0.3934[/C][C]0.34788[/C][/ROW]
[ROW][C]30[/C][C]-0.035842[/C][C]-0.2483[/C][C]0.402472[/C][/ROW]
[ROW][C]31[/C][C]-0.078455[/C][C]-0.5436[/C][C]0.294632[/C][/ROW]
[ROW][C]32[/C][C]-0.024521[/C][C]-0.1699[/C][C]0.432908[/C][/ROW]
[ROW][C]33[/C][C]0.004534[/C][C]0.0314[/C][C]0.487536[/C][/ROW]
[ROW][C]34[/C][C]-0.001153[/C][C]-0.008[/C][C]0.49683[/C][/ROW]
[ROW][C]35[/C][C]0.092721[/C][C]0.6424[/C][C]0.261838[/C][/ROW]
[ROW][C]36[/C][C]-0.067979[/C][C]-0.471[/C][C]0.319897[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63375&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63375&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
10.9394186.50850
2-0.139099-0.96370.170012
3-0.13876-0.96140.170595
4-0.145869-1.01060.158635
5-0.124366-0.86160.196587
6-0.064016-0.44350.329693
7-0.084492-0.58540.280517
8-0.049031-0.33970.367785
90.0151840.10520.45833
100.0200340.13880.445096
110.0148960.10320.459116
12-0.135882-0.94140.175602
130.0678850.47030.320128
14-0.045739-0.31690.376351
15-0.111424-0.7720.221959
16-0.17166-1.18930.120086
17-0.116362-0.80620.212058
180.0837290.58010.282283
19-0.041839-0.28990.386581
20-0.040667-0.28180.389673
21-0.033296-0.23070.409272
220.0213030.14760.44164
23-0.020467-0.14180.443916
240.0224520.15560.438519
250.0157470.10910.45679
260.1009970.69970.243738
27-0.182349-1.26330.106283
280.0631130.43730.331942
290.0567840.39340.34788
30-0.035842-0.24830.402472
31-0.078455-0.54360.294632
32-0.024521-0.16990.432908
330.0045340.03140.487536
34-0.001153-0.0080.49683
350.0927210.64240.261838
36-0.067979-0.4710.319897


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')