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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 computationThu, 03 Dec 2009 03:37:59 -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/t1259836717env1hs4mu59dm37.htm/, Retrieved Thu, 28 Mar 2024 19:02:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62671, Retrieved Thu, 28 Mar 2024 19:02:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact164
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 10:05:50] [2f674a53c3d7aaa1bcf80e66074d3c9b]
-   P           [(Partial) Autocorrelation Function] [] [2009-12-03 10:37:59] [5858ea01c9bd81debbf921a11363ad90] [Current]
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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 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=62671&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=62671&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62671&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
10.3600093.75860.000138
20.1529871.59720.056554
30.0337390.35220.362669
4-0.147809-1.54320.062844
5-0.223003-2.32820.010873
6-0.351691-3.67180.000187
7-0.245212-2.56010.005917
8-0.131999-1.37810.085496
90.0151420.15810.437339
100.0553150.57750.282393
110.2722542.84240.002673
120.7651247.98810
130.2493682.60350.005257
140.0825730.86210.195266
15-0.030658-0.32010.374761
16-0.210612-2.19880.015001
17-0.238405-2.4890.007161
18-0.372755-3.89178.6e-05
19-0.266153-2.77870.003214
20-0.143996-1.50340.067819
21-0.057719-0.60260.274011
220.0181190.18920.425156
230.248772.59720.005347
240.6538076.82590
250.2457262.56550.005831
260.1058451.10510.135784
27-0.025335-0.26450.395946
28-0.162417-1.69570.0464
29-0.181455-1.89440.030408
30-0.328986-3.43470.00042
31-0.207543-2.16680.016213
32-0.131124-1.3690.08691
33-0.052389-0.5470.292764
340.0240590.25120.401072
350.2019072.1080.018663
360.5230675.4610

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.360009 & 3.7586 & 0.000138 \tabularnewline
2 & 0.152987 & 1.5972 & 0.056554 \tabularnewline
3 & 0.033739 & 0.3522 & 0.362669 \tabularnewline
4 & -0.147809 & -1.5432 & 0.062844 \tabularnewline
5 & -0.223003 & -2.3282 & 0.010873 \tabularnewline
6 & -0.351691 & -3.6718 & 0.000187 \tabularnewline
7 & -0.245212 & -2.5601 & 0.005917 \tabularnewline
8 & -0.131999 & -1.3781 & 0.085496 \tabularnewline
9 & 0.015142 & 0.1581 & 0.437339 \tabularnewline
10 & 0.055315 & 0.5775 & 0.282393 \tabularnewline
11 & 0.272254 & 2.8424 & 0.002673 \tabularnewline
12 & 0.765124 & 7.9881 & 0 \tabularnewline
13 & 0.249368 & 2.6035 & 0.005257 \tabularnewline
14 & 0.082573 & 0.8621 & 0.195266 \tabularnewline
15 & -0.030658 & -0.3201 & 0.374761 \tabularnewline
16 & -0.210612 & -2.1988 & 0.015001 \tabularnewline
