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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, 25 Nov 2009 11:52:43 -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/25/t1259175209fmha2kd1qp0de8s.htm/, Retrieved Mon, 06 May 2024 07:31:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59560, Retrieved Mon, 06 May 2024 07:31:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact229
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]
-    D        [(Partial) Autocorrelation Function] [ws8] [2009-11-24 20:12:27] [8b1aef4e7013bd33fbc2a5833375c5f5]
-    D            [(Partial) Autocorrelation Function] [SHw WS8] [2009-11-25 18:52:43] [d9efc2d105d810fc0b0ac636e31105d1] [Current]
- RMP               [Variance Reduction Matrix] [] [2009-12-11 17:08:26] [09f192433169b2c787c4a71fde86e883]
- RMP               [Spectral Analysis] [] [2009-12-11 17:10:53] [09f192433169b2c787c4a71fde86e883]
- RMP               [Univariate Data Series] [] [2009-12-11 17:23:55] [09f192433169b2c787c4a71fde86e883]
- RMPD              [Bivariate Granger Causality] [] [2009-12-11 18:06:37] [09f192433169b2c787c4a71fde86e883]
- RMPD              [Bivariate Granger Causality] [] [2009-12-11 18:09:47] [09f192433169b2c787c4a71fde86e883]
- RMPD              [Bivariate Granger Causality] [] [2009-12-11 18:26:06] [09f192433169b2c787c4a71fde86e883]
- RMPD                [Variance Reduction Matrix] [] [2009-12-17 11:59:50] [09f192433169b2c787c4a71fde86e883]
- RMPD                [Spectral Analysis] [] [2009-12-17 12:13:14] [09f192433169b2c787c4a71fde86e883]
- RMPD                [Spectral Analysis] [] [2009-12-17 12:14:53] [09f192433169b2c787c4a71fde86e883]
- RMPD                [Standard Deviation-Mean Plot] [] [2009-12-17 12:17:22] [09f192433169b2c787c4a71fde86e883]
- RMPD                [ARIMA Backward Selection] [] [2009-12-17 12:23:25] [09f192433169b2c787c4a71fde86e883]
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Dataseries X:
562
561
555
544
537
543
594
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




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59560&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]0 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=59560&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59560&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.893926.92430
20.731795.66840
30.6107984.73127e-06
40.5545714.29573.2e-05
50.5525614.28013.4e-05
60.5354364.14755.4e-05
70.466323.61210.000311
80.3876293.00260.00195
90.3620842.80470.003389
100.3868032.99620.001985
110.4459263.45410.000509
120.4555573.52870.000404
130.3211522.48760.007828
140.1587611.22980.111794
150.0411710.31890.375451
16-0.013558-0.1050.458357
17-0.023209-0.17980.428967
18-0.051066-0.39560.346919
19-0.12202-0.94520.174184
20-0.19054-1.47590.072598
21-0.210347-1.62930.05424
22-0.189554-1.46830.073625
23-0.148854-1.1530.126739
24-0.140767-1.09040.139954
25-0.229161-1.77510.040479
26-0.333023-2.57960.00618
27-0.391122-3.02960.001805
