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rwasp_autocorrelation.wasp

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(Partial) Autocorrelation Function

Date of computation

Fri, 11 Dec 2009 04:44:16 -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/Dec/11/t12605319010b0elnmh7j8ucim.htm/, Retrieved Mon, 29 Apr 2024 01:08:22 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=66022, Retrieved Mon, 29 Apr 2024 01:08:22 +0000

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-       [(Partial) Autocorrelation Function] [] [2009-12-11 11:44:16] [9f6463b67b1eb7bae5c03a796abf0348] [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=66022&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=66022&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66022&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	-0.484636	-3.3225	0.000867
2	0.081893	0.5614	0.288586
3	-0.10111	-0.6932	0.245806
4	0.199041	1.3646	0.089445
5	-0.198363	-1.3599	0.090174
6	0.070533	0.4836	0.315475
7	-0.035409	-0.2428	0.404627
8	-0.142746	-0.9786	0.16639
9	0.188447	1.2919	0.10135
10	-0.194835	-1.3357	0.094036
11	0.266072	1.8241	0.037249
12	-0.206381	-1.4149	0.081848
13	0.03619	0.2481	0.402567
14	0.001537	0.0105	0.49582
15	0.159615	1.0943	0.139708
16	-0.137475	-0.9425	0.175383
17	0.000856	0.0059	0.497672
18	-0.008167	-0.056	0.477794
19	0.045283	0.3104	0.378798
20	-0.005789	-0.0397	0.484255
21	-0.018294	-0.1254	0.450364
22	0.002239	0.0154	0.493908
23	0.041148	0.2821	0.389554
24	-0.195276	-1.3387	0.093547
25	0.202429	1.3878	0.085873
26	-0.067898	-0.4655	0.321867
27	-0.083981	-0.5757	0.283767
28	-0.062051	-0.4254	0.336244
29	0.20775	1.4243	0.080489
30	-0.052397	-0.3592	0.360522
31	-0.023505	-0.1611	0.436335
32	0.055395	0.3798	0.352914
33	-0.110686	-0.7588	0.225874
34	0.135165	0.9266	0.179423
35	-0.080081	-0.549	0.292799
36	0.056925	0.3903	0.349054

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.484636 & -3.3225 & 0.000867 \tabularnewline
2 & 0.081893 & 0.5614 & 0.288586 \tabularnewline
3 & -0.10111 & -0.6932 & 0.245806 \tabularnewline
4 & 0.199041 & 1.3646 & 0.089445 \tabularnewline
5 & -0.198363 & -1.3599 & 0.090174 \tabularnewline
6 & 0.070533 & 0.4836 & 0.315475 \tabularnewline
7 & -0.035409 & -0.2428 & 0.404627 \tabularnewline
8 & -0.142746 & -0.9786 & 0.16639 \tabularnewline
9 & 0.188447 & 1.2919 & 0.10135 \tabularnewline
10 & -0.194835 & -1.3357 & 0.094036 \tabularnewline
11 & 0.266072 & 1.8241 & 0.037249 \tabularnewline
12 & -0.206381 & -1.4149 & 0.081848 \tabularnewline
13 & 0.03619 & 0.2481 & 0.402567 \tabularnewline
14 & 0.001537 & 0.0105 & 0.49582 \tabularnewline
15 & 0.159615 & 1.0943 & 0.139708 \tabularnewline
16 & -0.137475 & -0.9425 & 0.175383 \tabularnewline
17 & 0.000856 & 0.0059 & 0.497672 \tabularnewline
