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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 06:56:07 -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/t1259848667sjw490fam6rdc6k.htm/, Retrieved Thu, 28 Mar 2024 14:59:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62794, Retrieved Thu, 28 Mar 2024 14:59:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordssdws9
Estimated Impact141
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]
-   PD        [(Partial) Autocorrelation Function] [ACF (d=0, D=1)] [2009-11-27 10:14:21] [f7fc9270f813d017f9fa5b506fdc7682]
-   P             [(Partial) Autocorrelation Function] [] [2009-12-03 13:56:07] [2d672adbf8ae6977476cb9852ecac1a3] [Current]
- RMPD              [] [WS 9 review] [-0001-11-30 00:00:00] [830e13ac5e5ac1e5b21c6af0c149b21d]
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Dataseries X:
593530
610943
612613
611324
594167
595454
590865
589379
584428
573100
567456
569028
620735
628884
628232
612117
595404
597141
593408
590072
579799
574205
572775
572942
619567
625809
619916
587625
565742
557274
560576
548854
531673
525919
511038
498662
555362
564591
541657
527070
509846
514258
516922
507561
492622
490243
469357
477580
528379
533590
517945
506174
501866
516141
528222
532638
536322
536535
523597
536214
586570
596594
580523




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=62794&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=62794&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62794&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
10.9219686.58420
20.8399495.99840
30.7495245.35271e-06
40.6504494.64511.2e-05
50.5444593.88820.000147
60.4398913.14140.001399
70.3285132.34610.011449
80.235091.67890.049647
90.1508181.07710.143262
100.0702460.50170.309035
110.0005660.0040.498396
12-0.071704-0.51210.305406
13-0.135226-0.96570.169374
14-0.189174-1.3510.091334
15-0.254204-1.81540.037674
16-0.319426-2.28120.013374
17-0.360942-2.57760.00644
18-0.406372-2.90210.002731
19-0.447289-3.19430.001202
20-0.484285-3.45850.000553
21-0.512186-3.65770.000301
22-0.531133-3.7930.000198
23-0.527602-3.76780.000214
24-0.505896-3.61280.000346
25-0.458089-3.27140.000961
26-0.424454-3.03120.001911
27-0.367746-2.62620.005685
28-0.299855-2.14140.018521
29-0.239168-1.7080.046859
30-0.192897-1.37760.087177
31-0.140816-1.00560.159671
32-0.095857-0.68460.248361
33-0.052702-0.37640.354102
34-0.004407-0.03150.487507
350.0381630.27250.393154
360.0646950.4620.323018

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.921968 & 6.5842 & 0 \tabularnewline
2 & 0.839949 & 5.9984 & 0 \tabularnewline
3 & 0.749524 & 5.3527 & 1e-06 \tabularnewline
4 & 0.650449 & 4.6451 & 1.2e-05 \tabularnewline
5 & 0.544459 & 3.8882 & 0.000147 \tabularnewline
6 & 0.439891 & 3.1414 & 0.001399 \tabularnewline
7 & 0.328513 & 2.3461 & 0.011449 \tabularnewline
8 & 0.23509 & 1.6789 & 0.049647 \tabularnewline
