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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 12:26:38 -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/t1259350043tmsx98tuku9i7p0.htm/, Retrieved Mon, 29 Apr 2024 04:30:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61169, Retrieved Mon, 29 Apr 2024 04:30:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact129

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 12:26:39] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [WS8-ACF3] [2009-11-25 18:58:26] [a94022e7c2399c0f4d62eea578db3411]
-    D            [(Partial) Autocorrelation Function] [WS8] [2009-11-27 19:26:38] [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=61169&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=61169&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61169&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
1-0.491217-3.36760.00076
20.2138411.4660.074651
30.1768051.21210.115763
4-0.148506-1.01810.15692
5-0.01443-0.09890.460809
60.2266831.55410.06344
7-0.355333-2.4360.009347
80.183631.25890.107141
90.072060.4940.311797
10-0.311265-2.13390.019048
110.2262171.55090.063821
12-0.126595-0.86790.194932
13-0.133983-0.91850.181513
140.1133170.77690.220565
15-0.032612-0.22360.412027
16-0.129673-0.8890.189266
170.1868831.28120.103204
18-0.157308-1.07840.143169
19-0.060818-0.41690.339308
200.157051.07670.14356
21-0.136766-0.93760.176616
22-0.069224-0.47460.318644
230.2957172.02730.02416
24-0.298978-2.04970.022999
250.2874871.97090.02732
26-0.086527-0.59320.277945
27-0.003568-0.02450.490295
280.0153170.1050.458407
290.0704560.4830.315661
30-0.152667-1.04660.150312
310.1558281.06830.14542
32-0.114134-0.78250.218933
330.0307390.21070.417001
340.0388460.26630.395581
35-0.125176-0.85820.197578
360.0528960.36260.359251

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.491217 & -3.3676 & 0.00076 \tabularnewline
2 & 0.213841 & 1.466 & 0.074651 \tabularnewline
3 & 0.176805 & 1.2121 & 0.115763 \tabularnewline
4 & -0.148506 & -1.0181 & 0.15692 \tabularnewline
5 & -0.01443 & -0.0989 & 0.460809 \tabularnewline
6 & 0.226683 & 1.5541 & 0.06344 \tabularnewline
7 & -0.355333 & -2.436 & 0.009347 \tabularnewline
8 & 0.18363 & 1.2589 & 0.107141 \tabularnewline
9 & 0.07206 & 0.494 & 0.311797 \tabularnewline
10 & -0.311265 & -2.1339 & 0.019048 \tabularnewline
11 & 0.226217 & 1.5509 & 0.063821 \tabularnewline
12 & -0.126595 & -0.8679 & 0.194932 \tabularnewline
13 & -0.133983 & -0.9185 & 0.181513 \tabularnewline
14 & 0.113317 & 0.7769 & 0.220565 \tabularnewline
15 & -0.032612 & -0.2236 & 0.412027 \tabularnewline
16 & -0.129673 & -0.889 & 0.189266 \tabularnewline
17 & 0.186883 & 1.2812 & 0.103204 \tabularnewline
