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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 computationWed, 02 Dec 2009 09:08:32 -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/02/t1259770140b0y99a3fpjittsi.htm/, Retrieved Sun, 28 Apr 2024 07:46:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62407, Retrieved Sun, 28 Apr 2024 07:46:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact121
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]
- R  D          [(Partial) Autocorrelation Function] [] [2009-12-02 16:08:32] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
267413
267366
264777
258863
254844
254868
277267
285351
286602
283042
276687
277915
277128
277103
275037
270150
267140
264993
287259
291186
292300
288186
281477
282656
280190
280408
276836
275216
274352
271311
289802
290726
292300
278506
269826
265861
269034
264176
255198
253353
246057
235372
258556
260993
254663
250643
243422
247105
248541
245039
237080
237085
225554
226839
247934
248333
246969
245098
246263
255765
264319
268347
273046
273963
267430
271993
292710




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=62407&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=62407&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62407&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
10.8686667.11030
20.7332326.00180
30.6383525.22511e-06
40.5747974.70497e-06
50.5516284.51531.3e-05
60.5097984.17294.4e-05
70.4236893.4680.00046
80.3236342.64910.005029
90.2762012.26080.013512
100.2741012.24360.014084
110.3137572.56820.006229
120.3174182.59820.005757
130.1660721.35940.089295
140.044120.36110.359566
15-0.039548-0.32370.37358
16-0.093645-0.76650.223031
17-0.102129-0.8360.203073
18-0.138466-1.13340.130545
19-0.206783-1.69260.04759
20-0.281659-2.30550.012122
21-0.302251-2.4740.00795
22-0.288172-2.35880.010629
23-0.241911-1.98010.025899
24-0.22831-1.86880.033012
25-0.318648-2.60820.005606
26-0.36185-2.96190.002114
27-0.385883-3.15860.001189
28-0.370492-3.03260.001723
29-0.323996-2.6520.004989
30-0.302018-2.47210.007989
31-0.313438-2.56560.006272
32-0.322647-2.6410.005139
33-0.293843-2.40520.009466
34-0.2417-1.97840.025999
35-0.184884-1.51330.067448
36-0.143517-1.17470.122128

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.868666 & 7.1103 & 0 \tabularnewline
2 & 0.733232 & 6.0018 & 0 \tabularnewline
3 & 0.638352 & 5.2251 & 1e-06 \tabularnewline
4 & 0.574797 & 4.7049 & 7e-06 \tabularnewline
5 & 0.551628 & 4.5153 & 1.3e-05 \tabularnewline
6 & 0.509798 & 4.1729 & 4.4e-05 \tabularnewline
7 & 0.423689 & 3.468 & 0.00046 \tabularnewline
8 & 0.323634 & 2.6491 & 0.005029 \tabularnewline
9 & 0.276201 & 2.2608 & 0.013512 \tabularnewline
10 & 0.274101 & 2.2436 & 0.014084 \tabularnewline
11 & 0.313757 & 2.5682 & 0.006229 \tabularnewline
