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rwasp_autocorrelation.wasp

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(Partial) Autocorrelation Function

Date of computation

Sun, 07 Dec 2008 06:17:10 -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/07/t12286558672k5gd7n4sbe02ef.htm/, Retrieved Sun, 19 May 2024 09:18:20 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29942, Retrieved Sun, 19 May 2024 09:18:20 +0000

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187

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

F       [(Partial) Autocorrelation Function] [] [2008-12-07 13:17:10] [19ef54504342c1b076371d395a2ab19f] [Current]
F         [(Partial) Autocorrelation Function] [] [2008-12-08 19:35:49] [ffbe22449df335faef31f462015daa42] 

Feedback Forum

2008-12-16 08:10:59 [Glenn De Maeyer] [reply] 
p: Wanneer we de autocorrelatiefunctie in beschouwing nemen merken we een duidelijk patroon over de eerste 6 lags. We merken dat ze alle 6 positief zijn. Om vervolgens de orde te bepalen dienen we naar de Partial Correlation te kijken. Hier kunnen we vaststellen dat zowel lag 1 als lag 2 significant zijn (lag 2 overschrijdt het betrouwbaarheidsinterval niet, maar we mogen deze uitrekken tot buiten het betrouwbaarheidsinterval). We kunnen dus p gelijk stellen aan 2. 
 
P: We bekijken lag 12, vervolgens lag 24 en lag 36 en kunnen geen patroon vaststellen. P is dus in dit geval gelijk aan 0. 
 
q: Ook q is gelijk aan 0 want we wanneer we de eerste 6 lags van de partial autcorrelation function bekijken kunnen we geen vast patroon vaststellen. 
 
Q: We stelen negatieve lags 12, 24 en 36 vast. Wanneer we vervolgens de autocorrelatiefunctie bekijken om de orde te bepalen merken we dat enkel lag 12 significant verschillend is van 0. Q stellen we dus gelijk aan 1. 

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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	'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29942&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29942&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29942&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	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.187552	3.5536	0.000215
2	0.317794	6.0213	0
3	0.179563	3.4022	0.000372
4	0.155303	2.9426	0.001733
5	0.127596	2.4176	0.008061
6	0.06371	1.2071	0.114087
7	-0.054701	-1.0364	0.150347
8	-0.011735	-0.2224	0.412083
9	-0.080833	-1.5316	0.063255
10	-0.174708	-3.3102	0.000513
11	-0.055263	-1.0471	0.147883
12	-0.480698	-9.1079	0
13	-0.168514	-3.1929	0.000767
14	-0.172913	-3.2762	0.000577
15	-0.128287	-2.4307	0.007779
16	-0.163167	-3.0916	0.001073
17	-0.121097	-2.2945	0.01117
18	-0.103099	-1.9534	0.025772
19	0.020128	0.3814	0.351578
20	-0.002775	-0.0526	0.479049
21	-0.006426	-0.1217	0.451583
22	-0.006358	-0.1205	0.45209
23	-0.004364	-0.0827	0.467075
24	-0.006343	-0.1202	0.452205
25	0.094911	1.7983	0.036484
26	-0.008505	-0.1611	0.436036
27	0.017661	0.3346	0.369052
28	0.077035	1.4596	0.072638
29	0.068023	1.2888	0.09914
30	0.041632	0.7888	0.215369
31	0.032895	0.6233	0.266752
32	-0.068171	-1.2917	0.098653
33	0.011323	0.2145	0.415122
34	0.002674	0.0507	0.479811
35	-0.0721	-1.3661	0.08638
36	-0.031172	-0.5906	0.277571