18 & -0.008167 & -0.056 & 0.477794 \tabularnewline
19 & 0.045283 & 0.3104 & 0.378798 \tabularnewline
20 & -0.005789 & -0.0397 & 0.484255 \tabularnewline
21 & -0.018294 & -0.1254 & 0.450364 \tabularnewline
22 & 0.002239 & 0.0154 & 0.493908 \tabularnewline
23 & 0.041148 & 0.2821 & 0.389554 \tabularnewline
24 & -0.195276 & -1.3387 & 0.093547 \tabularnewline
25 & 0.202429 & 1.3878 & 0.085873 \tabularnewline
26 & -0.067898 & -0.4655 & 0.321867 \tabularnewline
27 & -0.083981 & -0.5757 & 0.283767 \tabularnewline
28 & -0.062051 & -0.4254 & 0.336244 \tabularnewline
29 & 0.20775 & 1.4243 & 0.080489 \tabularnewline
30 & -0.052397 & -0.3592 & 0.360522 \tabularnewline
31 & -0.023505 & -0.1611 & 0.436335 \tabularnewline
32 & 0.055395 & 0.3798 & 0.352914 \tabularnewline
33 & -0.110686 & -0.7588 & 0.225874 \tabularnewline
34 & 0.135165 & 0.9266 & 0.179423 \tabularnewline
35 & -0.080081 & -0.549 & 0.292799 \tabularnewline
36 & 0.056925 & 0.3903 & 0.349054 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66022&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]-0.484636[/C][C]-3.3225[/C][C]0.000867[/C][/ROW]
[ROW][C]2[/C][C]0.081893[/C][C]0.5614[/C][C]0.288586[/C][/ROW]
[ROW][C]3[/C][C]-0.10111[/C][C]-0.6932[/C][C]0.245806[/C][/ROW]
[ROW][C]4[/C][C]0.199041[/C][C]1.3646[/C][C]0.089445[/C][/ROW]
[ROW][C]5[/C][C]-0.198363[/C][C]-1.3599[/C][C]0.090174[/C][/ROW]
[ROW][C]6[/C][C]0.070533[/C][C]0.4836[/C][C]0.315475[/C][/ROW]
[ROW][C]7[/C][C]-0.035409[/C][C]-0.2428[/C][C]0.404627[/C][/ROW]
[ROW][C]8[/C][C]-0.142746[/C][C]-0.9786[/C][C]0.16639[/C][/ROW]
[ROW][C]9[/C][C]0.188447[/C][C]1.2919[/C][C]0.10135[/C][/ROW]
[ROW][C]10[/C][C]-0.194835[/C][C]-1.3357[/C][C]0.094036[/C][/ROW]
[ROW][C]11[/C][C]0.266072[/C][C]1.8241[/C][C]0.037249[/C][/ROW]
[ROW][C]12[/C][C]-0.206381[/C][C]-1.4149[/C][C]0.081848[/C][/ROW]
[ROW][C]13[/C][C]0.03619[/C][C]0.2481[/C][C]0.402567[/C][/ROW]
[ROW][C]14[/C][C]0.001537[/C][C]0.0105[/C][C]0.49582[/C][/ROW]
[ROW][C]15[/C][C]0.159615[/C][C]1.0943[/C][C]0.139708[/C][/ROW]
[ROW][C]16[/C][C]-0.137475[/C][C]-0.9425[/C][C]0.175383[/C][/ROW]
[ROW][C]17[/C][C]0.000856[/C][C]0.0059[/C][C]0.497672[/C][/ROW]
[ROW][C]18[/C][C]-0.008167[/C][C]-0.056[/C][C]0.477794[/C][/ROW]
[ROW][C]19[/C][C]0.045283[/C][C]0.3104[/C][C]0.378798[/C][/ROW]
[ROW][C]20[/C][C]-0.005789[/C][C]-0.0397[/C][C]0.484255[/C][/ROW]
[ROW][C]21[/C][C]-0.018294[/C][C]-0.1254[/C][C]0.450364[/C][/ROW]
[ROW][C]22[/C][C]0.002239[/C][C]0.0154[/C][C]0.493908[/C][/ROW]
[ROW][C]23[/C][C]0.041148[/C][C]0.2821[/C][C]0.389554[/C][/ROW]
[ROW][C]24[/C][C]-0.195276[/C][C]-1.3387[/C][C]0.093547[/C][/ROW]
[ROW][C]25[/C][C]0.202429[/C][C]1.3878[/C][C]0.085873[/C][/ROW]
[ROW][C]26[/C][C]-0.067898[/C][C]-0.4655[/C][C]0.321867[/C][/ROW]
[ROW][C]27[/C][C]-0.083981[/C][C]-0.5757[/C][C]0.283767[/C][/ROW]
