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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Tue, 02 Dec 2008 11:11:41 -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/02/t12282415572fjofrpg0ms1zom.htm/, Retrieved Sat, 25 May 2024 07:45:18 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28187, Retrieved Sat, 25 May 2024 07:45:18 +0000

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User-defined keywords

Estimated Impact

178

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

F     [(Partial) Autocorrelation Function] [nsts Q8 (1)] [2008-12-02 16:54:05] [b1bd16d1f47bfe13feacf1c27a0abba5]
F   PD  [(Partial) Autocorrelation Function] [nsts Q8 (2)] [2008-12-02 16:58:46] [b1bd16d1f47bfe13feacf1c27a0abba5]
F   PD    [(Partial) Autocorrelation Function] [nsts Q8 (5)] [2008-12-02 17:09:15] [b1bd16d1f47bfe13feacf1c27a0abba5]
-   PD      [(Partial) Autocorrelation Function] [nsts Q8 (6)] [2008-12-02 17:12:08] [b1bd16d1f47bfe13feacf1c27a0abba5]
-   P         [(Partial) Autocorrelation Function] [nsts Q8 (7)] [2008-12-02 17:14:26] [b1bd16d1f47bfe13feacf1c27a0abba5]
F   P             [(Partial) Autocorrelation Function] [nsts Q8 (10)] [2008-12-02 18:11:41] [e7b1048c2c3a353441b9143db4404b91] [Current]

Feedback Forum

2008-12-08 19:18:05 [Jasmine Hendrikx] [reply] 
Eigen evaluatie: 
De berekening is goed uitgevoerd. Er is inderdaad geen sprake meer van een seizoenale trend. Lag 12 heeft zelfs een negatieve autocorrelatiecoëfficiënt. Er is duidelijk geen sprake meer van seizoenaliteit. Ook liggen de meeste autocorrelatiecoëfficiënten nu binnen het betrouwbaarheidsinterval en zijn ze dus niet significant verschillend van 0.

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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	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28187&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28187&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28187&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	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.049447	0.4225	0.33696
2	0.075338	0.6437	0.260898
3	0.255944	2.1868	0.015982
4	-0.079086	-0.6757	0.250679
5	0.069557	0.5943	0.277076
6	0.202407	1.7294	0.043985
7	-0.123561	-1.0557	0.147292
8	0.098289	0.8398	0.201887
9	0.245897	2.1009	0.01955
10	-0.142219	-1.2151	0.114117
11	-0.061772	-0.5278	0.299626
12	-0.123248	-1.053	0.1479
13	-0.217966	-1.8623	0.033292
14	0.067523	0.5769	0.282885
15	-0.044216	-0.3778	0.353344
16	-0.115137	-0.9837	0.164249
17	0.174872	1.4941	0.069729
18	-0.003031	-0.0259	0.489706
19	-0.213824	-1.8269	0.0359
20	-0.008931	-0.0763	0.469693
21	-0.005941	-0.0508	0.479829
22	-0.156868	-1.3403	0.092155
23	0.147919	1.2638	0.105158
24	-0.247278	-2.1127	0.019021
25	-0.096518	-0.8247	0.206128
26	0.046657	0.3986	0.345662
27	-0.001879	-0.0161	0.493619
28	-0.102246	-0.8736	0.192603
29	0.039662	0.3389	0.367838
30	-0.021062	-0.18	0.428844
31	0.070744	0.6044	0.273714
32	0.142729	1.2195	0.113295
33	-0.130517	-1.1151	0.134225
34	0.059094	0.5049	0.307574
35	0.15231	1.3013	0.098617
36	0.049651	0.4242	0.336327

