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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Mon, 01 Dec 2008 11:45:53 -0700

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/01/t122815728289xbd41t33lyzja.htm/, Retrieved Sun, 05 May 2024 15:01:18 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27132, Retrieved Sun, 05 May 2024 15:01:18 +0000

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User-defined keywords

Estimated Impact

286

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD  [(Partial) Autocorrelation Function] [NSTS_Q5] [2008-11-30 17:55:01] [9f5bfe3b95f9ec3d2ed4c0a560a9648a]
F   PD      [(Partial) Autocorrelation Function] [NSTS_Q7 (bouw)] [2008-12-01 18:45:53] [a9e6d7cd6e144e8b311d9f96a24c5a25] [Current]
- RMPD        [ARIMA Forecasting] [ARIMA FORECASTING...] [2008-12-09 18:50:24] [9f5bfe3b95f9ec3d2ed4c0a560a9648a] 

Feedback Forum

2008-12-10 08:25:16 [Lana Van Wesemael] [reply] 
Hier had ik nog kunnen bijschrijven dat de originele autocorrelatie (zonder transformatie) seizoenaliteit vertoonde want op lag 12, 24, 36 zijn er pieken te zien. Om de tijdreeks stationair te maken moet er dus seizoenaal gedifferentieerd worden. Na de differentiatie vallen wel degelijk alle streepjes binnen het 95% betrouwbaarheidsinterval. Het eerste valt er wel buiten maar zoals in de les werd aangehaald moeten we dit staafje negeren. 
2008-12-10 10:19:05 [Peter Van Doninck] [reply] 
De stundent geeft hier enkel de eindoplossing. Er is geen lange termijntrend aanwezig en de seizoenaliteit is ook gezuiverd. Voor de rest kan je hier weinig commentaar op geven.

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27132&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27132&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27132&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.094194	-0.6526	0.258565
2	0.20824	1.4427	0.077796
3	0.055139	0.382	0.352069
4	0.166807	1.1557	0.126767
5	0.095895	0.6644	0.254812
6	0.20209	1.4001	0.083954
7	-0.059065	-0.4092	0.342102
8	0.186938	1.2951	0.100733
9	0.200831	1.3914	0.085261
10	-0.020102	-0.1393	0.444909
11	0.078727	0.5454	0.29399
12	-0.168396	-1.1667	0.124552
13	0.046895	0.3249	0.373335
14	-0.111289	-0.771	0.222233
15	0.103798	0.7191	0.237773
16	-0.209014	-1.4481	0.077046
17	0.121197	0.8397	0.202626
18	-0.091108	-0.6312	0.265448
19	0.010078	0.0698	0.472311
20	-0.222109	-1.5388	0.065208
21	-0.003924	-0.0272	0.489213
22	-0.250558	-1.7359	0.044497
23	-0.012287	-0.0851	0.466258
24	-0.143634	-0.9951	0.162332
25	-0.175376	-1.215	0.115147
26	0.059464	0.412	0.341093
27	-0.079423	-0.5503	0.292347
28	-0.115728	-0.8018	0.213314
29	-0.085094	-0.5895	0.27913
30	-0.069681	-0.4828	0.315728
31	-0.118511	-0.8211	0.207833
32	0.034693	0.2404	0.405538
33	-0.080035	-0.5545	0.290906
34	0.02787	0.1931	0.423852
35	0.047448	0.3287	0.371894
36	-0.059884	-0.4149	0.340035

