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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 computationMon, 30 Nov 2009 13:36:49 -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/30/t1259613487wrdeprwyy0xmg1h.htm/, Retrieved Wed, 01 May 2024 16:43:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61889, Retrieved Wed, 01 May 2024 16:43:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
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] [W8] [2009-11-25 18:19:32] [315ba876df544ad397193b5931d5f354]
-    D          [(Partial) Autocorrelation Function] [ws8 1.1] [2009-11-27 16:22:27] [95cead3ebb75668735f848316249436a]
-   P             [(Partial) Autocorrelation Function] [ws8.2] [2009-11-27 16:33:59] [95cead3ebb75668735f848316249436a]
-                     [(Partial) Autocorrelation Function] [workshop 8 review] [2009-11-30 20:36:49] [6198946fb53eb5eb18db46bb758f7fde] [Current]
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Dataseries X:
2.05
2.11
2.09
2.05
2.08
2.06
2.06
2.08
2.07
2.06
2.07
2.06
2.09
2.07
2.09
2.28
2.33
2.35
2.52
2.63
2.58
2.70
2.81
2.97
3.04
3.28
3.33
3.50
3.56
3.57
3.69
3.82
3.79
3.96
4.06
4.05
4.03
3.94
4.02
3.88
4.02
4.03
4.09
3.99
4.01
4.01
4.19
4.30
4.27
3.82
3.15
2.49
1.81
1.26
1.06
0.84
0.78
0.70
0.36
0.35




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=61889&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=61889&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61889&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
10.9368247.25660
20.8480056.56860
30.7486095.79870
40.6362744.92863e-06
50.5167234.00258.7e-05
60.3985293.0870.00153
70.28072.17430.016819
80.1767931.36940.087984
90.0911680.70620.241403
100.0255710.19810.42183
11-0.017439-0.13510.446499
12-0.044787-0.34690.364934
13-0.070718-0.54780.292938
14-0.102283-0.79230.215658
15-0.14086-1.09110.139795
16-0.179391-1.38960.084899
17-0.217527-1.6850.048596
18-0.250663-1.94160.028441
19-0.281071-2.17720.016706
20-0.308424-2.3890.010027
21-0.337199-2.61190.005679
22-0.357533-2.76940.003731
23-0.375581-2.90920.002537
24-0.385714-2.98770.002034
25-0.389218-3.01490.001882
26-0.383709-2.97220.002125
27-0.375482-2.90850.002543
28-0.364563-2.82390.003215
29-0.34519-2.67380.004823
30-0.32552-2.52150.00718
31-0.303844-2.35360.010944
32-0.276156-2.13910.018253
33-0.246673-1.91070.030411
34-0.216412-1.67630.04944
35-0.181787-1.40810.082129
36-0.150377-1.16480.124351

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.936824 & 7.2566 & 0 \tabularnewline
2 & 0.848005 & 6.5686 & 0 \tabularnewline
3 & 0.748609 & 5.7987 & 0 \tabularnewline
4 & 0.636274 & 4.9286 & 3e-06 \tabularnewline
5 & 0.516723 & 4.0025 & 8.7e-05 \tabularnewline
6 & 0.398529 & 3.087 & 0.00153 \tabularnewline
7 & 0.2807 & 2.1743 & 0.016819 \tabularnewline
8 & 0.176793 & 1.3694 & 0.087984 \tabularnewline
