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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 05:34:02 -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/t1259325326him958w5tkscoxk.htm/, Retrieved Mon, 29 Apr 2024 00:13:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60651, Retrieved Mon, 29 Apr 2024 00:13:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsshws8vr3
Estimated Impact143

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]
- R  D          [(Partial) Autocorrelation Function] [] [2009-11-27 12:34:02] [4407d6264e55b051ec65750e6dca2820] [Current]
-   PD            [(Partial) Autocorrelation Function] [] [2009-11-27 16:59:24] [023d83ebdf42a2acf423907b4076e8a1]
-    D            [(Partial) Autocorrelation Function] [] [2010-12-24 14:45:05] [6e5489189f7de5cfbcc25dd35ae15009]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
15912,8
13866,5
17823,2
17872
17420,4
16704,4
15991,2
16583,6
19123,5
17838,7
17209,4
18586,5
16258,1
15141,6
19202,1
17746,5
19090,1
18040,3
17515,5
17751,8
21072,4
17170
19439,5
19795,4
17574,9
16165,4
19464,6
19932,1
19961,2
17343,4
18924,2
18574,1
21350,6
18594,6
19823,1
20844,4
19640,2
17735,4
19813,6
22160
20664,3
17877,4
20906,5
21164,1
21374,4
22952,3
21343,5
23899,3
22392,9
18274,1
22786,7
22321,5
17842,2
16373,5
15993,8
16446,1
17729
16643
16196,7
18252,1
17304

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=60651&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=60651&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60651&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
1-0.566145-3.92240.000139
20.0770160.53360.298046
30.3693362.55880.006855
4-0.351697-2.43660.009292
50.1557781.07930.142932
60.1616261.11980.134191
7-0.38018-2.6340.005662
80.2959252.05020.022913
9-0.12635-0.87540.192865
10-0.090464-0.62680.266896
110.1603861.11120.136012
12-0.13069-0.90540.184875
13-0.000731-0.00510.497989
140.0594720.4120.341075
150.0282580.19580.422805
16-0.169637-1.17530.12284
170.1773121.22850.112633
18-0.097413-0.67490.25149
19-0.070805-0.49050.31299
200.1736341.2030.117444
21-0.094466-0.65450.257963
22-0.180851-1.2530.108142
230.3789592.62550.005787
24-0.335662-2.32550.012158
250.1402920.9720.16797
260.0664280.46020.323717
27-0.156247-1.08250.142217
280.1053280.72970.23455
290.0305610.21170.416607
30-0.132376-0.91710.18183
310.1439490.99730.161808
32-0.107403-0.74410.23022
330.0239870.16620.434353
340.0794530.55050.292277
35-0.139727-0.96810.168934
360.0511980.35470.362181

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.566145 & -3.9224 & 0.000139 \tabularnewline
2 & 0.077016 & 0.5336 & 0.298046 \tabularnewline
3 & 0.369336 & 2.5588 & 0.006855 \tabularnewline
4 & -0.351697 & -2.4366 & 0.009292 \tabularnewline
5 & 0.155778 & 1.0793 & 0.142932 \tabularnewline
6 & 0.161626 & 1.1198 & 0.134191 \tabularnewline
