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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Thu, 26 Nov 2009 08:05:01 -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/2009/Nov/26/t1259248500s4tzqr31bpvr3fk.htm/, Retrieved Mon, 29 Apr 2024 05:56:30 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60075, Retrieved Mon, 29 Apr 2024 05:56:30 +0000

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IsPrivate?

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User-defined keywords

Estimated Impact

120

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 12:19:56] [b98453cac15ba1066b407e146608df68]
F    D          [(Partial) Autocorrelation Function] [Method 1] [2009-11-26 15:05:01] [cf272a759dc2b193d9a85354803ede7b] [Current]

Feedback Forum

2009-12-01 15:32:36 [a188887590c4678b1377f46ca2c7883d] [reply] 
Nadat je dan D=1 hebt gedaan, wat seizonale trend moet verwijderen, zeg je dat deze er plots wel is. Deze valt ook helemaal niet te zien op ACF. Het verwijderen van LT-trend is 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=60075&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=60075&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60075&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	0.939167	6.5742	0
2	0.84169	5.8918	0
3	0.717593	5.0232	4e-06
4	0.58283	4.0798	8.3e-05
5	0.426941	2.9886	0.002186
6	0.253036	1.7713	0.041369
7	0.082193	0.5753	0.283844
8	-0.069728	-0.4881	0.313829
9	-0.178327	-1.2483	0.108928
10	-0.278444	-1.9491	0.028509
11	-0.35726	-2.5008	0.007892
12	-0.416491	-2.9154	0.002671
13	-0.425964	-2.9817	0.002227
14	-0.406504	-2.8455	0.003228
15	-0.3729	-2.6103	0.005984
16	-0.335079	-2.3456	0.011546
17	-0.302759	-2.1193	0.019578
18	-0.265033	-1.8552	0.034792
19	-0.22154	-1.5508	0.063695
20	-0.189317	-1.3252	0.095622
21	-0.176743	-1.2372	0.110955
22	-0.166327	-1.1643	0.124972
23	-0.155237	-1.0867	0.141252
24	-0.140231	-0.9816	0.165555
25	-0.116027	-0.8122	0.210305
26	-0.093938	-0.6576	0.256946
27	-0.078982	-0.5529	0.291431
28	-0.056036	-0.3923	0.348287
29	-0.032849	-0.2299	0.409548
30	-0.012525	-0.0877	0.465245
31	0.003096	0.0217	0.491398
32	0.016503	0.1155	0.454253
33	0.029836	0.2089	0.417714
34	0.043853	0.307	0.380083
35	0.058411	0.4089	0.342206
36	0.062882	0.4402	0.330873