18 & -0.157308 & -1.0784 & 0.143169 \tabularnewline
19 & -0.060818 & -0.4169 & 0.339308 \tabularnewline
20 & 0.15705 & 1.0767 & 0.14356 \tabularnewline
21 & -0.136766 & -0.9376 & 0.176616 \tabularnewline
22 & -0.069224 & -0.4746 & 0.318644 \tabularnewline
23 & 0.295717 & 2.0273 & 0.02416 \tabularnewline
24 & -0.298978 & -2.0497 & 0.022999 \tabularnewline
25 & 0.287487 & 1.9709 & 0.02732 \tabularnewline
26 & -0.086527 & -0.5932 & 0.277945 \tabularnewline
27 & -0.003568 & -0.0245 & 0.490295 \tabularnewline
28 & 0.015317 & 0.105 & 0.458407 \tabularnewline
29 & 0.070456 & 0.483 & 0.315661 \tabularnewline
30 & -0.152667 & -1.0466 & 0.150312 \tabularnewline
31 & 0.155828 & 1.0683 & 0.14542 \tabularnewline
32 & -0.114134 & -0.7825 & 0.218933 \tabularnewline
33 & 0.030739 & 0.2107 & 0.417001 \tabularnewline
34 & 0.038846 & 0.2663 & 0.395581 \tabularnewline
35 & -0.125176 & -0.8582 & 0.197578 \tabularnewline
36 & 0.052896 & 0.3626 & 0.359251 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61169&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]-0.491217[/C][C]-3.3676[/C][C]0.00076[/C][/ROW]
[ROW][C]2[/C][C]0.213841[/C][C]1.466[/C][C]0.074651[/C][/ROW]
[ROW][C]3[/C][C]0.176805[/C][C]1.2121[/C][C]0.115763[/C][/ROW]
[ROW][C]4[/C][C]-0.148506[/C][C]-1.0181[/C][C]0.15692[/C][/ROW]
[ROW][C]5[/C][C]-0.01443[/C][C]-0.0989[/C][C]0.460809[/C][/ROW]
[ROW][C]6[/C][C]0.226683[/C][C]1.5541[/C][C]0.06344[/C][/ROW]
[ROW][C]7[/C][C]-0.355333[/C][C]-2.436[/C][C]0.009347[/C][/ROW]
[ROW][C]8[/C][C]0.18363[/C][C]1.2589[/C][C]0.107141[/C][/ROW]
[ROW][C]9[/C][C]0.07206[/C][C]0.494[/C][C]0.311797[/C][/ROW]
[ROW][C]10[/C][C]-0.311265[/C][C]-2.1339[/C][C]0.019048[/C][/ROW]
[ROW][C]11[/C][C]0.226217[/C][C]1.5509[/C][C]0.063821[/C][/ROW]
[ROW][C]12[/C][C]-0.126595[/C][C]-0.8679[/C][C]0.194932[/C][/ROW]
[ROW][C]13[/C][C]-0.133983[/C][C]-0.9185[/C][C]0.181513[/C][/ROW]
[ROW][C]14[/C][C]0.113317[/C][C]0.7769[/C][C]0.220565[/C][/ROW]
[ROW][C]15[/C][C]-0.032612[/C][C]-0.2236[/C][C]0.412027[/C][/ROW]
[ROW][C]16[/C][C]-0.129673[/C][C]-0.889[/C][C]0.189266[/C][/ROW]
[ROW][C]17[/C][C]0.186883[/C][C]1.2812[/C][C]0.103204[/C][/ROW]
[ROW][C]18[/C][C]-0.157308[/C][C]-1.0784[/C][C]0.143169[/C][/ROW]
[ROW][C]19[/C][C]-0.060818[/C][C]-0.4169[/C][C]0.339308[/C][/ROW]
[ROW][C]20[/C][C]0.15705[/C][C]1.0767[/C][C]0.14356[/C][/ROW]
[ROW][C]21[/C][C]-0.136766[/C][C]-0.9376[/C][C]0.176616[/C][/ROW]
[ROW][C]22[/C][C]-0.069224[/C][C]-0.4746[/C][C]0.318644[/C][/ROW]
[ROW][C]23[/C][C]0.295717[/C][C]2.0273[/C][C]0.02416[/C][/ROW]
[ROW][C]24[/C][C]-0.298978[/C][C]-2.0497[/C][C]0.022999[/C][/ROW]
[ROW][C]25[/C][C]0.287487[/C][C]1.9709[/C][C]0.02732[/C][/ROW]
[ROW][C]26[/C][C]-0.086527[/C][C]-0.5932[/C][C]0.277945[/C][/ROW]