9 & 0.150818 & 1.0771 & 0.143262 \tabularnewline
10 & 0.070246 & 0.5017 & 0.309035 \tabularnewline
11 & 0.000566 & 0.004 & 0.498396 \tabularnewline
12 & -0.071704 & -0.5121 & 0.305406 \tabularnewline
13 & -0.135226 & -0.9657 & 0.169374 \tabularnewline
14 & -0.189174 & -1.351 & 0.091334 \tabularnewline
15 & -0.254204 & -1.8154 & 0.037674 \tabularnewline
16 & -0.319426 & -2.2812 & 0.013374 \tabularnewline
17 & -0.360942 & -2.5776 & 0.00644 \tabularnewline
18 & -0.406372 & -2.9021 & 0.002731 \tabularnewline
19 & -0.447289 & -3.1943 & 0.001202 \tabularnewline
20 & -0.484285 & -3.4585 & 0.000553 \tabularnewline
21 & -0.512186 & -3.6577 & 0.000301 \tabularnewline
22 & -0.531133 & -3.793 & 0.000198 \tabularnewline
23 & -0.527602 & -3.7678 & 0.000214 \tabularnewline
24 & -0.505896 & -3.6128 & 0.000346 \tabularnewline
25 & -0.458089 & -3.2714 & 0.000961 \tabularnewline
26 & -0.424454 & -3.0312 & 0.001911 \tabularnewline
27 & -0.367746 & -2.6262 & 0.005685 \tabularnewline
28 & -0.299855 & -2.1414 & 0.018521 \tabularnewline
29 & -0.239168 & -1.708 & 0.046859 \tabularnewline
30 & -0.192897 & -1.3776 & 0.087177 \tabularnewline
31 & -0.140816 & -1.0056 & 0.159671 \tabularnewline
32 & -0.095857 & -0.6846 & 0.248361 \tabularnewline
33 & -0.052702 & -0.3764 & 0.354102 \tabularnewline
34 & -0.004407 & -0.0315 & 0.487507 \tabularnewline
35 & 0.038163 & 0.2725 & 0.393154 \tabularnewline
36 & 0.064695 & 0.462 & 0.323018 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62794&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]0.921968[/C][C]6.5842[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.839949[/C][C]5.9984[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.749524[/C][C]5.3527[/C][C]1e-06[/C][/ROW]
[ROW][C]4[/C][C]0.650449[/C][C]4.6451[/C][C]1.2e-05[/C][/ROW]
[ROW][C]5[/C][C]0.544459[/C][C]3.8882[/C][C]0.000147[/C][/ROW]
[ROW][C]6[/C][C]0.439891[/C][C]3.1414[/C][C]0.001399[/C][/ROW]
[ROW][C]7[/C][C]0.328513[/C][C]2.3461[/C][C]0.011449[/C][/ROW]
[ROW][C]8[/C][C]0.23509[/C][C]1.6789[/C][C]0.049647[/C][/ROW]
[ROW][C]9[/C][C]0.150818[/C][C]1.0771[/C][C]0.143262[/C][/ROW]
[ROW][C]10[/C][C]0.070246[/C][C]0.5017[/C][C]0.309035[/C][/ROW]
[ROW][C]11[/C][C]0.000566[/C][C]0.004[/C][C]0.498396[/C][/ROW]
[ROW][C]12[/C][C]-0.071704[/C][C]-0.5121[/C][C]0.305406[/C][/ROW]
[ROW][C]13[/C][C]-0.135226[/C][C]-0.9657[/C][C]0.169374[/C][/ROW]
[ROW][C]14[/C][C]-0.189174[/C][C]-1.351[/C][C]0.091334[/C][/ROW]
[ROW][C]15[/C][C]-0.254204[/C][C]-1.8154[/C][C]0.037674[/C][/ROW]
[ROW][C]16[/C][C]-0.319426[/C][C]-2.2812[/C][C]0.013374[/C][/ROW]
[ROW][C]17[/C][C]-0.360942[/C][C]-2.5776[/C][C]0.00644[/C][/ROW]
[ROW][C]18[/C][C]-0.406372[/C][C]-2.9021[/C][C]0.002731[/C][/ROW]
[ROW][C]19[/C][C]-0.447289[/C][C]-3.1943[/C][C]0.001202[/C][/ROW]
[ROW][C]20[/C][C]-0.484285[/C][C]-3.4585[/C][C]0.000553[/C][/ROW]