28-0.388616-3.01020.001908
29-0.357727-2.77090.003715
30-0.338851-2.62470.005492
31-0.354144-2.74320.004006
32-0.369624-2.86310.002885
33-0.352454-2.73010.004149
34-0.311301-2.41130.009486
35-0.255676-1.98050.026121
36-0.220464-1.70770.04643

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.89392 & 6.9243 & 0 \tabularnewline
2 & 0.73179 & 5.6684 & 0 \tabularnewline
3 & 0.610798 & 4.7312 & 7e-06 \tabularnewline
4 & 0.554571 & 4.2957 & 3.2e-05 \tabularnewline
5 & 0.552561 & 4.2801 & 3.4e-05 \tabularnewline
6 & 0.535436 & 4.1475 & 5.4e-05 \tabularnewline
7 & 0.46632 & 3.6121 & 0.000311 \tabularnewline
8 & 0.387629 & 3.0026 & 0.00195 \tabularnewline
9 & 0.362084 & 2.8047 & 0.003389 \tabularnewline
10 & 0.386803 & 2.9962 & 0.001985 \tabularnewline
11 & 0.445926 & 3.4541 & 0.000509 \tabularnewline
12 & 0.455557 & 3.5287 & 0.000404 \tabularnewline
13 & 0.321152 & 2.4876 & 0.007828 \tabularnewline
14 & 0.158761 & 1.2298 & 0.111794 \tabularnewline
15 & 0.041171 & 0.3189 & 0.375451 \tabularnewline
16 & -0.013558 & -0.105 & 0.458357 \tabularnewline
17 & -0.023209 & -0.1798 & 0.428967 \tabularnewline
18 & -0.051066 & -0.3956 & 0.346919 \tabularnewline
19 & -0.12202 & -0.9452 & 0.174184 \tabularnewline
20 & -0.19054 & -1.4759 & 0.072598 \tabularnewline
21 & -0.210347 & -1.6293 & 0.05424 \tabularnewline
22 & -0.189554 & -1.4683 & 0.073625 \tabularnewline
23 & -0.148854 & -1.153 & 0.126739 \tabularnewline
24 & -0.140767 & -1.0904 & 0.139954 \tabularnewline
25 & -0.229161 & -1.7751 & 0.040479 \tabularnewline
26 & -0.333023 & -2.5796 & 0.00618 \tabularnewline
27 & -0.391122 & -3.0296 & 0.001805 \tabularnewline
28 & -0.388616 & -3.0102 & 0.001908 \tabularnewline
29 & -0.357727 & -2.7709 & 0.003715 \tabularnewline
30 & -0.338851 & -2.6247 & 0.005492 \tabularnewline
31 & -0.354144 & -2.7432 & 0.004006 \tabularnewline
32 & -0.369624 & -2.8631 & 0.002885 \tabularnewline
33 & -0.352454 & -2.7301 & 0.004149 \tabularnewline
34 & -0.311301 & -2.4113 & 0.009486 \tabularnewline
35 & -0.255676 & -1.9805 & 0.026121 \tabularnewline
36 & -0.220464 & -1.7077 & 0.04643 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59560&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]0.89392[/C][C]6.9243[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.73179[/C][C]5.6684[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.610798[/C][C]4.7312[/C][C]7e-06[/C][/ROW]
[ROW][C]4[/C][C]0.554571[/C][C]4.2957[/C][C]3.2e-05[/C][/ROW]
[ROW][C]5[/C][C]0.552561[/C][C]4.2801[/C][C]3.4e-05[/C][/ROW]
[ROW][C]6[/C][C]0.535436[/C][C]4.1475[/C][C]5.4e-05[/C][/ROW]
[ROW][C]7[/C][C]0.46632[/C][C]3.6121[/C][C]0.000311[/C][/ROW]
[ROW][C]8[/C][C]0.387629[/C][C]3.0026[/C][C]0.00195[/C][/ROW]
[ROW][C]9[/C][C]0.362084[/C][C]2.8047[/C][C]0.003389[/C][/ROW]
[ROW][C]10[/C][C]0.386803[/C][C]2.9962[/C][C]0.001985[/C][/ROW]
[ROW][C]11[/C][C]0.445926[/C][C]3.4541[/C][C]0.000509[/C][/ROW]
[ROW][C]12[/C][C]0.455557[/C][C]3.5287[/C][C]0.000404[/C][/ROW]
[ROW][C]13[/C][C]0.321152[/C][C]2.4876[/C][C]0.007828[/C][/ROW]