9 & 0.091168 & 0.7062 & 0.241403 \tabularnewline
10 & 0.025571 & 0.1981 & 0.42183 \tabularnewline
11 & -0.017439 & -0.1351 & 0.446499 \tabularnewline
12 & -0.044787 & -0.3469 & 0.364934 \tabularnewline
13 & -0.070718 & -0.5478 & 0.292938 \tabularnewline
14 & -0.102283 & -0.7923 & 0.215658 \tabularnewline
15 & -0.14086 & -1.0911 & 0.139795 \tabularnewline
16 & -0.179391 & -1.3896 & 0.084899 \tabularnewline
17 & -0.217527 & -1.685 & 0.048596 \tabularnewline
18 & -0.250663 & -1.9416 & 0.028441 \tabularnewline
19 & -0.281071 & -2.1772 & 0.016706 \tabularnewline
20 & -0.308424 & -2.389 & 0.010027 \tabularnewline
21 & -0.337199 & -2.6119 & 0.005679 \tabularnewline
22 & -0.357533 & -2.7694 & 0.003731 \tabularnewline
23 & -0.375581 & -2.9092 & 0.002537 \tabularnewline
24 & -0.385714 & -2.9877 & 0.002034 \tabularnewline
25 & -0.389218 & -3.0149 & 0.001882 \tabularnewline
26 & -0.383709 & -2.9722 & 0.002125 \tabularnewline
27 & -0.375482 & -2.9085 & 0.002543 \tabularnewline
28 & -0.364563 & -2.8239 & 0.003215 \tabularnewline
29 & -0.34519 & -2.6738 & 0.004823 \tabularnewline
30 & -0.32552 & -2.5215 & 0.00718 \tabularnewline
31 & -0.303844 & -2.3536 & 0.010944 \tabularnewline
32 & -0.276156 & -2.1391 & 0.018253 \tabularnewline
33 & -0.246673 & -1.9107 & 0.030411 \tabularnewline
34 & -0.216412 & -1.6763 & 0.04944 \tabularnewline
35 & -0.181787 & -1.4081 & 0.082129 \tabularnewline
36 & -0.150377 & -1.1648 & 0.124351 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61889&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]0.936824[/C][C]7.2566[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.848005[/C][C]6.5686[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.748609[/C][C]5.7987[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.636274[/C][C]4.9286[/C][C]3e-06[/C][/ROW]
[ROW][C]5[/C][C]0.516723[/C][C]4.0025[/C][C]8.7e-05[/C][/ROW]
[ROW][C]6[/C][C]0.398529[/C][C]3.087[/C][C]0.00153[/C][/ROW]
[ROW][C]7[/C][C]0.2807[/C][C]2.1743[/C][C]0.016819[/C][/ROW]
[ROW][C]8[/C][C]0.176793[/C][C]1.3694[/C][C]0.087984[/C][/ROW]
[ROW][C]9[/C][C]0.091168[/C][C]0.7062[/C][C]0.241403[/C][/ROW]
[ROW][C]10[/C][C]0.025571[/C][C]0.1981[/C][C]0.42183[/C][/ROW]
[ROW][C]11[/C][C]-0.017439[/C][C]-0.1351[/C][C]0.446499[/C][/ROW]
[ROW][C]12[/C][C]-0.044787[/C][C]-0.3469[/C][C]0.364934[/C][/ROW]
[ROW][C]13[/C][C]-0.070718[/C][C]-0.5478[/C][C]0.292938[/C][/ROW]
[ROW][C]14[/C][C]-0.102283[/C][C]-0.7923[/C][C]0.215658[/C][/ROW]
[ROW][C]15[/C][C]-0.14086[/C][C]-1.0911[/C][C]0.139795[/C][/ROW]
[ROW][C]16[/C][C]-0.179391[/C][C]-1.3896[/C][C]0.084899[/C][/ROW]
[ROW][C]17[/C][C]-0.217527[/C][C]-1.685[/C][C]0.048596[/C][/ROW]
[ROW][C]18[/C][C]-0.250663[/C][C]-1.9416[/C][C]0.028441[/C][/ROW]
[ROW][C]19[/C][C]-0.281071[/C][C]-2.1772[/C][C]0.016706[/C][/ROW]
[ROW][C]20[/C][C]-0.308424[/C][C]-2.389[/C][C]0.010027[/C][/ROW]