[ROW][C]21[/C][C]-0.512186[/C][C]-3.6577[/C][C]0.000301[/C][/ROW]
[ROW][C]22[/C][C]-0.531133[/C][C]-3.793[/C][C]0.000198[/C][/ROW]
[ROW][C]23[/C][C]-0.527602[/C][C]-3.7678[/C][C]0.000214[/C][/ROW]
[ROW][C]24[/C][C]-0.505896[/C][C]-3.6128[/C][C]0.000346[/C][/ROW]
[ROW][C]25[/C][C]-0.458089[/C][C]-3.2714[/C][C]0.000961[/C][/ROW]
[ROW][C]26[/C][C]-0.424454[/C][C]-3.0312[/C][C]0.001911[/C][/ROW]
[ROW][C]27[/C][C]-0.367746[/C][C]-2.6262[/C][C]0.005685[/C][/ROW]
[ROW][C]28[/C][C]-0.299855[/C][C]-2.1414[/C][C]0.018521[/C][/ROW]
[ROW][C]29[/C][C]-0.239168[/C][C]-1.708[/C][C]0.046859[/C][/ROW]
[ROW][C]30[/C][C]-0.192897[/C][C]-1.3776[/C][C]0.087177[/C][/ROW]
[ROW][C]31[/C][C]-0.140816[/C][C]-1.0056[/C][C]0.159671[/C][/ROW]
[ROW][C]32[/C][C]-0.095857[/C][C]-0.6846[/C][C]0.248361[/C][/ROW]
[ROW][C]33[/C][C]-0.052702[/C][C]-0.3764[/C][C]0.354102[/C][/ROW]
[ROW][C]34[/C][C]-0.004407[/C][C]-0.0315[/C][C]0.487507[/C][/ROW]
[ROW][C]35[/C][C]0.038163[/C][C]0.2725[/C][C]0.393154[/C][/ROW]
[ROW][C]36[/C][C]0.064695[/C][C]0.462[/C][C]0.323018[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62794&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62794&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
10.9219686.58420
20.8399495.99840
30.7495245.35271e-06
40.6504494.64511.2e-05
50.5444593.88820.000147
60.4398913.14140.001399
70.3285132.34610.011449
80.235091.67890.049647
90.1508181.07710.143262
100.0702460.50170.309035
110.0005660.0040.498396
12-0.071704-0.51210.305406
13-0.135226-0.96570.169374
14-0.189174-1.3510.091334
15-0.254204-1.81540.037674
16-0.319426-2.28120.013374
17-0.360942-2.57760.00644
18-0.406372-2.90210.002731
19-0.447289-3.19430.001202
20-0.484285-3.45850.000553
21-0.512186-3.65770.000301
22-0.531133-3.7930.000198
23-0.527602-3.76780.000214
24-0.505896-3.61280.000346
25-0.458089-3.27140.000961
26-0.424454-3.03120.001911
27-0.367746-2.62620.005685
28-0.299855-2.14140.018521
29-0.239168-1.7080.046859
30-0.192897-1.37760.087177
31-0.140816-1.00560.159671
32-0.095857-0.68460.248361
33-0.052702-0.37640.354102
34-0.004407-0.03150.487507
350.0381630.27250.393154
360.0646950.4620.323018







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9219686.58420
2-0.067186-0.47980.316708
3-0.100255-0.7160.238639
4-0.107967-0.7710.22212
5-0.103316-0.73780.232001
6-0.053614-0.38290.351699
7-0.114262-0.8160.209149
80.0445430.31810.375853
9-0.009791-0.06990.472264
10-0.055279-0.39480.347329
11-0.012956-0.09250.463322
12-0.111812-0.79850.214142
13-0.028043-0.20030.421034
14-0.030039-0.21450.415499
15-0.158981-1.13540.130767
16-0.091569-0.65390.258045
170.063390.45270.326344
18-0.098728-0.70510.24199
19-0.075763-0.54110.295412
20-0.083519-0.59640.276759
21-0.029585-0.21130.416755
22-0.053769-0.3840.351291
230.0337930.24130.405134
240.0727170.51930.302898
250.1080630.77170.221919
26-0.162922-1.16350.125021
270.0954950.6820.249173
280.0251380.17950.429121
