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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 computationThu, 26 Nov 2009 14:14:29 -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/26/t1259270146y1ybsunwclvc5dc.htm/, Retrieved Mon, 29 Apr 2024 01:54:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60425, Retrieved Mon, 29 Apr 2024 01:54:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact122

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 12:16:10] [b98453cac15ba1066b407e146608df68]
-   PD        [(Partial) Autocorrelation Function] [WS8 d=1 D=1] [2009-11-25 16:19:15] [445b292c553470d9fed8bc2796fd3a00]
-   PD          [(Partial) Autocorrelation Function] [ws 8 d=2 D=1] [2009-11-25 21:12:55] [134dc66689e3d457a82860db6471d419]
-   P             [(Partial) Autocorrelation Function] [wsact d=2 D=0] [2009-11-25 22:00:58] [134dc66689e3d457a82860db6471d419]
-   PD                [(Partial) Autocorrelation Function] [WS8 ACF d=2 D=0] [2009-11-26 21:14:29] [17416e80e7873ecccac25c455c5f767e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
153,4
145
137,7
148,3
152,2
169,4
168,6
161,1
174,1
179
190,6
190
181,6
174,8
180,5
196,8
193,8
197
216,3
221,4
217,9
229,7
227,4
204,2
196,6
198,8
207,5
190,7
201,6
210,5
223,5
223,8
231,2
244
234,7
250,2
265,7
287,6
283,3
295,4
312,3
333,8
347,7
383,2
407,1
413,6
362,7
321,9
239,4
191
159,7
163,4
157,6
166,2
176,7
198,3
226,2
216,2
235,9
226,9

Tables (Output of Computation)





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=60425&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=60425&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60425&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.308281-2.34780.011159
20.1811971.380.086448
3-0.199232-1.51730.06731
40.1340361.02080.155796
5-0.248027-1.88890.031953
6-0.128053-0.97520.166749
70.0801040.61010.272104
8-0.047506-0.36180.359409
9-0.091371-0.69590.244648
10-0.064027-0.48760.31383
110.2265521.72540.044893
12-0.043449-0.33090.370958
13-0.077056-0.58680.279794
140.0647820.49340.311809
150.1467361.11750.134192
16-0.073457-0.55940.289012
17-0.062925-0.47920.316792
18-0.019699-0.150.440635
190.1090390.83040.204855
20-0.21455-1.6340.053841
210.131050.99810.1612
22-0.080116-0.61010.272074
230.1718711.30890.09786
24-0.209297-1.5940.05819
250.185411.4120.081641
260.0433210.32990.371324
27-0.021212-0.16150.436112
28-0.043075-0.32810.372028
29-0.041011-0.31230.377953
300.0921030.70140.242918
31-0.171572-1.30670.098244
320.0764750.58240.281273
33-0.061217-0.46620.321405
340.0524950.39980.34539
35-0.000999-0.00760.496979
360.0166220.12660.449852

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.308281 & -2.3478 & 0.011159 \tabularnewline
2 & 0.181197 & 1.38 & 0.086448 \tabularnewline
3 & -0.199232 & -1.5173 & 0.06731 \tabularnewline
4 & 0.134036 & 1.0208 & 0.155796 \tabularnewline
5 & -0.248027 & -1.8889 & 0.031953 \tabularnewline
