Free Statistics

of Irreproducible Research!

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, 03 Dec 2009 03:10:51 -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/Dec/03/t1259835096yf5xf6w6whs1q5h.htm/, Retrieved Tue, 16 Apr 2024 23:18:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62661, Retrieved Tue, 16 Apr 2024 23:18:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [] [2009-11-27 14:46:03] [b98453cac15ba1066b407e146608df68]
-   PD    [(Partial) Autocorrelation Function] [] [2009-12-03 10:03:52] [2f674a53c3d7aaa1bcf80e66074d3c9b]
-   P         [(Partial) Autocorrelation Function] [] [2009-12-03 10:10:51] [5858ea01c9bd81debbf921a11363ad90] [Current]
Feedback Forum

Post a new message
Dataseries X:
21790
13253
37702
30364
32609
30212
29965
28352
25814
22414
20506
28806
22228
13971
36845
35338
35022
34777
26887
23970
22780
17351
21382
24561
17409
11514
31514
27071
29462
26105
22397
23843
21705
18089
20764
25316
17704
15548
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835
20205
17789
20520
22518
15572
11509
25447
24090
27786
26195
20516
22759
19028
16971
20036
22485
18730




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62661&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]2 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=62661&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62661&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.522291-5.11741e-06
20.1701331.6670.049391
3-0.092503-0.90630.183512
40.0222520.2180.413936
5-0.031027-0.3040.380892
60.1418621.390.083878
7-0.191115-1.87250.032088
80.048860.47870.31661
90.1720531.68580.047544
10-0.176113-1.72560.043823
110.0957480.93810.175265
12-0.148557-1.45560.074388
13-0.081524-0.79880.213197
140.0553020.54180.29459
150.138891.36080.088376
16-0.219491-2.15060.017011
170.1525641.49480.069121
18-0.071503-0.70060.242627
19-0.018255-0.17890.429213
200.0338460.33160.370449
210.0256230.25110.401155
22-0.183102-1.7940.037978
230.295032.89070.002377
24-0.228041-2.23430.01389
250.1101031.07880.141693
260.0520760.51020.305529
27-0.027227-0.26680.395109
28-0.07302-0.71550.238034
290.1806951.77040.039914
30-0.162161-1.58880.057692
310.0972130.95250.17162
32-0.001687-0.01650.493424
33-0.089675-0.87860.190897
340.0345330.33830.36792
350.1373171.34540.090828
36-0.25812-2.5290.006533

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.522291 & -5.1174 & 1e-06 \tabularnewline
2 & 0.170133 & 1.667 & 0.049391 \tabularnewline
3 & -0.092503 & -0.9063 & 0.183512 \tabularnewline
4 & 0.022252 & 0.218 & 0.413936 \tabularnewline
5 & -0.031027 & -0.304 & 0.380892 \tabularnewline
6 & 0.141862 & 1.39 & 0.083878 \tabularnewline
7 & -0.191115 & -1.8725 & 0.032088 \tabularnewline
8 & 0.04886 & 0.4787 & 0.31661 \tabularnewline
9 & 0.172053 & 1.6858 & 0.047544 \tabularnewline
10 & -0.176113 & -1.7256 & 0.043823 \tabularnewline