[ROW][C]28[/C][C]-0.062051[/C][C]-0.4254[/C][C]0.336244[/C][/ROW]
[ROW][C]29[/C][C]0.20775[/C][C]1.4243[/C][C]0.080489[/C][/ROW]
[ROW][C]30[/C][C]-0.052397[/C][C]-0.3592[/C][C]0.360522[/C][/ROW]
[ROW][C]31[/C][C]-0.023505[/C][C]-0.1611[/C][C]0.436335[/C][/ROW]
[ROW][C]32[/C][C]0.055395[/C][C]0.3798[/C][C]0.352914[/C][/ROW]
[ROW][C]33[/C][C]-0.110686[/C][C]-0.7588[/C][C]0.225874[/C][/ROW]
[ROW][C]34[/C][C]0.135165[/C][C]0.9266[/C][C]0.179423[/C][/ROW]
[ROW][C]35[/C][C]-0.080081[/C][C]-0.549[/C][C]0.292799[/C][/ROW]
[ROW][C]36[/C][C]0.056925[/C][C]0.3903[/C][C]0.349054[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66022&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66022&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	-0.484636	-3.3225	0.000867
2	0.081893	0.5614	0.288586
3	-0.10111	-0.6932	0.245806
4	0.199041	1.3646	0.089445
5	-0.198363	-1.3599	0.090174
6	0.070533	0.4836	0.315475
7	-0.035409	-0.2428	0.404627
8	-0.142746	-0.9786	0.16639
9	0.188447	1.2919	0.10135
10	-0.194835	-1.3357	0.094036
11	0.266072	1.8241	0.037249
12	-0.206381	-1.4149	0.081848
13	0.03619	0.2481	0.402567
14	0.001537	0.0105	0.49582
15	0.159615	1.0943	0.139708
16	-0.137475	-0.9425	0.175383
17	0.000856	0.0059	0.497672
18	-0.008167	-0.056	0.477794
19	0.045283	0.3104	0.378798
20	-0.005789	-0.0397	0.484255
21	-0.018294	-0.1254	0.450364
22	0.002239	0.0154	0.493908
23	0.041148	0.2821	0.389554
24	-0.195276	-1.3387	0.093547
25	0.202429	1.3878	0.085873
26	-0.067898	-0.4655	0.321867
27	-0.083981	-0.5757	0.283767
28	-0.062051	-0.4254	0.336244
29	0.20775	1.4243	0.080489
30	-0.052397	-0.3592	0.360522
31	-0.023505	-0.1611	0.436335
32	0.055395	0.3798	0.352914
33	-0.110686	-0.7588	0.225874
34	0.135165	0.9266	0.179423
35	-0.080081	-0.549	0.292799
36	0.056925	0.3903	0.349054

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.484636	-3.3225	0.000867
2	-0.19994	-1.3707	0.088487
3	-0.204732	-1.4036	0.083509
4	0.089529	0.6138	0.27116
5	-0.074328	-0.5096	0.306369
6	-0.064669	-0.4434	0.329773
7	-0.05144	-0.3527	0.362961
8	-0.307027	-2.1049	0.020338
9	-0.007049	-0.0483	0.48083
10	-0.216201	-1.4822	0.072481
11	0.141878	0.9727	0.16785
12	0.013649	0.0936	0.462924
13	-0.198345	-1.3598	0.090193
14	-0.018997	-0.1302	0.448467
15	0.015687	0.1075	0.457408
16	0.055045	0.3774	0.353799
17	0.005752	0.0394	0.484357
18	-0.139023	-0.9531	0.17271
19	0.069125	0.4739	0.318883
20	-0.055738	-0.3821	0.352046
21	0.047996	0.329	0.371792
22	0.025042	0.1717	0.432212
23	0.074689	0.512	0.30551
24	-0.227095	-1.5569	0.063103
25	-0.035691	-0.2447	0.403882
26	-0.053907	-0.3696	0.356683
27	-0.135915	-0.9318	0.178105
28	-0.171963	-1.1789	0.122182
29	-0.030694	-0.2104	0.417122
30	0.029859	0.2047	0.419344
31	0.003904	0.0268	0.48938
32	0.002747	0.0188	0.492527
33	-0.125089	-0.8576	0.197741
34	-0.10793	-0.7399	0.23151
