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rwasp_autocorrelation.wasp

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(Partial) Autocorrelation Function

Date of computation

Fri, 27 Nov 2009 15:44:35 -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/27/t1259361904ut0eknvzfyl5gm6.htm/, Retrieved Sun, 28 Apr 2024 22:28:40 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61323, Retrieved Sun, 28 Apr 2024 22:28:40 +0000

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112

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-       [(Partial) Autocorrelation Function] [ACF 3a] [2009-11-27 22:44:35] [b42c0aeada8a5fa89825c81e73c10645] [Current]

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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=61323&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=61323&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61323&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	0.311882	2.1382	0.018867
2	0.239559	1.6423	0.053598
3	-0.397598	-2.7258	0.004492
4	-0.289991	-1.9881	0.026323
5	-0.265892	-1.8229	0.037344
6	0.026746	0.1834	0.427651
7	0.116739	0.8003	0.213776
8	0.226502	1.5528	0.063587
9	0.131673	0.9027	0.185644
10	-0.074532	-0.511	0.305884
11	-0.245478	-1.6829	0.049513
12	-0.45853	-3.1435	0.001445
13	-0.2567	-1.7598	0.04247
14	-0.160996	-1.1037	0.137664
15	0.124311	0.8522	0.199202
16	0.104893	0.7191	0.237817
17	0.166579	1.142	0.129618
18	0.025242	0.173	0.431678
19	0.144834	0.9929	0.162913
20	-0.062986	-0.4318	0.333927
21	0.096244	0.6598	0.256297
22	-0.136275	-0.9343	0.177474
23	0.093543	0.6413	0.262222
24	0.007028	0.0482	0.480888
25	0.15118	1.0364	0.15265
26	0.063354	0.4343	0.333016
27	0.05602	0.3841	0.351336
28	-0.033534	-0.2299	0.409585
29	-0.063792	-0.4373	0.331935
30	-0.08592	-0.589	0.279328
31	-0.116259	-0.797	0.21472
32	-0.015263	-0.1046	0.458553
33	-0.061448	-0.4213	0.337739
34	0.095727	0.6563	0.257426
35	0.022681	0.1555	0.438549
36	0.042751	0.2931	0.385373