11 & 0.095748 & 0.9381 & 0.175265 \tabularnewline
12 & -0.148557 & -1.4556 & 0.074388 \tabularnewline
13 & -0.081524 & -0.7988 & 0.213197 \tabularnewline
14 & 0.055302 & 0.5418 & 0.29459 \tabularnewline
15 & 0.13889 & 1.3608 & 0.088376 \tabularnewline
16 & -0.219491 & -2.1506 & 0.017011 \tabularnewline
17 & 0.152564 & 1.4948 & 0.069121 \tabularnewline
18 & -0.071503 & -0.7006 & 0.242627 \tabularnewline
19 & -0.018255 & -0.1789 & 0.429213 \tabularnewline
20 & 0.033846 & 0.3316 & 0.370449 \tabularnewline
21 & 0.025623 & 0.2511 & 0.401155 \tabularnewline
22 & -0.183102 & -1.794 & 0.037978 \tabularnewline
23 & 0.29503 & 2.8907 & 0.002377 \tabularnewline
24 & -0.228041 & -2.2343 & 0.01389 \tabularnewline
25 & 0.110103 & 1.0788 & 0.141693 \tabularnewline
26 & 0.052076 & 0.5102 & 0.305529 \tabularnewline
27 & -0.027227 & -0.2668 & 0.395109 \tabularnewline
28 & -0.07302 & -0.7155 & 0.238034 \tabularnewline
29 & 0.180695 & 1.7704 & 0.039914 \tabularnewline
30 & -0.162161 & -1.5888 & 0.057692 \tabularnewline
31 & 0.097213 & 0.9525 & 0.17162 \tabularnewline
32 & -0.001687 & -0.0165 & 0.493424 \tabularnewline
33 & -0.089675 & -0.8786 & 0.190897 \tabularnewline
34 & 0.034533 & 0.3383 & 0.36792 \tabularnewline
35 & 0.137317 & 1.3454 & 0.090828 \tabularnewline
36 & -0.25812 & -2.529 & 0.006533 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62661&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]-0.522291[/C][C]-5.1174[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.170133[/C][C]1.667[/C][C]0.049391[/C][/ROW]
[ROW][C]3[/C][C]-0.092503[/C][C]-0.9063[/C][C]0.183512[/C][/ROW]
[ROW][C]4[/C][C]0.022252[/C][C]0.218[/C][C]0.413936[/C][/ROW]
[ROW][C]5[/C][C]-0.031027[/C][C]-0.304[/C][C]0.380892[/C][/ROW]
[ROW][C]6[/C][C]0.141862[/C][C]1.39[/C][C]0.083878[/C][/ROW]
[ROW][C]7[/C][C]-0.191115[/C][C]-1.8725[/C][C]0.032088[/C][/ROW]
[ROW][C]8[/C][C]0.04886[/C][C]0.4787[/C][C]0.31661[/C][/ROW]
[ROW][C]9[/C][C]0.172053[/C][C]1.6858[/C][C]0.047544[/C][/ROW]
[ROW][C]10[/C][C]-0.176113[/C][C]-1.7256[/C][C]0.043823[/C][/ROW]
[ROW][C]11[/C][C]0.095748[/C][C]0.9381[/C][C]0.175265[/C][/ROW]
[ROW][C]12[/C][C]-0.148557[/C][C]-1.4556[/C][C]0.074388[/C][/ROW]
[ROW][C]13[/C][C]-0.081524[/C][C]-0.7988[/C][C]0.213197[/C][/ROW]
[ROW][C]14[/C][C]0.055302[/C][C]0.5418[/C][C]0.29459[/C][/ROW]
[ROW][C]15[/C][C]0.13889[/C][C]1.3608[/C][C]0.088376[/C][/ROW]
[ROW][C]16[/C][C]-0.219491[/C][C]-2.1506[/C][C]0.017011[/C][/ROW]
[ROW][C]17[/C][C]0.152564[/C][C]1.4948[/C][C]0.069121[/C][/ROW]
[ROW][C]18[/C][C]-0.071503[/C][C]-0.7006[/C][C]0.242627[/C][/ROW]
[ROW][C]19[/C][C]-0.018255[/C][C]-0.1789[/C][C]0.429213[/C][/ROW]
[ROW][C]20[/C][C]0.033846[/C][C]0.3316[/C][C]0.370449[/C][/ROW]
[ROW][C]21[/C][C]0.025623[/C][C]0.2511[/C][C]0.401155[/C][/ROW]
[ROW][C]22[/C][C]-0.183102[/C][C]-1.794[/C][C]0.037978[/C][/ROW]
