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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 computationSat, 28 Nov 2009 03:08:19 -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/28/t1259403007arqr8u28w841pou.htm/, Retrieved Fri, 03 May 2024 11:58:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61399, Retrieved Fri, 03 May 2024 11:58:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact129
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Autocorrelatie fu...] [2009-11-28 10:08:19] [762da55b2e2304daaed24a7cc507d14d] [Current]
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Dataseries X:
611
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




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=61399&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=61399&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61399&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
10.1485981.01870.156771
20.2341171.6050.057594
30.3184332.18310.01703
40.2256421.54690.064295
50.0848360.58160.281806
60.1632711.11930.134344
70.0221350.15170.440017
80.1570341.07660.143584
90.0439510.30130.382254
10-0.04843-0.3320.370676
110.3130542.14620.018526
12-0.065284-0.44760.328261
13-0.014012-0.09610.461941
140.1166140.79950.214022
150.0540040.37020.356437
16-0.033172-0.22740.410543
170.1027160.70420.242397
18-0.131299-0.90010.186317
190.0443520.30410.381213
20-0.078343-0.53710.29687
21-0.216853-1.48670.07189
22-0.091392-0.62660.266993
23-0.08969-0.61490.270798
24-0.216832-1.48650.071909
25-0.155607-1.06680.145759
26-0.144028-0.98740.16425
27-0.211328-1.44880.077018
28-0.133981-0.91850.181517
29-0.145869-10.161209
30-0.08716-0.59750.276509
31-0.043139-0.29570.384364
32-0.136566-0.93620.176966
33-0.017344-0.11890.452928
340.0233160.15980.436843
35-0.033314-0.22840.410167
36-0.043913-0.30110.382352

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.148598 & 1.0187 & 0.156771 \tabularnewline
2 & 0.234117 & 1.605 & 0.057594 \tabularnewline
3 & 0.318433 & 2.1831 & 0.01703 \tabularnewline
4 & 0.225642 & 1.5469 & 0.064295 \tabularnewline
5 & 0.084836 & 0.5816 & 0.281806 \tabularnewline
6 & 0.163271 & 1.1193 & 0.134344 \tabularnewline
7 & 0.022135 & 0.1517 & 0.440017 \tabularnewline
8 & 0.157034 & 1.0766 & 0.143584 \tabularnewline
9 & 0.043951 & 0.3013 & 0.382254 \tabularnewline
10 & -0.04843 & -0.332 & 0.370676 \tabularnewline
11 & 0.313054 & 2.1462 & 0.018526 \tabularnewline
12 & -0.065284 & -0.4476 & 0.328261 \tabularnewline
13 & -0.014012 & -0.0961 & 0.461941 \tabularnewline
14 & 0.116614 & 0.7995 & 0.214022 \tabularnewline
15 & 0.054004 & 0.3702 & 0.356437 \tabularnewline
16 & -0.033172 & -0.2274 & 0.410543 \tabularnewline
17 & 0.102716 & 0.7042 & 0.242397 \tabularnewline
