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Description of Statistical Computation

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 computationFri, 27 Nov 2009 12:22:50 -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/27/t12593498101a3b0jdq419xf4i.htm/, Retrieved Sun, 28 Apr 2024 19:55:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61167, Retrieved Sun, 28 Apr 2024 19:55:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147

Tree of Dependent Computations

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 12:19:56] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [WS8-ACF2] [2009-11-25 18:52:28] [a94022e7c2399c0f4d62eea578db3411]
-    D            [(Partial) Autocorrelation Function] [WS8] [2009-11-27 19:22:50] [48076ccf082563ab8a2c81e57fdb5364] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10414,9
12476,8
12384,6
12266,7
12919,9
11497,3
12142
13919,4
12656,8
12034,1
13199,7
10881,3
11301,2
13643,9
12517
13981,1
14275,7
13435
13565,7
16216,3
12970
14079,9
14235
12213,4
12581
14130,4
14210,8
14378,5
13142,8
13714,7
13621,9
15379,8
13306,3
14391,2
14909,9
14025,4
12951,2
14344,3
16093,4
15413,6
14705,7
15972,8
16241,4
16626,4
17136,2
15622,9
18003,9
16136,1
14423,7
16789,4
16782,2
14133,8
12607
12004,5
12175,4
13268
12299,3
11800,6
13873,3
12269,6

Tables (Output of Computation)





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=61167&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=61167&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61167&T=0

As an alternative you can also use a QR Code:  
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
10.7967075.51971e-06
20.7415855.13793e-06
30.625124.3313.8e-05
40.4244642.94080.002513
50.2991952.07290.021787
60.1597331.10670.136978
7-0.051649-0.35780.361017
8-0.117107-0.81130.210588
9-0.220705-1.52910.066403
10-0.313747-2.17370.017346
11-0.269518-1.86730.033988
12-0.318154-2.20420.016168
13-0.313697-2.17340.017359
14-0.244122-1.69130.048629
15-0.251989-1.74580.043619
16-0.193239-1.33880.093471
17-0.140182-0.97120.168157
18-0.122857-0.85120.199448
19-0.061753-0.42780.335343
200.0075080.0520.479366
210.0123480.08550.466092
220.0775470.53730.296785
230.1292920.89580.187425
240.0849220.58840.279525
250.1681131.16470.124944
260.1362830.94420.174899
270.1183460.81990.208156
280.1026570.71120.240193
290.0547590.37940.353038
30-0.002144-0.01490.494105
31-0.00941-0.06520.474144
32-0.093583-0.64840.25992
33-0.1209-0.83760.203197
34-0.126622-0.87730.192357
35-0.176701-1.22420.113421
36-0.170483-1.18110.121684