17 & -0.238405 & -2.489 & 0.007161 \tabularnewline
18 & -0.372755 & -3.8917 & 8.6e-05 \tabularnewline
19 & -0.266153 & -2.7787 & 0.003214 \tabularnewline
20 & -0.143996 & -1.5034 & 0.067819 \tabularnewline
21 & -0.057719 & -0.6026 & 0.274011 \tabularnewline
22 & 0.018119 & 0.1892 & 0.425156 \tabularnewline
23 & 0.24877 & 2.5972 & 0.005347 \tabularnewline
24 & 0.653807 & 6.8259 & 0 \tabularnewline
25 & 0.245726 & 2.5655 & 0.005831 \tabularnewline
26 & 0.105845 & 1.1051 & 0.135784 \tabularnewline
27 & -0.025335 & -0.2645 & 0.395946 \tabularnewline
28 & -0.162417 & -1.6957 & 0.0464 \tabularnewline
29 & -0.181455 & -1.8944 & 0.030408 \tabularnewline
30 & -0.328986 & -3.4347 & 0.00042 \tabularnewline
31 & -0.207543 & -2.1668 & 0.016213 \tabularnewline
32 & -0.131124 & -1.369 & 0.08691 \tabularnewline
33 & -0.052389 & -0.547 & 0.292764 \tabularnewline
34 & 0.024059 & 0.2512 & 0.401072 \tabularnewline
35 & 0.201907 & 2.108 & 0.018663 \tabularnewline
36 & 0.523067 & 5.461 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62671&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]0.360009[/C][C]3.7586[/C][C]0.000138[/C][/ROW]
[ROW][C]2[/C][C]0.152987[/C][C]1.5972[/C][C]0.056554[/C][/ROW]
[ROW][C]3[/C][C]0.033739[/C][C]0.3522[/C][C]0.362669[/C][/ROW]
[ROW][C]4[/C][C]-0.147809[/C][C]-1.5432[/C][C]0.062844[/C][/ROW]
[ROW][C]5[/C][C]-0.223003[/C][C]-2.3282[/C][C]0.010873[/C][/ROW]
[ROW][C]6[/C][C]-0.351691[/C][C]-3.6718[/C][C]0.000187[/C][/ROW]
[ROW][C]7[/C][C]-0.245212[/C][C]-2.5601[/C][C]0.005917[/C][/ROW]
[ROW][C]8[/C][C]-0.131999[/C][C]-1.3781[/C][C]0.085496[/C][/ROW]
[ROW][C]9[/C][C]0.015142[/C][C]0.1581[/C][C]0.437339[/C][/ROW]
[ROW][C]10[/C][C]0.055315[/C][C]0.5775[/C][C]0.282393[/C][/ROW]
[ROW][C]11[/C][C]0.272254[/C][C]2.8424[/C][C]0.002673[/C][/ROW]
[ROW][C]12[/C][C]0.765124[/C][C]7.9881[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.249368[/C][C]2.6035[/C][C]0.005257[/C][/ROW]
[ROW][C]14[/C][C]0.082573[/C][C]0.8621[/C][C]0.195266[/C][/ROW]
[ROW][C]15[/C][C]-0.030658[/C][C]-0.3201[/C][C]0.374761[/C][/ROW]
[ROW][C]16[/C][C]-0.210612[/C][C]-2.1988[/C][C]0.015001[/C][/ROW]
[ROW][C]17[/C][C]-0.238405[/C][C]-2.489[/C][C]0.007161[/C][/ROW]
[ROW][C]18[/C][C]-0.372755[/C][C]-3.8917[/C][C]8.6e-05[/C][/ROW]
[ROW][C]19[/C][C]-0.266153[/C][C]-2.7787[/C][C]0.003214[/C][/ROW]
[ROW][C]20[/C][C]-0.143996[/C][C]-1.5034[/C][C]0.067819[/C][/ROW]
[ROW][C]21[/C][C]-0.057719[/C][C]-0.6026[/C][C]0.274011[/C][/ROW]
[ROW][C]22[/C][C]0.018119[/C][C]0.1892[/C][C]0.425156[/C][/ROW]
[ROW][C]23[/C][C]0.24877[/C][C]2.5972[/C][C]0.005347[/C][/ROW]
[ROW][C]24[/C][C]0.653807[/C][C]6.8259[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.245726[/C][C]2.5655[/C][C]0.005831[/C][/ROW]
[ROW][C]26[/C][C]0.105845[/C][C]1.1051[/C][C]0.135784[/C][/ROW]
