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rwasp_autocorrelation.wasp

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(Partial) Autocorrelation Function

Date of computation

Thu, 26 Nov 2009 11:35:46 -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/t1259260589yas1qfbtaei6li2.htm/, Retrieved Mon, 29 Apr 2024 07:23:11 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60251, Retrieved Mon, 29 Apr 2024 07:23:11 +0000

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122

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-       [(Partial) Autocorrelation Function] [] [2009-11-26 18:35:46] [8551abdd6804649d94d88b1829ac2b1a] [Current]
-   PD    [(Partial) Autocorrelation Function] [] [2009-11-26 20:12:06] [875a981b2b01315c1c471abd4dd66675] 
-   P       [(Partial) Autocorrelation Function] [] [2009-11-26 20:23:33] [875a981b2b01315c1c471abd4dd66675] 
-   P       [(Partial) Autocorrelation Function] [] [2009-11-26 20:35:07] [875a981b2b01315c1c471abd4dd66675] 

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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=60251&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=60251&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60251&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	0.633074	4.9038	4e-06
2	0.398772	3.0889	0.001521
3	0.38314	2.9678	0.002152
4	0.37581	2.911	0.002525
5	0.341304	2.6437	0.005224
6	0.205791	1.5941	0.058089
7	0.155536	1.2048	0.11651
8	-0.010487	-0.0812	0.467765
9	-0.174592	-1.3524	0.090664
10	-0.30106	-2.332	0.011538
11	-0.159473	-1.2353	0.110772
12	0.079549	0.6162	0.270051
13	-0.143283	-1.1099	0.135742
14	-0.312037	-2.417	0.009352
15	-0.229668	-1.779	0.040153
16	-0.12197	-0.9448	0.174281
17	-0.081969	-0.6349	0.263945
18	-0.098273	-0.7612	0.224754
19	-0.07034	-0.5449	0.293936
20	-0.126249	-0.9779	0.166019
21	-0.210683	-1.6319	0.053965
22	-0.26819	-2.0774	0.021027
23	-0.136671	-1.0587	0.147001
24	0.012741	0.0987	0.460857
25	-0.133543	-1.0344	0.152546
26	-0.289445	-2.242	0.014334
27	-0.23251	-1.801	0.038363
28	-0.123484	-0.9565	0.171328
29	-0.128867	-0.9982	0.161095
30	-0.120442	-0.9329	0.177294
31	-0.113299	-0.8776	0.191827
32	-0.141661	-1.0973	0.138446
33	-0.187635	-1.4534	0.07566
34	-0.186746	-1.4465	0.076617
35	-0.085487	-0.6622	0.255196
36	0.041682	0.3229	0.37396