18 & -0.131299 & -0.9001 & 0.186317 \tabularnewline
19 & 0.044352 & 0.3041 & 0.381213 \tabularnewline
20 & -0.078343 & -0.5371 & 0.29687 \tabularnewline
21 & -0.216853 & -1.4867 & 0.07189 \tabularnewline
22 & -0.091392 & -0.6266 & 0.266993 \tabularnewline
23 & -0.08969 & -0.6149 & 0.270798 \tabularnewline
24 & -0.216832 & -1.4865 & 0.071909 \tabularnewline
25 & -0.155607 & -1.0668 & 0.145759 \tabularnewline
26 & -0.144028 & -0.9874 & 0.16425 \tabularnewline
27 & -0.211328 & -1.4488 & 0.077018 \tabularnewline
28 & -0.133981 & -0.9185 & 0.181517 \tabularnewline
29 & -0.145869 & -1 & 0.161209 \tabularnewline
30 & -0.08716 & -0.5975 & 0.276509 \tabularnewline
31 & -0.043139 & -0.2957 & 0.384364 \tabularnewline
32 & -0.136566 & -0.9362 & 0.176966 \tabularnewline
33 & -0.017344 & -0.1189 & 0.452928 \tabularnewline
34 & 0.023316 & 0.1598 & 0.436843 \tabularnewline
35 & -0.033314 & -0.2284 & 0.410167 \tabularnewline
36 & -0.043913 & -0.3011 & 0.382352 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61399&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]0.148598[/C][C]1.0187[/C][C]0.156771[/C][/ROW]
[ROW][C]2[/C][C]0.234117[/C][C]1.605[/C][C]0.057594[/C][/ROW]
[ROW][C]3[/C][C]0.318433[/C][C]2.1831[/C][C]0.01703[/C][/ROW]
[ROW][C]4[/C][C]0.225642[/C][C]1.5469[/C][C]0.064295[/C][/ROW]
[ROW][C]5[/C][C]0.084836[/C][C]0.5816[/C][C]0.281806[/C][/ROW]
[ROW][C]6[/C][C]0.163271[/C][C]1.1193[/C][C]0.134344[/C][/ROW]
[ROW][C]7[/C][C]0.022135[/C][C]0.1517[/C][C]0.440017[/C][/ROW]
[ROW][C]8[/C][C]0.157034[/C][C]1.0766[/C][C]0.143584[/C][/ROW]
[ROW][C]9[/C][C]0.043951[/C][C]0.3013[/C][C]0.382254[/C][/ROW]
[ROW][C]10[/C][C]-0.04843[/C][C]-0.332[/C][C]0.370676[/C][/ROW]
[ROW][C]11[/C][C]0.313054[/C][C]2.1462[/C][C]0.018526[/C][/ROW]
[ROW][C]12[/C][C]-0.065284[/C][C]-0.4476[/C][C]0.328261[/C][/ROW]
[ROW][C]13[/C][C]-0.014012[/C][C]-0.0961[/C][C]0.461941[/C][/ROW]
[ROW][C]14[/C][C]0.116614[/C][C]0.7995[/C][C]0.214022[/C][/ROW]
[ROW][C]15[/C][C]0.054004[/C][C]0.3702[/C][C]0.356437[/C][/ROW]
[ROW][C]16[/C][C]-0.033172[/C][C]-0.2274[/C][C]0.410543[/C][/ROW]
[ROW][C]17[/C][C]0.102716[/C][C]0.7042[/C][C]0.242397[/C][/ROW]
[ROW][C]18[/C][C]-0.131299[/C][C]-0.9001[/C][C]0.186317[/C][/ROW]
[ROW][C]19[/C][C]0.044352[/C][C]0.3041[/C][C]0.381213[/C][/ROW]
[ROW][C]20[/C][C]-0.078343[/C][C]-0.5371[/C][C]0.29687[/C][/ROW]
[ROW][C]21[/C][C]-0.216853[/C][C]-1.4867[/C][C]0.07189[/C][/ROW]
[ROW][C]22[/C][C]-0.091392[/C][C]-0.6266[/C][C]0.266993[/C][/ROW]
[ROW][C]23[/C][C]-0.08969[/C][C]-0.6149[/C][C]0.270798[/C][/ROW]
[ROW][C]24[/C][C]-0.216832[/C][C]-1.4865[/C][C]0.071909[/C][/ROW]
[ROW][C]25[/C][C]-0.155607[/C][C]-1.0668[/C][C]0.145759[/C][/ROW]