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.939167 & 6.5742 & 0 \tabularnewline
2 & 0.84169 & 5.8918 & 0 \tabularnewline
3 & 0.717593 & 5.0232 & 4e-06 \tabularnewline
4 & 0.58283 & 4.0798 & 8.3e-05 \tabularnewline
5 & 0.426941 & 2.9886 & 0.002186 \tabularnewline
6 & 0.253036 & 1.7713 & 0.041369 \tabularnewline
7 & 0.082193 & 0.5753 & 0.283844 \tabularnewline
8 & -0.069728 & -0.4881 & 0.313829 \tabularnewline
9 & -0.178327 & -1.2483 & 0.108928 \tabularnewline
10 & -0.278444 & -1.9491 & 0.028509 \tabularnewline
11 & -0.35726 & -2.5008 & 0.007892 \tabularnewline
12 & -0.416491 & -2.9154 & 0.002671 \tabularnewline
13 & -0.425964 & -2.9817 & 0.002227 \tabularnewline
14 & -0.406504 & -2.8455 & 0.003228 \tabularnewline
15 & -0.3729 & -2.6103 & 0.005984 \tabularnewline
16 & -0.335079 & -2.3456 & 0.011546 \tabularnewline
17 & -0.302759 & -2.1193 & 0.019578 \tabularnewline
18 & -0.265033 & -1.8552 & 0.034792 \tabularnewline
19 & -0.22154 & -1.5508 & 0.063695 \tabularnewline
20 & -0.189317 & -1.3252 & 0.095622 \tabularnewline
21 & -0.176743 & -1.2372 & 0.110955 \tabularnewline
22 & -0.166327 & -1.1643 & 0.124972 \tabularnewline
23 & -0.155237 & -1.0867 & 0.141252 \tabularnewline
24 & -0.140231 & -0.9816 & 0.165555 \tabularnewline
25 & -0.116027 & -0.8122 & 0.210305 \tabularnewline
26 & -0.093938 & -0.6576 & 0.256946 \tabularnewline
27 & -0.078982 & -0.5529 & 0.291431 \tabularnewline
28 & -0.056036 & -0.3923 & 0.348287 \tabularnewline
29 & -0.032849 & -0.2299 & 0.409548 \tabularnewline
30 & -0.012525 & -0.0877 & 0.465245 \tabularnewline
31 & 0.003096 & 0.0217 & 0.491398 \tabularnewline
32 & 0.016503 & 0.1155 & 0.454253 \tabularnewline
33 & 0.029836 & 0.2089 & 0.417714 \tabularnewline
34 & 0.043853 & 0.307 & 0.380083 \tabularnewline
35 & 0.058411 & 0.4089 & 0.342206 \tabularnewline
36 & 0.062882 & 0.4402 & 0.330873 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60075&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]0.939167[/C][C]6.5742[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.84169[/C][C]5.8918[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.717593[/C][C]5.0232[/C][C]4e-06[/C][/ROW]
[ROW][C]4[/C][C]0.58283[/C][C]4.0798[/C][C]8.3e-05[/C][/ROW]
[ROW][C]5[/C][C]0.426941[/C][C]2.9886[/C][C]0.002186[/C][/ROW]
[ROW][C]6[/C][C]0.253036[/C][C]1.7713[/C][C]0.041369[/C][/ROW]
[ROW][C]7[/C][C]0.082193[/C][C]0.5753[/C][C]0.283844[/C][/ROW]
[ROW][C]8[/C][C]-0.069728[/C][C]-0.4881[/C][C]0.313829[/C][/ROW]
[ROW][C]9[/C][C]-0.178327[/C][C]-1.2483[/C][C]0.108928[/C][/ROW]
[ROW][C]10[/C][C]-0.278444[/C][C]-1.9491[/C][C]0.028509[/C][/ROW]
[ROW][C]11[/C][C]-0.35726[/C][C]-2.5008[/C][C]0.007892[/C][/ROW]
[ROW][C]12[/C][C]-0.416491[/C][C]-2.9154[/C][C]0.002671[/C][/ROW]
[ROW][C]13[/C][C]-0.425964[/C][C]-2.9817[/C][C]0.002227[/C][/ROW]
[ROW][C]14[/C][C]-0.406504[/C][C]-2.8455[/C][C]0.003228[/C][/ROW]
[ROW][C]15[/C][C]-0.3729[/C][C]-2.6103[/C][C]0.005984[/C][/ROW]
[ROW][C]16[/C][C]-0.335079[/C][C]-2.3456[/C][C]0.011546[/C][/ROW]
[ROW][C]17[/C][C]-0.302759[/C][C]-2.1193[/C][C]0.019578[/C][/ROW]
[ROW][C]18[/C][C]-0.265033[/C][C]-1.8552[/C][C]0.034792[/C][/ROW]
[ROW][C]19[/C][C]-0.22154[/C][C]-1.5508[/C][C]0.063695[/C][/ROW]
[ROW][C]20[/C][C]-0.189317[/C][C]-1.3252[/C][C]0.095622[/C][/ROW]
[ROW][C]21[/C][C]-0.176743[/C][C]-1.2372[/C][C]0.110955[/C][/ROW]
[ROW][C]22[/C][C]-0.166327[/C][C]-1.1643[/C][C]0.124972[/C][/ROW]
[ROW][C]23[/C][C]-0.155237[/C][C]-1.0867[/C][C]0.141252[/C][/ROW]
[ROW][C]24[/C][C]-0.140231[/C][C]-0.9816[/C][C]0.165555[/C][/ROW]
[ROW][C]25[/C][C]-0.116027[/C][C]-0.8122[/C][C]0.210305[/C][/ROW]
[ROW][C]26[/C][C]-0.093938[/C][C]-0.6576[/C][C]0.256946[/C][/ROW]
[ROW][C]27[/C][C]-0.078982[/C][C]-0.5529[/C][C]0.291431[/C][/ROW]
[ROW][C]28[/C][C]-0.056036[/C][C]-0.3923[/C][C]0.348287[/C][/ROW]
[ROW][C]29[/C][C]-0.032849[/C][C]-0.2299[/C][C]0.409548[/C][/ROW]
[ROW][C]30[/C][C]-0.012525[/C][C]-0.0877[/C][C]0.465245[/C][/ROW]
[ROW][C]31[/C][C]0.003096[/C][C]0.0217[/C][C]0.491398[/C][/ROW]
[ROW][C]32[/C][C]0.016503[/C][C]0.1155[/C][C]0.454253[/C][/ROW]
[ROW][C]33[/C][C]0.029836[/C][C]0.2089[/C][C]0.417714[/C][/ROW]
[ROW][C]34[/C][C]0.043853[/C][C]0.307[/C][C]0.380083[/C][/ROW]
[ROW][C]35[/C][C]0.058411[/C][C]0.4089[/C][C]0.342206[/C][/ROW]
[ROW][C]36[/C][C]0.062882[/C][C]0.4402[/C][C]0.330873[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60075&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60075&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	0.939167	6.5742	0
2	0.84169	5.8918	0
3	0.717593	5.0232	4e-06
4	0.58283	4.0798	8.3e-05
5	0.426941	2.9886	0.002186
6	0.253036	1.7713	0.041369
7	0.082193	0.5753	0.283844
8	-0.069728	-0.4881	0.313829
9	-0.178327	-1.2483	0.108928
10	-0.278444	-1.9491	0.028509
11	-0.35726	-2.5008	0.007892
12	-0.416491	-2.9154	0.002671
13	-0.425964	-2.9817	0.002227
14	-0.406504	-2.8455	0.003228
15	-0.3729	-2.6103	0.005984
16	-0.335079	-2.3456	0.011546
17	-0.302759	-2.1193	0.019578
18	-0.265033	-1.8552	0.034792
19	-0.22154	-1.5508	0.063695
20	-0.189317	-1.3252	0.095622
21	-0.176743	-1.2372	0.110955
22	-0.166327	-1.1643	0.124972
23	-0.155237	-1.0867	0.141252
24	-0.140231	-0.9816	0.165555
25	-0.116027	-0.8122	0.210305
26	-0.093938	-0.6576	0.256946
27	-0.078982	-0.5529	0.291431
28	-0.056036	-0.3923	0.348287
29	-0.032849	-0.2299	0.409548
30	-0.012525	-0.0877	0.465245
31	0.003096	0.0217	0.491398
32	0.016503	0.1155	0.454253
33	0.029836	0.2089	0.417714
34	0.043853	0.307	0.380083
35	0.058411	0.4089	0.342206
36	0.062882	0.4402	0.330873