[ROW][C]27[/C][C]-0.003568[/C][C]-0.0245[/C][C]0.490295[/C][/ROW]
[ROW][C]28[/C][C]0.015317[/C][C]0.105[/C][C]0.458407[/C][/ROW]
[ROW][C]29[/C][C]0.070456[/C][C]0.483[/C][C]0.315661[/C][/ROW]
[ROW][C]30[/C][C]-0.152667[/C][C]-1.0466[/C][C]0.150312[/C][/ROW]
[ROW][C]31[/C][C]0.155828[/C][C]1.0683[/C][C]0.14542[/C][/ROW]
[ROW][C]32[/C][C]-0.114134[/C][C]-0.7825[/C][C]0.218933[/C][/ROW]
[ROW][C]33[/C][C]0.030739[/C][C]0.2107[/C][C]0.417001[/C][/ROW]
[ROW][C]34[/C][C]0.038846[/C][C]0.2663[/C][C]0.395581[/C][/ROW]
[ROW][C]35[/C][C]-0.125176[/C][C]-0.8582[/C][C]0.197578[/C][/ROW]
[ROW][C]36[/C][C]0.052896[/C][C]0.3626[/C][C]0.359251[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61169&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61169&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
1-0.491217-3.36760.00076
20.2138411.4660.074651
30.1768051.21210.115763
4-0.148506-1.01810.15692
5-0.01443-0.09890.460809
60.2266831.55410.06344
7-0.355333-2.4360.009347
80.183631.25890.107141
90.072060.4940.311797
10-0.311265-2.13390.019048
110.2262171.55090.063821
12-0.126595-0.86790.194932
13-0.133983-0.91850.181513
140.1133170.77690.220565
15-0.032612-0.22360.412027
16-0.129673-0.8890.189266
170.1868831.28120.103204
18-0.157308-1.07840.143169
19-0.060818-0.41690.339308
200.157051.07670.14356
21-0.136766-0.93760.176616
22-0.069224-0.47460.318644
230.2957172.02730.02416
24-0.298978-2.04970.022999
250.2874871.97090.02732
26-0.086527-0.59320.277945
27-0.003568-0.02450.490295
280.0153170.1050.458407
290.0704560.4830.315661
30-0.152667-1.04660.150312
310.1558281.06830.14542
32-0.114134-0.78250.218933
330.0307390.21070.417001
340.0388460.26630.395581
35-0.125176-0.85820.197578
360.0528960.36260.359251






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.491217-3.36760.00076
2-0.036184-0.24810.402582
30.353532.42370.009633
40.1238940.84940.199989
5-0.221768-1.52040.067559
60.1023380.70160.243196
7-0.150469-1.03160.153779
8-0.120762-0.82790.205956
90.1853431.27070.105053
10-0.117779-0.80750.211737
11-0.108756-0.74560.229813
12-0.098091-0.67250.252287
13-0.069251-0.47480.318578
14-0.080636-0.55280.291505
150.0822030.56360.287868
160.0663210.45470.325717
17-0.060693-0.41610.33962
18-0.088453-0.60640.273582
19-0.182617-1.2520.10839
20-0.031789-0.21790.414213
210.1162720.79710.214696
22-0.112433-0.77080.222341
230.179331.22940.112517
24-0.047274-0.32410.373653
250.1316130.90230.185751
26-0.108069-0.74090.231225
270.0201930.13840.445245
28-0.037327-0.25590.399572
29-0.091714-0.62880.266275
300.0768380.52680.300415
31-0.059138-0.40540.3435
32-0.095939-0.65770.256962
330.0756480.51860.303231
340.0088070.06040.476056
35-0.077319-0.53010.299278
36-0.082317-0.56430.287604

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.491217 & -3.3676 & 0.00076 \tabularnewline