[ROW][C]23[/C][C]0.29503[/C][C]2.8907[/C][C]0.002377[/C][/ROW]
[ROW][C]24[/C][C]-0.228041[/C][C]-2.2343[/C][C]0.01389[/C][/ROW]
[ROW][C]25[/C][C]0.110103[/C][C]1.0788[/C][C]0.141693[/C][/ROW]
[ROW][C]26[/C][C]0.052076[/C][C]0.5102[/C][C]0.305529[/C][/ROW]
[ROW][C]27[/C][C]-0.027227[/C][C]-0.2668[/C][C]0.395109[/C][/ROW]
[ROW][C]28[/C][C]-0.07302[/C][C]-0.7155[/C][C]0.238034[/C][/ROW]
[ROW][C]29[/C][C]0.180695[/C][C]1.7704[/C][C]0.039914[/C][/ROW]
[ROW][C]30[/C][C]-0.162161[/C][C]-1.5888[/C][C]0.057692[/C][/ROW]
[ROW][C]31[/C][C]0.097213[/C][C]0.9525[/C][C]0.17162[/C][/ROW]
[ROW][C]32[/C][C]-0.001687[/C][C]-0.0165[/C][C]0.493424[/C][/ROW]
[ROW][C]33[/C][C]-0.089675[/C][C]-0.8786[/C][C]0.190897[/C][/ROW]
[ROW][C]34[/C][C]0.034533[/C][C]0.3383[/C][C]0.36792[/C][/ROW]
[ROW][C]35[/C][C]0.137317[/C][C]1.3454[/C][C]0.090828[/C][/ROW]
[ROW][C]36[/C][C]-0.25812[/C][C]-2.529[/C][C]0.006533[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62661&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62661&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
1-0.522291-5.11741e-06
20.1701331.6670.049391
3-0.092503-0.90630.183512
40.0222520.2180.413936
5-0.031027-0.3040.380892
60.1418621.390.083878
7-0.191115-1.87250.032088
80.048860.47870.31661
90.1720531.68580.047544
10-0.176113-1.72560.043823
110.0957480.93810.175265
12-0.148557-1.45560.074388
13-0.081524-0.79880.213197
140.0553020.54180.29459
150.138891.36080.088376
16-0.219491-2.15060.017011
170.1525641.49480.069121
18-0.071503-0.70060.242627
19-0.018255-0.17890.429213
200.0338460.33160.370449
210.0256230.25110.401155
22-0.183102-1.7940.037978
230.295032.89070.002377
24-0.228041-2.23430.01389
250.1101031.07880.141693
260.0520760.51020.305529
27-0.027227-0.26680.395109
28-0.07302-0.71550.238034
290.1806951.77040.039914
30-0.162161-1.58880.057692
310.0972130.95250.17162
32-0.001687-0.01650.493424
33-0.089675-0.87860.190897
340.0345330.33830.36792
350.1373171.34540.090828
36-0.25812-2.5290.006533







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.522291-5.11741e-06
2-0.141163-1.38310.08492
3-0.09096-0.89120.18752
4-0.068386-0.670.252219
5-0.070798-0.69370.24478
60.1370221.34250.091293
7-0.067613-0.66250.254629
8-0.133136-1.30450.097597
90.2139542.09630.019342
100.027720.27160.393255
11-0.019927-0.19520.422809
12-0.15261-1.49530.069063
13-0.297131-2.91130.002238
14-0.245748-2.40780.008979
150.0516530.50610.306975
16-0.072764-0.71290.238808
17-0.057936-0.56770.285799
18-0.00102-0.010.496023
19-0.058243-0.57070.28478
20-0.099608-0.9760.165769
210.0989540.96950.167354
22-0.081591-0.79940.213008
230.0933510.91460.181334
24-0.152392-1.49310.069341
25-0.167613-1.64230.051903
26-0.010153-0.09950.460481
270.1214581.190.118483
28-0.017497-0.17140.43212
290.0746360.73130.233193
300.0022870.02240.491084
310.0183730.180.428758