[ROW][C]14[/C][C]0.158761[/C][C]1.2298[/C][C]0.111794[/C][/ROW]
[ROW][C]15[/C][C]0.041171[/C][C]0.3189[/C][C]0.375451[/C][/ROW]
[ROW][C]16[/C][C]-0.013558[/C][C]-0.105[/C][C]0.458357[/C][/ROW]
[ROW][C]17[/C][C]-0.023209[/C][C]-0.1798[/C][C]0.428967[/C][/ROW]
[ROW][C]18[/C][C]-0.051066[/C][C]-0.3956[/C][C]0.346919[/C][/ROW]
[ROW][C]19[/C][C]-0.12202[/C][C]-0.9452[/C][C]0.174184[/C][/ROW]
[ROW][C]20[/C][C]-0.19054[/C][C]-1.4759[/C][C]0.072598[/C][/ROW]
[ROW][C]21[/C][C]-0.210347[/C][C]-1.6293[/C][C]0.05424[/C][/ROW]
[ROW][C]22[/C][C]-0.189554[/C][C]-1.4683[/C][C]0.073625[/C][/ROW]
[ROW][C]23[/C][C]-0.148854[/C][C]-1.153[/C][C]0.126739[/C][/ROW]
[ROW][C]24[/C][C]-0.140767[/C][C]-1.0904[/C][C]0.139954[/C][/ROW]
[ROW][C]25[/C][C]-0.229161[/C][C]-1.7751[/C][C]0.040479[/C][/ROW]
[ROW][C]26[/C][C]-0.333023[/C][C]-2.5796[/C][C]0.00618[/C][/ROW]
[ROW][C]27[/C][C]-0.391122[/C][C]-3.0296[/C][C]0.001805[/C][/ROW]
[ROW][C]28[/C][C]-0.388616[/C][C]-3.0102[/C][C]0.001908[/C][/ROW]
[ROW][C]29[/C][C]-0.357727[/C][C]-2.7709[/C][C]0.003715[/C][/ROW]
[ROW][C]30[/C][C]-0.338851[/C][C]-2.6247[/C][C]0.005492[/C][/ROW]
[ROW][C]31[/C][C]-0.354144[/C][C]-2.7432[/C][C]0.004006[/C][/ROW]
[ROW][C]32[/C][C]-0.369624[/C][C]-2.8631[/C][C]0.002885[/C][/ROW]
[ROW][C]33[/C][C]-0.352454[/C][C]-2.7301[/C][C]0.004149[/C][/ROW]
[ROW][C]34[/C][C]-0.311301[/C][C]-2.4113[/C][C]0.009486[/C][/ROW]
[ROW][C]35[/C][C]-0.255676[/C][C]-1.9805[/C][C]0.026121[/C][/ROW]
[ROW][C]36[/C][C]-0.220464[/C][C]-1.7077[/C][C]0.04643[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59560&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59560&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
10.893926.92430
20.731795.66840
30.6107984.73127e-06
40.5545714.29573.2e-05
50.5525614.28013.4e-05
60.5354364.14755.4e-05
70.466323.61210.000311
80.3876293.00260.00195
90.3620842.80470.003389
100.3868032.99620.001985
110.4459263.45410.000509
120.4555573.52870.000404
130.3211522.48760.007828
140.1587611.22980.111794
150.0411710.31890.375451
16-0.013558-0.1050.458357
17-0.023209-0.17980.428967
18-0.051066-0.39560.346919
19-0.12202-0.94520.174184
20-0.19054-1.47590.072598
21-0.210347-1.62930.05424
22-0.189554-1.46830.073625
23-0.148854-1.1530.126739
24-0.140767-1.09040.139954
25-0.229161-1.77510.040479
26-0.333023-2.57960.00618
27-0.391122-3.02960.001805
28-0.388616-3.01020.001908
29-0.357727-2.77090.003715
30-0.338851-2.62470.005492
31-0.354144-2.74320.004006
32-0.369624-2.86310.002885
33-0.352454-2.73010.004149
34-0.311301-2.41130.009486
35-0.255676-1.98050.026121
36-0.220464-1.70770.04643







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.893926.92430
2-0.335002-2.59490.005938
30.2072011.6050.056875
40.1413921.09520.1389
50.1584231.22710.112281
6-0.134661-1.04310.150548
7-0.119095-0.92250.17998
80.0779780.6040.274054
90.2110261.63460.053685
100.0409860.31750.375991
110.1555351.20480.116512
12-0.204899-1.58710.058869
13-0.57561-4.45871.8e-05
140.1346041.04260.15065