6 & -0.128053 & -0.9752 & 0.166749 \tabularnewline
7 & 0.080104 & 0.6101 & 0.272104 \tabularnewline
8 & -0.047506 & -0.3618 & 0.359409 \tabularnewline
9 & -0.091371 & -0.6959 & 0.244648 \tabularnewline
10 & -0.064027 & -0.4876 & 0.31383 \tabularnewline
11 & 0.226552 & 1.7254 & 0.044893 \tabularnewline
12 & -0.043449 & -0.3309 & 0.370958 \tabularnewline
13 & -0.077056 & -0.5868 & 0.279794 \tabularnewline
14 & 0.064782 & 0.4934 & 0.311809 \tabularnewline
15 & 0.146736 & 1.1175 & 0.134192 \tabularnewline
16 & -0.073457 & -0.5594 & 0.289012 \tabularnewline
17 & -0.062925 & -0.4792 & 0.316792 \tabularnewline
18 & -0.019699 & -0.15 & 0.440635 \tabularnewline
19 & 0.109039 & 0.8304 & 0.204855 \tabularnewline
20 & -0.21455 & -1.634 & 0.053841 \tabularnewline
21 & 0.13105 & 0.9981 & 0.1612 \tabularnewline
22 & -0.080116 & -0.6101 & 0.272074 \tabularnewline
23 & 0.171871 & 1.3089 & 0.09786 \tabularnewline
24 & -0.209297 & -1.594 & 0.05819 \tabularnewline
25 & 0.18541 & 1.412 & 0.081641 \tabularnewline
26 & 0.043321 & 0.3299 & 0.371324 \tabularnewline
27 & -0.021212 & -0.1615 & 0.436112 \tabularnewline
28 & -0.043075 & -0.3281 & 0.372028 \tabularnewline
29 & -0.041011 & -0.3123 & 0.377953 \tabularnewline
30 & 0.092103 & 0.7014 & 0.242918 \tabularnewline
31 & -0.171572 & -1.3067 & 0.098244 \tabularnewline
32 & 0.076475 & 0.5824 & 0.281273 \tabularnewline
33 & -0.061217 & -0.4662 & 0.321405 \tabularnewline
34 & 0.052495 & 0.3998 & 0.34539 \tabularnewline
35 & -0.000999 & -0.0076 & 0.496979 \tabularnewline
36 & 0.016622 & 0.1266 & 0.449852 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60425&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]-0.308281[/C][C]-2.3478[/C][C]0.011159[/C][/ROW]
[ROW][C]2[/C][C]0.181197[/C][C]1.38[/C][C]0.086448[/C][/ROW]
[ROW][C]3[/C][C]-0.199232[/C][C]-1.5173[/C][C]0.06731[/C][/ROW]
[ROW][C]4[/C][C]0.134036[/C][C]1.0208[/C][C]0.155796[/C][/ROW]
[ROW][C]5[/C][C]-0.248027[/C][C]-1.8889[/C][C]0.031953[/C][/ROW]
[ROW][C]6[/C][C]-0.128053[/C][C]-0.9752[/C][C]0.166749[/C][/ROW]
[ROW][C]7[/C][C]0.080104[/C][C]0.6101[/C][C]0.272104[/C][/ROW]
[ROW][C]8[/C][C]-0.047506[/C][C]-0.3618[/C][C]0.359409[/C][/ROW]
[ROW][C]9[/C][C]-0.091371[/C][C]-0.6959[/C][C]0.244648[/C][/ROW]
[ROW][C]10[/C][C]-0.064027[/C][C]-0.4876[/C][C]0.31383[/C][/ROW]
[ROW][C]11[/C][C]0.226552[/C][C]1.7254[/C][C]0.044893[/C][/ROW]
[ROW][C]12[/C][C]-0.043449[/C][C]-0.3309[/C][C]0.370958[/C][/ROW]
[ROW][C]13[/C][C]-0.077056[/C][C]-0.5868[/C][C]0.279794[/C][/ROW]
[ROW][C]14[/C][C]0.064782[/C][C]0.4934[/C][C]0.311809[/C][/ROW]
[ROW][C]15[/C][C]0.146736[/C][C]1.1175[/C][C]0.134192[/C][/ROW]
[ROW][C]16[/C][C]-0.073457[/C][C]-0.5594[/C][C]0.289012[/C][/ROW]
[ROW][C]17[/C][C]-0.062925[/C][C]-0.4792[/C][C]0.316792[/C][/ROW]
[ROW][C]18[/C][C]-0.019699[/C][C]-0.15[/C][C]0.440635[/C][/ROW]
[ROW][C]19[/C][C]0.109039[/C][C]0.8304[/C][C]0.204855[/C][/ROW]