12 & 0.317418 & 2.5982 & 0.005757 \tabularnewline
13 & 0.166072 & 1.3594 & 0.089295 \tabularnewline
14 & 0.04412 & 0.3611 & 0.359566 \tabularnewline
15 & -0.039548 & -0.3237 & 0.37358 \tabularnewline
16 & -0.093645 & -0.7665 & 0.223031 \tabularnewline
17 & -0.102129 & -0.836 & 0.203073 \tabularnewline
18 & -0.138466 & -1.1334 & 0.130545 \tabularnewline
19 & -0.206783 & -1.6926 & 0.04759 \tabularnewline
20 & -0.281659 & -2.3055 & 0.012122 \tabularnewline
21 & -0.302251 & -2.474 & 0.00795 \tabularnewline
22 & -0.288172 & -2.3588 & 0.010629 \tabularnewline
23 & -0.241911 & -1.9801 & 0.025899 \tabularnewline
24 & -0.22831 & -1.8688 & 0.033012 \tabularnewline
25 & -0.318648 & -2.6082 & 0.005606 \tabularnewline
26 & -0.36185 & -2.9619 & 0.002114 \tabularnewline
27 & -0.385883 & -3.1586 & 0.001189 \tabularnewline
28 & -0.370492 & -3.0326 & 0.001723 \tabularnewline
29 & -0.323996 & -2.652 & 0.004989 \tabularnewline
30 & -0.302018 & -2.4721 & 0.007989 \tabularnewline
31 & -0.313438 & -2.5656 & 0.006272 \tabularnewline
32 & -0.322647 & -2.641 & 0.005139 \tabularnewline
33 & -0.293843 & -2.4052 & 0.009466 \tabularnewline
34 & -0.2417 & -1.9784 & 0.025999 \tabularnewline
35 & -0.184884 & -1.5133 & 0.067448 \tabularnewline
36 & -0.143517 & -1.1747 & 0.122128 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62407&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]0.868666[/C][C]7.1103[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.733232[/C][C]6.0018[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.638352[/C][C]5.2251[/C][C]1e-06[/C][/ROW]
[ROW][C]4[/C][C]0.574797[/C][C]4.7049[/C][C]7e-06[/C][/ROW]
[ROW][C]5[/C][C]0.551628[/C][C]4.5153[/C][C]1.3e-05[/C][/ROW]
[ROW][C]6[/C][C]0.509798[/C][C]4.1729[/C][C]4.4e-05[/C][/ROW]
[ROW][C]7[/C][C]0.423689[/C][C]3.468[/C][C]0.00046[/C][/ROW]
[ROW][C]8[/C][C]0.323634[/C][C]2.6491[/C][C]0.005029[/C][/ROW]
[ROW][C]9[/C][C]0.276201[/C][C]2.2608[/C][C]0.013512[/C][/ROW]
[ROW][C]10[/C][C]0.274101[/C][C]2.2436[/C][C]0.014084[/C][/ROW]
[ROW][C]11[/C][C]0.313757[/C][C]2.5682[/C][C]0.006229[/C][/ROW]
[ROW][C]12[/C][C]0.317418[/C][C]2.5982[/C][C]0.005757[/C][/ROW]
[ROW][C]13[/C][C]0.166072[/C][C]1.3594[/C][C]0.089295[/C][/ROW]
[ROW][C]14[/C][C]0.04412[/C][C]0.3611[/C][C]0.359566[/C][/ROW]
[ROW][C]15[/C][C]-0.039548[/C][C]-0.3237[/C][C]0.37358[/C][/ROW]
[ROW][C]16[/C][C]-0.093645[/C][C]-0.7665[/C][C]0.223031[/C][/ROW]
[ROW][C]17[/C][C]-0.102129[/C][C]-0.836[/C][C]0.203073[/C][/ROW]
[ROW][C]18[/C][C]-0.138466[/C][C]-1.1334[/C][C]0.130545[/C][/ROW]
[ROW][C]19[/C][C]-0.206783[/C][C]-1.6926[/C][C]0.04759[/C][/ROW]
[ROW][C]20[/C][C]-0.281659[/C][C]-2.3055[/C][C]0.012122[/C][/ROW]
[ROW][C]21[/C][C]-0.302251[/C][C]-2.474[/C][C]0.00795[/C][/ROW]
[ROW][C]22[/C][C]-0.288172[/C][C]-2.3588[/C][C]0.010629[/C][/ROW]