29-0.069648-0.49740.310527
30-0.104751-0.74810.228927
310.0115360.08240.467331
32-0.000253-0.00180.499283
33-0.005669-0.04050.483933
340.0469960.33560.369266
350.0102210.0730.47105
36-0.1349-0.96340.169952

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.921968 & 6.5842 & 0 \tabularnewline
2 & -0.067186 & -0.4798 & 0.316708 \tabularnewline
3 & -0.100255 & -0.716 & 0.238639 \tabularnewline
4 & -0.107967 & -0.771 & 0.22212 \tabularnewline
5 & -0.103316 & -0.7378 & 0.232001 \tabularnewline
6 & -0.053614 & -0.3829 & 0.351699 \tabularnewline
7 & -0.114262 & -0.816 & 0.209149 \tabularnewline
8 & 0.044543 & 0.3181 & 0.375853 \tabularnewline
9 & -0.009791 & -0.0699 & 0.472264 \tabularnewline
10 & -0.055279 & -0.3948 & 0.347329 \tabularnewline
11 & -0.012956 & -0.0925 & 0.463322 \tabularnewline
12 & -0.111812 & -0.7985 & 0.214142 \tabularnewline
13 & -0.028043 & -0.2003 & 0.421034 \tabularnewline
14 & -0.030039 & -0.2145 & 0.415499 \tabularnewline
15 & -0.158981 & -1.1354 & 0.130767 \tabularnewline
16 & -0.091569 & -0.6539 & 0.258045 \tabularnewline
17 & 0.06339 & 0.4527 & 0.326344 \tabularnewline
18 & -0.098728 & -0.7051 & 0.24199 \tabularnewline
19 & -0.075763 & -0.5411 & 0.295412 \tabularnewline
20 & -0.083519 & -0.5964 & 0.276759 \tabularnewline
21 & -0.029585 & -0.2113 & 0.416755 \tabularnewline
22 & -0.053769 & -0.384 & 0.351291 \tabularnewline
23 & 0.033793 & 0.2413 & 0.405134 \tabularnewline
24 & 0.072717 & 0.5193 & 0.302898 \tabularnewline
25 & 0.108063 & 0.7717 & 0.221919 \tabularnewline
26 & -0.162922 & -1.1635 & 0.125021 \tabularnewline
27 & 0.095495 & 0.682 & 0.249173 \tabularnewline
28 & 0.025138 & 0.1795 & 0.429121 \tabularnewline
29 & -0.069648 & -0.4974 & 0.310527 \tabularnewline
30 & -0.104751 & -0.7481 & 0.228927 \tabularnewline
31 & 0.011536 & 0.0824 & 0.467331 \tabularnewline
32 & -0.000253 & -0.0018 & 0.499283 \tabularnewline
33 & -0.005669 & -0.0405 & 0.483933 \tabularnewline
34 & 0.046996 & 0.3356 & 0.369266 \tabularnewline
35 & 0.010221 & 0.073 & 0.47105 \tabularnewline
36 & -0.1349 & -0.9634 & 0.169952 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62794&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]0.921968[/C][C]6.5842[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.067186[/C][C]-0.4798[/C][C]0.316708[/C][/ROW]
[ROW][C]3[/C][C]-0.100255[/C][C]-0.716[/C][C]0.238639[/C][/ROW]
[ROW][C]4[/C][C]-0.107967[/C][C]-0.771[/C][C]0.22212[/C][/ROW]
[ROW][C]5[/C][C]-0.103316[/C][C]-0.7378[/C][C]0.232001[/C][/ROW]
[ROW][C]6[/C][C]-0.053614[/C][C]-0.3829[/C][C]0.351699[/C][/ROW]
[ROW][C]7[/C][C]-0.114262[/C][C]-0.816[/C][C]0.209149[/C][/ROW]
[ROW][C]8[/C][C]0.044543[/C][C]0.3181[/C][C]0.375853[/C][/ROW]
[ROW][C]9[/C][C]-0.009791[/C][C]-0.0699[/C][C]0.472264[/C][/ROW]
[ROW][C]10[/C][C]-0.055279[/C][C]-0.3948[/C][C]0.347329[/C][/ROW]
[ROW][C]11[/C][C]-0.012956[/C][C]-0.0925[/C][C]0.463322[/C][/ROW]