7 & -0.38018 & -2.634 & 0.005662 \tabularnewline
8 & 0.295925 & 2.0502 & 0.022913 \tabularnewline
9 & -0.12635 & -0.8754 & 0.192865 \tabularnewline
10 & -0.090464 & -0.6268 & 0.266896 \tabularnewline
11 & 0.160386 & 1.1112 & 0.136012 \tabularnewline
12 & -0.13069 & -0.9054 & 0.184875 \tabularnewline
13 & -0.000731 & -0.0051 & 0.497989 \tabularnewline
14 & 0.059472 & 0.412 & 0.341075 \tabularnewline
15 & 0.028258 & 0.1958 & 0.422805 \tabularnewline
16 & -0.169637 & -1.1753 & 0.12284 \tabularnewline
17 & 0.177312 & 1.2285 & 0.112633 \tabularnewline
18 & -0.097413 & -0.6749 & 0.25149 \tabularnewline
19 & -0.070805 & -0.4905 & 0.31299 \tabularnewline
20 & 0.173634 & 1.203 & 0.117444 \tabularnewline
21 & -0.094466 & -0.6545 & 0.257963 \tabularnewline
22 & -0.180851 & -1.253 & 0.108142 \tabularnewline
23 & 0.378959 & 2.6255 & 0.005787 \tabularnewline
24 & -0.335662 & -2.3255 & 0.012158 \tabularnewline
25 & 0.140292 & 0.972 & 0.16797 \tabularnewline
26 & 0.066428 & 0.4602 & 0.323717 \tabularnewline
27 & -0.156247 & -1.0825 & 0.142217 \tabularnewline
28 & 0.105328 & 0.7297 & 0.23455 \tabularnewline
29 & 0.030561 & 0.2117 & 0.416607 \tabularnewline
30 & -0.132376 & -0.9171 & 0.18183 \tabularnewline
31 & 0.143949 & 0.9973 & 0.161808 \tabularnewline
32 & -0.107403 & -0.7441 & 0.23022 \tabularnewline
33 & 0.023987 & 0.1662 & 0.434353 \tabularnewline
34 & 0.079453 & 0.5505 & 0.292277 \tabularnewline
35 & -0.139727 & -0.9681 & 0.168934 \tabularnewline
36 & 0.051198 & 0.3547 & 0.362181 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60651&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]-0.566145[/C][C]-3.9224[/C][C]0.000139[/C][/ROW]
[ROW][C]2[/C][C]0.077016[/C][C]0.5336[/C][C]0.298046[/C][/ROW]
[ROW][C]3[/C][C]0.369336[/C][C]2.5588[/C][C]0.006855[/C][/ROW]
[ROW][C]4[/C][C]-0.351697[/C][C]-2.4366[/C][C]0.009292[/C][/ROW]
[ROW][C]5[/C][C]0.155778[/C][C]1.0793[/C][C]0.142932[/C][/ROW]
[ROW][C]6[/C][C]0.161626[/C][C]1.1198[/C][C]0.134191[/C][/ROW]
[ROW][C]7[/C][C]-0.38018[/C][C]-2.634[/C][C]0.005662[/C][/ROW]
[ROW][C]8[/C][C]0.295925[/C][C]2.0502[/C][C]0.022913[/C][/ROW]
[ROW][C]9[/C][C]-0.12635[/C][C]-0.8754[/C][C]0.192865[/C][/ROW]
[ROW][C]10[/C][C]-0.090464[/C][C]-0.6268[/C][C]0.266896[/C][/ROW]
[ROW][C]11[/C][C]0.160386[/C][C]1.1112[/C][C]0.136012[/C][/ROW]
[ROW][C]12[/C][C]-0.13069[/C][C]-0.9054[/C][C]0.184875[/C][/ROW]
[ROW][C]13[/C][C]-0.000731[/C][C]-0.0051[/C][C]0.497989[/C][/ROW]
[ROW][C]14[/C][C]0.059472[/C][C]0.412[/C][C]0.341075[/C][/ROW]
[ROW][C]15[/C][C]0.028258[/C][C]0.1958[/C][C]0.422805[/C][/ROW]
[ROW][C]16[/C][C]-0.169637[/C][C]-1.1753[/C][C]0.12284[/C][/ROW]
[ROW][C]17[/C][C]0.177312[/C][C]1.2285[/C][C]0.112633[/C][/ROW]
[ROW][C]18[/C][C]-0.097413[/C][C]-0.6749[/C][C]0.25149[/C][/ROW]
[ROW][C]19[/C][C]-0.070805[/C][C]-0.4905[/C][C]0.31299[/C][/ROW]
[ROW][C]20[/C][C]0.173634[/C][C]1.203[/C][C]0.117444[/C][/ROW]