15-0.073207-0.56710.286394
16-0.054918-0.42540.336035
17-0.042218-0.3270.372397
18-0.033647-0.26060.397637
190.0097070.07520.470158
200.0076310.05910.476531
21-0.043176-0.33440.369606
22-0.011526-0.08930.46458
23-0.086564-0.67050.25255
240.1266310.98090.165295
25-0.074152-0.57440.28393
26-0.052793-0.40890.342024
270.0575890.44610.328571
280.0482180.37350.355048
29-0.095854-0.74250.230345
300.1398541.08330.141503
31-0.035974-0.27870.390735
32-0.021058-0.16310.435488
33-0.073087-0.56610.286709
340.0004730.00370.498543
350.0502790.38950.349157
36-0.016709-0.12940.448728

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.89392 & 6.9243 & 0 \tabularnewline
2 & -0.335002 & -2.5949 & 0.005938 \tabularnewline
3 & 0.207201 & 1.605 & 0.056875 \tabularnewline
4 & 0.141392 & 1.0952 & 0.1389 \tabularnewline
5 & 0.158423 & 1.2271 & 0.112281 \tabularnewline
6 & -0.134661 & -1.0431 & 0.150548 \tabularnewline
7 & -0.119095 & -0.9225 & 0.17998 \tabularnewline
8 & 0.077978 & 0.604 & 0.274054 \tabularnewline
9 & 0.211026 & 1.6346 & 0.053685 \tabularnewline
10 & 0.040986 & 0.3175 & 0.375991 \tabularnewline
11 & 0.155535 & 1.2048 & 0.116512 \tabularnewline
12 & -0.204899 & -1.5871 & 0.058869 \tabularnewline
13 & -0.57561 & -4.4587 & 1.8e-05 \tabularnewline
14 & 0.134604 & 1.0426 & 0.15065 \tabularnewline
15 & -0.073207 & -0.5671 & 0.286394 \tabularnewline
16 & -0.054918 & -0.4254 & 0.336035 \tabularnewline
17 & -0.042218 & -0.327 & 0.372397 \tabularnewline
18 & -0.033647 & -0.2606 & 0.397637 \tabularnewline
19 & 0.009707 & 0.0752 & 0.470158 \tabularnewline
20 & 0.007631 & 0.0591 & 0.476531 \tabularnewline
21 & -0.043176 & -0.3344 & 0.369606 \tabularnewline
22 & -0.011526 & -0.0893 & 0.46458 \tabularnewline
23 & -0.086564 & -0.6705 & 0.25255 \tabularnewline
24 & 0.126631 & 0.9809 & 0.165295 \tabularnewline
25 & -0.074152 & -0.5744 & 0.28393 \tabularnewline
26 & -0.052793 & -0.4089 & 0.342024 \tabularnewline
27 & 0.057589 & 0.4461 & 0.328571 \tabularnewline
28 & 0.048218 & 0.3735 & 0.355048 \tabularnewline
29 & -0.095854 & -0.7425 & 0.230345 \tabularnewline
30 & 0.139854 & 1.0833 & 0.141503 \tabularnewline
31 & -0.035974 & -0.2787 & 0.390735 \tabularnewline
32 & -0.021058 & -0.1631 & 0.435488 \tabularnewline
33 & -0.073087 & -0.5661 & 0.286709 \tabularnewline
34 & 0.000473 & 0.0037 & 0.498543 \tabularnewline
35 & 0.050279 & 0.3895 & 0.349157 \tabularnewline
36 & -0.016709 & -0.1294 & 0.448728 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59560&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]0.89392[/C][C]6.9243[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.335002[/C][C]-2.5949[/C][C]0.005938[/C][/ROW]
[ROW][C]3[/C][C]0.207201[/C][C]1.605[/C][C]0.056875[/C][/ROW]
[ROW][C]4[/C][C]0.141392[/C][C]1.0952[/C][C]0.1389[/C][/ROW]
[ROW][C]5[/C][C]0.158423[/C][C]1.2271[/C][C]0.112281[/C][/ROW]
[ROW][C]6[/C][C]-0.134661[/C][C]-1.0431[/C][C]0.150548[/C][/ROW]
[ROW][C]7[/C][C]-0.119095[/C][C]-0.9225[/C][C]0.17998[/C][/ROW]