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.187552 & 3.5536 & 0.000215 \tabularnewline
2 & 0.317794 & 6.0213 & 0 \tabularnewline
3 & 0.179563 & 3.4022 & 0.000372 \tabularnewline
4 & 0.155303 & 2.9426 & 0.001733 \tabularnewline
5 & 0.127596 & 2.4176 & 0.008061 \tabularnewline
6 & 0.06371 & 1.2071 & 0.114087 \tabularnewline
7 & -0.054701 & -1.0364 & 0.150347 \tabularnewline
8 & -0.011735 & -0.2224 & 0.412083 \tabularnewline
9 & -0.080833 & -1.5316 & 0.063255 \tabularnewline
10 & -0.174708 & -3.3102 & 0.000513 \tabularnewline
11 & -0.055263 & -1.0471 & 0.147883 \tabularnewline
12 & -0.480698 & -9.1079 & 0 \tabularnewline
13 & -0.168514 & -3.1929 & 0.000767 \tabularnewline
14 & -0.172913 & -3.2762 & 0.000577 \tabularnewline
15 & -0.128287 & -2.4307 & 0.007779 \tabularnewline
16 & -0.163167 & -3.0916 & 0.001073 \tabularnewline
17 & -0.121097 & -2.2945 & 0.01117 \tabularnewline
18 & -0.103099 & -1.9534 & 0.025772 \tabularnewline
19 & 0.020128 & 0.3814 & 0.351578 \tabularnewline
20 & -0.002775 & -0.0526 & 0.479049 \tabularnewline
21 & -0.006426 & -0.1217 & 0.451583 \tabularnewline
22 & -0.006358 & -0.1205 & 0.45209 \tabularnewline
23 & -0.004364 & -0.0827 & 0.467075 \tabularnewline
24 & -0.006343 & -0.1202 & 0.452205 \tabularnewline
25 & 0.094911 & 1.7983 & 0.036484 \tabularnewline
26 & -0.008505 & -0.1611 & 0.436036 \tabularnewline
27 & 0.017661 & 0.3346 & 0.369052 \tabularnewline
28 & 0.077035 & 1.4596 & 0.072638 \tabularnewline
29 & 0.068023 & 1.2888 & 0.09914 \tabularnewline
30 & 0.041632 & 0.7888 & 0.215369 \tabularnewline
31 & 0.032895 & 0.6233 & 0.266752 \tabularnewline
32 & -0.068171 & -1.2917 & 0.098653 \tabularnewline
33 & 0.011323 & 0.2145 & 0.415122 \tabularnewline
34 & 0.002674 & 0.0507 & 0.479811 \tabularnewline
35 & -0.0721 & -1.3661 & 0.08638 \tabularnewline
36 & -0.031172 & -0.5906 & 0.277571 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29942&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]0.187552[/C][C]3.5536[/C][C]0.000215[/C][/ROW]
[ROW][C]2[/C][C]0.317794[/C][C]6.0213[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.179563[/C][C]3.4022[/C][C]0.000372[/C][/ROW]
[ROW][C]4[/C][C]0.155303[/C][C]2.9426[/C][C]0.001733[/C][/ROW]
[ROW][C]5[/C][C]0.127596[/C][C]2.4176[/C][C]0.008061[/C][/ROW]
[ROW][C]6[/C][C]0.06371[/C][C]1.2071[/C][C]0.114087[/C][/ROW]
[ROW][C]7[/C][C]-0.054701[/C][C]-1.0364[/C][C]0.150347[/C][/ROW]
[ROW][C]8[/C][C]-0.011735[/C][C]-0.2224[/C][C]0.412083[/C][/ROW]
[ROW][C]9[/C][C]-0.080833[/C][C]-1.5316[/C][C]0.063255[/C][/ROW]
[ROW][C]10[/C][C]-0.174708[/C][C]-3.3102[/C][C]0.000513[/C][/ROW]
[ROW][C]11[/C][C]-0.055263[/C][C]-1.0471[/C][C]0.147883[/C][/ROW]
[ROW][C]12[/C][C]-0.480698[/C][C]-9.1079[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.168514[/C][C]-3.1929[/C][C]0.000767[/C][/ROW]
[ROW][C]14[/C][C]-0.172913[/C][C]-3.2762[/C][C]0.000577[/C][/ROW]
[ROW][C]15[/C][C]-0.128287[/C][C]-2.4307[/C][C]0.007779[/C][/ROW]
[ROW][C]16[/C][C]-0.163167[/C][C]-3.0916[/C][C]0.001073[/C][/ROW]
[ROW][C]17[/C][C]-0.121097[/C][C]-2.2945[/C][C]0.01117[/C][/ROW]
[ROW][C]18[/C][C]-0.103099[/C][C]-1.9534[/C][C]0.025772[/C][/ROW]
[ROW][C]19[/C][C]0.020128[/C][C]0.3814[/C][C]0.351578[/C][/ROW]
[ROW][C]20[/C][C]-0.002775[/C][C]-0.0526[/C][C]0.479049[/C][/ROW]
[ROW][C]21[/C][C]-0.006426[/C][C]-0.1217[/C][C]0.451583[/C][/ROW]
[ROW][C]22[/C][C]-0.006358[/C][C]-0.1205[/C][C]0.45209[/C][/ROW]
[ROW][C]23[/C][C]-0.004364[/C][C]-0.0827[/C][C]0.467075[/C][/ROW]
[ROW][C]24[/C][C]-0.006343[/C][C]-0.1202[/C][C]0.452205[/C][/ROW]
[ROW][C]25[/C][C]0.094911[/C][C]1.7983[/C][C]0.036484[/C][/ROW]
[ROW][C]26[/C][C]-0.008505[/C][C]-0.1611[/C][C]0.436036[/C][/ROW]
[ROW][C]27[/C][C]0.017661[/C][C]0.3346[/C][C]0.369052[/C][/ROW]
[ROW][C]28[/C][C]0.077035[/C][C]1.4596[/C][C]0.072638[/C][/ROW]
[ROW][C]29[/C][C]0.068023[/C][C]1.2888[/C][C]0.09914[/C][/ROW]
[ROW][C]30[/C][C]0.041632[/C][C]0.7888[/C][C]0.215369[/C][/ROW]
[ROW][C]31[/C][C]0.032895[/C][C]0.6233[/C][C]0.266752[/C][/ROW]
[ROW][C]32[/C][C]-0.068171[/C][C]-1.2917[/C][C]0.098653[/C][/ROW]
[ROW][C]33[/C][C]0.011323[/C][C]0.2145[/C][C]0.415122[/C][/ROW]
[ROW][C]34[/C][C]0.002674[/C][C]0.0507[/C][C]0.479811[/C][/ROW]
[ROW][C]35[/C][C]-0.0721[/C][C]-1.3661[/C][C]0.08638[/C][/ROW]
[ROW][C]36[/C][C]-0.031172[/C][C]-0.5906[/C][C]0.277571[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29942&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29942&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	0.187552	3.5536	0.000215
2	0.317794	6.0213	0
3	0.179563	3.4022	0.000372
4	0.155303	2.9426	0.001733
5	0.127596	2.4176	0.008061
6	0.06371	1.2071	0.114087
7	-0.054701	-1.0364	0.150347
8	-0.011735	-0.2224	0.412083
9	-0.080833	-1.5316	0.063255
10	-0.174708	-3.3102	0.000513
11	-0.055263	-1.0471	0.147883
12	-0.480698	-9.1079	0
13	-0.168514	-3.1929	0.000767
14	-0.172913	-3.2762	0.000577
15	-0.128287	-2.4307	0.007779
16	-0.163167	-3.0916	0.001073
17	-0.121097	-2.2945	0.01117
18	-0.103099	-1.9534	0.025772
19	0.020128	0.3814	0.351578
20	-0.002775	-0.0526	0.479049
21	-0.006426	-0.1217	0.451583
22	-0.006358	-0.1205	0.45209
23	-0.004364	-0.0827	0.467075
24	-0.006343	-0.1202	0.452205
25	0.094911	1.7983	0.036484
26	-0.008505	-0.1611	0.436036
27	0.017661	0.3346	0.369052
28	0.077035	1.4596	0.072638
29	0.068023	1.2888	0.09914
30	0.041632	0.7888	0.215369
31	0.032895	0.6233	0.266752
32	-0.068171	-1.2917	0.098653
33	0.011323	0.2145	0.415122
34	0.002674	0.0507	0.479811
35	-0.0721	-1.3661	0.08638
36	-0.031172	-0.5906	0.277571