[ROW][C]21[/C][C]-0.094466[/C][C]-0.6545[/C][C]0.257963[/C][/ROW]
[ROW][C]22[/C][C]-0.180851[/C][C]-1.253[/C][C]0.108142[/C][/ROW]
[ROW][C]23[/C][C]0.378959[/C][C]2.6255[/C][C]0.005787[/C][/ROW]
[ROW][C]24[/C][C]-0.335662[/C][C]-2.3255[/C][C]0.012158[/C][/ROW]
[ROW][C]25[/C][C]0.140292[/C][C]0.972[/C][C]0.16797[/C][/ROW]
[ROW][C]26[/C][C]0.066428[/C][C]0.4602[/C][C]0.323717[/C][/ROW]
[ROW][C]27[/C][C]-0.156247[/C][C]-1.0825[/C][C]0.142217[/C][/ROW]
[ROW][C]28[/C][C]0.105328[/C][C]0.7297[/C][C]0.23455[/C][/ROW]
[ROW][C]29[/C][C]0.030561[/C][C]0.2117[/C][C]0.416607[/C][/ROW]
[ROW][C]30[/C][C]-0.132376[/C][C]-0.9171[/C][C]0.18183[/C][/ROW]
[ROW][C]31[/C][C]0.143949[/C][C]0.9973[/C][C]0.161808[/C][/ROW]
[ROW][C]32[/C][C]-0.107403[/C][C]-0.7441[/C][C]0.23022[/C][/ROW]
[ROW][C]33[/C][C]0.023987[/C][C]0.1662[/C][C]0.434353[/C][/ROW]
[ROW][C]34[/C][C]0.079453[/C][C]0.5505[/C][C]0.292277[/C][/ROW]
[ROW][C]35[/C][C]-0.139727[/C][C]-0.9681[/C][C]0.168934[/C][/ROW]
[ROW][C]36[/C][C]0.051198[/C][C]0.3547[/C][C]0.362181[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60651&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60651&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
1-0.566145-3.92240.000139
20.0770160.53360.298046
30.3693362.55880.006855
4-0.351697-2.43660.009292
50.1557781.07930.142932
60.1616261.11980.134191
7-0.38018-2.6340.005662
80.2959252.05020.022913
9-0.12635-0.87540.192865
10-0.090464-0.62680.266896
110.1603861.11120.136012
12-0.13069-0.90540.184875
13-0.000731-0.00510.497989
140.0594720.4120.341075
150.0282580.19580.422805
16-0.169637-1.17530.12284
170.1773121.22850.112633
18-0.097413-0.67490.25149
19-0.070805-0.49050.31299
200.1736341.2030.117444
21-0.094466-0.65450.257963
22-0.180851-1.2530.108142
230.3789592.62550.005787
24-0.335662-2.32550.012158
250.1402920.9720.16797
260.0664280.46020.323717
27-0.156247-1.08250.142217
280.1053280.72970.23455
290.0305610.21170.416607
30-0.132376-0.91710.18183
310.1439490.99730.161808
32-0.107403-0.74410.23022
330.0239870.16620.434353
340.0794530.55050.292277
35-0.139727-0.96810.168934
360.0511980.35470.362181






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.566145-3.92240.000139
2-0.358369-2.48290.008291
30.381072.64010.005573
40.2028151.40510.083209
50.0020270.0140.494426
60.1047360.72560.235794
7-0.244622-1.69480.048297
8-0.168536-1.16770.124357
9-0.153756-1.06530.146046
100.0443410.30720.380008
110.1053170.72970.234573
120.1001160.69360.24563
130.0305280.21150.416696
14-0.161833-1.12120.133888
150.1365370.9460.174454
16-0.186769-1.2940.100933
17-0.087962-0.60940.272561
18-0.067381-0.46680.321368
19-0.053874-0.37320.355303
200.1306090.90490.185023
210.2365081.63860.05392
22-0.157886-1.09390.139737
23-0.047006-0.32570.373045
24-0.068587-0.47520.318404
250.0159860.11080.456135
26-0.098909-0.68530.248237