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.633074 & 4.9038 & 4e-06 \tabularnewline
2 & 0.398772 & 3.0889 & 0.001521 \tabularnewline
3 & 0.38314 & 2.9678 & 0.002152 \tabularnewline
4 & 0.37581 & 2.911 & 0.002525 \tabularnewline
5 & 0.341304 & 2.6437 & 0.005224 \tabularnewline
6 & 0.205791 & 1.5941 & 0.058089 \tabularnewline
7 & 0.155536 & 1.2048 & 0.11651 \tabularnewline
8 & -0.010487 & -0.0812 & 0.467765 \tabularnewline
9 & -0.174592 & -1.3524 & 0.090664 \tabularnewline
10 & -0.30106 & -2.332 & 0.011538 \tabularnewline
11 & -0.159473 & -1.2353 & 0.110772 \tabularnewline
12 & 0.079549 & 0.6162 & 0.270051 \tabularnewline
13 & -0.143283 & -1.1099 & 0.135742 \tabularnewline
14 & -0.312037 & -2.417 & 0.009352 \tabularnewline
15 & -0.229668 & -1.779 & 0.040153 \tabularnewline
16 & -0.12197 & -0.9448 & 0.174281 \tabularnewline
17 & -0.081969 & -0.6349 & 0.263945 \tabularnewline
18 & -0.098273 & -0.7612 & 0.224754 \tabularnewline
19 & -0.07034 & -0.5449 & 0.293936 \tabularnewline
20 & -0.126249 & -0.9779 & 0.166019 \tabularnewline
21 & -0.210683 & -1.6319 & 0.053965 \tabularnewline
22 & -0.26819 & -2.0774 & 0.021027 \tabularnewline
23 & -0.136671 & -1.0587 & 0.147001 \tabularnewline
24 & 0.012741 & 0.0987 & 0.460857 \tabularnewline
25 & -0.133543 & -1.0344 & 0.152546 \tabularnewline
26 & -0.289445 & -2.242 & 0.014334 \tabularnewline
27 & -0.23251 & -1.801 & 0.038363 \tabularnewline
28 & -0.123484 & -0.9565 & 0.171328 \tabularnewline
29 & -0.128867 & -0.9982 & 0.161095 \tabularnewline
30 & -0.120442 & -0.9329 & 0.177294 \tabularnewline
31 & -0.113299 & -0.8776 & 0.191827 \tabularnewline
32 & -0.141661 & -1.0973 & 0.138446 \tabularnewline
33 & -0.187635 & -1.4534 & 0.07566 \tabularnewline
34 & -0.186746 & -1.4465 & 0.076617 \tabularnewline
35 & -0.085487 & -0.6622 & 0.255196 \tabularnewline
36 & 0.041682 & 0.3229 & 0.37396 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60251&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]0.633074[/C][C]4.9038[/C][C]4e-06[/C][/ROW]
[ROW][C]2[/C][C]0.398772[/C][C]3.0889[/C][C]0.001521[/C][/ROW]
[ROW][C]3[/C][C]0.38314[/C][C]2.9678[/C][C]0.002152[/C][/ROW]
[ROW][C]4[/C][C]0.37581[/C][C]2.911[/C][C]0.002525[/C][/ROW]
[ROW][C]5[/C][C]0.341304[/C][C]2.6437[/C][C]0.005224[/C][/ROW]
[ROW][C]6[/C][C]0.205791[/C][C]1.5941[/C][C]0.058089[/C][/ROW]
[ROW][C]7[/C][C]0.155536[/C][C]1.2048[/C][C]0.11651[/C][/ROW]
[ROW][C]8[/C][C]-0.010487[/C][C]-0.0812[/C][C]0.467765[/C][/ROW]
[ROW][C]9[/C][C]-0.174592[/C][C]-1.3524[/C][C]0.090664[/C][/ROW]
[ROW][C]10[/C][C]-0.30106[/C][C]-2.332[/C][C]0.011538[/C][/ROW]
[ROW][C]11[/C][C]-0.159473[/C][C]-1.2353[/C][C]0.110772[/C][/ROW]
[ROW][C]12[/C][C]0.079549[/C][C]0.6162[/C][C]0.270051[/C][/ROW]