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.311882 & 2.1382 & 0.018867 \tabularnewline
2 & 0.239559 & 1.6423 & 0.053598 \tabularnewline
3 & -0.397598 & -2.7258 & 0.004492 \tabularnewline
4 & -0.289991 & -1.9881 & 0.026323 \tabularnewline
5 & -0.265892 & -1.8229 & 0.037344 \tabularnewline
6 & 0.026746 & 0.1834 & 0.427651 \tabularnewline
7 & 0.116739 & 0.8003 & 0.213776 \tabularnewline
8 & 0.226502 & 1.5528 & 0.063587 \tabularnewline
9 & 0.131673 & 0.9027 & 0.185644 \tabularnewline
10 & -0.074532 & -0.511 & 0.305884 \tabularnewline
11 & -0.245478 & -1.6829 & 0.049513 \tabularnewline
12 & -0.45853 & -3.1435 & 0.001445 \tabularnewline
13 & -0.2567 & -1.7598 & 0.04247 \tabularnewline
14 & -0.160996 & -1.1037 & 0.137664 \tabularnewline
15 & 0.124311 & 0.8522 & 0.199202 \tabularnewline
16 & 0.104893 & 0.7191 & 0.237817 \tabularnewline
17 & 0.166579 & 1.142 & 0.129618 \tabularnewline
18 & 0.025242 & 0.173 & 0.431678 \tabularnewline
19 & 0.144834 & 0.9929 & 0.162913 \tabularnewline
20 & -0.062986 & -0.4318 & 0.333927 \tabularnewline
21 & 0.096244 & 0.6598 & 0.256297 \tabularnewline
22 & -0.136275 & -0.9343 & 0.177474 \tabularnewline
23 & 0.093543 & 0.6413 & 0.262222 \tabularnewline
24 & 0.007028 & 0.0482 & 0.480888 \tabularnewline
25 & 0.15118 & 1.0364 & 0.15265 \tabularnewline
26 & 0.063354 & 0.4343 & 0.333016 \tabularnewline
27 & 0.05602 & 0.3841 & 0.351336 \tabularnewline
28 & -0.033534 & -0.2299 & 0.409585 \tabularnewline
29 & -0.063792 & -0.4373 & 0.331935 \tabularnewline
30 & -0.08592 & -0.589 & 0.279328 \tabularnewline
31 & -0.116259 & -0.797 & 0.21472 \tabularnewline
32 & -0.015263 & -0.1046 & 0.458553 \tabularnewline
33 & -0.061448 & -0.4213 & 0.337739 \tabularnewline
34 & 0.095727 & 0.6563 & 0.257426 \tabularnewline
35 & 0.022681 & 0.1555 & 0.438549 \tabularnewline
36 & 0.042751 & 0.2931 & 0.385373 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61323&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]0.311882[/C][C]2.1382[/C][C]0.018867[/C][/ROW]
[ROW][C]2[/C][C]0.239559[/C][C]1.6423[/C][C]0.053598[/C][/ROW]
[ROW][C]3[/C][C]-0.397598[/C][C]-2.7258[/C][C]0.004492[/C][/ROW]
[ROW][C]4[/C][C]-0.289991[/C][C]-1.9881[/C][C]0.026323[/C][/ROW]
[ROW][C]5[/C][C]-0.265892[/C][C]-1.8229[/C][C]0.037344[/C][/ROW]
[ROW][C]6[/C][C]0.026746[/C][C]0.1834[/C][C]0.427651[/C][/ROW]
[ROW][C]7[/C][C]0.116739[/C][C]0.8003[/C][C]0.213776[/C][/ROW]
[ROW][C]8[/C][C]0.226502[/C][C]1.5528[/C][C]0.063587[/C][/ROW]
[ROW][C]9[/C][C]0.131673[/C][C]0.9027[/C][C]0.185644[/C][/ROW]
[ROW][C]10[/C][C]-0.074532[/C][C]-0.511[/C][C]0.305884[/C][/ROW]
[ROW][C]11[/C][C]-0.245478[/C][C]-1.6829[/C][C]0.049513[/C][/ROW]
[ROW][C]12[/C][C]-0.45853[/C][C]-3.1435[/C][C]0.001445[/C][/ROW]
[ROW][C]13[/C][C]-0.2567[/C][C]-1.7598[/C][C]0.04247[/C][/ROW]
[ROW][C]14[/C][C]-0.160996[/C][C]-1.1037[/C][C]0.137664[/C][/ROW]
[ROW][C]15[/C][C]0.124311[/C][C]0.8522[/C][C]0.199202[/C][/ROW]
[ROW][C]16[/C][C]0.104893[/C][C]0.7191[/C][C]0.237817[/C][/ROW]
[ROW][C]17[/C][C]0.166579[/C][C]1.142[/C][C]0.129618[/C][/ROW]
[ROW][C]18[/C][C]0.025242[/C][C]0.173[/C][C]0.431678[/C][/ROW]
[ROW][C]19[/C][C]0.144834[/C][C]0.9929[/C][C]0.162913[/C][/ROW]
[ROW][C]20[/C][C]-0.062986[/C][C]-0.4318[/C][C]0.333927[/C][/ROW]
[ROW][C]21[/C][C]0.096244[/C][C]0.6598[/C][C]0.256297[/C][/ROW]
[ROW][C]22[/C][C]-0.136275[/C][C]-0.9343[/C][C]0.177474[/C][/ROW]
[ROW][C]23[/C][C]0.093543[/C][C]0.6413[/C][C]0.262222[/C][/ROW]
[ROW][C]24[/C][C]0.007028[/C][C]0.0482[/C][C]0.480888[/C][/ROW]
[ROW][C]25[/C][C]0.15118[/C][C]1.0364[/C][C]0.15265[/C][/ROW]
[ROW][C]26[/C][C]0.063354[/C][C]0.4343[/C][C]0.333016[/C][/ROW]
[ROW][C]27[/C][C]0.05602[/C][C]0.3841[/C][C]0.351336[/C][/ROW]
[ROW][C]28[/C][C]-0.033534[/C][C]-0.2299[/C][C]0.409585[/C][/ROW]
[ROW][C]29[/C][C]-0.063792[/C][C]-0.4373[/C][C]0.331935[/C][/ROW]
[ROW][C]30[/C][C]-0.08592[/C][C]-0.589[/C][C]0.279328[/C][/ROW]
[ROW][C]31[/C][C]-0.116259[/C][C]-0.797[/C][C]0.21472[/C][/ROW]
[ROW][C]32[/C][C]-0.015263[/C][C]-0.1046[/C][C]0.458553[/C][/ROW]
[ROW][C]33[/C][C]-0.061448[/C][C]-0.4213[/C][C]0.337739[/C][/ROW]
[ROW][C]34[/C][C]0.095727[/C][C]0.6563[/C][C]0.257426[/C][/ROW]
[ROW][C]35[/C][C]0.022681[/C][C]0.1555[/C][C]0.438549[/C][/ROW]
[ROW][C]36[/C][C]0.042751[/C][C]0.2931[/C][C]0.385373[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61323&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61323&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	0.311882	2.1382	0.018867
2	0.239559	1.6423	0.053598
3	-0.397598	-2.7258	0.004492
4	-0.289991	-1.9881	0.026323
5	-0.265892	-1.8229	0.037344
6	0.026746	0.1834	0.427651
7	0.116739	0.8003	0.213776
8	0.226502	1.5528	0.063587
9	0.131673	0.9027	0.185644
10	-0.074532	-0.511	0.305884
11	-0.245478	-1.6829	0.049513
12	-0.45853	-3.1435	0.001445
13	-0.2567	-1.7598	0.04247
14	-0.160996	-1.1037	0.137664
15	0.124311	0.8522	0.199202
16	0.104893	0.7191	0.237817
17	0.166579	1.142	0.129618
18	0.025242	0.173	0.431678
19	0.144834	0.9929	0.162913
20	-0.062986	-0.4318	0.333927
21	0.096244	0.6598	0.256297
22	-0.136275	-0.9343	0.177474
23	0.093543	0.6413	0.262222
24	0.007028	0.0482	0.480888
25	0.15118	1.0364	0.15265
26	0.063354	0.4343	0.333016
27	0.05602	0.3841	0.351336
28	-0.033534	-0.2299	0.409585
29	-0.063792	-0.4373	0.331935
30	-0.08592	-0.589	0.279328
31	-0.116259	-0.797	0.21472
32	-0.015263	-0.1046	0.458553
33	-0.061448	-0.4213	0.337739
34	0.095727	0.6563	0.257426
35	0.022681	0.1555	0.438549
36	0.042751	0.2931	0.385373