[ROW][C]26[/C][C]-0.144028[/C][C]-0.9874[/C][C]0.16425[/C][/ROW]
[ROW][C]27[/C][C]-0.211328[/C][C]-1.4488[/C][C]0.077018[/C][/ROW]
[ROW][C]28[/C][C]-0.133981[/C][C]-0.9185[/C][C]0.181517[/C][/ROW]
[ROW][C]29[/C][C]-0.145869[/C][C]-1[/C][C]0.161209[/C][/ROW]
[ROW][C]30[/C][C]-0.08716[/C][C]-0.5975[/C][C]0.276509[/C][/ROW]
[ROW][C]31[/C][C]-0.043139[/C][C]-0.2957[/C][C]0.384364[/C][/ROW]
[ROW][C]32[/C][C]-0.136566[/C][C]-0.9362[/C][C]0.176966[/C][/ROW]
[ROW][C]33[/C][C]-0.017344[/C][C]-0.1189[/C][C]0.452928[/C][/ROW]
[ROW][C]34[/C][C]0.023316[/C][C]0.1598[/C][C]0.436843[/C][/ROW]
[ROW][C]35[/C][C]-0.033314[/C][C]-0.2284[/C][C]0.410167[/C][/ROW]
[ROW][C]36[/C][C]-0.043913[/C][C]-0.3011[/C][C]0.382352[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61399&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61399&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
10.1485981.01870.156771
20.2341171.6050.057594
30.3184332.18310.01703
40.2256421.54690.064295
50.0848360.58160.281806
60.1632711.11930.134344
70.0221350.15170.440017
80.1570341.07660.143584
90.0439510.30130.382254
10-0.04843-0.3320.370676
110.3130542.14620.018526
12-0.065284-0.44760.328261
13-0.014012-0.09610.461941
140.1166140.79950.214022
150.0540040.37020.356437
16-0.033172-0.22740.410543
170.1027160.70420.242397
18-0.131299-0.90010.186317
190.0443520.30410.381213
20-0.078343-0.53710.29687
21-0.216853-1.48670.07189
22-0.091392-0.62660.266993
23-0.08969-0.61490.270798
24-0.216832-1.48650.071909
25-0.155607-1.06680.145759
26-0.144028-0.98740.16425
27-0.211328-1.44880.077018
28-0.133981-0.91850.181517
29-0.145869-10.161209
30-0.08716-0.59750.276509
31-0.043139-0.29570.384364
32-0.136566-0.93620.176966
33-0.017344-0.11890.452928
340.0233160.15980.436843
35-0.033314-0.22840.410167
36-0.043913-0.30110.382352







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1485981.01870.156771
20.2168231.48650.071917
30.2778781.9050.031452
40.1433580.98280.165365
5-0.063681-0.43660.332208
60.0096630.06620.473731
7-0.108867-0.74640.229584
80.1121150.76860.222981
90.0018990.0130.494834
10-0.110531-0.75780.226188
110.3260362.23520.015097
12-0.171489-1.17570.122824
13-0.054441-0.37320.355327
140.0185730.12730.44961
150.0076830.05270.479107
160.0322350.2210.413028
170.0128220.08790.465164
18-0.139968-0.95960.171091
19-0.016667-0.11430.454758
20-0.083776-0.57430.284238
21-0.151237-1.03680.15256
22-0.144372-0.98980.163678
230.0874380.59940.275878
24-0.01898-0.13010.448514
25-0.135608-0.92970.178643
26-0.031756-0.21770.414299
27-0.10064-0.690.246808
28-0.072883-0.49970.309822
290.1379250.94560.174603
30-0.010628-0.07290.471112
310.0958310.6570.257197
320.0088580.06070.475917
330.0431610.29590.384306
34-0.016319-0.11190.455699
350.0971120.66580.254408