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.187552	3.5536	0.000215
2	0.292922	5.5501	0
3	0.093512	1.7718	0.038638
4	0.033995	0.6441	0.259959
5	0.032214	0.6104	0.271005
6	-0.024285	-0.4601	0.322846
7	-0.139405	-2.6414	0.004309
8	-0.030697	-0.5816	0.280592
9	-0.045877	-0.8693	0.192645
10	-0.156693	-2.9689	0.001595
11	0.037591	0.7122	0.238389
12	-0.427945	-8.1084	0
13	-0.036401	-0.6897	0.245414
14	0.123319	2.3366	0.010006
15	0.047112	0.8926	0.186322
16	-0.060609	-1.1484	0.125789
17	-0.017722	-0.3358	0.368615
18	0.007818	0.1481	0.44116
19	0.023368	0.4428	0.329106
20	0.047983	0.9091	0.181941
21	-0.03962	-0.7507	0.226664
22	-0.157258	-2.9796	0.001541
23	0.010195	0.1932	0.42347
24	-0.263321	-4.9892	0
25	0.056986	1.0797	0.140495
26	0.017452	0.3307	0.370544
27	-0.01152	-0.2183	0.413674
28	0.033761	0.6397	0.261394
29	0.035746	0.6773	0.249331
30	-0.027638	-0.5237	0.300414
31	0.037568	0.7118	0.238523
32	-0.076586	-1.4511	0.073812
33	-0.04242	-0.8037	0.211038
34	-0.086262	-1.6344	0.051522
35	-0.078156	-1.4808	0.069763
36	-0.219062	-4.1506	2.1e-05