[ROW][C]13[/C][C]-0.143283[/C][C]-1.1099[/C][C]0.135742[/C][/ROW]
[ROW][C]14[/C][C]-0.312037[/C][C]-2.417[/C][C]0.009352[/C][/ROW]
[ROW][C]15[/C][C]-0.229668[/C][C]-1.779[/C][C]0.040153[/C][/ROW]
[ROW][C]16[/C][C]-0.12197[/C][C]-0.9448[/C][C]0.174281[/C][/ROW]
[ROW][C]17[/C][C]-0.081969[/C][C]-0.6349[/C][C]0.263945[/C][/ROW]
[ROW][C]18[/C][C]-0.098273[/C][C]-0.7612[/C][C]0.224754[/C][/ROW]
[ROW][C]19[/C][C]-0.07034[/C][C]-0.5449[/C][C]0.293936[/C][/ROW]
[ROW][C]20[/C][C]-0.126249[/C][C]-0.9779[/C][C]0.166019[/C][/ROW]
[ROW][C]21[/C][C]-0.210683[/C][C]-1.6319[/C][C]0.053965[/C][/ROW]
[ROW][C]22[/C][C]-0.26819[/C][C]-2.0774[/C][C]0.021027[/C][/ROW]
[ROW][C]23[/C][C]-0.136671[/C][C]-1.0587[/C][C]0.147001[/C][/ROW]
[ROW][C]24[/C][C]0.012741[/C][C]0.0987[/C][C]0.460857[/C][/ROW]
[ROW][C]25[/C][C]-0.133543[/C][C]-1.0344[/C][C]0.152546[/C][/ROW]
[ROW][C]26[/C][C]-0.289445[/C][C]-2.242[/C][C]0.014334[/C][/ROW]
[ROW][C]27[/C][C]-0.23251[/C][C]-1.801[/C][C]0.038363[/C][/ROW]
[ROW][C]28[/C][C]-0.123484[/C][C]-0.9565[/C][C]0.171328[/C][/ROW]
[ROW][C]29[/C][C]-0.128867[/C][C]-0.9982[/C][C]0.161095[/C][/ROW]
[ROW][C]30[/C][C]-0.120442[/C][C]-0.9329[/C][C]0.177294[/C][/ROW]
[ROW][C]31[/C][C]-0.113299[/C][C]-0.8776[/C][C]0.191827[/C][/ROW]
[ROW][C]32[/C][C]-0.141661[/C][C]-1.0973[/C][C]0.138446[/C][/ROW]
[ROW][C]33[/C][C]-0.187635[/C][C]-1.4534[/C][C]0.07566[/C][/ROW]
[ROW][C]34[/C][C]-0.186746[/C][C]-1.4465[/C][C]0.076617[/C][/ROW]
[ROW][C]35[/C][C]-0.085487[/C][C]-0.6622[/C][C]0.255196[/C][/ROW]
[ROW][C]36[/C][C]0.041682[/C][C]0.3229[/C][C]0.37396[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60251&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60251&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	0.633074	4.9038	4e-06
2	0.398772	3.0889	0.001521
3	0.38314	2.9678	0.002152
4	0.37581	2.911	0.002525
5	0.341304	2.6437	0.005224
6	0.205791	1.5941	0.058089
7	0.155536	1.2048	0.11651
8	-0.010487	-0.0812	0.467765
9	-0.174592	-1.3524	0.090664
10	-0.30106	-2.332	0.011538
11	-0.159473	-1.2353	0.110772
12	0.079549	0.6162	0.270051
13	-0.143283	-1.1099	0.135742
14	-0.312037	-2.417	0.009352
15	-0.229668	-1.779	0.040153
16	-0.12197	-0.9448	0.174281
17	-0.081969	-0.6349	0.263945
18	-0.098273	-0.7612	0.224754
19	-0.07034	-0.5449	0.293936
20	-0.126249	-0.9779	0.166019
21	-0.210683	-1.6319	0.053965
22	-0.26819	-2.0774	0.021027
23	-0.136671	-1.0587	0.147001
24	0.012741	0.0987	0.460857
25	-0.133543	-1.0344	0.152546
26	-0.289445	-2.242	0.014334
27	-0.23251	-1.801	0.038363
28	-0.123484	-0.9565	0.171328
29	-0.128867	-0.9982	0.161095
30	-0.120442	-0.9329	0.177294
31	-0.113299	-0.8776	0.191827
32	-0.141661	-1.0973	0.138446
33	-0.187635	-1.4534	0.07566
34	-0.186746	-1.4465	0.076617
35	-0.085487	-0.6622	0.255196
36	0.041682	0.3229	0.37396