[ROW][C]20[/C][C]-0.21455[/C][C]-1.634[/C][C]0.053841[/C][/ROW]
[ROW][C]21[/C][C]0.13105[/C][C]0.9981[/C][C]0.1612[/C][/ROW]
[ROW][C]22[/C][C]-0.080116[/C][C]-0.6101[/C][C]0.272074[/C][/ROW]
[ROW][C]23[/C][C]0.171871[/C][C]1.3089[/C][C]0.09786[/C][/ROW]
[ROW][C]24[/C][C]-0.209297[/C][C]-1.594[/C][C]0.05819[/C][/ROW]
[ROW][C]25[/C][C]0.18541[/C][C]1.412[/C][C]0.081641[/C][/ROW]
[ROW][C]26[/C][C]0.043321[/C][C]0.3299[/C][C]0.371324[/C][/ROW]
[ROW][C]27[/C][C]-0.021212[/C][C]-0.1615[/C][C]0.436112[/C][/ROW]
[ROW][C]28[/C][C]-0.043075[/C][C]-0.3281[/C][C]0.372028[/C][/ROW]
[ROW][C]29[/C][C]-0.041011[/C][C]-0.3123[/C][C]0.377953[/C][/ROW]
[ROW][C]30[/C][C]0.092103[/C][C]0.7014[/C][C]0.242918[/C][/ROW]
[ROW][C]31[/C][C]-0.171572[/C][C]-1.3067[/C][C]0.098244[/C][/ROW]
[ROW][C]32[/C][C]0.076475[/C][C]0.5824[/C][C]0.281273[/C][/ROW]
[ROW][C]33[/C][C]-0.061217[/C][C]-0.4662[/C][C]0.321405[/C][/ROW]
[ROW][C]34[/C][C]0.052495[/C][C]0.3998[/C][C]0.34539[/C][/ROW]
[ROW][C]35[/C][C]-0.000999[/C][C]-0.0076[/C][C]0.496979[/C][/ROW]
[ROW][C]36[/C][C]0.016622[/C][C]0.1266[/C][C]0.449852[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60425&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60425&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
1-0.308281-2.34780.011159
20.1811971.380.086448
3-0.199232-1.51730.06731
40.1340361.02080.155796
5-0.248027-1.88890.031953
6-0.128053-0.97520.166749
70.0801040.61010.272104
8-0.047506-0.36180.359409
9-0.091371-0.69590.244648
10-0.064027-0.48760.31383
110.2265521.72540.044893
12-0.043449-0.33090.370958
13-0.077056-0.58680.279794
140.0647820.49340.311809
150.1467361.11750.134192
16-0.073457-0.55940.289012
17-0.062925-0.47920.316792
18-0.019699-0.150.440635
190.1090390.83040.204855
20-0.21455-1.6340.053841
210.131050.99810.1612
22-0.080116-0.61010.272074
230.1718711.30890.09786
24-0.209297-1.5940.05819
250.185411.4120.081641
260.0433210.32990.371324
27-0.021212-0.16150.436112
28-0.043075-0.32810.372028
29-0.041011-0.31230.377953
300.0921030.70140.242918
31-0.171572-1.30670.098244
320.0764750.58240.281273
33-0.061217-0.46620.321405
340.0524950.39980.34539
35-0.000999-0.00760.496979
360.0166220.12660.449852






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.308281-2.34780.011159
20.0952090.72510.235657
3-0.133079-1.01350.157515
40.0334180.25450.400002
5-0.192005-1.46230.074533
6-0.323863-2.46650.008311
70.019620.14940.440869
8-0.061226-0.46630.321381
9-0.22919-1.74550.0431
10-0.212343-1.61720.055636
110.0510430.38870.349448
12-0.015743-0.11990.45249
13-0.225997-1.72110.045278
14-0.108751-0.82820.205471
150.0693010.52780.299833
16-0.019469-0.14830.441321
17-0.105306-0.8020.212918
18-0.220419-1.67870.049299
190.016260.12380.450938
20-0.090054-0.68580.247776
210.0028180.02150.491475
22-0.202774-1.54430.06398
23-0.029237-0.22270.412291
24-0.030228-0.23020.409369
250.0068120.05190.479402