[ROW][C]23[/C][C]-0.241911[/C][C]-1.9801[/C][C]0.025899[/C][/ROW]
[ROW][C]24[/C][C]-0.22831[/C][C]-1.8688[/C][C]0.033012[/C][/ROW]
[ROW][C]25[/C][C]-0.318648[/C][C]-2.6082[/C][C]0.005606[/C][/ROW]
[ROW][C]26[/C][C]-0.36185[/C][C]-2.9619[/C][C]0.002114[/C][/ROW]
[ROW][C]27[/C][C]-0.385883[/C][C]-3.1586[/C][C]0.001189[/C][/ROW]
[ROW][C]28[/C][C]-0.370492[/C][C]-3.0326[/C][C]0.001723[/C][/ROW]
[ROW][C]29[/C][C]-0.323996[/C][C]-2.652[/C][C]0.004989[/C][/ROW]
[ROW][C]30[/C][C]-0.302018[/C][C]-2.4721[/C][C]0.007989[/C][/ROW]
[ROW][C]31[/C][C]-0.313438[/C][C]-2.5656[/C][C]0.006272[/C][/ROW]
[ROW][C]32[/C][C]-0.322647[/C][C]-2.641[/C][C]0.005139[/C][/ROW]
[ROW][C]33[/C][C]-0.293843[/C][C]-2.4052[/C][C]0.009466[/C][/ROW]
[ROW][C]34[/C][C]-0.2417[/C][C]-1.9784[/C][C]0.025999[/C][/ROW]
[ROW][C]35[/C][C]-0.184884[/C][C]-1.5133[/C][C]0.067448[/C][/ROW]
[ROW][C]36[/C][C]-0.143517[/C][C]-1.1747[/C][C]0.122128[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62407&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62407&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
10.8686667.11030
20.7332326.00180
30.6383525.22511e-06
40.5747974.70497e-06
50.5516284.51531.3e-05
60.5097984.17294.4e-05
70.4236893.4680.00046
80.3236342.64910.005029
90.2762012.26080.013512
100.2741012.24360.014084
110.3137572.56820.006229
120.3174182.59820.005757
130.1660721.35940.089295
140.044120.36110.359566
15-0.039548-0.32370.37358
16-0.093645-0.76650.223031
17-0.102129-0.8360.203073
18-0.138466-1.13340.130545
19-0.206783-1.69260.04759
20-0.281659-2.30550.012122
21-0.302251-2.4740.00795
22-0.288172-2.35880.010629
23-0.241911-1.98010.025899
24-0.22831-1.86880.033012
25-0.318648-2.60820.005606
26-0.36185-2.96190.002114
27-0.385883-3.15860.001189
28-0.370492-3.03260.001723
29-0.323996-2.6520.004989
30-0.302018-2.47210.007989
31-0.313438-2.56560.006272
32-0.322647-2.6410.005139
33-0.293843-2.40520.009466
34-0.2417-1.97840.025999
35-0.184884-1.51330.067448
36-0.143517-1.17470.122128







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8686667.11030
2-0.086991-0.7120.239454
30.0885870.72510.235453
40.0632710.51790.303118
50.1410971.15490.126111
6-0.070702-0.57870.282358
7-0.152919-1.25170.107517
8-0.094459-0.77320.221068
90.1351491.10620.13629
100.0969880.79390.215034
110.1699411.3910.08441
12-0.07965-0.6520.258328
13-0.572364-4.6857e-06
140.0538650.44090.33035
15-0.025543-0.20910.417511
16-0.037456-0.30660.380054
170.0577720.47290.318918
18-0.053358-0.43680.331848
190.0356620.29190.385629
20-0.058537-0.47910.316698
21-0.021594-0.17680.430117
22-0.084534-0.69190.245682
230.0049240.04030.483985
240.0618270.50610.307232
25-0.102694-0.84060.201784
260.0653660.5350.297196
27-0.076479-0.6260.266717
280.0717840.58760.279397
29-0.027499-0.22510.411299
300.0515460.42190.337216