[ROW][C]27[/C][C]-0.025335[/C][C]-0.2645[/C][C]0.395946[/C][/ROW]
[ROW][C]28[/C][C]-0.162417[/C][C]-1.6957[/C][C]0.0464[/C][/ROW]
[ROW][C]29[/C][C]-0.181455[/C][C]-1.8944[/C][C]0.030408[/C][/ROW]
[ROW][C]30[/C][C]-0.328986[/C][C]-3.4347[/C][C]0.00042[/C][/ROW]
[ROW][C]31[/C][C]-0.207543[/C][C]-2.1668[/C][C]0.016213[/C][/ROW]
[ROW][C]32[/C][C]-0.131124[/C][C]-1.369[/C][C]0.08691[/C][/ROW]
[ROW][C]33[/C][C]-0.052389[/C][C]-0.547[/C][C]0.292764[/C][/ROW]
[ROW][C]34[/C][C]0.024059[/C][C]0.2512[/C][C]0.401072[/C][/ROW]
[ROW][C]35[/C][C]0.201907[/C][C]2.108[/C][C]0.018663[/C][/ROW]
[ROW][C]36[/C][C]0.523067[/C][C]5.461[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62671&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62671&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
10.3600093.75860.000138
20.1529871.59720.056554
30.0337390.35220.362669
4-0.147809-1.54320.062844
5-0.223003-2.32820.010873
6-0.351691-3.67180.000187
7-0.245212-2.56010.005917
8-0.131999-1.37810.085496
90.0151420.15810.437339
100.0553150.57750.282393
110.2722542.84240.002673
120.7651247.98810
130.2493682.60350.005257
140.0825730.86210.195266
15-0.030658-0.32010.374761
16-0.210612-2.19880.015001
17-0.238405-2.4890.007161
18-0.372755-3.89178.6e-05
19-0.266153-2.77870.003214
20-0.143996-1.50340.067819
21-0.057719-0.60260.274011
220.0181190.18920.425156
230.248772.59720.005347
240.6538076.82590
250.2457262.56550.005831
260.1058451.10510.135784
27-0.025335-0.26450.395946
28-0.162417-1.69570.0464
29-0.181455-1.89440.030408
30-0.328986-3.43470.00042
31-0.207543-2.16680.016213
32-0.131124-1.3690.08691
33-0.052389-0.5470.292764
340.0240590.25120.401072
350.2019072.1080.018663
360.5230675.4610







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3600093.75860.000138
20.0268620.28050.389831
3-0.033951-0.35450.36184
4-0.176534-1.84310.034018
5-0.135737-1.41710.079648
6-0.248359-2.59290.005411
7-0.041261-0.43080.333742
8-0.01873-0.19550.422664
90.0686170.71640.237645
10-0.048856-0.51010.305515
110.2109882.20280.014858
120.7044927.35510
13-0.363923-3.79950.00012
14-0.195989-2.04620.021572
150.0137960.1440.442871
16-0.069151-0.7220.235934
17-0.038399-0.40090.344641
18-0.027459-0.28670.387452
19-0.009151-0.09550.462032
20-0.104018-1.0860.139941
21-0.153521-1.60280.055936
220.1875891.95850.026364
230.0948640.99040.162084
240.0281850.29430.384559
250.0377540.39420.347116
260.0188970.19730.421986
27-0.063537-0.66330.254254
280.1116091.16520.123235
290.0741960.77460.220117
30-0.028899-0.30170.381721
310.0009270.00970.49615
32-0.098203-1.02530.153753
330.0898530.93810.175136
340.0037750.03940.484315
35-0.149688-1.56280.0605
36-0.051743-0.54020.295076

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.360009 & 3.7586 & 0.000138 \tabularnewline