[ROW][C]12[/C][C]-0.111812[/C][C]-0.7985[/C][C]0.214142[/C][/ROW]
[ROW][C]13[/C][C]-0.028043[/C][C]-0.2003[/C][C]0.421034[/C][/ROW]
[ROW][C]14[/C][C]-0.030039[/C][C]-0.2145[/C][C]0.415499[/C][/ROW]
[ROW][C]15[/C][C]-0.158981[/C][C]-1.1354[/C][C]0.130767[/C][/ROW]
[ROW][C]16[/C][C]-0.091569[/C][C]-0.6539[/C][C]0.258045[/C][/ROW]
[ROW][C]17[/C][C]0.06339[/C][C]0.4527[/C][C]0.326344[/C][/ROW]
[ROW][C]18[/C][C]-0.098728[/C][C]-0.7051[/C][C]0.24199[/C][/ROW]
[ROW][C]19[/C][C]-0.075763[/C][C]-0.5411[/C][C]0.295412[/C][/ROW]
[ROW][C]20[/C][C]-0.083519[/C][C]-0.5964[/C][C]0.276759[/C][/ROW]
[ROW][C]21[/C][C]-0.029585[/C][C]-0.2113[/C][C]0.416755[/C][/ROW]
[ROW][C]22[/C][C]-0.053769[/C][C]-0.384[/C][C]0.351291[/C][/ROW]
[ROW][C]23[/C][C]0.033793[/C][C]0.2413[/C][C]0.405134[/C][/ROW]
[ROW][C]24[/C][C]0.072717[/C][C]0.5193[/C][C]0.302898[/C][/ROW]
[ROW][C]25[/C][C]0.108063[/C][C]0.7717[/C][C]0.221919[/C][/ROW]
[ROW][C]26[/C][C]-0.162922[/C][C]-1.1635[/C][C]0.125021[/C][/ROW]
[ROW][C]27[/C][C]0.095495[/C][C]0.682[/C][C]0.249173[/C][/ROW]
[ROW][C]28[/C][C]0.025138[/C][C]0.1795[/C][C]0.429121[/C][/ROW]
[ROW][C]29[/C][C]-0.069648[/C][C]-0.4974[/C][C]0.310527[/C][/ROW]
[ROW][C]30[/C][C]-0.104751[/C][C]-0.7481[/C][C]0.228927[/C][/ROW]
[ROW][C]31[/C][C]0.011536[/C][C]0.0824[/C][C]0.467331[/C][/ROW]
[ROW][C]32[/C][C]-0.000253[/C][C]-0.0018[/C][C]0.499283[/C][/ROW]
[ROW][C]33[/C][C]-0.005669[/C][C]-0.0405[/C][C]0.483933[/C][/ROW]
[ROW][C]34[/C][C]0.046996[/C][C]0.3356[/C][C]0.369266[/C][/ROW]
[ROW][C]35[/C][C]0.010221[/C][C]0.073[/C][C]0.47105[/C][/ROW]
[ROW][C]36[/C][C]-0.1349[/C][C]-0.9634[/C][C]0.169952[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62794&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62794&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
10.9219686.58420
2-0.067186-0.47980.316708
3-0.100255-0.7160.238639
4-0.107967-0.7710.22212
5-0.103316-0.73780.232001
6-0.053614-0.38290.351699
7-0.114262-0.8160.209149
80.0445430.31810.375853
9-0.009791-0.06990.472264
10-0.055279-0.39480.347329
11-0.012956-0.09250.463322
12-0.111812-0.79850.214142
13-0.028043-0.20030.421034
14-0.030039-0.21450.415499
15-0.158981-1.13540.130767
16-0.091569-0.65390.258045
170.063390.45270.326344
18-0.098728-0.70510.24199
19-0.075763-0.54110.295412
20-0.083519-0.59640.276759
21-0.029585-0.21130.416755
22-0.053769-0.3840.351291
230.0337930.24130.405134
240.0727170.51930.302898
250.1080630.77170.221919
26-0.162922-1.16350.125021
270.0954950.6820.249173
280.0251380.17950.429121
29-0.069648-0.49740.310527
30-0.104751-0.74810.228927
310.0115360.08240.467331
32-0.000253-0.00180.499283
33-0.005669-0.04050.483933
340.0469960.33560.369266
350.0102210.0730.47105
36-0.1349-0.96340.169952



Parameters (Session):
par1 = 36 ; par2 = 1.2 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1.2 ; 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')