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.187552 & 3.5536 & 0.000215 \tabularnewline
2 & 0.292922 & 5.5501 & 0 \tabularnewline
3 & 0.093512 & 1.7718 & 0.038638 \tabularnewline
4 & 0.033995 & 0.6441 & 0.259959 \tabularnewline
5 & 0.032214 & 0.6104 & 0.271005 \tabularnewline
6 & -0.024285 & -0.4601 & 0.322846 \tabularnewline
7 & -0.139405 & -2.6414 & 0.004309 \tabularnewline
8 & -0.030697 & -0.5816 & 0.280592 \tabularnewline
9 & -0.045877 & -0.8693 & 0.192645 \tabularnewline
10 & -0.156693 & -2.9689 & 0.001595 \tabularnewline
11 & 0.037591 & 0.7122 & 0.238389 \tabularnewline
12 & -0.427945 & -8.1084 & 0 \tabularnewline
13 & -0.036401 & -0.6897 & 0.245414 \tabularnewline
14 & 0.123319 & 2.3366 & 0.010006 \tabularnewline
15 & 0.047112 & 0.8926 & 0.186322 \tabularnewline
16 & -0.060609 & -1.1484 & 0.125789 \tabularnewline
17 & -0.017722 & -0.3358 & 0.368615 \tabularnewline
18 & 0.007818 & 0.1481 & 0.44116 \tabularnewline
19 & 0.023368 & 0.4428 & 0.329106 \tabularnewline
20 & 0.047983 & 0.9091 & 0.181941 \tabularnewline
21 & -0.03962 & -0.7507 & 0.226664 \tabularnewline
22 & -0.157258 & -2.9796 & 0.001541 \tabularnewline
23 & 0.010195 & 0.1932 & 0.42347 \tabularnewline
24 & -0.263321 & -4.9892 & 0 \tabularnewline
25 & 0.056986 & 1.0797 & 0.140495 \tabularnewline
26 & 0.017452 & 0.3307 & 0.370544 \tabularnewline
27 & -0.01152 & -0.2183 & 0.413674 \tabularnewline
28 & 0.033761 & 0.6397 & 0.261394 \tabularnewline
29 & 0.035746 & 0.6773 & 0.249331 \tabularnewline
30 & -0.027638 & -0.5237 & 0.300414 \tabularnewline
31 & 0.037568 & 0.7118 & 0.238523 \tabularnewline
32 & -0.076586 & -1.4511 & 0.073812 \tabularnewline
33 & -0.04242 & -0.8037 & 0.211038 \tabularnewline
34 & -0.086262 & -1.6344 & 0.051522 \tabularnewline
35 & -0.078156 & -1.4808 & 0.069763 \tabularnewline
36 & -0.219062 & -4.1506 & 2.1e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29942&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]0.187552[/C][C]3.5536[/C][C]0.000215[/C][/ROW]
[ROW][C]2[/C][C]0.292922[/C][C]5.5501[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.093512[/C][C]1.7718[/C][C]0.038638[/C][/ROW]
[ROW][C]4[/C][C]0.033995[/C][C]0.6441[/C][C]0.259959[/C][/ROW]
[ROW][C]5[/C][C]0.032214[/C][C]0.6104[/C][C]0.271005[/C][/ROW]
[ROW][C]6[/C][C]-0.024285[/C][C]-0.4601[/C][C]0.322846[/C][/ROW]
[ROW][C]7[/C][C]-0.139405[/C][C]-2.6414[/C][C]0.004309[/C][/ROW]
[ROW][C]8[/C][C]-0.030697[/C][C]-0.5816[/C][C]0.280592[/C][/ROW]
[ROW][C]9[/C][C]-0.045877[/C][C]-0.8693[/C][C]0.192645[/C][/ROW]
[ROW][C]10[/C][C]-0.156693[/C][C]-2.9689[/C][C]0.001595[/C][/ROW]
[ROW][C]11[/C][C]0.037591[/C][C]0.7122[/C][C]0.238389[/C][/ROW]
[ROW][C]12[/C][C]-0.427945[/C][C]-8.1084[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.036401[/C][C]-0.6897[/C][C]0.245414[/C][/ROW]
[ROW][C]14[/C][C]0.123319[/C][C]2.3366[/C][C]0.010006[/C][/ROW]