2 & 0.026862 & 0.2805 & 0.389831 \tabularnewline
3 & -0.033951 & -0.3545 & 0.36184 \tabularnewline
4 & -0.176534 & -1.8431 & 0.034018 \tabularnewline
5 & -0.135737 & -1.4171 & 0.079648 \tabularnewline
6 & -0.248359 & -2.5929 & 0.005411 \tabularnewline
7 & -0.041261 & -0.4308 & 0.333742 \tabularnewline
8 & -0.01873 & -0.1955 & 0.422664 \tabularnewline
9 & 0.068617 & 0.7164 & 0.237645 \tabularnewline
10 & -0.048856 & -0.5101 & 0.305515 \tabularnewline
11 & 0.210988 & 2.2028 & 0.014858 \tabularnewline
12 & 0.704492 & 7.3551 & 0 \tabularnewline
13 & -0.363923 & -3.7995 & 0.00012 \tabularnewline
14 & -0.195989 & -2.0462 & 0.021572 \tabularnewline
15 & 0.013796 & 0.144 & 0.442871 \tabularnewline
16 & -0.069151 & -0.722 & 0.235934 \tabularnewline
17 & -0.038399 & -0.4009 & 0.344641 \tabularnewline
18 & -0.027459 & -0.2867 & 0.387452 \tabularnewline
19 & -0.009151 & -0.0955 & 0.462032 \tabularnewline
20 & -0.104018 & -1.086 & 0.139941 \tabularnewline
21 & -0.153521 & -1.6028 & 0.055936 \tabularnewline
22 & 0.187589 & 1.9585 & 0.026364 \tabularnewline
23 & 0.094864 & 0.9904 & 0.162084 \tabularnewline
24 & 0.028185 & 0.2943 & 0.384559 \tabularnewline
25 & 0.037754 & 0.3942 & 0.347116 \tabularnewline
26 & 0.018897 & 0.1973 & 0.421986 \tabularnewline
27 & -0.063537 & -0.6633 & 0.254254 \tabularnewline
28 & 0.111609 & 1.1652 & 0.123235 \tabularnewline
29 & 0.074196 & 0.7746 & 0.220117 \tabularnewline
30 & -0.028899 & -0.3017 & 0.381721 \tabularnewline
31 & 0.000927 & 0.0097 & 0.49615 \tabularnewline
32 & -0.098203 & -1.0253 & 0.153753 \tabularnewline
33 & 0.089853 & 0.9381 & 0.175136 \tabularnewline
34 & 0.003775 & 0.0394 & 0.484315 \tabularnewline
35 & -0.149688 & -1.5628 & 0.0605 \tabularnewline
36 & -0.051743 & -0.5402 & 0.295076 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62671&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]0.360009[/C][C]3.7586[/C][C]0.000138[/C][/ROW]
[ROW][C]2[/C][C]0.026862[/C][C]0.2805[/C][C]0.389831[/C][/ROW]
[ROW][C]3[/C][C]-0.033951[/C][C]-0.3545[/C][C]0.36184[/C][/ROW]
[ROW][C]4[/C][C]-0.176534[/C][C]-1.8431[/C][C]0.034018[/C][/ROW]
[ROW][C]5[/C][C]-0.135737[/C][C]-1.4171[/C][C]0.079648[/C][/ROW]
[ROW][C]6[/C][C]-0.248359[/C][C]-2.5929[/C][C]0.005411[/C][/ROW]
[ROW][C]7[/C][C]-0.041261[/C][C]-0.4308[/C][C]0.333742[/C][/ROW]
[ROW][C]8[/C][C]-0.01873[/C][C]-0.1955[/C][C]0.422664[/C][/ROW]
[ROW][C]9[/C][C]0.068617[/C][C]0.7164[/C][C]0.237645[/C][/ROW]
[ROW][C]10[/C][C]-0.048856[/C][C]-0.5101[/C][C]0.305515[/C][/ROW]
[ROW][C]11[/C][C]0.210988[/C][C]2.2028[/C][C]0.014858[/C][/ROW]
[ROW][C]12[/C][C]0.704492[/C][C]7.3551[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.363923[/C][C]-3.7995[/C][C]0.00012[/C][/ROW]