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.094194 & -0.6526 & 0.258565 \tabularnewline
2 & 0.20824 & 1.4427 & 0.077796 \tabularnewline
3 & 0.055139 & 0.382 & 0.352069 \tabularnewline
4 & 0.166807 & 1.1557 & 0.126767 \tabularnewline
5 & 0.095895 & 0.6644 & 0.254812 \tabularnewline
6 & 0.20209 & 1.4001 & 0.083954 \tabularnewline
7 & -0.059065 & -0.4092 & 0.342102 \tabularnewline
8 & 0.186938 & 1.2951 & 0.100733 \tabularnewline
9 & 0.200831 & 1.3914 & 0.085261 \tabularnewline
10 & -0.020102 & -0.1393 & 0.444909 \tabularnewline
11 & 0.078727 & 0.5454 & 0.29399 \tabularnewline
12 & -0.168396 & -1.1667 & 0.124552 \tabularnewline
13 & 0.046895 & 0.3249 & 0.373335 \tabularnewline
14 & -0.111289 & -0.771 & 0.222233 \tabularnewline
15 & 0.103798 & 0.7191 & 0.237773 \tabularnewline
16 & -0.209014 & -1.4481 & 0.077046 \tabularnewline
17 & 0.121197 & 0.8397 & 0.202626 \tabularnewline
18 & -0.091108 & -0.6312 & 0.265448 \tabularnewline
19 & 0.010078 & 0.0698 & 0.472311 \tabularnewline
20 & -0.222109 & -1.5388 & 0.065208 \tabularnewline
21 & -0.003924 & -0.0272 & 0.489213 \tabularnewline
22 & -0.250558 & -1.7359 & 0.044497 \tabularnewline
23 & -0.012287 & -0.0851 & 0.466258 \tabularnewline
24 & -0.143634 & -0.9951 & 0.162332 \tabularnewline
25 & -0.175376 & -1.215 & 0.115147 \tabularnewline
26 & 0.059464 & 0.412 & 0.341093 \tabularnewline
27 & -0.079423 & -0.5503 & 0.292347 \tabularnewline
28 & -0.115728 & -0.8018 & 0.213314 \tabularnewline
29 & -0.085094 & -0.5895 & 0.27913 \tabularnewline
30 & -0.069681 & -0.4828 & 0.315728 \tabularnewline
31 & -0.118511 & -0.8211 & 0.207833 \tabularnewline
32 & 0.034693 & 0.2404 & 0.405538 \tabularnewline
33 & -0.080035 & -0.5545 & 0.290906 \tabularnewline
34 & 0.02787 & 0.1931 & 0.423852 \tabularnewline
35 & 0.047448 & 0.3287 & 0.371894 \tabularnewline
36 & -0.059884 & -0.4149 & 0.340035 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27132&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]-0.094194[/C][C]-0.6526[/C][C]0.258565[/C][/ROW]
[ROW][C]2[/C][C]0.20824[/C][C]1.4427[/C][C]0.077796[/C][/ROW]
[ROW][C]3[/C][C]0.055139[/C][C]0.382[/C][C]0.352069[/C][/ROW]
[ROW][C]4[/C][C]0.166807[/C][C]1.1557[/C][C]0.126767[/C][/ROW]
[ROW][C]5[/C][C]0.095895[/C][C]0.6644[/C][C]0.254812[/C][/ROW]
[ROW][C]6[/C][C]0.20209[/C][C]1.4001[/C][C]0.083954[/C][/ROW]
[ROW][C]7[/C][C]-0.059065[/C][C]-0.4092[/C][C]0.342102[/C][/ROW]
[ROW][C]8[/C][C]0.186938[/C][C]1.2951[/C][C]0.100733[/C][/ROW]
[ROW][C]9[/C][C]0.200831[/C][C]1.3914[/C][C]0.085261[/C][/ROW]
[ROW][C]10[/C][C]-0.020102[/C][C]-0.1393[/C][C]0.444909[/C][/ROW]
[ROW][C]11[/C][C]0.078727[/C][C]0.5454[/C][C]0.29399[/C][/ROW]
[ROW][C]12[/C][C]-0.168396[/C][C]-1.1667[/C][C]0.124552[/C][/ROW]
[ROW][C]13[/C][C]0.046895[/C][C]0.3249[/C][C]0.373335[/C][/ROW]
[ROW][C]14[/C][C]-0.111289[/C][C]-0.771[/C][C]0.222233[/C][/ROW]
[ROW][C]15[/C][C]0.103798[/C][C]0.7191[/C][C]0.237773[/C][/ROW]
[ROW][C]16[/C][C]-0.209014[/C][C]-1.4481[/C][C]0.077046[/C][/ROW]
[ROW][C]17[/C][C]0.121197[/C][C]0.8397[/C][C]0.202626[/C][/ROW]
[ROW][C]18[/C][C]-0.091108[/C][C]-0.6312[/C][C]0.265448[/C][/ROW]
[ROW][C]19[/C][C]0.010078[/C][C]0.0698[/C][C]0.472311[/C][/ROW]
[ROW][C]20[/C][C]-0.222109[/C][C]-1.5388[/C][C]0.065208[/C][/ROW]
[ROW][C]21[/C][C]-0.003924[/C][C]-0.0272[/C][C]0.489213[/C][/ROW]
[ROW][C]22[/C][C]-0.250558[/C][C]-1.7359[/C][C]0.044497[/C][/ROW]
[ROW][C]23[/C][C]-0.012287[/C][C]-0.0851[/C][C]0.466258[/C][/ROW]
[ROW][C]24[/C][C]-0.143634[/C][C]-0.9951[/C][C]0.162332[/C][/ROW]
[ROW][C]25[/C][C]-0.175376[/C][C]-1.215[/C][C]0.115147[/C][/ROW]
[ROW][C]26[/C][C]0.059464[/C][C]0.412[/C][C]0.341093[/C][/ROW]
[ROW][C]27[/C][C]-0.079423[/C][C]-0.5503[/C][C]0.292347[/C][/ROW]
[ROW][C]28[/C][C]-0.115728[/C][C]-0.8018[/C][C]0.213314[/C][/ROW]
[ROW][C]29[/C][C]-0.085094[/C][C]-0.5895[/C][C]0.27913[/C][/ROW]
[ROW][C]30[/C][C]-0.069681[/C][C]-0.4828[/C][C]0.315728[/C][/ROW]
[ROW][C]31[/C][C]-0.118511[/C][C]-0.8211[/C][C]0.207833[/C][/ROW]
[ROW][C]32[/C][C]0.034693[/C][C]0.2404[/C][C]0.405538[/C][/ROW]
[ROW][C]33[/C][C]-0.080035[/C][C]-0.5545[/C][C]0.290906[/C][/ROW]
[ROW][C]34[/C][C]0.02787[/C][C]0.1931[/C][C]0.423852[/C][/ROW]
[ROW][C]35[/C][C]0.047448[/C][C]0.3287[/C][C]0.371894[/C][/ROW]
[ROW][C]36[/C][C]-0.059884[/C][C]-0.4149[/C][C]0.340035[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27132&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27132&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 k	ACF(k)	T-STAT	P-value
1	-0.094194	-0.6526	0.258565
2	0.20824	1.4427	0.077796
3	0.055139	0.382	0.352069
4	0.166807	1.1557	0.126767
5	0.095895	0.6644	0.254812
6	0.20209	1.4001	0.083954
7	-0.059065	-0.4092	0.342102
8	0.186938	1.2951	0.100733
9	0.200831	1.3914	0.085261
10	-0.020102	-0.1393	0.444909
11	0.078727	0.5454	0.29399
12	-0.168396	-1.1667	0.124552
13	0.046895	0.3249	0.373335
14	-0.111289	-0.771	0.222233
15	0.103798	0.7191	0.237773
16	-0.209014	-1.4481	0.077046
17	0.121197	0.8397	0.202626
18	-0.091108	-0.6312	0.265448
19	0.010078	0.0698	0.472311
20	-0.222109	-1.5388	0.065208
21	-0.003924	-0.0272	0.489213
22	-0.250558	-1.7359	0.044497
23	-0.012287	-0.0851	0.466258
24	-0.143634	-0.9951	0.162332
25	-0.175376	-1.215	0.115147
26	0.059464	0.412	0.341093
27	-0.079423	-0.5503	0.292347
28	-0.115728	-0.8018	0.213314
29	-0.085094	-0.5895	0.27913
30	-0.069681	-0.4828	0.315728
31	-0.118511	-0.8211	0.207833
32	0.034693	0.2404	0.405538
33	-0.080035	-0.5545	0.290906
34	0.02787	0.1931	0.423852
35	0.047448	0.3287	0.371894
36	-0.059884	-0.4149	0.340035

