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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Sat, 06 Dec 2008 11:22:51 -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/06/t1228587810i1c62cpt2g8dhh2.htm/, Retrieved Sat, 18 May 2024 05:51:22 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29794, Retrieved Sat, 18 May 2024 05:51:22 +0000

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User-defined keywords

Estimated Impact

202

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMP   [Variance Reduction Matrix] [step 2] [2008-12-06 09:12:19] [9f5bfe3b95f9ec3d2ed4c0a560a9648a]
F RMPD    [(Partial) Autocorrelation Function] [step 2] [2008-12-06 18:17:03] [9f5bfe3b95f9ec3d2ed4c0a560a9648a]
F   P         [(Partial) Autocorrelation Function] [step 3] [2008-12-06 18:22:51] [a9e6d7cd6e144e8b311d9f96a24c5a25] [Current]

Feedback Forum

2008-12-13 11:26:44 [Ken Wright] [reply] 
volledig correct, seizoenaliteit en niet seizoenaliteit zijn volledig verdwenen: het langzaam dalende trend is weg een ook de hangmattenstructuur is weg
2008-12-16 19:11:16 [Kevin Vermeiren] [reply] 
Het klopt dat de lambda waarde op -0.1 ingesteld moet worden en d=1 en D=1. De student geeft hier een goede conclusie maar wel een zeer beperkte. Er is nu duidelijk geen patroon te herkennen in de autocorrelatie coëfficiënten en alsook niet in de seizoenale autocorrelatie coëfficiënten. Bijgevolg is de transformatie met lambda op -0.5 en de differentiatie met d=1 en D=1 voldoende.

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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	'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=29794&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=29794&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29794&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	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.449656	-3.9966	7.2e-05
2	-0.117433	-1.0438	0.149888
3	0.299291	2.6602	0.004727
4	-0.198313	-1.7626	0.040914
5	0.007989	0.071	0.471784
6	0.176299	1.567	0.060558
7	-0.198396	-1.7634	0.040851
8	-0.075577	-0.6717	0.251854
9	0.294694	2.6193	0.00528
10	-0.203844	-1.8118	0.036908
11	-0.00504	-0.0448	0.482191
12	0.036714	0.3263	0.372521
13	-0.118145	-1.0501	0.148439
14	0.047995	0.4266	0.33542
15	0.035756	0.3178	0.375737
16	-0.188857	-1.6786	0.048591
17	0.160793	1.4292	0.07845
18	0.076284	0.678	0.249867
19	-0.199247	-1.7709	0.040213
20	0.188347	1.6741	0.049036
21	0.039227	0.3487	0.364139
22	-0.216762	-1.9266	0.028812
23	0.308746	2.7442	0.003752
24	-0.229651	-2.0412	0.022286
25	0.000743	0.0066	0.497374
26	0.246713	2.1928	0.015631
27	-0.147259	-1.3089	0.097187
28	-0.122509	-1.0889	0.139758
29	0.207575	1.845	0.034395
30	-0.110852	-0.9853	0.163749
31	-0.031765	-0.2823	0.389212
32	0.09285	0.8253	0.205853
33	-0.181861	-1.6164	0.054996
34	0.096621	0.8588	0.196529
35	0.060215	0.5352	0.297007
36	-0.121311	-1.0782	0.142106