31-0.042111-0.34470.365704
320.0289560.2370.406684
33-0.029221-0.23920.405847
34-0.007173-0.05870.476677
35-0.114528-0.93750.175947
360.1442531.18080.120935

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.868666 & 7.1103 & 0 \tabularnewline
2 & -0.086991 & -0.712 & 0.239454 \tabularnewline
3 & 0.088587 & 0.7251 & 0.235453 \tabularnewline
4 & 0.063271 & 0.5179 & 0.303118 \tabularnewline
5 & 0.141097 & 1.1549 & 0.126111 \tabularnewline
6 & -0.070702 & -0.5787 & 0.282358 \tabularnewline
7 & -0.152919 & -1.2517 & 0.107517 \tabularnewline
8 & -0.094459 & -0.7732 & 0.221068 \tabularnewline
9 & 0.135149 & 1.1062 & 0.13629 \tabularnewline
10 & 0.096988 & 0.7939 & 0.215034 \tabularnewline
11 & 0.169941 & 1.391 & 0.08441 \tabularnewline
12 & -0.07965 & -0.652 & 0.258328 \tabularnewline
13 & -0.572364 & -4.685 & 7e-06 \tabularnewline
14 & 0.053865 & 0.4409 & 0.33035 \tabularnewline
15 & -0.025543 & -0.2091 & 0.417511 \tabularnewline
16 & -0.037456 & -0.3066 & 0.380054 \tabularnewline
17 & 0.057772 & 0.4729 & 0.318918 \tabularnewline
18 & -0.053358 & -0.4368 & 0.331848 \tabularnewline
19 & 0.035662 & 0.2919 & 0.385629 \tabularnewline
20 & -0.058537 & -0.4791 & 0.316698 \tabularnewline
21 & -0.021594 & -0.1768 & 0.430117 \tabularnewline
22 & -0.084534 & -0.6919 & 0.245682 \tabularnewline
23 & 0.004924 & 0.0403 & 0.483985 \tabularnewline
24 & 0.061827 & 0.5061 & 0.307232 \tabularnewline
25 & -0.102694 & -0.8406 & 0.201784 \tabularnewline
26 & 0.065366 & 0.535 & 0.297196 \tabularnewline
27 & -0.076479 & -0.626 & 0.266717 \tabularnewline
28 & 0.071784 & 0.5876 & 0.279397 \tabularnewline
29 & -0.027499 & -0.2251 & 0.411299 \tabularnewline
30 & 0.051546 & 0.4219 & 0.337216 \tabularnewline
31 & -0.042111 & -0.3447 & 0.365704 \tabularnewline
32 & 0.028956 & 0.237 & 0.406684 \tabularnewline
33 & -0.029221 & -0.2392 & 0.405847 \tabularnewline
34 & -0.007173 & -0.0587 & 0.476677 \tabularnewline
35 & -0.114528 & -0.9375 & 0.175947 \tabularnewline
36 & 0.144253 & 1.1808 & 0.120935 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62407&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]0.868666[/C][C]7.1103[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.086991[/C][C]-0.712[/C][C]0.239454[/C][/ROW]
[ROW][C]3[/C][C]0.088587[/C][C]0.7251[/C][C]0.235453[/C][/ROW]
[ROW][C]4[/C][C]0.063271[/C][C]0.5179[/C][C]0.303118[/C][/ROW]
[ROW][C]5[/C][C]0.141097[/C][C]1.1549[/C][C]0.126111[/C][/ROW]
[ROW][C]6[/C][C]-0.070702[/C][C]-0.5787[/C][C]0.282358[/C][/ROW]
[ROW][C]7[/C][C]-0.152919[/C][C]-1.2517[/C][C]0.107517[/C][/ROW]
[ROW][C]8[/C][C]-0.094459[/C][C]-0.7732[/C][C]0.221068[/C][/ROW]
[ROW][C]9[/C][C]0.135149[/C][C]1.1062[/C][C]0.13629[/C][/ROW]
[ROW][C]10[/C][C]0.096988[/C][C]0.7939[/C][C]0.215034[/C][/ROW]