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.796707 & 5.5197 & 1e-06 \tabularnewline
2 & 0.741585 & 5.1379 & 3e-06 \tabularnewline
3 & 0.62512 & 4.331 & 3.8e-05 \tabularnewline
4 & 0.424464 & 2.9408 & 0.002513 \tabularnewline
5 & 0.299195 & 2.0729 & 0.021787 \tabularnewline
6 & 0.159733 & 1.1067 & 0.136978 \tabularnewline
7 & -0.051649 & -0.3578 & 0.361017 \tabularnewline
8 & -0.117107 & -0.8113 & 0.210588 \tabularnewline
9 & -0.220705 & -1.5291 & 0.066403 \tabularnewline
10 & -0.313747 & -2.1737 & 0.017346 \tabularnewline
11 & -0.269518 & -1.8673 & 0.033988 \tabularnewline
12 & -0.318154 & -2.2042 & 0.016168 \tabularnewline
13 & -0.313697 & -2.1734 & 0.017359 \tabularnewline
14 & -0.244122 & -1.6913 & 0.048629 \tabularnewline
15 & -0.251989 & -1.7458 & 0.043619 \tabularnewline
16 & -0.193239 & -1.3388 & 0.093471 \tabularnewline
17 & -0.140182 & -0.9712 & 0.168157 \tabularnewline
18 & -0.122857 & -0.8512 & 0.199448 \tabularnewline
19 & -0.061753 & -0.4278 & 0.335343 \tabularnewline
20 & 0.007508 & 0.052 & 0.479366 \tabularnewline
21 & 0.012348 & 0.0855 & 0.466092 \tabularnewline
22 & 0.077547 & 0.5373 & 0.296785 \tabularnewline
23 & 0.129292 & 0.8958 & 0.187425 \tabularnewline
24 & 0.084922 & 0.5884 & 0.279525 \tabularnewline
25 & 0.168113 & 1.1647 & 0.124944 \tabularnewline
26 & 0.136283 & 0.9442 & 0.174899 \tabularnewline
27 & 0.118346 & 0.8199 & 0.208156 \tabularnewline
28 & 0.102657 & 0.7112 & 0.240193 \tabularnewline
29 & 0.054759 & 0.3794 & 0.353038 \tabularnewline
30 & -0.002144 & -0.0149 & 0.494105 \tabularnewline
31 & -0.00941 & -0.0652 & 0.474144 \tabularnewline
32 & -0.093583 & -0.6484 & 0.25992 \tabularnewline
33 & -0.1209 & -0.8376 & 0.203197 \tabularnewline
34 & -0.126622 & -0.8773 & 0.192357 \tabularnewline
35 & -0.176701 & -1.2242 & 0.113421 \tabularnewline
36 & -0.170483 & -1.1811 & 0.121684 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61167&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]0.796707[/C][C]5.5197[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.741585[/C][C]5.1379[/C][C]3e-06[/C][/ROW]
[ROW][C]3[/C][C]0.62512[/C][C]4.331[/C][C]3.8e-05[/C][/ROW]
[ROW][C]4[/C][C]0.424464[/C][C]2.9408[/C][C]0.002513[/C][/ROW]
[ROW][C]5[/C][C]0.299195[/C][C]2.0729[/C][C]0.021787[/C][/ROW]
[ROW][C]6[/C][C]0.159733[/C][C]1.1067[/C][C]0.136978[/C][/ROW]
[ROW][C]7[/C][C]-0.051649[/C][C]-0.3578[/C][C]0.361017[/C][/ROW]
[ROW][C]8[/C][C]-0.117107[/C][C]-0.8113[/C][C]0.210588[/C][/ROW]
[ROW][C]9[/C][C]-0.220705[/C][C]-1.5291[/C][C]0.066403[/C][/ROW]
[ROW][C]10[/C][C]-0.313747[/C][C]-2.1737[/C][C]0.017346[/C][/ROW]
[ROW][C]11[/C][C]-0.269518[/C][C]-1.8673[/C][C]0.033988[/C][/ROW]