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.094194	-0.6526	0.258565
2	0.201152	1.3936	0.084926
3	0.094378	0.6539	0.258159
4	0.145908	1.0109	0.158571
5	0.103341	0.716	0.23874
6	0.173305	1.2007	0.117881
7	-0.082496	-0.5715	0.285147
8	0.079291	0.5493	0.292657
9	0.2258	1.5644	0.062148
10	-0.078245	-0.5421	0.295131
11	-0.040654	-0.2817	0.389708
12	-0.259479	-1.7977	0.039256
13	-0.083956	-0.5817	0.281758
14	-0.181169	-1.2552	0.107745
15	0.055804	0.3866	0.350372
16	-0.106745	-0.7395	0.231588
17	0.059765	0.4141	0.340336
18	0.057013	0.395	0.347297
19	0.010816	0.0749	0.470289
20	-0.121325	-0.8406	0.20238
21	0.036887	0.2556	0.39969
22	-0.15013	-1.0401	0.151744
23	-0.065073	-0.4508	0.327068
24	-0.102596	-0.7108	0.240321
25	-0.146642	-1.016	0.15737
26	0.082261	0.5699	0.285694
27	0.084188	0.5833	0.281221
28	-0.025869	-0.1792	0.429257
29	0.070497	0.4884	0.31374
30	0.036162	0.2505	0.40162
31	0.052758	0.3655	0.358166
32	-0.057705	-0.3998	0.345542
33	0.102847	0.7125	0.239788
34	-0.036831	-0.2552	0.39984
35	0.038213	0.2647	0.396168
36	-0.182762	-1.2662	0.105774