[ROW][C]11[/C][C]0.169941[/C][C]1.391[/C][C]0.08441[/C][/ROW]
[ROW][C]12[/C][C]-0.07965[/C][C]-0.652[/C][C]0.258328[/C][/ROW]
[ROW][C]13[/C][C]-0.572364[/C][C]-4.685[/C][C]7e-06[/C][/ROW]
[ROW][C]14[/C][C]0.053865[/C][C]0.4409[/C][C]0.33035[/C][/ROW]
[ROW][C]15[/C][C]-0.025543[/C][C]-0.2091[/C][C]0.417511[/C][/ROW]
[ROW][C]16[/C][C]-0.037456[/C][C]-0.3066[/C][C]0.380054[/C][/ROW]
[ROW][C]17[/C][C]0.057772[/C][C]0.4729[/C][C]0.318918[/C][/ROW]
[ROW][C]18[/C][C]-0.053358[/C][C]-0.4368[/C][C]0.331848[/C][/ROW]
[ROW][C]19[/C][C]0.035662[/C][C]0.2919[/C][C]0.385629[/C][/ROW]
[ROW][C]20[/C][C]-0.058537[/C][C]-0.4791[/C][C]0.316698[/C][/ROW]
[ROW][C]21[/C][C]-0.021594[/C][C]-0.1768[/C][C]0.430117[/C][/ROW]
[ROW][C]22[/C][C]-0.084534[/C][C]-0.6919[/C][C]0.245682[/C][/ROW]
[ROW][C]23[/C][C]0.004924[/C][C]0.0403[/C][C]0.483985[/C][/ROW]
[ROW][C]24[/C][C]0.061827[/C][C]0.5061[/C][C]0.307232[/C][/ROW]
[ROW][C]25[/C][C]-0.102694[/C][C]-0.8406[/C][C]0.201784[/C][/ROW]
[ROW][C]26[/C][C]0.065366[/C][C]0.535[/C][C]0.297196[/C][/ROW]
[ROW][C]27[/C][C]-0.076479[/C][C]-0.626[/C][C]0.266717[/C][/ROW]
[ROW][C]28[/C][C]0.071784[/C][C]0.5876[/C][C]0.279397[/C][/ROW]
[ROW][C]29[/C][C]-0.027499[/C][C]-0.2251[/C][C]0.411299[/C][/ROW]
[ROW][C]30[/C][C]0.051546[/C][C]0.4219[/C][C]0.337216[/C][/ROW]
[ROW][C]31[/C][C]-0.042111[/C][C]-0.3447[/C][C]0.365704[/C][/ROW]
[ROW][C]32[/C][C]0.028956[/C][C]0.237[/C][C]0.406684[/C][/ROW]
[ROW][C]33[/C][C]-0.029221[/C][C]-0.2392[/C][C]0.405847[/C][/ROW]
[ROW][C]34[/C][C]-0.007173[/C][C]-0.0587[/C][C]0.476677[/C][/ROW]
[ROW][C]35[/C][C]-0.114528[/C][C]-0.9375[/C][C]0.175947[/C][/ROW]
[ROW][C]36[/C][C]0.144253[/C][C]1.1808[/C][C]0.120935[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62407&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62407&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
10.8686667.11030
2-0.086991-0.7120.239454
30.0885870.72510.235453
40.0632710.51790.303118
50.1410971.15490.126111
6-0.070702-0.57870.282358
7-0.152919-1.25170.107517
8-0.094459-0.77320.221068
90.1351491.10620.13629
100.0969880.79390.215034
110.1699411.3910.08441
12-0.07965-0.6520.258328
13-0.572364-4.6857e-06
140.0538650.44090.33035
15-0.025543-0.20910.417511
16-0.037456-0.30660.380054
170.0577720.47290.318918
18-0.053358-0.43680.331848
190.0356620.29190.385629
20-0.058537-0.47910.316698
21-0.021594-0.17680.430117
22-0.084534-0.69190.245682
230.0049240.04030.483985
240.0618270.50610.307232
25-0.102694-0.84060.201784
260.0653660.5350.297196
27-0.076479-0.6260.266717
280.0717840.58760.279397
29-0.027499-0.22510.411299
300.0515460.42190.337216
31-0.042111-0.34470.365704
320.0289560.2370.406684
33-0.029221-0.23920.405847
34-0.007173-0.05870.476677
35-0.114528-0.93750.175947
360.1442531.18080.120935



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')