32-0.067376-0.66020.255369
33-0.013107-0.12840.449041
34-0.117577-1.1520.126088
350.1266471.24090.108837
36-0.219557-2.15120.016985

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.522291 & -5.1174 & 1e-06 \tabularnewline
2 & -0.141163 & -1.3831 & 0.08492 \tabularnewline
3 & -0.09096 & -0.8912 & 0.18752 \tabularnewline
4 & -0.068386 & -0.67 & 0.252219 \tabularnewline
5 & -0.070798 & -0.6937 & 0.24478 \tabularnewline
6 & 0.137022 & 1.3425 & 0.091293 \tabularnewline
7 & -0.067613 & -0.6625 & 0.254629 \tabularnewline
8 & -0.133136 & -1.3045 & 0.097597 \tabularnewline
9 & 0.213954 & 2.0963 & 0.019342 \tabularnewline
10 & 0.02772 & 0.2716 & 0.393255 \tabularnewline
11 & -0.019927 & -0.1952 & 0.422809 \tabularnewline
12 & -0.15261 & -1.4953 & 0.069063 \tabularnewline
13 & -0.297131 & -2.9113 & 0.002238 \tabularnewline
14 & -0.245748 & -2.4078 & 0.008979 \tabularnewline
15 & 0.051653 & 0.5061 & 0.306975 \tabularnewline
16 & -0.072764 & -0.7129 & 0.238808 \tabularnewline
17 & -0.057936 & -0.5677 & 0.285799 \tabularnewline
18 & -0.00102 & -0.01 & 0.496023 \tabularnewline
19 & -0.058243 & -0.5707 & 0.28478 \tabularnewline
20 & -0.099608 & -0.976 & 0.165769 \tabularnewline
21 & 0.098954 & 0.9695 & 0.167354 \tabularnewline
22 & -0.081591 & -0.7994 & 0.213008 \tabularnewline
23 & 0.093351 & 0.9146 & 0.181334 \tabularnewline
24 & -0.152392 & -1.4931 & 0.069341 \tabularnewline
25 & -0.167613 & -1.6423 & 0.051903 \tabularnewline
26 & -0.010153 & -0.0995 & 0.460481 \tabularnewline
27 & 0.121458 & 1.19 & 0.118483 \tabularnewline
28 & -0.017497 & -0.1714 & 0.43212 \tabularnewline
29 & 0.074636 & 0.7313 & 0.233193 \tabularnewline
30 & 0.002287 & 0.0224 & 0.491084 \tabularnewline
31 & 0.018373 & 0.18 & 0.428758 \tabularnewline
32 & -0.067376 & -0.6602 & 0.255369 \tabularnewline
33 & -0.013107 & -0.1284 & 0.449041 \tabularnewline
34 & -0.117577 & -1.152 & 0.126088 \tabularnewline
35 & 0.126647 & 1.2409 & 0.108837 \tabularnewline
36 & -0.219557 & -2.1512 & 0.016985 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62661&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]-0.522291[/C][C]-5.1174[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.141163[/C][C]-1.3831[/C][C]0.08492[/C][/ROW]
[ROW][C]3[/C][C]-0.09096[/C][C]-0.8912[/C][C]0.18752[/C][/ROW]
[ROW][C]4[/C][C]-0.068386[/C][C]-0.67[/C][C]0.252219[/C][/ROW]
[ROW][C]5[/C][C]-0.070798[/C][C]-0.6937[/C][C]0.24478[/C][/ROW]
[ROW][C]6[/C][C]0.137022[/C][C]1.3425[/C][C]0.091293[/C][/ROW]
[ROW][C]7[/C][C]-0.067613[/C][C]-0.6625[/C][C]0.254629[/C][/ROW]
[ROW][C]8[/C][C]-0.133136[/C][C]-1.3045[/C][C]0.097597[/C][/ROW]
[ROW][C]9[/C][C]0.213954[/C][C]2.0963[/C][C]0.019342[/C][/ROW]
[ROW][C]10[/C][C]0.02772[/C][C]0.2716[/C][C]0.393255[/C][/ROW]
[ROW][C]11[/C][C]-0.019927[/C][C]-0.1952[/C][C]0.422809[/C][/ROW]
[ROW][C]12[/C][C]-0.15261[/C][C]-1.4953[/C][C]0.069063[/C][/ROW]