[ROW][C]21[/C][C]-0.337199[/C][C]-2.6119[/C][C]0.005679[/C][/ROW]
[ROW][C]22[/C][C]-0.357533[/C][C]-2.7694[/C][C]0.003731[/C][/ROW]
[ROW][C]23[/C][C]-0.375581[/C][C]-2.9092[/C][C]0.002537[/C][/ROW]
[ROW][C]24[/C][C]-0.385714[/C][C]-2.9877[/C][C]0.002034[/C][/ROW]
[ROW][C]25[/C][C]-0.389218[/C][C]-3.0149[/C][C]0.001882[/C][/ROW]
[ROW][C]26[/C][C]-0.383709[/C][C]-2.9722[/C][C]0.002125[/C][/ROW]
[ROW][C]27[/C][C]-0.375482[/C][C]-2.9085[/C][C]0.002543[/C][/ROW]
[ROW][C]28[/C][C]-0.364563[/C][C]-2.8239[/C][C]0.003215[/C][/ROW]
[ROW][C]29[/C][C]-0.34519[/C][C]-2.6738[/C][C]0.004823[/C][/ROW]
[ROW][C]30[/C][C]-0.32552[/C][C]-2.5215[/C][C]0.00718[/C][/ROW]
[ROW][C]31[/C][C]-0.303844[/C][C]-2.3536[/C][C]0.010944[/C][/ROW]
[ROW][C]32[/C][C]-0.276156[/C][C]-2.1391[/C][C]0.018253[/C][/ROW]
[ROW][C]33[/C][C]-0.246673[/C][C]-1.9107[/C][C]0.030411[/C][/ROW]
[ROW][C]34[/C][C]-0.216412[/C][C]-1.6763[/C][C]0.04944[/C][/ROW]
[ROW][C]35[/C][C]-0.181787[/C][C]-1.4081[/C][C]0.082129[/C][/ROW]
[ROW][C]36[/C][C]-0.150377[/C][C]-1.1648[/C][C]0.124351[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61889&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61889&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
10.9368247.25660
20.8480056.56860
30.7486095.79870
40.6362744.92863e-06
50.5167234.00258.7e-05
60.3985293.0870.00153
70.28072.17430.016819
80.1767931.36940.087984
90.0911680.70620.241403
100.0255710.19810.42183
11-0.017439-0.13510.446499
12-0.044787-0.34690.364934
13-0.070718-0.54780.292938
14-0.102283-0.79230.215658
15-0.14086-1.09110.139795
16-0.179391-1.38960.084899
17-0.217527-1.6850.048596
18-0.250663-1.94160.028441
19-0.281071-2.17720.016706
20-0.308424-2.3890.010027
21-0.337199-2.61190.005679
22-0.357533-2.76940.003731
23-0.375581-2.90920.002537
24-0.385714-2.98770.002034
25-0.389218-3.01490.001882
26-0.383709-2.97220.002125
27-0.375482-2.90850.002543
28-0.364563-2.82390.003215
29-0.34519-2.67380.004823
30-0.32552-2.52150.00718
31-0.303844-2.35360.010944
32-0.276156-2.13910.018253
33-0.246673-1.91070.030411
34-0.216412-1.67630.04944
35-0.181787-1.40810.082129
36-0.150377-1.16480.124351







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9368247.25660
2-0.242198-1.87610.032757
3-0.09841-0.76230.22444
4-0.145466-1.12680.132163
5-0.097164-0.75260.227307
6-0.045864-0.35530.361819
7-0.080316-0.62210.268108
80.0360.27890.390658
90.0347730.26940.394291
100.0469330.36350.358738
110.0617390.47820.317113
12-0.00653-0.05060.479914
13-0.107395-0.83190.204387
14-0.14495-1.12280.133003
15-0.133493-1.0340.152635
16-0.04168-0.32290.373964
17-0.030064-0.23290.408326
180.035330.27370.392642
190.0078860.06110.475749
20-0.002885-0.02230.491122
21-0.081349-0.63010.265503
22-0.022388-0.17340.431455
23-0.119212-0.92340.179746
24-0.054153-0.41950.338187
25-0.056305-0.43610.332152
260.0152290.1180.453246
27-0.011593-0.08980.464373
28-0.006175-0.04780.481006