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.633074	4.9038	4e-06
2	-0.003354	-0.026	0.489678
3	0.22023	1.7059	0.0466
4	0.087446	0.6774	0.250391
5	0.068272	0.5288	0.299435
6	-0.136894	-1.0604	0.146611
7	0.029481	0.2284	0.410072
8	-0.307607	-2.3827	0.010185
9	-0.193832	-1.5014	0.069246
10	-0.294832	-2.2838	0.01297
11	0.312353	2.4195	0.009295
12	0.441768	3.4219	0.000563
13	-0.262852	-2.036	0.023084
14	-0.185823	-1.4394	0.07762
15	0.097256	0.7533	0.227096
16	0.008822	0.0683	0.472873
17	-0.087773	-0.6799	0.249595
18	-0.146639	-1.1359	0.130266
19	-0.145907	-1.1302	0.131447
20	-0.050373	-0.3902	0.348891
21	0.055388	0.429	0.334718
22	0.042917	0.3324	0.370361
23	-0.022575	-0.1749	0.430887
24	-0.124669	-0.9657	0.16904
25	0.064827	0.5021	0.3087
26	0.011044	0.0855	0.466056
27	-0.06713	-0.52	0.302492
28	-0.093017	-0.7205	0.237004
29	-0.170683	-1.3221	0.095576
30	-0.004528	-0.0351	0.486069
31	-0.078393	-0.6072	0.272994
32	-0.060211	-0.4664	0.321312
33	-0.04134	-0.3202	0.374957
34	0.066894	0.5182	0.303126
35	-0.08082	-0.626	0.266834
36	0.111951	0.8672	0.194653