[ROW][C]12[/C][C]-0.318154[/C][C]-2.2042[/C][C]0.016168[/C][/ROW]
[ROW][C]13[/C][C]-0.313697[/C][C]-2.1734[/C][C]0.017359[/C][/ROW]
[ROW][C]14[/C][C]-0.244122[/C][C]-1.6913[/C][C]0.048629[/C][/ROW]
[ROW][C]15[/C][C]-0.251989[/C][C]-1.7458[/C][C]0.043619[/C][/ROW]
[ROW][C]16[/C][C]-0.193239[/C][C]-1.3388[/C][C]0.093471[/C][/ROW]
[ROW][C]17[/C][C]-0.140182[/C][C]-0.9712[/C][C]0.168157[/C][/ROW]
[ROW][C]18[/C][C]-0.122857[/C][C]-0.8512[/C][C]0.199448[/C][/ROW]
[ROW][C]19[/C][C]-0.061753[/C][C]-0.4278[/C][C]0.335343[/C][/ROW]
[ROW][C]20[/C][C]0.007508[/C][C]0.052[/C][C]0.479366[/C][/ROW]
[ROW][C]21[/C][C]0.012348[/C][C]0.0855[/C][C]0.466092[/C][/ROW]
[ROW][C]22[/C][C]0.077547[/C][C]0.5373[/C][C]0.296785[/C][/ROW]
[ROW][C]23[/C][C]0.129292[/C][C]0.8958[/C][C]0.187425[/C][/ROW]
[ROW][C]24[/C][C]0.084922[/C][C]0.5884[/C][C]0.279525[/C][/ROW]
[ROW][C]25[/C][C]0.168113[/C][C]1.1647[/C][C]0.124944[/C][/ROW]
[ROW][C]26[/C][C]0.136283[/C][C]0.9442[/C][C]0.174899[/C][/ROW]
[ROW][C]27[/C][C]0.118346[/C][C]0.8199[/C][C]0.208156[/C][/ROW]
[ROW][C]28[/C][C]0.102657[/C][C]0.7112[/C][C]0.240193[/C][/ROW]
[ROW][C]29[/C][C]0.054759[/C][C]0.3794[/C][C]0.353038[/C][/ROW]
[ROW][C]30[/C][C]-0.002144[/C][C]-0.0149[/C][C]0.494105[/C][/ROW]
[ROW][C]31[/C][C]-0.00941[/C][C]-0.0652[/C][C]0.474144[/C][/ROW]
[ROW][C]32[/C][C]-0.093583[/C][C]-0.6484[/C][C]0.25992[/C][/ROW]
[ROW][C]33[/C][C]-0.1209[/C][C]-0.8376[/C][C]0.203197[/C][/ROW]
[ROW][C]34[/C][C]-0.126622[/C][C]-0.8773[/C][C]0.192357[/C][/ROW]
[ROW][C]35[/C][C]-0.176701[/C][C]-1.2242[/C][C]0.113421[/C][/ROW]
[ROW][C]36[/C][C]-0.170483[/C][C]-1.1811[/C][C]0.121684[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61167&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61167&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.7967075.51971e-06
20.7415855.13793e-06
30.625124.3313.8e-05
40.4244642.94080.002513
50.2991952.07290.021787
60.1597331.10670.136978
7-0.051649-0.35780.361017
8-0.117107-0.81130.210588
9-0.220705-1.52910.066403
10-0.313747-2.17370.017346
11-0.269518-1.86730.033988
12-0.318154-2.20420.016168
13-0.313697-2.17340.017359
14-0.244122-1.69130.048629
15-0.251989-1.74580.043619
16-0.193239-1.33880.093471
17-0.140182-0.97120.168157
18-0.122857-0.85120.199448
19-0.061753-0.42780.335343
200.0075080.0520.479366
210.0123480.08550.466092
220.0775470.53730.296785
230.1292920.89580.187425
240.0849220.58840.279525
250.1681131.16470.124944
260.1362830.94420.174899
270.1183460.81990.208156
280.1026570.71120.240193
290.0547590.37940.353038
30-0.002144-0.01490.494105
31-0.00941-0.06520.474144
32-0.093583-0.64840.25992
33-0.1209-0.83760.203197
34-0.126622-0.87730.192357
35-0.176701-1.22420.113421
36-0.170483-1.18110.121684