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.311882	2.1382	0.018867
2	0.15762	1.0806	0.142697
3	-0.579	-3.9694	0.000123
4	-0.073253	-0.5022	0.308936
5	0.192375	1.3189	0.096804
6	-0.058563	-0.4015	0.344941
7	-0.075555	-0.518	0.303451
8	0.149323	1.0237	0.155607
9	0.050363	0.3453	0.365715
10	-0.31334	-2.1482	0.018443
11	-0.154695	-1.0605	0.14716
12	-0.22367	-1.5334	0.06594
13	-0.049524	-0.3395	0.367867
14	-0.11192	-0.7673	0.223375
15	-0.22109	-1.5157	0.068145
16	-0.156336	-1.0718	0.144644
17	0.025219	0.1729	0.431739
18	-0.053249	-0.3651	0.358353
19	0.172603	1.1833	0.121319
20	-0.106882	-0.7327	0.233677
21	0.056832	0.3896	0.34929
22	-0.123326	-0.8455	0.201063
23	-0.031264	-0.2143	0.415605
24	-0.061567	-0.4221	0.337445
25	-0.139862	-0.9588	0.171272
26	-0.058215	-0.3991	0.345812
27	-0.079565	-0.5455	0.294005
28	-0.124758	-0.8553	0.198362
29	-0.088403	-0.6061	0.273695
30	-0.007418	-0.0509	0.479827
31	0.00516	0.0354	0.485964
32	-0.012074	-0.0828	0.467192
33	-0.069913	-0.4793	0.316974
34	-0.024889	-0.1706	0.432624
35	0.08566	0.5873	0.279921
36	-0.154581	-1.0598	0.147337