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.449656 & -3.9966 & 7.2e-05 \tabularnewline
2 & -0.117433 & -1.0438 & 0.149888 \tabularnewline
3 & 0.299291 & 2.6602 & 0.004727 \tabularnewline
4 & -0.198313 & -1.7626 & 0.040914 \tabularnewline
5 & 0.007989 & 0.071 & 0.471784 \tabularnewline
6 & 0.176299 & 1.567 & 0.060558 \tabularnewline
7 & -0.198396 & -1.7634 & 0.040851 \tabularnewline
8 & -0.075577 & -0.6717 & 0.251854 \tabularnewline
9 & 0.294694 & 2.6193 & 0.00528 \tabularnewline
10 & -0.203844 & -1.8118 & 0.036908 \tabularnewline
11 & -0.00504 & -0.0448 & 0.482191 \tabularnewline
12 & 0.036714 & 0.3263 & 0.372521 \tabularnewline
13 & -0.118145 & -1.0501 & 0.148439 \tabularnewline
14 & 0.047995 & 0.4266 & 0.33542 \tabularnewline
15 & 0.035756 & 0.3178 & 0.375737 \tabularnewline
16 & -0.188857 & -1.6786 & 0.048591 \tabularnewline
17 & 0.160793 & 1.4292 & 0.07845 \tabularnewline
18 & 0.076284 & 0.678 & 0.249867 \tabularnewline
19 & -0.199247 & -1.7709 & 0.040213 \tabularnewline
20 & 0.188347 & 1.6741 & 0.049036 \tabularnewline
21 & 0.039227 & 0.3487 & 0.364139 \tabularnewline
22 & -0.216762 & -1.9266 & 0.028812 \tabularnewline
23 & 0.308746 & 2.7442 & 0.003752 \tabularnewline
24 & -0.229651 & -2.0412 & 0.022286 \tabularnewline
25 & 0.000743 & 0.0066 & 0.497374 \tabularnewline
26 & 0.246713 & 2.1928 & 0.015631 \tabularnewline
27 & -0.147259 & -1.3089 & 0.097187 \tabularnewline
28 & -0.122509 & -1.0889 & 0.139758 \tabularnewline
29 & 0.207575 & 1.845 & 0.034395 \tabularnewline
30 & -0.110852 & -0.9853 & 0.163749 \tabularnewline
31 & -0.031765 & -0.2823 & 0.389212 \tabularnewline
32 & 0.09285 & 0.8253 & 0.205853 \tabularnewline
33 & -0.181861 & -1.6164 & 0.054996 \tabularnewline
34 & 0.096621 & 0.8588 & 0.196529 \tabularnewline
35 & 0.060215 & 0.5352 & 0.297007 \tabularnewline
36 & -0.121311 & -1.0782 & 0.142106 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29794&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]-0.449656[/C][C]-3.9966[/C][C]7.2e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.117433[/C][C]-1.0438[/C][C]0.149888[/C][/ROW]
[ROW][C]3[/C][C]0.299291[/C][C]2.6602[/C][C]0.004727[/C][/ROW]
[ROW][C]4[/C][C]-0.198313[/C][C]-1.7626[/C][C]0.040914[/C][/ROW]
[ROW][C]5[/C][C]0.007989[/C][C]0.071[/C][C]0.471784[/C][/ROW]
[ROW][C]6[/C][C]0.176299[/C][C]1.567[/C][C]0.060558[/C][/ROW]
[ROW][C]7[/C][C]-0.198396[/C][C]-1.7634[/C][C]0.040851[/C][/ROW]
[ROW][C]8[/C][C]-0.075577[/C][C]-0.6717[/C][C]0.251854[/C][/ROW]
[ROW][C]9[/C][C]0.294694[/C][C]2.6193[/C][C]0.00528[/C][/ROW]
[ROW][C]10[/C][C]-0.203844[/C][C]-1.8118[/C][C]0.036908[/C][/ROW]
[ROW][C]11[/C][C]-0.00504[/C][C]-0.0448[/C][C]0.482191[/C][/ROW]
[ROW][C]12[/C][C]0.036714[/C][C]0.3263[/C][C]0.372521[/C][/ROW]
[ROW][C]13[/C][C]-0.118145[/C][C]-1.0501[/C][C]0.148439[/C][/ROW]
[ROW][C]14[/C][C]0.047995[/C][C]0.4266[/C][C]0.33542[/C][/ROW]
[ROW][C]15[/C][C]0.035756[/C][C]0.3178[/C][C]0.375737[/C][/ROW]
[ROW][C]16[/C][C]-0.188857[/C][C]-1.6786[/C][C]0.048591[/C][/ROW]
[ROW][C]17[/C][C]0.160793[/C][C]1.4292[/C][C]0.07845[/C][/ROW]
[ROW][C]18[/C][C]0.076284[/C][C]0.678[/C][C]0.249867[/C][/ROW]
[ROW][C]19[/C][C]-0.199247[/C][C]-1.7709[/C][C]0.040213[/C][/ROW]
[ROW][C]20[/C][C]0.188347[/C][C]1.6741[/C][C]0.049036[/C][/ROW]
[ROW][C]21[/C][C]0.039227[/C][C]0.3487[/C][C]0.364139[/C][/ROW]
[ROW][C]22[/C][C]-0.216762[/C][C]-1.9266[/C][C]0.028812[/C][/ROW]
[ROW][C]23[/C][C]0.308746[/C][C]2.7442[/C][C]0.003752[/C][/ROW]
[ROW][C]24[/C][C]-0.229651[/C][C]-2.0412[/C][C]0.022286[/C][/ROW]
[ROW][C]25[/C][C]0.000743[/C][C]0.0066[/C][C]0.497374[/C][/ROW]
[ROW][C]26[/C][C]0.246713[/C][C]2.1928[/C][C]0.015631[/C][/ROW]
[ROW][C]27[/C][C]-0.147259[/C][C]-1.3089[/C][C]0.097187[/C][/ROW]
[ROW][C]28[/C][C]-0.122509[/C][C]-1.0889[/C][C]0.139758[/C][/ROW]
[ROW][C]29[/C][C]0.207575[/C][C]1.845[/C][C]0.034395[/C][/ROW]
[ROW][C]30[/C][C]-0.110852[/C][C]-0.9853[/C][C]0.163749[/C][/ROW]
[ROW][C]31[/C][C]-0.031765[/C][C]-0.2823[/C][C]0.389212[/C][/ROW]
[ROW][C]32[/C][C]0.09285[/C][C]0.8253[/C][C]0.205853[/C][/ROW]
[ROW][C]33[/C][C]-0.181861[/C][C]-1.6164[/C][C]0.054996[/C][/ROW]
[ROW][C]34[/C][C]0.096621[/C][C]0.8588[/C][C]0.196529[/C][/ROW]
[ROW][C]35[/C][C]0.060215[/C][C]0.5352[/C][C]0.297007[/C][/ROW]
[ROW][C]36[/C][C]-0.121311[/C][C]-1.0782[/C][C]0.142106[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29794&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29794&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	-0.449656	-3.9966	7.2e-05
2	-0.117433	-1.0438	0.149888
3	0.299291	2.6602	0.004727
4	-0.198313	-1.7626	0.040914
5	0.007989	0.071	0.471784
6	0.176299	1.567	0.060558
7	-0.198396	-1.7634	0.040851
8	-0.075577	-0.6717	0.251854
9	0.294694	2.6193	0.00528
10	-0.203844	-1.8118	0.036908
11	-0.00504	-0.0448	0.482191
12	0.036714	0.3263	0.372521
13	-0.118145	-1.0501	0.148439
14	0.047995	0.4266	0.33542
15	0.035756	0.3178	0.375737
16	-0.188857	-1.6786	0.048591
17	0.160793	1.4292	0.07845
18	0.076284	0.678	0.249867
19	-0.199247	-1.7709	0.040213
20	0.188347	1.6741	0.049036
21	0.039227	0.3487	0.364139
22	-0.216762	-1.9266	0.028812
23	0.308746	2.7442	0.003752
24	-0.229651	-2.0412	0.022286
25	0.000743	0.0066	0.497374
26	0.246713	2.1928	0.015631
27	-0.147259	-1.3089	0.097187
28	-0.122509	-1.0889	0.139758
29	0.207575	1.845	0.034395
30	-0.110852	-0.9853	0.163749
31	-0.031765	-0.2823	0.389212
32	0.09285	0.8253	0.205853
33	-0.181861	-1.6164	0.054996
34	0.096621	0.8588	0.196529
35	0.060215	0.5352	0.297007
36	-0.121311	-1.0782	0.142106