35	0.013178	0.0903	0.464199
36	-0.05897	-0.4043	0.343921

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.484636 & -3.3225 & 0.000867 \tabularnewline
2 & -0.19994 & -1.3707 & 0.088487 \tabularnewline
3 & -0.204732 & -1.4036 & 0.083509 \tabularnewline
4 & 0.089529 & 0.6138 & 0.27116 \tabularnewline
5 & -0.074328 & -0.5096 & 0.306369 \tabularnewline
6 & -0.064669 & -0.4434 & 0.329773 \tabularnewline
7 & -0.05144 & -0.3527 & 0.362961 \tabularnewline
8 & -0.307027 & -2.1049 & 0.020338 \tabularnewline
9 & -0.007049 & -0.0483 & 0.48083 \tabularnewline
10 & -0.216201 & -1.4822 & 0.072481 \tabularnewline
11 & 0.141878 & 0.9727 & 0.16785 \tabularnewline
12 & 0.013649 & 0.0936 & 0.462924 \tabularnewline
13 & -0.198345 & -1.3598 & 0.090193 \tabularnewline
14 & -0.018997 & -0.1302 & 0.448467 \tabularnewline
15 & 0.015687 & 0.1075 & 0.457408 \tabularnewline
16 & 0.055045 & 0.3774 & 0.353799 \tabularnewline
17 & 0.005752 & 0.0394 & 0.484357 \tabularnewline
18 & -0.139023 & -0.9531 & 0.17271 \tabularnewline
19 & 0.069125 & 0.4739 & 0.318883 \tabularnewline
20 & -0.055738 & -0.3821 & 0.352046 \tabularnewline
21 & 0.047996 & 0.329 & 0.371792 \tabularnewline
22 & 0.025042 & 0.1717 & 0.432212 \tabularnewline
23 & 0.074689 & 0.512 & 0.30551 \tabularnewline
24 & -0.227095 & -1.5569 & 0.063103 \tabularnewline
25 & -0.035691 & -0.2447 & 0.403882 \tabularnewline
26 & -0.053907 & -0.3696 & 0.356683 \tabularnewline
27 & -0.135915 & -0.9318 & 0.178105 \tabularnewline
28 & -0.171963 & -1.1789 & 0.122182 \tabularnewline
29 & -0.030694 & -0.2104 & 0.417122 \tabularnewline
30 & 0.029859 & 0.2047 & 0.419344 \tabularnewline
31 & 0.003904 & 0.0268 & 0.48938 \tabularnewline
32 & 0.002747 & 0.0188 & 0.492527 \tabularnewline
33 & -0.125089 & -0.8576 & 0.197741 \tabularnewline
34 & -0.10793 & -0.7399 & 0.23151 \tabularnewline
35 & 0.013178 & 0.0903 & 0.464199 \tabularnewline
36 & -0.05897 & -0.4043 & 0.343921 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66022&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]-0.484636[/C][C]-3.3225[/C][C]0.000867[/C][/ROW]
[ROW][C]2[/C][C]-0.19994[/C][C]-1.3707[/C][C]0.088487[/C][/ROW]
[ROW][C]3[/C][C]-0.204732[/C][C]-1.4036[/C][C]0.083509[/C][/ROW]
[ROW][C]4[/C][C]0.089529[/C][C]0.6138[/C][C]0.27116[/C][/ROW]
[ROW][C]5[/C][C]-0.074328[/C][C]-0.5096[/C][C]0.306369[/C][/ROW]
[ROW][C]6[/C][C]-0.064669[/C][C]-0.4434[/C][C]0.329773[/C][/ROW]
[ROW][C]7[/C][C]-0.05144[/C][C]-0.3527[/C][C]0.362961[/C][/ROW]
[ROW][C]8[/C][C]-0.307027[/C][C]-2.1049[/C][C]0.020338[/C][/ROW]
[ROW][C]9[/C][C]-0.007049[/C][C]-0.0483[/C][C]0.48083[/C][/ROW]
[ROW][C]10[/C][C]-0.216201[/C][C]-1.4822[/C][C]0.072481[/C][/ROW]
[ROW][C]11[/C][C]0.141878[/C][C]0.9727[/C][C]0.16785[/C][/ROW]
[ROW][C]12[/C][C]0.013649[/C][C]0.0936[/C][C]0.462924[/C][/ROW]