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.311882 & 2.1382 & 0.018867 \tabularnewline
2 & 0.15762 & 1.0806 & 0.142697 \tabularnewline
3 & -0.579 & -3.9694 & 0.000123 \tabularnewline
4 & -0.073253 & -0.5022 & 0.308936 \tabularnewline
5 & 0.192375 & 1.3189 & 0.096804 \tabularnewline
6 & -0.058563 & -0.4015 & 0.344941 \tabularnewline
7 & -0.075555 & -0.518 & 0.303451 \tabularnewline
8 & 0.149323 & 1.0237 & 0.155607 \tabularnewline
9 & 0.050363 & 0.3453 & 0.365715 \tabularnewline
10 & -0.31334 & -2.1482 & 0.018443 \tabularnewline
11 & -0.154695 & -1.0605 & 0.14716 \tabularnewline
12 & -0.22367 & -1.5334 & 0.06594 \tabularnewline
13 & -0.049524 & -0.3395 & 0.367867 \tabularnewline
14 & -0.11192 & -0.7673 & 0.223375 \tabularnewline
15 & -0.22109 & -1.5157 & 0.068145 \tabularnewline
16 & -0.156336 & -1.0718 & 0.144644 \tabularnewline
17 & 0.025219 & 0.1729 & 0.431739 \tabularnewline
18 & -0.053249 & -0.3651 & 0.358353 \tabularnewline
19 & 0.172603 & 1.1833 & 0.121319 \tabularnewline
20 & -0.106882 & -0.7327 & 0.233677 \tabularnewline
21 & 0.056832 & 0.3896 & 0.34929 \tabularnewline
22 & -0.123326 & -0.8455 & 0.201063 \tabularnewline
23 & -0.031264 & -0.2143 & 0.415605 \tabularnewline
24 & -0.061567 & -0.4221 & 0.337445 \tabularnewline
25 & -0.139862 & -0.9588 & 0.171272 \tabularnewline
26 & -0.058215 & -0.3991 & 0.345812 \tabularnewline
27 & -0.079565 & -0.5455 & 0.294005 \tabularnewline
28 & -0.124758 & -0.8553 & 0.198362 \tabularnewline
29 & -0.088403 & -0.6061 & 0.273695 \tabularnewline
30 & -0.007418 & -0.0509 & 0.479827 \tabularnewline
31 & 0.00516 & 0.0354 & 0.485964 \tabularnewline
32 & -0.012074 & -0.0828 & 0.467192 \tabularnewline
33 & -0.069913 & -0.4793 & 0.316974 \tabularnewline
34 & -0.024889 & -0.1706 & 0.432624 \tabularnewline
35 & 0.08566 & 0.5873 & 0.279921 \tabularnewline
36 & -0.154581 & -1.0598 & 0.147337 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61323&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]0.311882[/C][C]2.1382[/C][C]0.018867[/C][/ROW]
[ROW][C]2[/C][C]0.15762[/C][C]1.0806[/C][C]0.142697[/C][/ROW]
[ROW][C]3[/C][C]-0.579[/C][C]-3.9694[/C][C]0.000123[/C][/ROW]
[ROW][C]4[/C][C]-0.073253[/C][C]-0.5022[/C][C]0.308936[/C][/ROW]
[ROW][C]5[/C][C]0.192375[/C][C]1.3189[/C][C]0.096804[/C][/ROW]
[ROW][C]6[/C][C]-0.058563[/C][C]-0.4015[/C][C]0.344941[/C][/ROW]
[ROW][C]7[/C][C]-0.075555[/C][C]-0.518[/C][C]0.303451[/C][/ROW]
[ROW][C]8[/C][C]0.149323[/C][C]1.0237[/C][C]0.155607[/C][/ROW]
[ROW][C]9[/C][C]0.050363[/C][C]0.3453[/C][C]0.365715[/C][/ROW]
[ROW][C]10[/C][C]-0.31334[/C][C]-2.1482[/C][C]0.018443[/C][/ROW]
[ROW][C]11[/C][C]-0.154695[/C][C]-1.0605[/C][C]0.14716[/C][/ROW]
[ROW][C]12[/C][C]-0.22367[/C][C]-1.5334[/C][C]0.06594[/C][/ROW]
[ROW][C]13[/C][C]-0.049524[/C][C]-0.3395[/C][C]0.367867[/C][/ROW]