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.049447 & 0.4225 & 0.33696 \tabularnewline
2 & 0.075338 & 0.6437 & 0.260898 \tabularnewline
3 & 0.255944 & 2.1868 & 0.015982 \tabularnewline
4 & -0.079086 & -0.6757 & 0.250679 \tabularnewline
5 & 0.069557 & 0.5943 & 0.277076 \tabularnewline
6 & 0.202407 & 1.7294 & 0.043985 \tabularnewline
7 & -0.123561 & -1.0557 & 0.147292 \tabularnewline
8 & 0.098289 & 0.8398 & 0.201887 \tabularnewline
9 & 0.245897 & 2.1009 & 0.01955 \tabularnewline
10 & -0.142219 & -1.2151 & 0.114117 \tabularnewline
11 & -0.061772 & -0.5278 & 0.299626 \tabularnewline
12 & -0.123248 & -1.053 & 0.1479 \tabularnewline
13 & -0.217966 & -1.8623 & 0.033292 \tabularnewline
14 & 0.067523 & 0.5769 & 0.282885 \tabularnewline
15 & -0.044216 & -0.3778 & 0.353344 \tabularnewline
16 & -0.115137 & -0.9837 & 0.164249 \tabularnewline
17 & 0.174872 & 1.4941 & 0.069729 \tabularnewline
18 & -0.003031 & -0.0259 & 0.489706 \tabularnewline
19 & -0.213824 & -1.8269 & 0.0359 \tabularnewline
20 & -0.008931 & -0.0763 & 0.469693 \tabularnewline
21 & -0.005941 & -0.0508 & 0.479829 \tabularnewline
22 & -0.156868 & -1.3403 & 0.092155 \tabularnewline
23 & 0.147919 & 1.2638 & 0.105158 \tabularnewline
24 & -0.247278 & -2.1127 & 0.019021 \tabularnewline
25 & -0.096518 & -0.8247 & 0.206128 \tabularnewline
26 & 0.046657 & 0.3986 & 0.345662 \tabularnewline
27 & -0.001879 & -0.0161 & 0.493619 \tabularnewline
28 & -0.102246 & -0.8736 & 0.192603 \tabularnewline
29 & 0.039662 & 0.3389 & 0.367838 \tabularnewline
30 & -0.021062 & -0.18 & 0.428844 \tabularnewline
31 & 0.070744 & 0.6044 & 0.273714 \tabularnewline
32 & 0.142729 & 1.2195 & 0.113295 \tabularnewline
33 & -0.130517 & -1.1151 & 0.134225 \tabularnewline
34 & 0.059094 & 0.5049 & 0.307574 \tabularnewline
35 & 0.15231 & 1.3013 & 0.098617 \tabularnewline
36 & 0.049651 & 0.4242 & 0.336327 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28187&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]0.049447[/C][C]0.4225[/C][C]0.33696[/C][/ROW]
[ROW][C]2[/C][C]0.075338[/C][C]0.6437[/C][C]0.260898[/C][/ROW]
[ROW][C]3[/C][C]0.255944[/C][C]2.1868[/C][C]0.015982[/C][/ROW]
[ROW][C]4[/C][C]-0.079086[/C][C]-0.6757[/C][C]0.250679[/C][/ROW]
[ROW][C]5[/C][C]0.069557[/C][C]0.5943[/C][C]0.277076[/C][/ROW]
[ROW][C]6[/C][C]0.202407[/C][C]1.7294[/C][C]0.043985[/C][/ROW]
[ROW][C]7[/C][C]-0.123561[/C][C]-1.0557[/C][C]0.147292[/C][/ROW]
[ROW][C]8[/C][C]0.098289[/C][C]0.8398[/C][C]0.201887[/C][/ROW]
[ROW][C]9[/C][C]0.245897[/C][C]2.1009[/C][C]0.01955[/C][/ROW]
[ROW][C]10[/C][C]-0.142219[/C][C]-1.2151[/C][C]0.114117[/C][/ROW]
[ROW][C]11[/C][C]-0.061772[/C][C]-0.5278[/C][C]0.299626[/C][/ROW]
[ROW][C]12[/C][C]-0.123248[/C][C]-1.053[/C][C]0.1479[/C][/ROW]