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7967075.51971e-06
20.2925162.02660.024139
3-0.077632-0.53790.296583
4-0.390401-2.70480.004715
5-0.107558-0.74520.229897
60.0194320.13460.446734
7-0.289353-2.00470.025327
80.0685680.47510.318451
90.0868020.60140.275208
10-0.071576-0.49590.311116
110.161841.12130.133877
12-0.079912-0.55360.291195
13-0.114687-0.79460.215385
140.0095880.06640.473657
15-0.040351-0.27960.390508
160.0007040.00490.498065
17-0.065511-0.45390.325982
180.0834010.57780.283044
190.0228680.15840.43739
200.0867110.60070.275416
21-0.012427-0.08610.465874
22-0.061495-0.42610.335988
230.1404110.97280.167765
24-0.236232-1.63670.054121
250.142980.99060.163426
26-0.03311-0.22940.409769
27-0.036953-0.2560.399515
28-0.098338-0.68130.249476
290.0023210.01610.493619
300.0555020.38450.351141
31-0.091343-0.63280.26492
32-0.009043-0.06260.475153
330.0079590.05510.478127
34-0.011398-0.0790.468694
350.0531750.36840.357093
36-0.132994-0.92140.180722

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.796707 & 5.5197 & 1e-06 \tabularnewline
2 & 0.292516 & 2.0266 & 0.024139 \tabularnewline
3 & -0.077632 & -0.5379 & 0.296583 \tabularnewline
4 & -0.390401 & -2.7048 & 0.004715 \tabularnewline
5 & -0.107558 & -0.7452 & 0.229897 \tabularnewline
6 & 0.019432 & 0.1346 & 0.446734 \tabularnewline
7 & -0.289353 & -2.0047 & 0.025327 \tabularnewline
8 & 0.068568 & 0.4751 & 0.318451 \tabularnewline
9 & 0.086802 & 0.6014 & 0.275208 \tabularnewline
10 & -0.071576 & -0.4959 & 0.311116 \tabularnewline
11 & 0.16184 & 1.1213 & 0.133877 \tabularnewline
12 & -0.079912 & -0.5536 & 0.291195 \tabularnewline
13 & -0.114687 & -0.7946 & 0.215385 \tabularnewline
14 & 0.009588 & 0.0664 & 0.473657 \tabularnewline
15 & -0.040351 & -0.2796 & 0.390508 \tabularnewline
16 & 0.000704 & 0.0049 & 0.498065 \tabularnewline
17 & -0.065511 & -0.4539 & 0.325982 \tabularnewline
18 & 0.083401 & 0.5778 & 0.283044 \tabularnewline
19 & 0.022868 & 0.1584 & 0.43739 \tabularnewline
20 & 0.086711 & 0.6007 & 0.275416 \tabularnewline
21 & -0.012427 & -0.0861 & 0.465874 \tabularnewline
22 & -0.061495 & -0.4261 & 0.335988 \tabularnewline
23 & 0.140411 & 0.9728 & 0.167765 \tabularnewline
24 & -0.236232 & -1.6367 & 0.054121 \tabularnewline
25 & 0.14298 & 0.9906 & 0.163426 \tabularnewline
26 & -0.03311 & -0.2294 & 0.409769 \tabularnewline
27 & -0.036953 & -0.256 & 0.399515 \tabularnewline
28 & -0.098338 & -0.6813 & 0.249476 \tabularnewline
29 & 0.002321 & 0.0161 & 0.493619 \tabularnewline
30 & 0.055502 & 0.3845 & 0.351141 \tabularnewline
31 & -0.091343 & -0.6328 & 0.26492 \tabularnewline
32 & -0.009043 & -0.0626 & 0.475153 \tabularnewline
33 & 0.007959 & 0.0551 & 0.478127 \tabularnewline
34 & -0.011398 & -0.079 & 0.468694 \tabularnewline
35 & 0.053175 & 0.3684 & 0.357093 \tabularnewline
36 & -0.132994 & -0.9214 & 0.180722 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61167&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]0.796707[/C][C]5.5197[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.292516[/C][C]2.0266[/C][C]0.024139[/C][/ROW]
[ROW][C]3[/C][C]-0.077632[/C][C]-0.5379[/C][C]0.296583[/C][/ROW]
[ROW][C]4[/C][C]-0.390401[/C][C]-2.7048[/C][C]0.004715[/C][/ROW]
[ROW][C]5[/C][C]-0.107558[/C][C]-0.7452[/C][C]0.229897[/C][/ROW]