[ROW][C]14[/C][C]-0.11192[/C][C]-0.7673[/C][C]0.223375[/C][/ROW]
[ROW][C]15[/C][C]-0.22109[/C][C]-1.5157[/C][C]0.068145[/C][/ROW]
[ROW][C]16[/C][C]-0.156336[/C][C]-1.0718[/C][C]0.144644[/C][/ROW]
[ROW][C]17[/C][C]0.025219[/C][C]0.1729[/C][C]0.431739[/C][/ROW]
[ROW][C]18[/C][C]-0.053249[/C][C]-0.3651[/C][C]0.358353[/C][/ROW]
[ROW][C]19[/C][C]0.172603[/C][C]1.1833[/C][C]0.121319[/C][/ROW]
[ROW][C]20[/C][C]-0.106882[/C][C]-0.7327[/C][C]0.233677[/C][/ROW]
[ROW][C]21[/C][C]0.056832[/C][C]0.3896[/C][C]0.34929[/C][/ROW]
[ROW][C]22[/C][C]-0.123326[/C][C]-0.8455[/C][C]0.201063[/C][/ROW]
[ROW][C]23[/C][C]-0.031264[/C][C]-0.2143[/C][C]0.415605[/C][/ROW]
[ROW][C]24[/C][C]-0.061567[/C][C]-0.4221[/C][C]0.337445[/C][/ROW]
[ROW][C]25[/C][C]-0.139862[/C][C]-0.9588[/C][C]0.171272[/C][/ROW]
[ROW][C]26[/C][C]-0.058215[/C][C]-0.3991[/C][C]0.345812[/C][/ROW]
[ROW][C]27[/C][C]-0.079565[/C][C]-0.5455[/C][C]0.294005[/C][/ROW]
[ROW][C]28[/C][C]-0.124758[/C][C]-0.8553[/C][C]0.198362[/C][/ROW]
[ROW][C]29[/C][C]-0.088403[/C][C]-0.6061[/C][C]0.273695[/C][/ROW]
[ROW][C]30[/C][C]-0.007418[/C][C]-0.0509[/C][C]0.479827[/C][/ROW]
[ROW][C]31[/C][C]0.00516[/C][C]0.0354[/C][C]0.485964[/C][/ROW]
[ROW][C]32[/C][C]-0.012074[/C][C]-0.0828[/C][C]0.467192[/C][/ROW]
[ROW][C]33[/C][C]-0.069913[/C][C]-0.4793[/C][C]0.316974[/C][/ROW]
[ROW][C]34[/C][C]-0.024889[/C][C]-0.1706[/C][C]0.432624[/C][/ROW]
[ROW][C]35[/C][C]0.08566[/C][C]0.5873[/C][C]0.279921[/C][/ROW]
[ROW][C]36[/C][C]-0.154581[/C][C]-1.0598[/C][C]0.147337[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61323&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61323&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	0.311882	2.1382	0.018867
2	0.15762	1.0806	0.142697
3	-0.579	-3.9694	0.000123
4	-0.073253	-0.5022	0.308936
5	0.192375	1.3189	0.096804
6	-0.058563	-0.4015	0.344941
7	-0.075555	-0.518	0.303451
8	0.149323	1.0237	0.155607
9	0.050363	0.3453	0.365715
10	-0.31334	-2.1482	0.018443
11	-0.154695	-1.0605	0.14716
12	-0.22367	-1.5334	0.06594
13	-0.049524	-0.3395	0.367867
14	-0.11192	-0.7673	0.223375
15	-0.22109	-1.5157	0.068145
16	-0.156336	-1.0718	0.144644
17	0.025219	0.1729	0.431739
18	-0.053249	-0.3651	0.358353
19	0.172603	1.1833	0.121319
20	-0.106882	-0.7327	0.233677
21	0.056832	0.3896	0.34929
22	-0.123326	-0.8455	0.201063
23	-0.031264	-0.2143	0.415605
24	-0.061567	-0.4221	0.337445
25	-0.139862	-0.9588	0.171272
26	-0.058215	-0.3991	0.345812
27	-0.079565	-0.5455	0.294005
28	-0.124758	-0.8553	0.198362
29	-0.088403	-0.6061	0.273695
30	-0.007418	-0.0509	0.479827
31	0.00516	0.0354	0.485964
32	-0.012074	-0.0828	0.467192
33	-0.069913	-0.4793	0.316974
34	-0.024889	-0.1706	0.432624
35	0.08566	0.5873	0.279921
36	-0.154581	-1.0598	0.147337

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; 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