[ROW][C]8[/C][C]0.077978[/C][C]0.604[/C][C]0.274054[/C][/ROW]
[ROW][C]9[/C][C]0.211026[/C][C]1.6346[/C][C]0.053685[/C][/ROW]
[ROW][C]10[/C][C]0.040986[/C][C]0.3175[/C][C]0.375991[/C][/ROW]
[ROW][C]11[/C][C]0.155535[/C][C]1.2048[/C][C]0.116512[/C][/ROW]
[ROW][C]12[/C][C]-0.204899[/C][C]-1.5871[/C][C]0.058869[/C][/ROW]
[ROW][C]13[/C][C]-0.57561[/C][C]-4.4587[/C][C]1.8e-05[/C][/ROW]
[ROW][C]14[/C][C]0.134604[/C][C]1.0426[/C][C]0.15065[/C][/ROW]
[ROW][C]15[/C][C]-0.073207[/C][C]-0.5671[/C][C]0.286394[/C][/ROW]
[ROW][C]16[/C][C]-0.054918[/C][C]-0.4254[/C][C]0.336035[/C][/ROW]
[ROW][C]17[/C][C]-0.042218[/C][C]-0.327[/C][C]0.372397[/C][/ROW]
[ROW][C]18[/C][C]-0.033647[/C][C]-0.2606[/C][C]0.397637[/C][/ROW]
[ROW][C]19[/C][C]0.009707[/C][C]0.0752[/C][C]0.470158[/C][/ROW]
[ROW][C]20[/C][C]0.007631[/C][C]0.0591[/C][C]0.476531[/C][/ROW]
[ROW][C]21[/C][C]-0.043176[/C][C]-0.3344[/C][C]0.369606[/C][/ROW]
[ROW][C]22[/C][C]-0.011526[/C][C]-0.0893[/C][C]0.46458[/C][/ROW]
[ROW][C]23[/C][C]-0.086564[/C][C]-0.6705[/C][C]0.25255[/C][/ROW]
[ROW][C]24[/C][C]0.126631[/C][C]0.9809[/C][C]0.165295[/C][/ROW]
[ROW][C]25[/C][C]-0.074152[/C][C]-0.5744[/C][C]0.28393[/C][/ROW]
[ROW][C]26[/C][C]-0.052793[/C][C]-0.4089[/C][C]0.342024[/C][/ROW]
[ROW][C]27[/C][C]0.057589[/C][C]0.4461[/C][C]0.328571[/C][/ROW]
[ROW][C]28[/C][C]0.048218[/C][C]0.3735[/C][C]0.355048[/C][/ROW]
[ROW][C]29[/C][C]-0.095854[/C][C]-0.7425[/C][C]0.230345[/C][/ROW]
[ROW][C]30[/C][C]0.139854[/C][C]1.0833[/C][C]0.141503[/C][/ROW]
[ROW][C]31[/C][C]-0.035974[/C][C]-0.2787[/C][C]0.390735[/C][/ROW]
[ROW][C]32[/C][C]-0.021058[/C][C]-0.1631[/C][C]0.435488[/C][/ROW]
[ROW][C]33[/C][C]-0.073087[/C][C]-0.5661[/C][C]0.286709[/C][/ROW]
[ROW][C]34[/C][C]0.000473[/C][C]0.0037[/C][C]0.498543[/C][/ROW]
[ROW][C]35[/C][C]0.050279[/C][C]0.3895[/C][C]0.349157[/C][/ROW]
[ROW][C]36[/C][C]-0.016709[/C][C]-0.1294[/C][C]0.448728[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59560&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59560&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
10.893926.92430
2-0.335002-2.59490.005938
30.2072011.6050.056875
40.1413921.09520.1389
50.1584231.22710.112281
6-0.134661-1.04310.150548
7-0.119095-0.92250.17998
80.0779780.6040.274054
90.2110261.63460.053685
100.0409860.31750.375991
110.1555351.20480.116512
12-0.204899-1.58710.058869
13-0.57561-4.45871.8e-05
140.1346041.04260.15065
15-0.073207-0.56710.286394
16-0.054918-0.42540.336035
17-0.042218-0.3270.372397
18-0.033647-0.26060.397637
190.0097070.07520.470158
200.0076310.05910.476531
21-0.043176-0.33440.369606
22-0.011526-0.08930.46458
23-0.086564-0.67050.25255
240.1266310.98090.165295
25-0.074152-0.57440.28393
26-0.052793-0.40890.342024
270.0575890.44610.328571
280.0482180.37350.355048
29-0.095854-0.74250.230345
300.1398541.08330.141503
31-0.035974-0.27870.390735
32-0.021058-0.16310.435488
33-0.073087-0.56610.286709
340.0004730.00370.498543
350.0502790.38950.349157
36-0.016709-0.12940.448728



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')