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.939167	6.5742	0
2	-0.342011	-2.3941	0.010267
3	-0.211627	-1.4814	0.072453
4	-0.075872	-0.5311	0.298872
5	-0.247296	-1.7311	0.044866
6	-0.224507	-1.5716	0.061245
7	-0.024971	-0.1748	0.430979
8	0.032498	0.2275	0.410497
9	0.230084	1.6106	0.056847
10	-0.212315	-1.4862	0.071816
11	-0.015695	-0.1099	0.456483
12	-0.042043	-0.2943	0.384886
13	0.194926	1.3645	0.089325
14	-0.051283	-0.359	0.360575
15	-0.074808	-0.5237	0.301439
16	-0.068263	-0.4778	0.317444
17	-0.160194	-1.1214	0.133801
18	-0.145821	-1.0207	0.156194
19	0.085475	0.5983	0.276189
20	-0.136481	-0.9554	0.172041
21	0.013914	0.0974	0.461405
22	0.014455	0.1012	0.459908
23	0.000237	0.0017	0.499341
24	-0.008815	-0.0617	0.475525
25	0.171497	1.2005	0.117863
26	-0.026926	-0.1885	0.425638
27	-0.118065	-0.8265	0.206277
28	-0.028315	-0.1982	0.421852
29	-0.153146	-1.072	0.14448
30	-0.109799	-0.7686	0.222912
31	0.043071	0.3015	0.382155
32	-0.032655	-0.2286	0.410071
33	0.042562	0.2979	0.383508
34	0.027593	0.1932	0.423819
35	0.008787	0.0615	0.475601
36	-0.03368	-0.2358	0.407301