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.449656	-3.9966	7.2e-05
2	-0.400626	-3.5608	0.000315
3	0.06747	0.5997	0.275216
4	-0.044439	-0.395	0.346961
5	-0.021353	-0.1898	0.424981
6	0.121761	1.0822	0.14122
7	-0.030465	-0.2708	0.393633
8	-0.221987	-1.9731	0.025993
9	0.094235	0.8376	0.202397
10	0.029095	0.2586	0.398309
11	0.013834	0.123	0.451227
12	-0.151818	-1.3494	0.090534
13	-0.156863	-1.3942	0.083579
14	-0.128828	-1.145	0.127823
15	-0.094335	-0.8385	0.202149
16	-0.227133	-2.0188	0.02345
17	0.008906	0.0792	0.468553
18	0.118904	1.0568	0.146903
19	-0.035894	-0.319	0.375271
20	0.038585	0.3429	0.366274
21	0.200431	1.7815	0.03934
22	-0.023748	-0.2111	0.416686
23	0.17661	1.5697	0.060236
24	-0.164434	-1.4615	0.07392
25	0.015496	0.1377	0.445401
26	0.070055	0.6227	0.267651
27	0.054176	0.4815	0.315738
28	-0.167703	-1.4906	0.070028
29	-0.022933	-0.2038	0.419505
30	-0.060265	-0.5357	0.296852
31	0.071342	0.6341	0.263924
32	-0.095222	-0.8463	0.199957
33	0.025816	0.2295	0.409554
34	0.077189	0.6861	0.247338
35	0.048271	0.429	0.334529
36	-0.084375	-0.7499	0.227759