[ROW][C]14[/C][C]-0.195989[/C][C]-2.0462[/C][C]0.021572[/C][/ROW]
[ROW][C]15[/C][C]0.013796[/C][C]0.144[/C][C]0.442871[/C][/ROW]
[ROW][C]16[/C][C]-0.069151[/C][C]-0.722[/C][C]0.235934[/C][/ROW]
[ROW][C]17[/C][C]-0.038399[/C][C]-0.4009[/C][C]0.344641[/C][/ROW]
[ROW][C]18[/C][C]-0.027459[/C][C]-0.2867[/C][C]0.387452[/C][/ROW]
[ROW][C]19[/C][C]-0.009151[/C][C]-0.0955[/C][C]0.462032[/C][/ROW]
[ROW][C]20[/C][C]-0.104018[/C][C]-1.086[/C][C]0.139941[/C][/ROW]
[ROW][C]21[/C][C]-0.153521[/C][C]-1.6028[/C][C]0.055936[/C][/ROW]
[ROW][C]22[/C][C]0.187589[/C][C]1.9585[/C][C]0.026364[/C][/ROW]
[ROW][C]23[/C][C]0.094864[/C][C]0.9904[/C][C]0.162084[/C][/ROW]
[ROW][C]24[/C][C]0.028185[/C][C]0.2943[/C][C]0.384559[/C][/ROW]
[ROW][C]25[/C][C]0.037754[/C][C]0.3942[/C][C]0.347116[/C][/ROW]
[ROW][C]26[/C][C]0.018897[/C][C]0.1973[/C][C]0.421986[/C][/ROW]
[ROW][C]27[/C][C]-0.063537[/C][C]-0.6633[/C][C]0.254254[/C][/ROW]
[ROW][C]28[/C][C]0.111609[/C][C]1.1652[/C][C]0.123235[/C][/ROW]
[ROW][C]29[/C][C]0.074196[/C][C]0.7746[/C][C]0.220117[/C][/ROW]
[ROW][C]30[/C][C]-0.028899[/C][C]-0.3017[/C][C]0.381721[/C][/ROW]
[ROW][C]31[/C][C]0.000927[/C][C]0.0097[/C][C]0.49615[/C][/ROW]
[ROW][C]32[/C][C]-0.098203[/C][C]-1.0253[/C][C]0.153753[/C][/ROW]
[ROW][C]33[/C][C]0.089853[/C][C]0.9381[/C][C]0.175136[/C][/ROW]
[ROW][C]34[/C][C]0.003775[/C][C]0.0394[/C][C]0.484315[/C][/ROW]
[ROW][C]35[/C][C]-0.149688[/C][C]-1.5628[/C][C]0.0605[/C][/ROW]
[ROW][C]36[/C][C]-0.051743[/C][C]-0.5402[/C][C]0.295076[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62671&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62671&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
10.3600093.75860.000138
20.0268620.28050.389831
3-0.033951-0.35450.36184
4-0.176534-1.84310.034018
5-0.135737-1.41710.079648
6-0.248359-2.59290.005411
7-0.041261-0.43080.333742
8-0.01873-0.19550.422664
90.0686170.71640.237645
10-0.048856-0.51010.305515
110.2109882.20280.014858
120.7044927.35510
13-0.363923-3.79950.00012
14-0.195989-2.04620.021572
150.0137960.1440.442871
16-0.069151-0.7220.235934
17-0.038399-0.40090.344641
18-0.027459-0.28670.387452
19-0.009151-0.09550.462032
20-0.104018-1.0860.139941
21-0.153521-1.60280.055936
220.1875891.95850.026364
230.0948640.99040.162084
240.0281850.29430.384559
250.0377540.39420.347116
260.0188970.19730.421986
27-0.063537-0.66330.254254
280.1116091.16520.123235
290.0741960.77460.220117
30-0.028899-0.30170.381721
310.0009270.00970.49615
32-0.098203-1.02530.153753
330.0898530.93810.175136
340.0037750.03940.484315
35-0.149688-1.56280.0605
36-0.051743-0.54020.295076



Parameters (Session):
par1 = FALSE ; par2 = 0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;
Parameters (R input):
par1 = 36 ; par2 = 1.0 ; 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')