360.0328610.22530.411367

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.148598 & 1.0187 & 0.156771 \tabularnewline
2 & 0.216823 & 1.4865 & 0.071917 \tabularnewline
3 & 0.277878 & 1.905 & 0.031452 \tabularnewline
4 & 0.143358 & 0.9828 & 0.165365 \tabularnewline
5 & -0.063681 & -0.4366 & 0.332208 \tabularnewline
6 & 0.009663 & 0.0662 & 0.473731 \tabularnewline
7 & -0.108867 & -0.7464 & 0.229584 \tabularnewline
8 & 0.112115 & 0.7686 & 0.222981 \tabularnewline
9 & 0.001899 & 0.013 & 0.494834 \tabularnewline
10 & -0.110531 & -0.7578 & 0.226188 \tabularnewline
11 & 0.326036 & 2.2352 & 0.015097 \tabularnewline
12 & -0.171489 & -1.1757 & 0.122824 \tabularnewline
13 & -0.054441 & -0.3732 & 0.355327 \tabularnewline
14 & 0.018573 & 0.1273 & 0.44961 \tabularnewline
15 & 0.007683 & 0.0527 & 0.479107 \tabularnewline
16 & 0.032235 & 0.221 & 0.413028 \tabularnewline
17 & 0.012822 & 0.0879 & 0.465164 \tabularnewline
18 & -0.139968 & -0.9596 & 0.171091 \tabularnewline
19 & -0.016667 & -0.1143 & 0.454758 \tabularnewline
20 & -0.083776 & -0.5743 & 0.284238 \tabularnewline
21 & -0.151237 & -1.0368 & 0.15256 \tabularnewline
22 & -0.144372 & -0.9898 & 0.163678 \tabularnewline
23 & 0.087438 & 0.5994 & 0.275878 \tabularnewline
24 & -0.01898 & -0.1301 & 0.448514 \tabularnewline
25 & -0.135608 & -0.9297 & 0.178643 \tabularnewline
26 & -0.031756 & -0.2177 & 0.414299 \tabularnewline
27 & -0.10064 & -0.69 & 0.246808 \tabularnewline
28 & -0.072883 & -0.4997 & 0.309822 \tabularnewline
29 & 0.137925 & 0.9456 & 0.174603 \tabularnewline
30 & -0.010628 & -0.0729 & 0.471112 \tabularnewline
31 & 0.095831 & 0.657 & 0.257197 \tabularnewline
32 & 0.008858 & 0.0607 & 0.475917 \tabularnewline
33 & 0.043161 & 0.2959 & 0.384306 \tabularnewline
34 & -0.016319 & -0.1119 & 0.455699 \tabularnewline
35 & 0.097112 & 0.6658 & 0.254408 \tabularnewline
36 & 0.032861 & 0.2253 & 0.411367 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61399&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]0.148598[/C][C]1.0187[/C][C]0.156771[/C][/ROW]
[ROW][C]2[/C][C]0.216823[/C][C]1.4865[/C][C]0.071917[/C][/ROW]
[ROW][C]3[/C][C]0.277878[/C][C]1.905[/C][C]0.031452[/C][/ROW]
[ROW][C]4[/C][C]0.143358[/C][C]0.9828[/C][C]0.165365[/C][/ROW]
[ROW][C]5[/C][C]-0.063681[/C][C]-0.4366[/C][C]0.332208[/C][/ROW]
[ROW][C]6[/C][C]0.009663[/C][C]0.0662[/C][C]0.473731[/C][/ROW]
[ROW][C]7[/C][C]-0.108867[/C][C]-0.7464[/C][C]0.229584[/C][/ROW]
[ROW][C]8[/C][C]0.112115[/C][C]0.7686[/C][C]0.222981[/C][/ROW]
[ROW][C]9[/C][C]0.001899[/C][C]0.013[/C][C]0.494834[/C][/ROW]
[ROW][C]10[/C][C]-0.110531[/C][C]-0.7578[/C][C]0.226188[/C][/ROW]
[ROW][C]11[/C][C]0.326036[/C][C]2.2352[/C][C]0.015097[/C][/ROW]
[ROW][C]12[/C][C]-0.171489[/C][C]-1.1757[/C][C]0.122824[/C][/ROW]