2 & -0.036184 & -0.2481 & 0.402582 \tabularnewline
3 & 0.35353 & 2.4237 & 0.009633 \tabularnewline
4 & 0.123894 & 0.8494 & 0.199989 \tabularnewline
5 & -0.221768 & -1.5204 & 0.067559 \tabularnewline
6 & 0.102338 & 0.7016 & 0.243196 \tabularnewline
7 & -0.150469 & -1.0316 & 0.153779 \tabularnewline
8 & -0.120762 & -0.8279 & 0.205956 \tabularnewline
9 & 0.185343 & 1.2707 & 0.105053 \tabularnewline
10 & -0.117779 & -0.8075 & 0.211737 \tabularnewline
11 & -0.108756 & -0.7456 & 0.229813 \tabularnewline
12 & -0.098091 & -0.6725 & 0.252287 \tabularnewline
13 & -0.069251 & -0.4748 & 0.318578 \tabularnewline
14 & -0.080636 & -0.5528 & 0.291505 \tabularnewline
15 & 0.082203 & 0.5636 & 0.287868 \tabularnewline
16 & 0.066321 & 0.4547 & 0.325717 \tabularnewline
17 & -0.060693 & -0.4161 & 0.33962 \tabularnewline
18 & -0.088453 & -0.6064 & 0.273582 \tabularnewline
19 & -0.182617 & -1.252 & 0.10839 \tabularnewline
20 & -0.031789 & -0.2179 & 0.414213 \tabularnewline
21 & 0.116272 & 0.7971 & 0.214696 \tabularnewline
22 & -0.112433 & -0.7708 & 0.222341 \tabularnewline
23 & 0.17933 & 1.2294 & 0.112517 \tabularnewline
24 & -0.047274 & -0.3241 & 0.373653 \tabularnewline
25 & 0.131613 & 0.9023 & 0.185751 \tabularnewline
26 & -0.108069 & -0.7409 & 0.231225 \tabularnewline
27 & 0.020193 & 0.1384 & 0.445245 \tabularnewline
28 & -0.037327 & -0.2559 & 0.399572 \tabularnewline
29 & -0.091714 & -0.6288 & 0.266275 \tabularnewline
30 & 0.076838 & 0.5268 & 0.300415 \tabularnewline
31 & -0.059138 & -0.4054 & 0.3435 \tabularnewline
32 & -0.095939 & -0.6577 & 0.256962 \tabularnewline
33 & 0.075648 & 0.5186 & 0.303231 \tabularnewline
34 & 0.008807 & 0.0604 & 0.476056 \tabularnewline
35 & -0.077319 & -0.5301 & 0.299278 \tabularnewline
36 & -0.082317 & -0.5643 & 0.287604 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61169&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]-0.491217[/C][C]-3.3676[/C][C]0.00076[/C][/ROW]
[ROW][C]2[/C][C]-0.036184[/C][C]-0.2481[/C][C]0.402582[/C][/ROW]
[ROW][C]3[/C][C]0.35353[/C][C]2.4237[/C][C]0.009633[/C][/ROW]
[ROW][C]4[/C][C]0.123894[/C][C]0.8494[/C][C]0.199989[/C][/ROW]
[ROW][C]5[/C][C]-0.221768[/C][C]-1.5204[/C][C]0.067559[/C][/ROW]
[ROW][C]6[/C][C]0.102338[/C][C]0.7016[/C][C]0.243196[/C][/ROW]
[ROW][C]7[/C][C]-0.150469[/C][C]-1.0316[/C][C]0.153779[/C][/ROW]
[ROW][C]8[/C][C]-0.120762[/C][C]-0.8279[/C][C]0.205956[/C][/ROW]
[ROW][C]9[/C][C]0.185343[/C][C]1.2707[/C][C]0.105053[/C][/ROW]
[ROW][C]10[/C][C]-0.117779[/C][C]-0.8075[/C][C]0.211737[/C][/ROW]
[ROW][C]11[/C][C]-0.108756[/C][C]-0.7456[/C][C]0.229813[/C][/ROW]
[ROW][C]12[/C][C]-0.098091[/C][C]-0.6725[/C][C]0.252287[/C][/ROW]
[ROW][C]13[/C][C]-0.069251[/C][C]-0.4748[/C][C]0.318578[/C][/ROW]