270.1138910.78910.216979
280.020340.14090.444261
29-0.039192-0.27150.393574
300.0474370.32870.371925
31-0.007464-0.05170.479486
32-0.089444-0.61970.269197
33-0.028933-0.20050.420986
340.0590370.4090.342172
35-0.080301-0.55630.29028
36-0.10093-0.69930.243881

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.566145 & -3.9224 & 0.000139 \tabularnewline
2 & -0.358369 & -2.4829 & 0.008291 \tabularnewline
3 & 0.38107 & 2.6401 & 0.005573 \tabularnewline
4 & 0.202815 & 1.4051 & 0.083209 \tabularnewline
5 & 0.002027 & 0.014 & 0.494426 \tabularnewline
6 & 0.104736 & 0.7256 & 0.235794 \tabularnewline
7 & -0.244622 & -1.6948 & 0.048297 \tabularnewline
8 & -0.168536 & -1.1677 & 0.124357 \tabularnewline
9 & -0.153756 & -1.0653 & 0.146046 \tabularnewline
10 & 0.044341 & 0.3072 & 0.380008 \tabularnewline
11 & 0.105317 & 0.7297 & 0.234573 \tabularnewline
12 & 0.100116 & 0.6936 & 0.24563 \tabularnewline
13 & 0.030528 & 0.2115 & 0.416696 \tabularnewline
14 & -0.161833 & -1.1212 & 0.133888 \tabularnewline
15 & 0.136537 & 0.946 & 0.174454 \tabularnewline
16 & -0.186769 & -1.294 & 0.100933 \tabularnewline
17 & -0.087962 & -0.6094 & 0.272561 \tabularnewline
18 & -0.067381 & -0.4668 & 0.321368 \tabularnewline
19 & -0.053874 & -0.3732 & 0.355303 \tabularnewline
20 & 0.130609 & 0.9049 & 0.185023 \tabularnewline
21 & 0.236508 & 1.6386 & 0.05392 \tabularnewline
22 & -0.157886 & -1.0939 & 0.139737 \tabularnewline
23 & -0.047006 & -0.3257 & 0.373045 \tabularnewline
24 & -0.068587 & -0.4752 & 0.318404 \tabularnewline
25 & 0.015986 & 0.1108 & 0.456135 \tabularnewline
26 & -0.098909 & -0.6853 & 0.248237 \tabularnewline
27 & 0.113891 & 0.7891 & 0.216979 \tabularnewline
28 & 0.02034 & 0.1409 & 0.444261 \tabularnewline
29 & -0.039192 & -0.2715 & 0.393574 \tabularnewline
30 & 0.047437 & 0.3287 & 0.371925 \tabularnewline
31 & -0.007464 & -0.0517 & 0.479486 \tabularnewline
32 & -0.089444 & -0.6197 & 0.269197 \tabularnewline
33 & -0.028933 & -0.2005 & 0.420986 \tabularnewline
34 & 0.059037 & 0.409 & 0.342172 \tabularnewline
35 & -0.080301 & -0.5563 & 0.29028 \tabularnewline
36 & -0.10093 & -0.6993 & 0.243881 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60651&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]-0.566145[/C][C]-3.9224[/C][C]0.000139[/C][/ROW]
[ROW][C]2[/C][C]-0.358369[/C][C]-2.4829[/C][C]0.008291[/C][/ROW]
[ROW][C]3[/C][C]0.38107[/C][C]2.6401[/C][C]0.005573[/C][/ROW]
[ROW][C]4[/C][C]0.202815[/C][C]1.4051[/C][C]0.083209[/C][/ROW]
[ROW][C]5[/C][C]0.002027[/C][C]0.014[/C][C]0.494426[/C][/ROW]
[ROW][C]6[/C][C]0.104736[/C][C]0.7256[/C][C]0.235794[/C][/ROW]
[ROW][C]7[/C][C]-0.244622[/C][C]-1.6948[/C][C]0.048297[/C][/ROW]
[ROW][C]8[/C][C]-0.168536[/C][C]-1.1677[/C][C]0.124357[/C][/ROW]
[ROW][C]9[/C][C]-0.153756[/C][C]-1.0653[/C][C]0.146046[/C][/ROW]
[ROW][C]10[/C][C]0.044341[/C][C]0.3072[/C][C]0.380008[/C][/ROW]