[ROW][C]15[/C][C]0.047112[/C][C]0.8926[/C][C]0.186322[/C][/ROW]
[ROW][C]16[/C][C]-0.060609[/C][C]-1.1484[/C][C]0.125789[/C][/ROW]
[ROW][C]17[/C][C]-0.017722[/C][C]-0.3358[/C][C]0.368615[/C][/ROW]
[ROW][C]18[/C][C]0.007818[/C][C]0.1481[/C][C]0.44116[/C][/ROW]
[ROW][C]19[/C][C]0.023368[/C][C]0.4428[/C][C]0.329106[/C][/ROW]
[ROW][C]20[/C][C]0.047983[/C][C]0.9091[/C][C]0.181941[/C][/ROW]
[ROW][C]21[/C][C]-0.03962[/C][C]-0.7507[/C][C]0.226664[/C][/ROW]
[ROW][C]22[/C][C]-0.157258[/C][C]-2.9796[/C][C]0.001541[/C][/ROW]
[ROW][C]23[/C][C]0.010195[/C][C]0.1932[/C][C]0.42347[/C][/ROW]
[ROW][C]24[/C][C]-0.263321[/C][C]-4.9892[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.056986[/C][C]1.0797[/C][C]0.140495[/C][/ROW]
[ROW][C]26[/C][C]0.017452[/C][C]0.3307[/C][C]0.370544[/C][/ROW]
[ROW][C]27[/C][C]-0.01152[/C][C]-0.2183[/C][C]0.413674[/C][/ROW]
[ROW][C]28[/C][C]0.033761[/C][C]0.6397[/C][C]0.261394[/C][/ROW]
[ROW][C]29[/C][C]0.035746[/C][C]0.6773[/C][C]0.249331[/C][/ROW]
[ROW][C]30[/C][C]-0.027638[/C][C]-0.5237[/C][C]0.300414[/C][/ROW]
[ROW][C]31[/C][C]0.037568[/C][C]0.7118[/C][C]0.238523[/C][/ROW]
[ROW][C]32[/C][C]-0.076586[/C][C]-1.4511[/C][C]0.073812[/C][/ROW]
[ROW][C]33[/C][C]-0.04242[/C][C]-0.8037[/C][C]0.211038[/C][/ROW]
[ROW][C]34[/C][C]-0.086262[/C][C]-1.6344[/C][C]0.051522[/C][/ROW]
[ROW][C]35[/C][C]-0.078156[/C][C]-1.4808[/C][C]0.069763[/C][/ROW]
[ROW][C]36[/C][C]-0.219062[/C][C]-4.1506[/C][C]2.1e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29942&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29942&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	0.187552	3.5536	0.000215
2	0.292922	5.5501	0
3	0.093512	1.7718	0.038638
4	0.033995	0.6441	0.259959
5	0.032214	0.6104	0.271005
6	-0.024285	-0.4601	0.322846
7	-0.139405	-2.6414	0.004309
8	-0.030697	-0.5816	0.280592
9	-0.045877	-0.8693	0.192645
10	-0.156693	-2.9689	0.001595
11	0.037591	0.7122	0.238389
12	-0.427945	-8.1084	0
13	-0.036401	-0.6897	0.245414
14	0.123319	2.3366	0.010006
15	0.047112	0.8926	0.186322
16	-0.060609	-1.1484	0.125789
17	-0.017722	-0.3358	0.368615
18	0.007818	0.1481	0.44116
19	0.023368	0.4428	0.329106
20	0.047983	0.9091	0.181941
21	-0.03962	-0.7507	0.226664
22	-0.157258	-2.9796	0.001541
23	0.010195	0.1932	0.42347
24	-0.263321	-4.9892	0
25	0.056986	1.0797	0.140495
26	0.017452	0.3307	0.370544
27	-0.01152	-0.2183	0.413674
28	0.033761	0.6397	0.261394
29	0.035746	0.6773	0.249331
30	-0.027638	-0.5237	0.300414
31	0.037568	0.7118	0.238523
32	-0.076586	-1.4511	0.073812
33	-0.04242	-0.8037	0.211038
34	-0.086262	-1.6344	0.051522
35	-0.078156	-1.4808	0.069763
36	-0.219062	-4.1506	2.1e-05

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 36 ; par2 = 0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;

Parameters (R input):

par1 = 36 ; par2 = 0.5 ; par3 = 1 ; 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