[ROW][C]14[/C][C]-0.080636[/C][C]-0.5528[/C][C]0.291505[/C][/ROW]
[ROW][C]15[/C][C]0.082203[/C][C]0.5636[/C][C]0.287868[/C][/ROW]
[ROW][C]16[/C][C]0.066321[/C][C]0.4547[/C][C]0.325717[/C][/ROW]
[ROW][C]17[/C][C]-0.060693[/C][C]-0.4161[/C][C]0.33962[/C][/ROW]
[ROW][C]18[/C][C]-0.088453[/C][C]-0.6064[/C][C]0.273582[/C][/ROW]
[ROW][C]19[/C][C]-0.182617[/C][C]-1.252[/C][C]0.10839[/C][/ROW]
[ROW][C]20[/C][C]-0.031789[/C][C]-0.2179[/C][C]0.414213[/C][/ROW]
[ROW][C]21[/C][C]0.116272[/C][C]0.7971[/C][C]0.214696[/C][/ROW]
[ROW][C]22[/C][C]-0.112433[/C][C]-0.7708[/C][C]0.222341[/C][/ROW]
[ROW][C]23[/C][C]0.17933[/C][C]1.2294[/C][C]0.112517[/C][/ROW]
[ROW][C]24[/C][C]-0.047274[/C][C]-0.3241[/C][C]0.373653[/C][/ROW]
[ROW][C]25[/C][C]0.131613[/C][C]0.9023[/C][C]0.185751[/C][/ROW]
[ROW][C]26[/C][C]-0.108069[/C][C]-0.7409[/C][C]0.231225[/C][/ROW]
[ROW][C]27[/C][C]0.020193[/C][C]0.1384[/C][C]0.445245[/C][/ROW]
[ROW][C]28[/C][C]-0.037327[/C][C]-0.2559[/C][C]0.399572[/C][/ROW]
[ROW][C]29[/C][C]-0.091714[/C][C]-0.6288[/C][C]0.266275[/C][/ROW]
[ROW][C]30[/C][C]0.076838[/C][C]0.5268[/C][C]0.300415[/C][/ROW]
[ROW][C]31[/C][C]-0.059138[/C][C]-0.4054[/C][C]0.3435[/C][/ROW]
[ROW][C]32[/C][C]-0.095939[/C][C]-0.6577[/C][C]0.256962[/C][/ROW]
[ROW][C]33[/C][C]0.075648[/C][C]0.5186[/C][C]0.303231[/C][/ROW]
[ROW][C]34[/C][C]0.008807[/C][C]0.0604[/C][C]0.476056[/C][/ROW]
[ROW][C]35[/C][C]-0.077319[/C][C]-0.5301[/C][C]0.299278[/C][/ROW]
[ROW][C]36[/C][C]-0.082317[/C][C]-0.5643[/C][C]0.287604[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61169&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61169&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
1-0.491217-3.36760.00076
2-0.036184-0.24810.402582
30.353532.42370.009633
40.1238940.84940.199989
5-0.221768-1.52040.067559
60.1023380.70160.243196
7-0.150469-1.03160.153779
8-0.120762-0.82790.205956
90.1853431.27070.105053
10-0.117779-0.80750.211737
11-0.108756-0.74560.229813
12-0.098091-0.67250.252287
13-0.069251-0.47480.318578
14-0.080636-0.55280.291505
150.0822030.56360.287868
160.0663210.45470.325717
17-0.060693-0.41610.33962
18-0.088453-0.60640.273582
19-0.182617-1.2520.10839
20-0.031789-0.21790.414213
210.1162720.79710.214696
22-0.112433-0.77080.222341
230.179331.22940.112517
24-0.047274-0.32410.373653
250.1316130.90230.185751
26-0.108069-0.74090.231225
270.0201930.13840.445245
28-0.037327-0.25590.399572
29-0.091714-0.62880.266275
300.0768380.52680.300415
31-0.059138-0.40540.3435
32-0.095939-0.65770.256962
330.0756480.51860.303231
340.0088070.06040.476056
35-0.077319-0.53010.299278
36-0.082317-0.56430.287604


Figures (Output of Computation)

Input Parameters & R Code

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