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.094194 & -0.6526 & 0.258565 \tabularnewline
2 & 0.201152 & 1.3936 & 0.084926 \tabularnewline
3 & 0.094378 & 0.6539 & 0.258159 \tabularnewline
4 & 0.145908 & 1.0109 & 0.158571 \tabularnewline
5 & 0.103341 & 0.716 & 0.23874 \tabularnewline
6 & 0.173305 & 1.2007 & 0.117881 \tabularnewline
7 & -0.082496 & -0.5715 & 0.285147 \tabularnewline
8 & 0.079291 & 0.5493 & 0.292657 \tabularnewline
9 & 0.2258 & 1.5644 & 0.062148 \tabularnewline
10 & -0.078245 & -0.5421 & 0.295131 \tabularnewline
11 & -0.040654 & -0.2817 & 0.389708 \tabularnewline
12 & -0.259479 & -1.7977 & 0.039256 \tabularnewline
13 & -0.083956 & -0.5817 & 0.281758 \tabularnewline
14 & -0.181169 & -1.2552 & 0.107745 \tabularnewline
15 & 0.055804 & 0.3866 & 0.350372 \tabularnewline
16 & -0.106745 & -0.7395 & 0.231588 \tabularnewline
17 & 0.059765 & 0.4141 & 0.340336 \tabularnewline
18 & 0.057013 & 0.395 & 0.347297 \tabularnewline
19 & 0.010816 & 0.0749 & 0.470289 \tabularnewline
20 & -0.121325 & -0.8406 & 0.20238 \tabularnewline
21 & 0.036887 & 0.2556 & 0.39969 \tabularnewline
22 & -0.15013 & -1.0401 & 0.151744 \tabularnewline
23 & -0.065073 & -0.4508 & 0.327068 \tabularnewline
24 & -0.102596 & -0.7108 & 0.240321 \tabularnewline
25 & -0.146642 & -1.016 & 0.15737 \tabularnewline
26 & 0.082261 & 0.5699 & 0.285694 \tabularnewline
27 & 0.084188 & 0.5833 & 0.281221 \tabularnewline
28 & -0.025869 & -0.1792 & 0.429257 \tabularnewline
29 & 0.070497 & 0.4884 & 0.31374 \tabularnewline
30 & 0.036162 & 0.2505 & 0.40162 \tabularnewline
31 & 0.052758 & 0.3655 & 0.358166 \tabularnewline
32 & -0.057705 & -0.3998 & 0.345542 \tabularnewline
33 & 0.102847 & 0.7125 & 0.239788 \tabularnewline
34 & -0.036831 & -0.2552 & 0.39984 \tabularnewline
35 & 0.038213 & 0.2647 & 0.396168 \tabularnewline
36 & -0.182762 & -1.2662 & 0.105774 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27132&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]-0.094194[/C][C]-0.6526[/C][C]0.258565[/C][/ROW]
[ROW][C]2[/C][C]0.201152[/C][C]1.3936[/C][C]0.084926[/C][/ROW]
[ROW][C]3[/C][C]0.094378[/C][C]0.6539[/C][C]0.258159[/C][/ROW]
[ROW][C]4[/C][C]0.145908[/C][C]1.0109[/C][C]0.158571[/C][/ROW]
[ROW][C]5[/C][C]0.103341[/C][C]0.716[/C][C]0.23874[/C][/ROW]
[ROW][C]6[/C][C]0.173305[/C][C]1.2007[/C][C]0.117881[/C][/ROW]
[ROW][C]7[/C][C]-0.082496[/C][C]-0.5715[/C][C]0.285147[/C][/ROW]
[ROW][C]8[/C][C]0.079291[/C][C]0.5493[/C][C]0.292657[/C][/ROW]
[ROW][C]9[/C][C]0.2258[/C][C]1.5644[/C][C]0.062148[/C][/ROW]
[ROW][C]10[/C][C]-0.078245[/C][C]-0.5421[/C][C]0.295131[/C][/ROW]
[ROW][C]11[/C][C]-0.040654[/C][C]-0.2817[/C][C]0.389708[/C][/ROW]
[ROW][C]12[/C][C]-0.259479[/C][C]-1.7977[/C][C]0.039256[/C][/ROW]
[ROW][C]13[/C][C]-0.083956[/C][C]-0.5817[/C][C]0.281758[/C][/ROW]
[ROW][C]14[/C][C]-0.181169[/C][C]-1.2552[/C][C]0.107745[/C][/ROW]
[ROW][C]15[/C][C]0.055804[/C][C]0.3866[/C][C]0.350372[/C][/ROW]