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.939167 & 6.5742 & 0 \tabularnewline
2 & -0.342011 & -2.3941 & 0.010267 \tabularnewline
3 & -0.211627 & -1.4814 & 0.072453 \tabularnewline
4 & -0.075872 & -0.5311 & 0.298872 \tabularnewline
5 & -0.247296 & -1.7311 & 0.044866 \tabularnewline
6 & -0.224507 & -1.5716 & 0.061245 \tabularnewline
7 & -0.024971 & -0.1748 & 0.430979 \tabularnewline
8 & 0.032498 & 0.2275 & 0.410497 \tabularnewline
9 & 0.230084 & 1.6106 & 0.056847 \tabularnewline
10 & -0.212315 & -1.4862 & 0.071816 \tabularnewline
11 & -0.015695 & -0.1099 & 0.456483 \tabularnewline
12 & -0.042043 & -0.2943 & 0.384886 \tabularnewline
13 & 0.194926 & 1.3645 & 0.089325 \tabularnewline
14 & -0.051283 & -0.359 & 0.360575 \tabularnewline
15 & -0.074808 & -0.5237 & 0.301439 \tabularnewline
16 & -0.068263 & -0.4778 & 0.317444 \tabularnewline
17 & -0.160194 & -1.1214 & 0.133801 \tabularnewline
18 & -0.145821 & -1.0207 & 0.156194 \tabularnewline
19 & 0.085475 & 0.5983 & 0.276189 \tabularnewline
20 & -0.136481 & -0.9554 & 0.172041 \tabularnewline
21 & 0.013914 & 0.0974 & 0.461405 \tabularnewline
22 & 0.014455 & 0.1012 & 0.459908 \tabularnewline
23 & 0.000237 & 0.0017 & 0.499341 \tabularnewline
24 & -0.008815 & -0.0617 & 0.475525 \tabularnewline
25 & 0.171497 & 1.2005 & 0.117863 \tabularnewline
26 & -0.026926 & -0.1885 & 0.425638 \tabularnewline
27 & -0.118065 & -0.8265 & 0.206277 \tabularnewline
28 & -0.028315 & -0.1982 & 0.421852 \tabularnewline
29 & -0.153146 & -1.072 & 0.14448 \tabularnewline
30 & -0.109799 & -0.7686 & 0.222912 \tabularnewline
31 & 0.043071 & 0.3015 & 0.382155 \tabularnewline
32 & -0.032655 & -0.2286 & 0.410071 \tabularnewline
33 & 0.042562 & 0.2979 & 0.383508 \tabularnewline
34 & 0.027593 & 0.1932 & 0.423819 \tabularnewline
35 & 0.008787 & 0.0615 & 0.475601 \tabularnewline
36 & -0.03368 & -0.2358 & 0.407301 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60075&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]0.939167[/C][C]6.5742[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.342011[/C][C]-2.3941[/C][C]0.010267[/C][/ROW]
[ROW][C]3[/C][C]-0.211627[/C][C]-1.4814[/C][C]0.072453[/C][/ROW]
[ROW][C]4[/C][C]-0.075872[/C][C]-0.5311[/C][C]0.298872[/C][/ROW]
[ROW][C]5[/C][C]-0.247296[/C][C]-1.7311[/C][C]0.044866[/C][/ROW]
[ROW][C]6[/C][C]-0.224507[/C][C]-1.5716[/C][C]0.061245[/C][/ROW]
[ROW][C]7[/C][C]-0.024971[/C][C]-0.1748[/C][C]0.430979[/C][/ROW]
[ROW][C]8[/C][C]0.032498[/C][C]0.2275[/C][C]0.410497[/C][/ROW]
[ROW][C]9[/C][C]0.230084[/C][C]1.6106[/C][C]0.056847[/C][/ROW]
[ROW][C]10[/C][C]-0.212315[/C][C]-1.4862[/C][C]0.071816[/C][/ROW]
[ROW][C]11[/C][C]-0.015695[/C][C]-0.1099[/C][C]0.456483[/C][/ROW]
[ROW][C]12[/C][C]-0.042043[/C][C]-0.2943[/C][C]0.384886[/C][/ROW]
[ROW][C]13[/C][C]0.194926[/C][C]1.3645[/C][C]0.089325[/C][/ROW]
[ROW][C]14[/C][C]-0.051283[/C][C]-0.359[/C][C]0.360575[/C][/ROW]