260.0217940.1660.434376
27-0.080023-0.60940.272306
280.0303650.23130.408966
29-0.029418-0.2240.411756
30-0.016021-0.1220.451655
31-0.046732-0.35590.361604
320.0246720.18790.425807
33-0.009038-0.06880.472681
34-0.069234-0.52730.30001
350.1307280.99560.161791
360.025470.1940.423436

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.308281 & -2.3478 & 0.011159 \tabularnewline
2 & 0.095209 & 0.7251 & 0.235657 \tabularnewline
3 & -0.133079 & -1.0135 & 0.157515 \tabularnewline
4 & 0.033418 & 0.2545 & 0.400002 \tabularnewline
5 & -0.192005 & -1.4623 & 0.074533 \tabularnewline
6 & -0.323863 & -2.4665 & 0.008311 \tabularnewline
7 & 0.01962 & 0.1494 & 0.440869 \tabularnewline
8 & -0.061226 & -0.4663 & 0.321381 \tabularnewline
9 & -0.22919 & -1.7455 & 0.0431 \tabularnewline
10 & -0.212343 & -1.6172 & 0.055636 \tabularnewline
11 & 0.051043 & 0.3887 & 0.349448 \tabularnewline
12 & -0.015743 & -0.1199 & 0.45249 \tabularnewline
13 & -0.225997 & -1.7211 & 0.045278 \tabularnewline
14 & -0.108751 & -0.8282 & 0.205471 \tabularnewline
15 & 0.069301 & 0.5278 & 0.299833 \tabularnewline
16 & -0.019469 & -0.1483 & 0.441321 \tabularnewline
17 & -0.105306 & -0.802 & 0.212918 \tabularnewline
18 & -0.220419 & -1.6787 & 0.049299 \tabularnewline
19 & 0.01626 & 0.1238 & 0.450938 \tabularnewline
20 & -0.090054 & -0.6858 & 0.247776 \tabularnewline
21 & 0.002818 & 0.0215 & 0.491475 \tabularnewline
22 & -0.202774 & -1.5443 & 0.06398 \tabularnewline
23 & -0.029237 & -0.2227 & 0.412291 \tabularnewline
24 & -0.030228 & -0.2302 & 0.409369 \tabularnewline
25 & 0.006812 & 0.0519 & 0.479402 \tabularnewline
26 & 0.021794 & 0.166 & 0.434376 \tabularnewline
27 & -0.080023 & -0.6094 & 0.272306 \tabularnewline
28 & 0.030365 & 0.2313 & 0.408966 \tabularnewline
29 & -0.029418 & -0.224 & 0.411756 \tabularnewline
30 & -0.016021 & -0.122 & 0.451655 \tabularnewline
31 & -0.046732 & -0.3559 & 0.361604 \tabularnewline
32 & 0.024672 & 0.1879 & 0.425807 \tabularnewline
33 & -0.009038 & -0.0688 & 0.472681 \tabularnewline
34 & -0.069234 & -0.5273 & 0.30001 \tabularnewline
35 & 0.130728 & 0.9956 & 0.161791 \tabularnewline
36 & 0.02547 & 0.194 & 0.423436 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60425&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]-0.308281[/C][C]-2.3478[/C][C]0.011159[/C][/ROW]
[ROW][C]2[/C][C]0.095209[/C][C]0.7251[/C][C]0.235657[/C][/ROW]
[ROW][C]3[/C][C]-0.133079[/C][C]-1.0135[/C][C]0.157515[/C][/ROW]
[ROW][C]4[/C][C]0.033418[/C][C]0.2545[/C][C]0.400002[/C][/ROW]
[ROW][C]5[/C][C]-0.192005[/C][C]-1.4623[/C][C]0.074533[/C][/ROW]
[ROW][C]6[/C][C]-0.323863[/C][C]-2.4665[/C][C]0.008311[/C][/ROW]
[ROW][C]7[/C][C]0.01962[/C][C]0.1494[/C][C]0.440869[/C][/ROW]
[ROW][C]8[/C][C]-0.061226[/C][C]-0.4663[/C][C]0.321381[/C][/ROW]
[ROW][C]9[/C][C]-0.22919[/C][C]-1.7455[/C][C]0.0431[/C][/ROW]
[ROW][C]10[/C][C]-0.212343[/C][C]-1.6172[/C][C]0.055636[/C][/ROW]