[ROW][C]13[/C][C]-0.297131[/C][C]-2.9113[/C][C]0.002238[/C][/ROW]
[ROW][C]14[/C][C]-0.245748[/C][C]-2.4078[/C][C]0.008979[/C][/ROW]
[ROW][C]15[/C][C]0.051653[/C][C]0.5061[/C][C]0.306975[/C][/ROW]
[ROW][C]16[/C][C]-0.072764[/C][C]-0.7129[/C][C]0.238808[/C][/ROW]
[ROW][C]17[/C][C]-0.057936[/C][C]-0.5677[/C][C]0.285799[/C][/ROW]
[ROW][C]18[/C][C]-0.00102[/C][C]-0.01[/C][C]0.496023[/C][/ROW]
[ROW][C]19[/C][C]-0.058243[/C][C]-0.5707[/C][C]0.28478[/C][/ROW]
[ROW][C]20[/C][C]-0.099608[/C][C]-0.976[/C][C]0.165769[/C][/ROW]
[ROW][C]21[/C][C]0.098954[/C][C]0.9695[/C][C]0.167354[/C][/ROW]
[ROW][C]22[/C][C]-0.081591[/C][C]-0.7994[/C][C]0.213008[/C][/ROW]
[ROW][C]23[/C][C]0.093351[/C][C]0.9146[/C][C]0.181334[/C][/ROW]
[ROW][C]24[/C][C]-0.152392[/C][C]-1.4931[/C][C]0.069341[/C][/ROW]
[ROW][C]25[/C][C]-0.167613[/C][C]-1.6423[/C][C]0.051903[/C][/ROW]
[ROW][C]26[/C][C]-0.010153[/C][C]-0.0995[/C][C]0.460481[/C][/ROW]
[ROW][C]27[/C][C]0.121458[/C][C]1.19[/C][C]0.118483[/C][/ROW]
[ROW][C]28[/C][C]-0.017497[/C][C]-0.1714[/C][C]0.43212[/C][/ROW]
[ROW][C]29[/C][C]0.074636[/C][C]0.7313[/C][C]0.233193[/C][/ROW]
[ROW][C]30[/C][C]0.002287[/C][C]0.0224[/C][C]0.491084[/C][/ROW]
[ROW][C]31[/C][C]0.018373[/C][C]0.18[/C][C]0.428758[/C][/ROW]
[ROW][C]32[/C][C]-0.067376[/C][C]-0.6602[/C][C]0.255369[/C][/ROW]
[ROW][C]33[/C][C]-0.013107[/C][C]-0.1284[/C][C]0.449041[/C][/ROW]
[ROW][C]34[/C][C]-0.117577[/C][C]-1.152[/C][C]0.126088[/C][/ROW]
[ROW][C]35[/C][C]0.126647[/C][C]1.2409[/C][C]0.108837[/C][/ROW]
[ROW][C]36[/C][C]-0.219557[/C][C]-2.1512[/C][C]0.016985[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62661&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62661&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
1-0.522291-5.11741e-06
2-0.141163-1.38310.08492
3-0.09096-0.89120.18752
4-0.068386-0.670.252219
5-0.070798-0.69370.24478
60.1370221.34250.091293
7-0.067613-0.66250.254629
8-0.133136-1.30450.097597
90.2139542.09630.019342
100.027720.27160.393255
11-0.019927-0.19520.422809
12-0.15261-1.49530.069063
13-0.297131-2.91130.002238
14-0.245748-2.40780.008979
150.0516530.50610.306975
16-0.072764-0.71290.238808
17-0.057936-0.56770.285799
18-0.00102-0.010.496023
19-0.058243-0.57070.28478
20-0.099608-0.9760.165769
210.0989540.96950.167354
22-0.081591-0.79940.213008
230.0933510.91460.181334
24-0.152392-1.49310.069341
25-0.167613-1.64230.051903
26-0.010153-0.09950.460481
270.1214581.190.118483
28-0.017497-0.17140.43212
290.0746360.73130.233193
300.0022870.02240.491084
310.0183730.180.428758
32-0.067376-0.66020.255369
33-0.013107-0.12840.449041
34-0.117577-1.1520.126088
350.1266471.24090.108837
36-0.219557-2.15120.016985



Parameters (Session):
par1 = 36 ; par2 = -0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = -0.5 ; par3 = 1 ; 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')