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.449656 & -3.9966 & 7.2e-05 \tabularnewline
2 & -0.400626 & -3.5608 & 0.000315 \tabularnewline
3 & 0.06747 & 0.5997 & 0.275216 \tabularnewline
4 & -0.044439 & -0.395 & 0.346961 \tabularnewline
5 & -0.021353 & -0.1898 & 0.424981 \tabularnewline
6 & 0.121761 & 1.0822 & 0.14122 \tabularnewline
7 & -0.030465 & -0.2708 & 0.393633 \tabularnewline
8 & -0.221987 & -1.9731 & 0.025993 \tabularnewline
9 & 0.094235 & 0.8376 & 0.202397 \tabularnewline
10 & 0.029095 & 0.2586 & 0.398309 \tabularnewline
11 & 0.013834 & 0.123 & 0.451227 \tabularnewline
12 & -0.151818 & -1.3494 & 0.090534 \tabularnewline
13 & -0.156863 & -1.3942 & 0.083579 \tabularnewline
14 & -0.128828 & -1.145 & 0.127823 \tabularnewline
15 & -0.094335 & -0.8385 & 0.202149 \tabularnewline
16 & -0.227133 & -2.0188 & 0.02345 \tabularnewline
17 & 0.008906 & 0.0792 & 0.468553 \tabularnewline
18 & 0.118904 & 1.0568 & 0.146903 \tabularnewline
19 & -0.035894 & -0.319 & 0.375271 \tabularnewline
20 & 0.038585 & 0.3429 & 0.366274 \tabularnewline
21 & 0.200431 & 1.7815 & 0.03934 \tabularnewline
22 & -0.023748 & -0.2111 & 0.416686 \tabularnewline
23 & 0.17661 & 1.5697 & 0.060236 \tabularnewline
24 & -0.164434 & -1.4615 & 0.07392 \tabularnewline
25 & 0.015496 & 0.1377 & 0.445401 \tabularnewline
26 & 0.070055 & 0.6227 & 0.267651 \tabularnewline
27 & 0.054176 & 0.4815 & 0.315738 \tabularnewline
28 & -0.167703 & -1.4906 & 0.070028 \tabularnewline
29 & -0.022933 & -0.2038 & 0.419505 \tabularnewline
30 & -0.060265 & -0.5357 & 0.296852 \tabularnewline
31 & 0.071342 & 0.6341 & 0.263924 \tabularnewline
32 & -0.095222 & -0.8463 & 0.199957 \tabularnewline
33 & 0.025816 & 0.2295 & 0.409554 \tabularnewline
34 & 0.077189 & 0.6861 & 0.247338 \tabularnewline
35 & 0.048271 & 0.429 & 0.334529 \tabularnewline
36 & -0.084375 & -0.7499 & 0.227759 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29794&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]-0.449656[/C][C]-3.9966[/C][C]7.2e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.400626[/C][C]-3.5608[/C][C]0.000315[/C][/ROW]
[ROW][C]3[/C][C]0.06747[/C][C]0.5997[/C][C]0.275216[/C][/ROW]
[ROW][C]4[/C][C]-0.044439[/C][C]-0.395[/C][C]0.346961[/C][/ROW]
[ROW][C]5[/C][C]-0.021353[/C][C]-0.1898[/C][C]0.424981[/C][/ROW]
[ROW][C]6[/C][C]0.121761[/C][C]1.0822[/C][C]0.14122[/C][/ROW]
[ROW][C]7[/C][C]-0.030465[/C][C]-0.2708[/C][C]0.393633[/C][/ROW]
[ROW][C]8[/C][C]-0.221987[/C][C]-1.9731[/C][C]0.025993[/C][/ROW]
[ROW][C]9[/C][C]0.094235[/C][C]0.8376[/C][C]0.202397[/C][/ROW]
[ROW][C]10[/C][C]0.029095[/C][C]0.2586[/C][C]0.398309[/C][/ROW]
[ROW][C]11[/C][C]0.013834[/C][C]0.123[/C][C]0.451227[/C][/ROW]
[ROW][C]12[/C][C]-0.151818[/C][C]-1.3494[/C][C]0.090534[/C][/ROW]
[ROW][C]13[/C][C]-0.156863[/C][C]-1.3942[/C][C]0.083579[/C][/ROW]
[ROW][C]14[/C][C]-0.128828[/C][C]-1.145[/C][C]0.127823[/C][/ROW]