[ROW][C]13[/C][C]-0.054441[/C][C]-0.3732[/C][C]0.355327[/C][/ROW]
[ROW][C]14[/C][C]0.018573[/C][C]0.1273[/C][C]0.44961[/C][/ROW]
[ROW][C]15[/C][C]0.007683[/C][C]0.0527[/C][C]0.479107[/C][/ROW]
[ROW][C]16[/C][C]0.032235[/C][C]0.221[/C][C]0.413028[/C][/ROW]
[ROW][C]17[/C][C]0.012822[/C][C]0.0879[/C][C]0.465164[/C][/ROW]
[ROW][C]18[/C][C]-0.139968[/C][C]-0.9596[/C][C]0.171091[/C][/ROW]
[ROW][C]19[/C][C]-0.016667[/C][C]-0.1143[/C][C]0.454758[/C][/ROW]
[ROW][C]20[/C][C]-0.083776[/C][C]-0.5743[/C][C]0.284238[/C][/ROW]
[ROW][C]21[/C][C]-0.151237[/C][C]-1.0368[/C][C]0.15256[/C][/ROW]
[ROW][C]22[/C][C]-0.144372[/C][C]-0.9898[/C][C]0.163678[/C][/ROW]
[ROW][C]23[/C][C]0.087438[/C][C]0.5994[/C][C]0.275878[/C][/ROW]
[ROW][C]24[/C][C]-0.01898[/C][C]-0.1301[/C][C]0.448514[/C][/ROW]
[ROW][C]25[/C][C]-0.135608[/C][C]-0.9297[/C][C]0.178643[/C][/ROW]
[ROW][C]26[/C][C]-0.031756[/C][C]-0.2177[/C][C]0.414299[/C][/ROW]
[ROW][C]27[/C][C]-0.10064[/C][C]-0.69[/C][C]0.246808[/C][/ROW]
[ROW][C]28[/C][C]-0.072883[/C][C]-0.4997[/C][C]0.309822[/C][/ROW]
[ROW][C]29[/C][C]0.137925[/C][C]0.9456[/C][C]0.174603[/C][/ROW]
[ROW][C]30[/C][C]-0.010628[/C][C]-0.0729[/C][C]0.471112[/C][/ROW]
[ROW][C]31[/C][C]0.095831[/C][C]0.657[/C][C]0.257197[/C][/ROW]
[ROW][C]32[/C][C]0.008858[/C][C]0.0607[/C][C]0.475917[/C][/ROW]
[ROW][C]33[/C][C]0.043161[/C][C]0.2959[/C][C]0.384306[/C][/ROW]
[ROW][C]34[/C][C]-0.016319[/C][C]-0.1119[/C][C]0.455699[/C][/ROW]
[ROW][C]35[/C][C]0.097112[/C][C]0.6658[/C][C]0.254408[/C][/ROW]
[ROW][C]36[/C][C]0.032861[/C][C]0.2253[/C][C]0.411367[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61399&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61399&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
10.1485981.01870.156771
20.2168231.48650.071917
30.2778781.9050.031452
40.1433580.98280.165365
5-0.063681-0.43660.332208
60.0096630.06620.473731
7-0.108867-0.74640.229584
80.1121150.76860.222981
90.0018990.0130.494834
10-0.110531-0.75780.226188
110.3260362.23520.015097
12-0.171489-1.17570.122824
13-0.054441-0.37320.355327
140.0185730.12730.44961
150.0076830.05270.479107
160.0322350.2210.413028
170.0128220.08790.465164
18-0.139968-0.95960.171091
19-0.016667-0.11430.454758
20-0.083776-0.57430.284238
21-0.151237-1.03680.15256
22-0.144372-0.98980.163678
230.0874380.59940.275878
24-0.01898-0.13010.448514
25-0.135608-0.92970.178643
26-0.031756-0.21770.414299
27-0.10064-0.690.246808
28-0.072883-0.49970.309822
290.1379250.94560.174603
30-0.010628-0.07290.471112
310.0958310.6570.257197
320.0088580.06070.475917
330.0431610.29590.384306
34-0.016319-0.11190.455699
350.0971120.66580.254408
360.0328610.22530.411367



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