[ROW][C]13[/C][C]-0.198345[/C][C]-1.3598[/C][C]0.090193[/C][/ROW]
[ROW][C]14[/C][C]-0.018997[/C][C]-0.1302[/C][C]0.448467[/C][/ROW]
[ROW][C]15[/C][C]0.015687[/C][C]0.1075[/C][C]0.457408[/C][/ROW]
[ROW][C]16[/C][C]0.055045[/C][C]0.3774[/C][C]0.353799[/C][/ROW]
[ROW][C]17[/C][C]0.005752[/C][C]0.0394[/C][C]0.484357[/C][/ROW]
[ROW][C]18[/C][C]-0.139023[/C][C]-0.9531[/C][C]0.17271[/C][/ROW]
[ROW][C]19[/C][C]0.069125[/C][C]0.4739[/C][C]0.318883[/C][/ROW]
[ROW][C]20[/C][C]-0.055738[/C][C]-0.3821[/C][C]0.352046[/C][/ROW]
[ROW][C]21[/C][C]0.047996[/C][C]0.329[/C][C]0.371792[/C][/ROW]
[ROW][C]22[/C][C]0.025042[/C][C]0.1717[/C][C]0.432212[/C][/ROW]
[ROW][C]23[/C][C]0.074689[/C][C]0.512[/C][C]0.30551[/C][/ROW]
[ROW][C]24[/C][C]-0.227095[/C][C]-1.5569[/C][C]0.063103[/C][/ROW]
[ROW][C]25[/C][C]-0.035691[/C][C]-0.2447[/C][C]0.403882[/C][/ROW]
[ROW][C]26[/C][C]-0.053907[/C][C]-0.3696[/C][C]0.356683[/C][/ROW]
[ROW][C]27[/C][C]-0.135915[/C][C]-0.9318[/C][C]0.178105[/C][/ROW]
[ROW][C]28[/C][C]-0.171963[/C][C]-1.1789[/C][C]0.122182[/C][/ROW]
[ROW][C]29[/C][C]-0.030694[/C][C]-0.2104[/C][C]0.417122[/C][/ROW]
[ROW][C]30[/C][C]0.029859[/C][C]0.2047[/C][C]0.419344[/C][/ROW]
[ROW][C]31[/C][C]0.003904[/C][C]0.0268[/C][C]0.48938[/C][/ROW]
[ROW][C]32[/C][C]0.002747[/C][C]0.0188[/C][C]0.492527[/C][/ROW]
[ROW][C]33[/C][C]-0.125089[/C][C]-0.8576[/C][C]0.197741[/C][/ROW]
[ROW][C]34[/C][C]-0.10793[/C][C]-0.7399[/C][C]0.23151[/C][/ROW]
[ROW][C]35[/C][C]0.013178[/C][C]0.0903[/C][C]0.464199[/C][/ROW]
[ROW][C]36[/C][C]-0.05897[/C][C]-0.4043[/C][C]0.343921[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66022&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66022&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	-0.484636	-3.3225	0.000867
2	-0.19994	-1.3707	0.088487
3	-0.204732	-1.4036	0.083509
4	0.089529	0.6138	0.27116
5	-0.074328	-0.5096	0.306369
6	-0.064669	-0.4434	0.329773
7	-0.05144	-0.3527	0.362961
8	-0.307027	-2.1049	0.020338
9	-0.007049	-0.0483	0.48083
10	-0.216201	-1.4822	0.072481
11	0.141878	0.9727	0.16785
12	0.013649	0.0936	0.462924
13	-0.198345	-1.3598	0.090193
14	-0.018997	-0.1302	0.448467
15	0.015687	0.1075	0.457408
16	0.055045	0.3774	0.353799
17	0.005752	0.0394	0.484357
18	-0.139023	-0.9531	0.17271
19	0.069125	0.4739	0.318883
20	-0.055738	-0.3821	0.352046
21	0.047996	0.329	0.371792
22	0.025042	0.1717	0.432212
23	0.074689	0.512	0.30551
24	-0.227095	-1.5569	0.063103
25	-0.035691	-0.2447	0.403882
26	-0.053907	-0.3696	0.356683
27	-0.135915	-0.9318	0.178105
28	-0.171963	-1.1789	0.122182
29	-0.030694	-0.2104	0.417122
30	0.029859	0.2047	0.419344
31	0.003904	0.0268	0.48938
32	0.002747	0.0188	0.492527
33	-0.125089	-0.8576	0.197741
34	-0.10793	-0.7399	0.23151
35	0.013178	0.0903	0.464199
36	-0.05897	-0.4043	0.343921

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