[ROW][C]16[/C][C]-0.106745[/C][C]-0.7395[/C][C]0.231588[/C][/ROW]
[ROW][C]17[/C][C]0.059765[/C][C]0.4141[/C][C]0.340336[/C][/ROW]
[ROW][C]18[/C][C]0.057013[/C][C]0.395[/C][C]0.347297[/C][/ROW]
[ROW][C]19[/C][C]0.010816[/C][C]0.0749[/C][C]0.470289[/C][/ROW]
[ROW][C]20[/C][C]-0.121325[/C][C]-0.8406[/C][C]0.20238[/C][/ROW]
[ROW][C]21[/C][C]0.036887[/C][C]0.2556[/C][C]0.39969[/C][/ROW]
[ROW][C]22[/C][C]-0.15013[/C][C]-1.0401[/C][C]0.151744[/C][/ROW]
[ROW][C]23[/C][C]-0.065073[/C][C]-0.4508[/C][C]0.327068[/C][/ROW]
[ROW][C]24[/C][C]-0.102596[/C][C]-0.7108[/C][C]0.240321[/C][/ROW]
[ROW][C]25[/C][C]-0.146642[/C][C]-1.016[/C][C]0.15737[/C][/ROW]
[ROW][C]26[/C][C]0.082261[/C][C]0.5699[/C][C]0.285694[/C][/ROW]
[ROW][C]27[/C][C]0.084188[/C][C]0.5833[/C][C]0.281221[/C][/ROW]
[ROW][C]28[/C][C]-0.025869[/C][C]-0.1792[/C][C]0.429257[/C][/ROW]
[ROW][C]29[/C][C]0.070497[/C][C]0.4884[/C][C]0.31374[/C][/ROW]
[ROW][C]30[/C][C]0.036162[/C][C]0.2505[/C][C]0.40162[/C][/ROW]
[ROW][C]31[/C][C]0.052758[/C][C]0.3655[/C][C]0.358166[/C][/ROW]
[ROW][C]32[/C][C]-0.057705[/C][C]-0.3998[/C][C]0.345542[/C][/ROW]
[ROW][C]33[/C][C]0.102847[/C][C]0.7125[/C][C]0.239788[/C][/ROW]
[ROW][C]34[/C][C]-0.036831[/C][C]-0.2552[/C][C]0.39984[/C][/ROW]
[ROW][C]35[/C][C]0.038213[/C][C]0.2647[/C][C]0.396168[/C][/ROW]
[ROW][C]36[/C][C]-0.182762[/C][C]-1.2662[/C][C]0.105774[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27132&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27132&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 k	PACF(k)	T-STAT	P-value
1	-0.094194	-0.6526	0.258565
2	0.201152	1.3936	0.084926
3	0.094378	0.6539	0.258159
4	0.145908	1.0109	0.158571
5	0.103341	0.716	0.23874
6	0.173305	1.2007	0.117881
7	-0.082496	-0.5715	0.285147
8	0.079291	0.5493	0.292657
9	0.2258	1.5644	0.062148
10	-0.078245	-0.5421	0.295131
11	-0.040654	-0.2817	0.389708
12	-0.259479	-1.7977	0.039256
13	-0.083956	-0.5817	0.281758
14	-0.181169	-1.2552	0.107745
15	0.055804	0.3866	0.350372
16	-0.106745	-0.7395	0.231588
17	0.059765	0.4141	0.340336
18	0.057013	0.395	0.347297
19	0.010816	0.0749	0.470289
20	-0.121325	-0.8406	0.20238
21	0.036887	0.2556	0.39969
22	-0.15013	-1.0401	0.151744
23	-0.065073	-0.4508	0.327068
24	-0.102596	-0.7108	0.240321
25	-0.146642	-1.016	0.15737
26	0.082261	0.5699	0.285694
27	0.084188	0.5833	0.281221
28	-0.025869	-0.1792	0.429257
29	0.070497	0.4884	0.31374
30	0.036162	0.2505	0.40162
31	0.052758	0.3655	0.358166
32	-0.057705	-0.3998	0.345542
33	0.102847	0.7125	0.239788
34	-0.036831	-0.2552	0.39984
35	0.038213	0.2647	0.396168
36	-0.182762	-1.2662	0.105774

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;

Parameters (R input):

par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;

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 (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='lags',ylab='ACF')
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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code