[ROW][C]15[/C][C]-0.074808[/C][C]-0.5237[/C][C]0.301439[/C][/ROW]
[ROW][C]16[/C][C]-0.068263[/C][C]-0.4778[/C][C]0.317444[/C][/ROW]
[ROW][C]17[/C][C]-0.160194[/C][C]-1.1214[/C][C]0.133801[/C][/ROW]
[ROW][C]18[/C][C]-0.145821[/C][C]-1.0207[/C][C]0.156194[/C][/ROW]
[ROW][C]19[/C][C]0.085475[/C][C]0.5983[/C][C]0.276189[/C][/ROW]
[ROW][C]20[/C][C]-0.136481[/C][C]-0.9554[/C][C]0.172041[/C][/ROW]
[ROW][C]21[/C][C]0.013914[/C][C]0.0974[/C][C]0.461405[/C][/ROW]
[ROW][C]22[/C][C]0.014455[/C][C]0.1012[/C][C]0.459908[/C][/ROW]
[ROW][C]23[/C][C]0.000237[/C][C]0.0017[/C][C]0.499341[/C][/ROW]
[ROW][C]24[/C][C]-0.008815[/C][C]-0.0617[/C][C]0.475525[/C][/ROW]
[ROW][C]25[/C][C]0.171497[/C][C]1.2005[/C][C]0.117863[/C][/ROW]
[ROW][C]26[/C][C]-0.026926[/C][C]-0.1885[/C][C]0.425638[/C][/ROW]
[ROW][C]27[/C][C]-0.118065[/C][C]-0.8265[/C][C]0.206277[/C][/ROW]
[ROW][C]28[/C][C]-0.028315[/C][C]-0.1982[/C][C]0.421852[/C][/ROW]
[ROW][C]29[/C][C]-0.153146[/C][C]-1.072[/C][C]0.14448[/C][/ROW]
[ROW][C]30[/C][C]-0.109799[/C][C]-0.7686[/C][C]0.222912[/C][/ROW]
[ROW][C]31[/C][C]0.043071[/C][C]0.3015[/C][C]0.382155[/C][/ROW]
[ROW][C]32[/C][C]-0.032655[/C][C]-0.2286[/C][C]0.410071[/C][/ROW]
[ROW][C]33[/C][C]0.042562[/C][C]0.2979[/C][C]0.383508[/C][/ROW]
[ROW][C]34[/C][C]0.027593[/C][C]0.1932[/C][C]0.423819[/C][/ROW]
[ROW][C]35[/C][C]0.008787[/C][C]0.0615[/C][C]0.475601[/C][/ROW]
[ROW][C]36[/C][C]-0.03368[/C][C]-0.2358[/C][C]0.407301[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60075&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60075&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	0.939167	6.5742	0
2	-0.342011	-2.3941	0.010267
3	-0.211627	-1.4814	0.072453
4	-0.075872	-0.5311	0.298872
5	-0.247296	-1.7311	0.044866
6	-0.224507	-1.5716	0.061245
7	-0.024971	-0.1748	0.430979
8	0.032498	0.2275	0.410497
9	0.230084	1.6106	0.056847
10	-0.212315	-1.4862	0.071816
11	-0.015695	-0.1099	0.456483
12	-0.042043	-0.2943	0.384886
13	0.194926	1.3645	0.089325
14	-0.051283	-0.359	0.360575
15	-0.074808	-0.5237	0.301439
16	-0.068263	-0.4778	0.317444
17	-0.160194	-1.1214	0.133801
18	-0.145821	-1.0207	0.156194
19	0.085475	0.5983	0.276189
20	-0.136481	-0.9554	0.172041
21	0.013914	0.0974	0.461405
22	0.014455	0.1012	0.459908
23	0.000237	0.0017	0.499341
24	-0.008815	-0.0617	0.475525
25	0.171497	1.2005	0.117863
26	-0.026926	-0.1885	0.425638
27	-0.118065	-0.8265	0.206277
28	-0.028315	-0.1982	0.421852
29	-0.153146	-1.072	0.14448
30	-0.109799	-0.7686	0.222912
31	0.043071	0.3015	0.382155
32	-0.032655	-0.2286	0.410071
33	0.042562	0.2979	0.383508
34	0.027593	0.1932	0.423819
35	0.008787	0.0615	0.475601
36	-0.03368	-0.2358	0.407301

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 ; par6 = MA ; par7 = 0.95 ;

Parameters (R input):

par1 = 36 ; par2 = 1 ; par3 = 0 ; 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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code