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.633074 & 4.9038 & 4e-06 \tabularnewline
2 & -0.003354 & -0.026 & 0.489678 \tabularnewline
3 & 0.22023 & 1.7059 & 0.0466 \tabularnewline
4 & 0.087446 & 0.6774 & 0.250391 \tabularnewline
5 & 0.068272 & 0.5288 & 0.299435 \tabularnewline
6 & -0.136894 & -1.0604 & 0.146611 \tabularnewline
7 & 0.029481 & 0.2284 & 0.410072 \tabularnewline
8 & -0.307607 & -2.3827 & 0.010185 \tabularnewline
9 & -0.193832 & -1.5014 & 0.069246 \tabularnewline
10 & -0.294832 & -2.2838 & 0.01297 \tabularnewline
11 & 0.312353 & 2.4195 & 0.009295 \tabularnewline
12 & 0.441768 & 3.4219 & 0.000563 \tabularnewline
13 & -0.262852 & -2.036 & 0.023084 \tabularnewline
14 & -0.185823 & -1.4394 & 0.07762 \tabularnewline
15 & 0.097256 & 0.7533 & 0.227096 \tabularnewline
16 & 0.008822 & 0.0683 & 0.472873 \tabularnewline
17 & -0.087773 & -0.6799 & 0.249595 \tabularnewline
18 & -0.146639 & -1.1359 & 0.130266 \tabularnewline
19 & -0.145907 & -1.1302 & 0.131447 \tabularnewline
20 & -0.050373 & -0.3902 & 0.348891 \tabularnewline
21 & 0.055388 & 0.429 & 0.334718 \tabularnewline
22 & 0.042917 & 0.3324 & 0.370361 \tabularnewline
23 & -0.022575 & -0.1749 & 0.430887 \tabularnewline
24 & -0.124669 & -0.9657 & 0.16904 \tabularnewline
25 & 0.064827 & 0.5021 & 0.3087 \tabularnewline
26 & 0.011044 & 0.0855 & 0.466056 \tabularnewline
27 & -0.06713 & -0.52 & 0.302492 \tabularnewline
28 & -0.093017 & -0.7205 & 0.237004 \tabularnewline
29 & -0.170683 & -1.3221 & 0.095576 \tabularnewline
30 & -0.004528 & -0.0351 & 0.486069 \tabularnewline
31 & -0.078393 & -0.6072 & 0.272994 \tabularnewline
32 & -0.060211 & -0.4664 & 0.321312 \tabularnewline
33 & -0.04134 & -0.3202 & 0.374957 \tabularnewline
34 & 0.066894 & 0.5182 & 0.303126 \tabularnewline
35 & -0.08082 & -0.626 & 0.266834 \tabularnewline
36 & 0.111951 & 0.8672 & 0.194653 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60251&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]0.633074[/C][C]4.9038[/C][C]4e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.003354[/C][C]-0.026[/C][C]0.489678[/C][/ROW]
[ROW][C]3[/C][C]0.22023[/C][C]1.7059[/C][C]0.0466[/C][/ROW]
[ROW][C]4[/C][C]0.087446[/C][C]0.6774[/C][C]0.250391[/C][/ROW]
[ROW][C]5[/C][C]0.068272[/C][C]0.5288[/C][C]0.299435[/C][/ROW]
[ROW][C]6[/C][C]-0.136894[/C][C]-1.0604[/C][C]0.146611[/C][/ROW]
[ROW][C]7[/C][C]0.029481[/C][C]0.2284[/C][C]0.410072[/C][/ROW]
[ROW][C]8[/C][C]-0.307607[/C][C]-2.3827[/C][C]0.010185[/C][/ROW]
[ROW][C]9[/C][C]-0.193832[/C][C]-1.5014[/C][C]0.069246[/C][/ROW]
[ROW][C]10[/C][C]-0.294832[/C][C]-2.2838[/C][C]0.01297[/C][/ROW]
[ROW][C]11[/C][C]0.312353[/C][C]2.4195[/C][C]0.009295[/C][/ROW]
[ROW][C]12[/C][C]0.441768[/C][C]3.4219[/C][C]0.000563[/C][/ROW]
[ROW][C]13[/C][C]-0.262852[/C][C]-2.036[/C][C]0.023084[/C][/ROW]
[ROW][C]14[/C][C]-0.185823[/C][C]-1.4394[/C][C]0.07762[/C][/ROW]
[ROW][C]15[/C][C]0.097256[/C][C]0.7533[/C][C]0.227096[/C][/ROW]
[ROW][C]16[/C][C]0.008822[/C][C]0.0683[/C][C]0.472873[/C][/ROW]
[ROW][C]17[/C][C]-0.087773[/C][C]-0.6799[/C][C]0.249595[/C][/ROW]
[ROW][C]18[/C][C]-0.146639[/C][C]-1.1359[/C][C]0.130266[/C][/ROW]
[ROW][C]19[/C][C]-0.145907[/C][C]-1.1302[/C][C]0.131447[/C][/ROW]
[ROW][C]20[/C][C]-0.050373[/C][C]-0.3902[/C][C]0.348891[/C][/ROW]
[ROW][C]21[/C][C]0.055388[/C][C]0.429[/C][C]0.334718[/C][/ROW]
[ROW][C]22[/C][C]0.042917[/C][C]0.3324[/C][C]0.370361[/C][/ROW]
[ROW][C]23[/C][C]-0.022575[/C][C]-0.1749[/C][C]0.430887[/C][/ROW]
[ROW][C]24[/C][C]-0.124669[/C][C]-0.9657[/C][C]0.16904[/C][/ROW]
[ROW][C]25[/C][C]0.064827[/C][C]0.5021[/C][C]0.3087[/C][/ROW]
[ROW][C]26[/C][C]0.011044[/C][C]0.0855[/C][C]0.466056[/C][/ROW]
[ROW][C]27[/C][C]-0.06713[/C][C]-0.52[/C][C]0.302492[/C][/ROW]
[ROW][C]28[/C][C]-0.093017[/C][C]-0.7205[/C][C]0.237004[/C][/ROW]
[ROW][C]29[/C][C]-0.170683[/C][C]-1.3221[/C][C]0.095576[/C][/ROW]
[ROW][C]30[/C][C]-0.004528[/C][C]-0.0351[/C][C]0.486069[/C][/ROW]
[ROW][C]31[/C][C]-0.078393[/C][C]-0.6072[/C][C]0.272994[/C][/ROW]
[ROW][C]32[/C][C]-0.060211[/C][C]-0.4664[/C][C]0.321312[/C][/ROW]
[ROW][C]33[/C][C]-0.04134[/C][C]-0.3202[/C][C]0.374957[/C][/ROW]
[ROW][C]34[/C][C]0.066894[/C][C]0.5182[/C][C]0.303126[/C][/ROW]
[ROW][C]35[/C][C]-0.08082[/C][C]-0.626[/C][C]0.266834[/C][/ROW]
[ROW][C]36[/C][C]0.111951[/C][C]0.8672[/C][C]0.194653[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60251&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60251&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	0.633074	4.9038	4e-06
2	-0.003354	-0.026	0.489678
3	0.22023	1.7059	0.0466
4	0.087446	0.6774	0.250391
5	0.068272	0.5288	0.299435
6	-0.136894	-1.0604	0.146611
7	0.029481	0.2284	0.410072
8	-0.307607	-2.3827	0.010185
9	-0.193832	-1.5014	0.069246
10	-0.294832	-2.2838	0.01297
11	0.312353	2.4195	0.009295
12	0.441768	3.4219	0.000563
13	-0.262852	-2.036	0.023084
14	-0.185823	-1.4394	0.07762
15	0.097256	0.7533	0.227096
16	0.008822	0.0683	0.472873
17	-0.087773	-0.6799	0.249595
18	-0.146639	-1.1359	0.130266
19	-0.145907	-1.1302	0.131447
20	-0.050373	-0.3902	0.348891
21	0.055388	0.429	0.334718
22	0.042917	0.3324	0.370361
23	-0.022575	-0.1749	0.430887
24	-0.124669	-0.9657	0.16904
25	0.064827	0.5021	0.3087
26	0.011044	0.0855	0.466056
27	-0.06713	-0.52	0.302492
28	-0.093017	-0.7205	0.237004
29	-0.170683	-1.3221	0.095576
30	-0.004528	-0.0351	0.486069
31	-0.078393	-0.6072	0.272994
32	-0.060211	-0.4664	0.321312
33	-0.04134	-0.3202	0.374957
34	0.066894	0.5182	0.303126
35	-0.08082	-0.626	0.266834
36	0.111951	0.8672	0.194653

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 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; 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