290.045020.34870.364258
30-0.072167-0.5590.289121
31-0.049554-0.38380.351225
32-0.027999-0.21690.414518
33-0.040692-0.31520.376851
34-0.019534-0.15130.440119
350.0287160.22240.412367
36-0.028496-0.22070.413026

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.936824 & 7.2566 & 0 \tabularnewline
2 & -0.242198 & -1.8761 & 0.032757 \tabularnewline
3 & -0.09841 & -0.7623 & 0.22444 \tabularnewline
4 & -0.145466 & -1.1268 & 0.132163 \tabularnewline
5 & -0.097164 & -0.7526 & 0.227307 \tabularnewline
6 & -0.045864 & -0.3553 & 0.361819 \tabularnewline
7 & -0.080316 & -0.6221 & 0.268108 \tabularnewline
8 & 0.036 & 0.2789 & 0.390658 \tabularnewline
9 & 0.034773 & 0.2694 & 0.394291 \tabularnewline
10 & 0.046933 & 0.3635 & 0.358738 \tabularnewline
11 & 0.061739 & 0.4782 & 0.317113 \tabularnewline
12 & -0.00653 & -0.0506 & 0.479914 \tabularnewline
13 & -0.107395 & -0.8319 & 0.204387 \tabularnewline
14 & -0.14495 & -1.1228 & 0.133003 \tabularnewline
15 & -0.133493 & -1.034 & 0.152635 \tabularnewline
16 & -0.04168 & -0.3229 & 0.373964 \tabularnewline
17 & -0.030064 & -0.2329 & 0.408326 \tabularnewline
18 & 0.03533 & 0.2737 & 0.392642 \tabularnewline
19 & 0.007886 & 0.0611 & 0.475749 \tabularnewline
20 & -0.002885 & -0.0223 & 0.491122 \tabularnewline
21 & -0.081349 & -0.6301 & 0.265503 \tabularnewline
22 & -0.022388 & -0.1734 & 0.431455 \tabularnewline
23 & -0.119212 & -0.9234 & 0.179746 \tabularnewline
24 & -0.054153 & -0.4195 & 0.338187 \tabularnewline
25 & -0.056305 & -0.4361 & 0.332152 \tabularnewline
26 & 0.015229 & 0.118 & 0.453246 \tabularnewline
27 & -0.011593 & -0.0898 & 0.464373 \tabularnewline
28 & -0.006175 & -0.0478 & 0.481006 \tabularnewline
29 & 0.04502 & 0.3487 & 0.364258 \tabularnewline
30 & -0.072167 & -0.559 & 0.289121 \tabularnewline
31 & -0.049554 & -0.3838 & 0.351225 \tabularnewline
32 & -0.027999 & -0.2169 & 0.414518 \tabularnewline
33 & -0.040692 & -0.3152 & 0.376851 \tabularnewline
34 & -0.019534 & -0.1513 & 0.440119 \tabularnewline
35 & 0.028716 & 0.2224 & 0.412367 \tabularnewline
36 & -0.028496 & -0.2207 & 0.413026 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61889&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]0.936824[/C][C]7.2566[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.242198[/C][C]-1.8761[/C][C]0.032757[/C][/ROW]
[ROW][C]3[/C][C]-0.09841[/C][C]-0.7623[/C][C]0.22444[/C][/ROW]
[ROW][C]4[/C][C]-0.145466[/C][C]-1.1268[/C][C]0.132163[/C][/ROW]
[ROW][C]5[/C][C]-0.097164[/C][C]-0.7526[/C][C]0.227307[/C][/ROW]
[ROW][C]6[/C][C]-0.045864[/C][C]-0.3553[/C][C]0.361819[/C][/ROW]
[ROW][C]7[/C][C]-0.080316[/C][C]-0.6221[/C][C]0.268108[/C][/ROW]
[ROW][C]8[/C][C]0.036[/C][C]0.2789[/C][C]0.390658[/C][/ROW]
[ROW][C]9[/C][C]0.034773[/C][C]0.2694[/C][C]0.394291[/C][/ROW]
[ROW][C]10[/C][C]0.046933[/C][C]0.3635[/C][C]0.358738[/C][/ROW]
[ROW][C]11[/C][C]0.061739[/C][C]0.4782[/C][C]0.317113[/C][/ROW]