[ROW][C]11[/C][C]0.105317[/C][C]0.7297[/C][C]0.234573[/C][/ROW]
[ROW][C]12[/C][C]0.100116[/C][C]0.6936[/C][C]0.24563[/C][/ROW]
[ROW][C]13[/C][C]0.030528[/C][C]0.2115[/C][C]0.416696[/C][/ROW]
[ROW][C]14[/C][C]-0.161833[/C][C]-1.1212[/C][C]0.133888[/C][/ROW]
[ROW][C]15[/C][C]0.136537[/C][C]0.946[/C][C]0.174454[/C][/ROW]
[ROW][C]16[/C][C]-0.186769[/C][C]-1.294[/C][C]0.100933[/C][/ROW]
[ROW][C]17[/C][C]-0.087962[/C][C]-0.6094[/C][C]0.272561[/C][/ROW]
[ROW][C]18[/C][C]-0.067381[/C][C]-0.4668[/C][C]0.321368[/C][/ROW]
[ROW][C]19[/C][C]-0.053874[/C][C]-0.3732[/C][C]0.355303[/C][/ROW]
[ROW][C]20[/C][C]0.130609[/C][C]0.9049[/C][C]0.185023[/C][/ROW]
[ROW][C]21[/C][C]0.236508[/C][C]1.6386[/C][C]0.05392[/C][/ROW]
[ROW][C]22[/C][C]-0.157886[/C][C]-1.0939[/C][C]0.139737[/C][/ROW]
[ROW][C]23[/C][C]-0.047006[/C][C]-0.3257[/C][C]0.373045[/C][/ROW]
[ROW][C]24[/C][C]-0.068587[/C][C]-0.4752[/C][C]0.318404[/C][/ROW]
[ROW][C]25[/C][C]0.015986[/C][C]0.1108[/C][C]0.456135[/C][/ROW]
[ROW][C]26[/C][C]-0.098909[/C][C]-0.6853[/C][C]0.248237[/C][/ROW]
[ROW][C]27[/C][C]0.113891[/C][C]0.7891[/C][C]0.216979[/C][/ROW]
[ROW][C]28[/C][C]0.02034[/C][C]0.1409[/C][C]0.444261[/C][/ROW]
[ROW][C]29[/C][C]-0.039192[/C][C]-0.2715[/C][C]0.393574[/C][/ROW]
[ROW][C]30[/C][C]0.047437[/C][C]0.3287[/C][C]0.371925[/C][/ROW]
[ROW][C]31[/C][C]-0.007464[/C][C]-0.0517[/C][C]0.479486[/C][/ROW]
[ROW][C]32[/C][C]-0.089444[/C][C]-0.6197[/C][C]0.269197[/C][/ROW]
[ROW][C]33[/C][C]-0.028933[/C][C]-0.2005[/C][C]0.420986[/C][/ROW]
[ROW][C]34[/C][C]0.059037[/C][C]0.409[/C][C]0.342172[/C][/ROW]
[ROW][C]35[/C][C]-0.080301[/C][C]-0.5563[/C][C]0.29028[/C][/ROW]
[ROW][C]36[/C][C]-0.10093[/C][C]-0.6993[/C][C]0.243881[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60651&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60651&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
1-0.566145-3.92240.000139
2-0.358369-2.48290.008291
30.381072.64010.005573
40.2028151.40510.083209
50.0020270.0140.494426
60.1047360.72560.235794
7-0.244622-1.69480.048297
8-0.168536-1.16770.124357
9-0.153756-1.06530.146046
100.0443410.30720.380008
110.1053170.72970.234573
120.1001160.69360.24563
130.0305280.21150.416696
14-0.161833-1.12120.133888
150.1365370.9460.174454
16-0.186769-1.2940.100933
17-0.087962-0.60940.272561
18-0.067381-0.46680.321368
19-0.053874-0.37320.355303
200.1306090.90490.185023
210.2365081.63860.05392
22-0.157886-1.09390.139737
23-0.047006-0.32570.373045
24-0.068587-0.47520.318404
250.0159860.11080.456135
26-0.098909-0.68530.248237
270.1138910.78910.216979
280.020340.14090.444261
29-0.039192-0.27150.393574
300.0474370.32870.371925
31-0.007464-0.05170.479486
32-0.089444-0.61970.269197
33-0.028933-0.20050.420986
340.0590370.4090.342172
35-0.080301-0.55630.29028
36-0.10093-0.69930.243881


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')