[ROW][C]13[/C][C]-0.217966[/C][C]-1.8623[/C][C]0.033292[/C][/ROW]
[ROW][C]14[/C][C]0.067523[/C][C]0.5769[/C][C]0.282885[/C][/ROW]
[ROW][C]15[/C][C]-0.044216[/C][C]-0.3778[/C][C]0.353344[/C][/ROW]
[ROW][C]16[/C][C]-0.115137[/C][C]-0.9837[/C][C]0.164249[/C][/ROW]
[ROW][C]17[/C][C]0.174872[/C][C]1.4941[/C][C]0.069729[/C][/ROW]
[ROW][C]18[/C][C]-0.003031[/C][C]-0.0259[/C][C]0.489706[/C][/ROW]
[ROW][C]19[/C][C]-0.213824[/C][C]-1.8269[/C][C]0.0359[/C][/ROW]
[ROW][C]20[/C][C]-0.008931[/C][C]-0.0763[/C][C]0.469693[/C][/ROW]
[ROW][C]21[/C][C]-0.005941[/C][C]-0.0508[/C][C]0.479829[/C][/ROW]
[ROW][C]22[/C][C]-0.156868[/C][C]-1.3403[/C][C]0.092155[/C][/ROW]
[ROW][C]23[/C][C]0.147919[/C][C]1.2638[/C][C]0.105158[/C][/ROW]
[ROW][C]24[/C][C]-0.247278[/C][C]-2.1127[/C][C]0.019021[/C][/ROW]
[ROW][C]25[/C][C]-0.096518[/C][C]-0.8247[/C][C]0.206128[/C][/ROW]
[ROW][C]26[/C][C]0.046657[/C][C]0.3986[/C][C]0.345662[/C][/ROW]
[ROW][C]27[/C][C]-0.001879[/C][C]-0.0161[/C][C]0.493619[/C][/ROW]
[ROW][C]28[/C][C]-0.102246[/C][C]-0.8736[/C][C]0.192603[/C][/ROW]
[ROW][C]29[/C][C]0.039662[/C][C]0.3389[/C][C]0.367838[/C][/ROW]
[ROW][C]30[/C][C]-0.021062[/C][C]-0.18[/C][C]0.428844[/C][/ROW]
[ROW][C]31[/C][C]0.070744[/C][C]0.6044[/C][C]0.273714[/C][/ROW]
[ROW][C]32[/C][C]0.142729[/C][C]1.2195[/C][C]0.113295[/C][/ROW]
[ROW][C]33[/C][C]-0.130517[/C][C]-1.1151[/C][C]0.134225[/C][/ROW]
[ROW][C]34[/C][C]0.059094[/C][C]0.5049[/C][C]0.307574[/C][/ROW]
[ROW][C]35[/C][C]0.15231[/C][C]1.3013[/C][C]0.098617[/C][/ROW]
[ROW][C]36[/C][C]0.049651[/C][C]0.4242[/C][C]0.336327[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28187&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28187&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	0.049447	0.4225	0.33696
2	0.075338	0.6437	0.260898
3	0.255944	2.1868	0.015982
4	-0.079086	-0.6757	0.250679
5	0.069557	0.5943	0.277076
6	0.202407	1.7294	0.043985
7	-0.123561	-1.0557	0.147292
8	0.098289	0.8398	0.201887
9	0.245897	2.1009	0.01955
10	-0.142219	-1.2151	0.114117
11	-0.061772	-0.5278	0.299626
12	-0.123248	-1.053	0.1479
13	-0.217966	-1.8623	0.033292
14	0.067523	0.5769	0.282885
15	-0.044216	-0.3778	0.353344
16	-0.115137	-0.9837	0.164249
17	0.174872	1.4941	0.069729
18	-0.003031	-0.0259	0.489706
19	-0.213824	-1.8269	0.0359
20	-0.008931	-0.0763	0.469693
21	-0.005941	-0.0508	0.479829
22	-0.156868	-1.3403	0.092155
23	0.147919	1.2638	0.105158
24	-0.247278	-2.1127	0.019021
25	-0.096518	-0.8247	0.206128
26	0.046657	0.3986	0.345662
27	-0.001879	-0.0161	0.493619
28	-0.102246	-0.8736	0.192603
29	0.039662	0.3389	0.367838
30	-0.021062	-0.18	0.428844
31	0.070744	0.6044	0.273714
32	0.142729	1.2195	0.113295
33	-0.130517	-1.1151	0.134225
34	0.059094	0.5049	0.307574
35	0.15231	1.3013	0.098617
36	0.049651	0.4242	0.336327