[ROW][C]12[/C][C]-0.00653[/C][C]-0.0506[/C][C]0.479914[/C][/ROW]
[ROW][C]13[/C][C]-0.107395[/C][C]-0.8319[/C][C]0.204387[/C][/ROW]
[ROW][C]14[/C][C]-0.14495[/C][C]-1.1228[/C][C]0.133003[/C][/ROW]
[ROW][C]15[/C][C]-0.133493[/C][C]-1.034[/C][C]0.152635[/C][/ROW]
[ROW][C]16[/C][C]-0.04168[/C][C]-0.3229[/C][C]0.373964[/C][/ROW]
[ROW][C]17[/C][C]-0.030064[/C][C]-0.2329[/C][C]0.408326[/C][/ROW]
[ROW][C]18[/C][C]0.03533[/C][C]0.2737[/C][C]0.392642[/C][/ROW]
[ROW][C]19[/C][C]0.007886[/C][C]0.0611[/C][C]0.475749[/C][/ROW]
[ROW][C]20[/C][C]-0.002885[/C][C]-0.0223[/C][C]0.491122[/C][/ROW]
[ROW][C]21[/C][C]-0.081349[/C][C]-0.6301[/C][C]0.265503[/C][/ROW]
[ROW][C]22[/C][C]-0.022388[/C][C]-0.1734[/C][C]0.431455[/C][/ROW]
[ROW][C]23[/C][C]-0.119212[/C][C]-0.9234[/C][C]0.179746[/C][/ROW]
[ROW][C]24[/C][C]-0.054153[/C][C]-0.4195[/C][C]0.338187[/C][/ROW]
[ROW][C]25[/C][C]-0.056305[/C][C]-0.4361[/C][C]0.332152[/C][/ROW]
[ROW][C]26[/C][C]0.015229[/C][C]0.118[/C][C]0.453246[/C][/ROW]
[ROW][C]27[/C][C]-0.011593[/C][C]-0.0898[/C][C]0.464373[/C][/ROW]
[ROW][C]28[/C][C]-0.006175[/C][C]-0.0478[/C][C]0.481006[/C][/ROW]
[ROW][C]29[/C][C]0.04502[/C][C]0.3487[/C][C]0.364258[/C][/ROW]
[ROW][C]30[/C][C]-0.072167[/C][C]-0.559[/C][C]0.289121[/C][/ROW]
[ROW][C]31[/C][C]-0.049554[/C][C]-0.3838[/C][C]0.351225[/C][/ROW]
[ROW][C]32[/C][C]-0.027999[/C][C]-0.2169[/C][C]0.414518[/C][/ROW]
[ROW][C]33[/C][C]-0.040692[/C][C]-0.3152[/C][C]0.376851[/C][/ROW]
[ROW][C]34[/C][C]-0.019534[/C][C]-0.1513[/C][C]0.440119[/C][/ROW]
[ROW][C]35[/C][C]0.028716[/C][C]0.2224[/C][C]0.412367[/C][/ROW]
[ROW][C]36[/C][C]-0.028496[/C][C]-0.2207[/C][C]0.413026[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61889&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61889&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
10.9368247.25660
2-0.242198-1.87610.032757
3-0.09841-0.76230.22444
4-0.145466-1.12680.132163
5-0.097164-0.75260.227307
6-0.045864-0.35530.361819
7-0.080316-0.62210.268108
80.0360.27890.390658
90.0347730.26940.394291
100.0469330.36350.358738
110.0617390.47820.317113
12-0.00653-0.05060.479914
13-0.107395-0.83190.204387
14-0.14495-1.12280.133003
15-0.133493-1.0340.152635
16-0.04168-0.32290.373964
17-0.030064-0.23290.408326
180.035330.27370.392642
190.0078860.06110.475749
20-0.002885-0.02230.491122
21-0.081349-0.63010.265503
22-0.022388-0.17340.431455
23-0.119212-0.92340.179746
24-0.054153-0.41950.338187
25-0.056305-0.43610.332152
260.0152290.1180.453246
27-0.011593-0.08980.464373
28-0.006175-0.04780.481006
290.045020.34870.364258
30-0.072167-0.5590.289121
31-0.049554-0.38380.351225
32-0.027999-0.21690.414518
33-0.040692-0.31520.376851
34-0.019534-0.15130.440119
350.0287160.22240.412367
36-0.028496-0.22070.413026



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; 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')