[ROW][C]15[/C][C]-0.094335[/C][C]-0.8385[/C][C]0.202149[/C][/ROW]
[ROW][C]16[/C][C]-0.227133[/C][C]-2.0188[/C][C]0.02345[/C][/ROW]
[ROW][C]17[/C][C]0.008906[/C][C]0.0792[/C][C]0.468553[/C][/ROW]
[ROW][C]18[/C][C]0.118904[/C][C]1.0568[/C][C]0.146903[/C][/ROW]
[ROW][C]19[/C][C]-0.035894[/C][C]-0.319[/C][C]0.375271[/C][/ROW]
[ROW][C]20[/C][C]0.038585[/C][C]0.3429[/C][C]0.366274[/C][/ROW]
[ROW][C]21[/C][C]0.200431[/C][C]1.7815[/C][C]0.03934[/C][/ROW]
[ROW][C]22[/C][C]-0.023748[/C][C]-0.2111[/C][C]0.416686[/C][/ROW]
[ROW][C]23[/C][C]0.17661[/C][C]1.5697[/C][C]0.060236[/C][/ROW]
[ROW][C]24[/C][C]-0.164434[/C][C]-1.4615[/C][C]0.07392[/C][/ROW]
[ROW][C]25[/C][C]0.015496[/C][C]0.1377[/C][C]0.445401[/C][/ROW]
[ROW][C]26[/C][C]0.070055[/C][C]0.6227[/C][C]0.267651[/C][/ROW]
[ROW][C]27[/C][C]0.054176[/C][C]0.4815[/C][C]0.315738[/C][/ROW]
[ROW][C]28[/C][C]-0.167703[/C][C]-1.4906[/C][C]0.070028[/C][/ROW]
[ROW][C]29[/C][C]-0.022933[/C][C]-0.2038[/C][C]0.419505[/C][/ROW]
[ROW][C]30[/C][C]-0.060265[/C][C]-0.5357[/C][C]0.296852[/C][/ROW]
[ROW][C]31[/C][C]0.071342[/C][C]0.6341[/C][C]0.263924[/C][/ROW]
[ROW][C]32[/C][C]-0.095222[/C][C]-0.8463[/C][C]0.199957[/C][/ROW]
[ROW][C]33[/C][C]0.025816[/C][C]0.2295[/C][C]0.409554[/C][/ROW]
[ROW][C]34[/C][C]0.077189[/C][C]0.6861[/C][C]0.247338[/C][/ROW]
[ROW][C]35[/C][C]0.048271[/C][C]0.429[/C][C]0.334529[/C][/ROW]
[ROW][C]36[/C][C]-0.084375[/C][C]-0.7499[/C][C]0.227759[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29794&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29794&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	-0.449656	-3.9966	7.2e-05
2	-0.400626	-3.5608	0.000315
3	0.06747	0.5997	0.275216
4	-0.044439	-0.395	0.346961
5	-0.021353	-0.1898	0.424981
6	0.121761	1.0822	0.14122
7	-0.030465	-0.2708	0.393633
8	-0.221987	-1.9731	0.025993
9	0.094235	0.8376	0.202397
10	0.029095	0.2586	0.398309
11	0.013834	0.123	0.451227
12	-0.151818	-1.3494	0.090534
13	-0.156863	-1.3942	0.083579
14	-0.128828	-1.145	0.127823
15	-0.094335	-0.8385	0.202149
16	-0.227133	-2.0188	0.02345
17	0.008906	0.0792	0.468553
18	0.118904	1.0568	0.146903
19	-0.035894	-0.319	0.375271
20	0.038585	0.3429	0.366274
21	0.200431	1.7815	0.03934
22	-0.023748	-0.2111	0.416686
23	0.17661	1.5697	0.060236
24	-0.164434	-1.4615	0.07392
25	0.015496	0.1377	0.445401
26	0.070055	0.6227	0.267651
27	0.054176	0.4815	0.315738
28	-0.167703	-1.4906	0.070028
29	-0.022933	-0.2038	0.419505
30	-0.060265	-0.5357	0.296852
31	0.071342	0.6341	0.263924
32	-0.095222	-0.8463	0.199957
33	0.025816	0.2295	0.409554
34	0.077189	0.6861	0.247338
35	0.048271	0.429	0.334529
36	-0.084375	-0.7499	0.227759

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 36 ; par2 = -0.1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;

Parameters (R input):

par1 = 36 ; par2 = -0.1 ; 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