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.049447	0.4225	0.33696
2	0.073072	0.6243	0.267181
3	0.250827	2.1431	0.017721
4	-0.110957	-0.948	0.173125
5	0.046588	0.3981	0.345877
6	0.157972	1.3497	0.09064
7	-0.114228	-0.976	0.166153
8	0.058164	0.497	0.310357
9	0.206868	1.7675	0.040664
10	-0.120288	-1.0277	0.153732
11	-0.18138	-1.5497	0.062768
12	-0.210512	-1.7986	0.038107
13	-0.080539	-0.6881	0.246777
14	0.093476	0.7987	0.21354
15	-0.016977	-0.1451	0.442534
16	0.00681	0.0582	0.476881
17	0.175175	1.4967	0.069392
18	0.030725	0.2625	0.396831
19	-0.225262	-1.9246	0.029086
20	-0.072064	-0.6157	0.269998
21	0.235937	2.0158	0.023749
22	-0.106049	-0.9061	0.183937
23	-0.074847	-0.6395	0.262253
24	-0.336588	-2.8758	0.002639
25	0.012041	0.1029	0.45917
26	-0.069125	-0.5906	0.278305
27	0.209117	1.7867	0.039069
28	0.073643	0.6292	0.26559
29	0.148989	1.273	0.103535
30	0.000767	0.0066	0.497394
31	-0.020706	-0.1769	0.430034
32	0.053252	0.455	0.325234
33	0.014594	0.1247	0.450554
34	0.028337	0.2421	0.404686
35	0.01195	0.1021	0.459478
36	-0.008424	-0.072	0.471411