[ROW][C]11[/C][C]0.051043[/C][C]0.3887[/C][C]0.349448[/C][/ROW]
[ROW][C]12[/C][C]-0.015743[/C][C]-0.1199[/C][C]0.45249[/C][/ROW]
[ROW][C]13[/C][C]-0.225997[/C][C]-1.7211[/C][C]0.045278[/C][/ROW]
[ROW][C]14[/C][C]-0.108751[/C][C]-0.8282[/C][C]0.205471[/C][/ROW]
[ROW][C]15[/C][C]0.069301[/C][C]0.5278[/C][C]0.299833[/C][/ROW]
[ROW][C]16[/C][C]-0.019469[/C][C]-0.1483[/C][C]0.441321[/C][/ROW]
[ROW][C]17[/C][C]-0.105306[/C][C]-0.802[/C][C]0.212918[/C][/ROW]
[ROW][C]18[/C][C]-0.220419[/C][C]-1.6787[/C][C]0.049299[/C][/ROW]
[ROW][C]19[/C][C]0.01626[/C][C]0.1238[/C][C]0.450938[/C][/ROW]
[ROW][C]20[/C][C]-0.090054[/C][C]-0.6858[/C][C]0.247776[/C][/ROW]
[ROW][C]21[/C][C]0.002818[/C][C]0.0215[/C][C]0.491475[/C][/ROW]
[ROW][C]22[/C][C]-0.202774[/C][C]-1.5443[/C][C]0.06398[/C][/ROW]
[ROW][C]23[/C][C]-0.029237[/C][C]-0.2227[/C][C]0.412291[/C][/ROW]
[ROW][C]24[/C][C]-0.030228[/C][C]-0.2302[/C][C]0.409369[/C][/ROW]
[ROW][C]25[/C][C]0.006812[/C][C]0.0519[/C][C]0.479402[/C][/ROW]
[ROW][C]26[/C][C]0.021794[/C][C]0.166[/C][C]0.434376[/C][/ROW]
[ROW][C]27[/C][C]-0.080023[/C][C]-0.6094[/C][C]0.272306[/C][/ROW]
[ROW][C]28[/C][C]0.030365[/C][C]0.2313[/C][C]0.408966[/C][/ROW]
[ROW][C]29[/C][C]-0.029418[/C][C]-0.224[/C][C]0.411756[/C][/ROW]
[ROW][C]30[/C][C]-0.016021[/C][C]-0.122[/C][C]0.451655[/C][/ROW]
[ROW][C]31[/C][C]-0.046732[/C][C]-0.3559[/C][C]0.361604[/C][/ROW]
[ROW][C]32[/C][C]0.024672[/C][C]0.1879[/C][C]0.425807[/C][/ROW]
[ROW][C]33[/C][C]-0.009038[/C][C]-0.0688[/C][C]0.472681[/C][/ROW]
[ROW][C]34[/C][C]-0.069234[/C][C]-0.5273[/C][C]0.30001[/C][/ROW]
[ROW][C]35[/C][C]0.130728[/C][C]0.9956[/C][C]0.161791[/C][/ROW]
[ROW][C]36[/C][C]0.02547[/C][C]0.194[/C][C]0.423436[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60425&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60425&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
1-0.308281-2.34780.011159
20.0952090.72510.235657
3-0.133079-1.01350.157515
40.0334180.25450.400002
5-0.192005-1.46230.074533
6-0.323863-2.46650.008311
70.019620.14940.440869
8-0.061226-0.46630.321381
9-0.22919-1.74550.0431
10-0.212343-1.61720.055636
110.0510430.38870.349448
12-0.015743-0.11990.45249
13-0.225997-1.72110.045278
14-0.108751-0.82820.205471
150.0693010.52780.299833
16-0.019469-0.14830.441321
17-0.105306-0.8020.212918
18-0.220419-1.67870.049299
190.016260.12380.450938
20-0.090054-0.68580.247776
210.0028180.02150.491475
22-0.202774-1.54430.06398
23-0.029237-0.22270.412291
24-0.030228-0.23020.409369
250.0068120.05190.479402
260.0217940.1660.434376
27-0.080023-0.60940.272306
280.0303650.23130.408966
29-0.029418-0.2240.411756
30-0.016021-0.1220.451655
31-0.046732-0.35590.361604
320.0246720.18790.425807
33-0.009038-0.06880.472681
34-0.069234-0.52730.30001
350.1307280.99560.161791
360.025470.1940.423436


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 2 ; 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')