[ROW][C]6[/C][C]0.019432[/C][C]0.1346[/C][C]0.446734[/C][/ROW]
[ROW][C]7[/C][C]-0.289353[/C][C]-2.0047[/C][C]0.025327[/C][/ROW]
[ROW][C]8[/C][C]0.068568[/C][C]0.4751[/C][C]0.318451[/C][/ROW]
[ROW][C]9[/C][C]0.086802[/C][C]0.6014[/C][C]0.275208[/C][/ROW]
[ROW][C]10[/C][C]-0.071576[/C][C]-0.4959[/C][C]0.311116[/C][/ROW]
[ROW][C]11[/C][C]0.16184[/C][C]1.1213[/C][C]0.133877[/C][/ROW]
[ROW][C]12[/C][C]-0.079912[/C][C]-0.5536[/C][C]0.291195[/C][/ROW]
[ROW][C]13[/C][C]-0.114687[/C][C]-0.7946[/C][C]0.215385[/C][/ROW]
[ROW][C]14[/C][C]0.009588[/C][C]0.0664[/C][C]0.473657[/C][/ROW]
[ROW][C]15[/C][C]-0.040351[/C][C]-0.2796[/C][C]0.390508[/C][/ROW]
[ROW][C]16[/C][C]0.000704[/C][C]0.0049[/C][C]0.498065[/C][/ROW]
[ROW][C]17[/C][C]-0.065511[/C][C]-0.4539[/C][C]0.325982[/C][/ROW]
[ROW][C]18[/C][C]0.083401[/C][C]0.5778[/C][C]0.283044[/C][/ROW]
[ROW][C]19[/C][C]0.022868[/C][C]0.1584[/C][C]0.43739[/C][/ROW]
[ROW][C]20[/C][C]0.086711[/C][C]0.6007[/C][C]0.275416[/C][/ROW]
[ROW][C]21[/C][C]-0.012427[/C][C]-0.0861[/C][C]0.465874[/C][/ROW]
[ROW][C]22[/C][C]-0.061495[/C][C]-0.4261[/C][C]0.335988[/C][/ROW]
[ROW][C]23[/C][C]0.140411[/C][C]0.9728[/C][C]0.167765[/C][/ROW]
[ROW][C]24[/C][C]-0.236232[/C][C]-1.6367[/C][C]0.054121[/C][/ROW]
[ROW][C]25[/C][C]0.14298[/C][C]0.9906[/C][C]0.163426[/C][/ROW]
[ROW][C]26[/C][C]-0.03311[/C][C]-0.2294[/C][C]0.409769[/C][/ROW]
[ROW][C]27[/C][C]-0.036953[/C][C]-0.256[/C][C]0.399515[/C][/ROW]
[ROW][C]28[/C][C]-0.098338[/C][C]-0.6813[/C][C]0.249476[/C][/ROW]
[ROW][C]29[/C][C]0.002321[/C][C]0.0161[/C][C]0.493619[/C][/ROW]
[ROW][C]30[/C][C]0.055502[/C][C]0.3845[/C][C]0.351141[/C][/ROW]
[ROW][C]31[/C][C]-0.091343[/C][C]-0.6328[/C][C]0.26492[/C][/ROW]
[ROW][C]32[/C][C]-0.009043[/C][C]-0.0626[/C][C]0.475153[/C][/ROW]
[ROW][C]33[/C][C]0.007959[/C][C]0.0551[/C][C]0.478127[/C][/ROW]
[ROW][C]34[/C][C]-0.011398[/C][C]-0.079[/C][C]0.468694[/C][/ROW]
[ROW][C]35[/C][C]0.053175[/C][C]0.3684[/C][C]0.357093[/C][/ROW]
[ROW][C]36[/C][C]-0.132994[/C][C]-0.9214[/C][C]0.180722[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61167&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61167&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7967075.51971e-06
20.2925162.02660.024139
3-0.077632-0.53790.296583
4-0.390401-2.70480.004715
5-0.107558-0.74520.229897
60.0194320.13460.446734
7-0.289353-2.00470.025327
80.0685680.47510.318451
90.0868020.60140.275208
10-0.071576-0.49590.311116
110.161841.12130.133877
12-0.079912-0.55360.291195
13-0.114687-0.79460.215385
140.0095880.06640.473657
15-0.040351-0.27960.390508
160.0007040.00490.498065
17-0.065511-0.45390.325982
180.0834010.57780.283044
190.0228680.15840.43739
200.0867110.60070.275416
21-0.012427-0.08610.465874
22-0.061495-0.42610.335988
230.1404110.97280.167765
24-0.236232-1.63670.054121
250.142980.99060.163426
26-0.03311-0.22940.409769
27-0.036953-0.2560.399515
28-0.098338-0.68130.249476
290.0023210.01610.493619
300.0555020.38450.351141
31-0.091343-0.63280.26492
32-0.009043-0.06260.475153
330.0079590.05510.478127
34-0.011398-0.0790.468694
350.0531750.36840.357093
36-0.132994-0.92140.180722


Figures (Output of Computation)

Input Parameters & R Code

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