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.049447 & 0.4225 & 0.33696 \tabularnewline
2 & 0.073072 & 0.6243 & 0.267181 \tabularnewline
3 & 0.250827 & 2.1431 & 0.017721 \tabularnewline
4 & -0.110957 & -0.948 & 0.173125 \tabularnewline
5 & 0.046588 & 0.3981 & 0.345877 \tabularnewline
6 & 0.157972 & 1.3497 & 0.09064 \tabularnewline
7 & -0.114228 & -0.976 & 0.166153 \tabularnewline
8 & 0.058164 & 0.497 & 0.310357 \tabularnewline
9 & 0.206868 & 1.7675 & 0.040664 \tabularnewline
10 & -0.120288 & -1.0277 & 0.153732 \tabularnewline
11 & -0.18138 & -1.5497 & 0.062768 \tabularnewline
12 & -0.210512 & -1.7986 & 0.038107 \tabularnewline
13 & -0.080539 & -0.6881 & 0.246777 \tabularnewline
14 & 0.093476 & 0.7987 & 0.21354 \tabularnewline
15 & -0.016977 & -0.1451 & 0.442534 \tabularnewline
16 & 0.00681 & 0.0582 & 0.476881 \tabularnewline
17 & 0.175175 & 1.4967 & 0.069392 \tabularnewline
18 & 0.030725 & 0.2625 & 0.396831 \tabularnewline
19 & -0.225262 & -1.9246 & 0.029086 \tabularnewline
20 & -0.072064 & -0.6157 & 0.269998 \tabularnewline
21 & 0.235937 & 2.0158 & 0.023749 \tabularnewline
22 & -0.106049 & -0.9061 & 0.183937 \tabularnewline
23 & -0.074847 & -0.6395 & 0.262253 \tabularnewline
24 & -0.336588 & -2.8758 & 0.002639 \tabularnewline
25 & 0.012041 & 0.1029 & 0.45917 \tabularnewline
26 & -0.069125 & -0.5906 & 0.278305 \tabularnewline
27 & 0.209117 & 1.7867 & 0.039069 \tabularnewline
28 & 0.073643 & 0.6292 & 0.26559 \tabularnewline
29 & 0.148989 & 1.273 & 0.103535 \tabularnewline
30 & 0.000767 & 0.0066 & 0.497394 \tabularnewline
31 & -0.020706 & -0.1769 & 0.430034 \tabularnewline
32 & 0.053252 & 0.455 & 0.325234 \tabularnewline
33 & 0.014594 & 0.1247 & 0.450554 \tabularnewline
34 & 0.028337 & 0.2421 & 0.404686 \tabularnewline
35 & 0.01195 & 0.1021 & 0.459478 \tabularnewline
36 & -0.008424 & -0.072 & 0.471411 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28187&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]0.049447[/C][C]0.4225[/C][C]0.33696[/C][/ROW]
[ROW][C]2[/C][C]0.073072[/C][C]0.6243[/C][C]0.267181[/C][/ROW]
[ROW][C]3[/C][C]0.250827[/C][C]2.1431[/C][C]0.017721[/C][/ROW]
[ROW][C]4[/C][C]-0.110957[/C][C]-0.948[/C][C]0.173125[/C][/ROW]
[ROW][C]5[/C][C]0.046588[/C][C]0.3981[/C][C]0.345877[/C][/ROW]
[ROW][C]6[/C][C]0.157972[/C][C]1.3497[/C][C]0.09064[/C][/ROW]
[ROW][C]7[/C][C]-0.114228[/C][C]-0.976[/C][C]0.166153[/C][/ROW]
[ROW][C]8[/C][C]0.058164[/C][C]0.497[/C][C]0.310357[/C][/ROW]
[ROW][C]9[/C][C]0.206868[/C][C]1.7675[/C][C]0.040664[/C][/ROW]
[ROW][C]10[/C][C]-0.120288[/C][C]-1.0277[/C][C]0.153732[/C][/ROW]
[ROW][C]11[/C][C]-0.18138[/C][C]-1.5497[/C][C]0.062768[/C][/ROW]
[ROW][C]12[/C][C]-0.210512[/C][C]-1.7986[/C][C]0.038107[/C][/ROW]
[ROW][C]13[/C][C]-0.080539[/C][C]-0.6881[/C][C]0.246777[/C][/ROW]
[ROW][C]14[/C][C]0.093476[/C][C]0.7987[/C][C]0.21354[/C][/ROW]
[ROW][C]15[/C][C]-0.016977[/C][C]-0.1451[/C][C]0.442534[/C][/ROW]
[ROW][C]16[/C][C]0.00681[/C][C]0.0582[/C][C]0.476881[/C][/ROW]
[ROW][C]17[/C][C]0.175175[/C][C]1.4967[/C][C]0.069392[/C][/ROW]
[ROW][C]18[/C][C]0.030725[/C][C]0.2625[/C][C]0.396831[/C][/ROW]
[ROW][C]19[/C][C]-0.225262[/C][C]-1.9246[/C][C]0.029086[/C][/ROW]
[ROW][C]20[/C][C]-0.072064[/C][C]-0.6157[/C][C]0.269998[/C][/ROW]
[ROW][C]21[/C][C]0.235937[/C][C]2.0158[/C][C]0.023749[/C][/ROW]
[ROW][C]22[/C][C]-0.106049[/C][C]-0.9061[/C][C]0.183937[/C][/ROW]
[ROW][C]23[/C][C]-0.074847[/C][C]-0.6395[/C][C]0.262253[/C][/ROW]
[ROW][C]24[/C][C]-0.336588[/C][C]-2.8758[/C][C]0.002639[/C][/ROW]
[ROW][C]25[/C][C]0.012041[/C][C]0.1029[/C][C]0.45917[/C][/ROW]
[ROW][C]26[/C][C]-0.069125[/C][C]-0.5906[/C][C]0.278305[/C][/ROW]
[ROW][C]27[/C][C]0.209117[/C][C]1.7867[/C][C]0.039069[/C][/ROW]
[ROW][C]28[/C][C]0.073643[/C][C]0.6292[/C][C]0.26559[/C][/ROW]
[ROW][C]29[/C][C]0.148989[/C][C]1.273[/C][C]0.103535[/C][/ROW]
[ROW][C]30[/C][C]0.000767[/C][C]0.0066[/C][C]0.497394[/C][/ROW]
[ROW][C]31[/C][C]-0.020706[/C][C]-0.1769[/C][C]0.430034[/C][/ROW]
[ROW][C]32[/C][C]0.053252[/C][C]0.455[/C][C]0.325234[/C][/ROW]
[ROW][C]33[/C][C]0.014594[/C][C]0.1247[/C][C]0.450554[/C][/ROW]
[ROW][C]34[/C][C]0.028337[/C][C]0.2421[/C][C]0.404686[/C][/ROW]
[ROW][C]35[/C][C]0.01195[/C][C]0.1021[/C][C]0.459478[/C][/ROW]
[ROW][C]36[/C][C]-0.008424[/C][C]-0.072[/C][C]0.471411[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28187&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28187&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	0.049447	0.4225	0.33696
2	0.073072	0.6243	0.267181
3	0.250827	2.1431	0.017721
4	-0.110957	-0.948	0.173125
5	0.046588	0.3981	0.345877
6	0.157972	1.3497	0.09064
7	-0.114228	-0.976	0.166153
8	0.058164	0.497	0.310357
9	0.206868	1.7675	0.040664
10	-0.120288	-1.0277	0.153732
11	-0.18138	-1.5497	0.062768
12	-0.210512	-1.7986	0.038107
13	-0.080539	-0.6881	0.246777
14	0.093476	0.7987	0.21354
15	-0.016977	-0.1451	0.442534
16	0.00681	0.0582	0.476881
17	0.175175	1.4967	0.069392
18	0.030725	0.2625	0.396831
19	-0.225262	-1.9246	0.029086
20	-0.072064	-0.6157	0.269998
21	0.235937	2.0158	0.023749
22	-0.106049	-0.9061	0.183937
23	-0.074847	-0.6395	0.262253
24	-0.336588	-2.8758	0.002639
25	0.012041	0.1029	0.45917
26	-0.069125	-0.5906	0.278305
27	0.209117	1.7867	0.039069
28	0.073643	0.6292	0.26559
29	0.148989	1.273	0.103535
30	0.000767	0.0066	0.497394
31	-0.020706	-0.1769	0.430034
32	0.053252	0.455	0.325234
33	0.014594	0.1247	0.450554
34	0.028337	0.2421	0.404686
35	0.01195	0.1021	0.459478
36	-0.008424	-0.072	0.471411

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 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