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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Fri, 29 Jul 2016 12:51:41 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Jul/29/t146979313234o928fu74kt0ii.htm/, Retrieved Mon, 29 Apr 2024 13:20:53 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=295965, Retrieved Mon, 29 Apr 2024 13:20:53 +0000

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169

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-       [(Partial) Autocorrelation Function] [] [2016-07-29 11:51:41] [1b498ae19017f51f703ef2d779b672b0] [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	'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295965&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295965&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295965&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	'Gertrude Mary Cox' @ cox.wessa.net

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.970905	10.6357	0
2	0.936079	10.2542	0
3	0.901958	9.8805	0
4	0.873269	9.5662	0
5	0.845997	9.2674	0
6	0.821367	8.9976	0
7	0.801873	8.7841	0
8	0.783996	8.5882	0
9	0.765076	8.381	0
10	0.745514	8.1667	0
11	0.725792	7.9507	0
12	0.703607	7.7076	0
13	0.672668	7.3687	0
14	0.636777	6.9755	0
15	0.601132	6.5851	0
16	0.57003	6.2444	0
17	0.541358	5.9303	0
18	0.515357	5.6455	0
19	0.496283	5.4365	0
20	0.479717	5.255	0
21	0.463209	5.0742	1e-06
22	0.446554	4.8917	2e-06
23	0.430234	4.713	3e-06
24	0.411492	4.5077	8e-06
25	0.385218	4.2199	2.4e-05
26	0.353704	3.8746	8.7e-05
27	0.323297	3.5415	0.000284
28	0.296137	3.244	0.000763
29	0.271268	2.9716	0.00179
30	0.248287	2.7198	0.003751
31	0.231061	2.5311	0.006331
32	0.215368	2.3592	0.009964
33	0.199689	2.1875	0.015323
34	0.184341	2.0194	0.022839
35	0.169078	1.8522	0.03323
36	0.152297	1.6683	0.048929
37	0.130468	1.4292	0.077771
38	0.103762	1.1367	0.128973
39	0.076888	0.8423	0.200656
40	0.051856	0.5681	0.28553
41	0.030065	0.3293	0.371235
42	0.011845	0.1298	0.448488
43	-0.000504	-0.0055	0.4978
44	-0.011506	-0.126	0.449957
45	-0.02153	-0.2359	0.406974
46	-0.031446	-0.3445	0.365548
47	-0.042088	-0.4611	0.322797
48	-0.053259	-0.5834	0.280352

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.970905 & 10.6357 & 0 \tabularnewline
2 & 0.936079 & 10.2542 & 0 \tabularnewline
3 & 0.901958 & 9.8805 & 0 \tabularnewline
4 & 0.873269 & 9.5662 & 0 \tabularnewline
5 & 0.845997 & 9.2674 & 0 \tabularnewline
6 & 0.821367 & 8.9976 & 0 \tabularnewline
7 & 0.801873 & 8.7841 & 0 \tabularnewline
8 & 0.783996 & 8.5882 & 0 \tabularnewline
9 & 0.765076 & 8.381 & 0 \tabularnewline
10 & 0.745514 & 8.1667 & 0 \tabularnewline
11 & 0.725792 & 7.9507 & 0 \tabularnewline
12 & 0.703607 & 7.7076 & 0 \tabularnewline
13 & 0.672668 & 7.3687 & 0 \tabularnewline
14 & 0.636777 & 6.9755 & 0 \tabularnewline
15 & 0.601132 & 6.5851 & 0 \tabularnewline
16 & 0.57003 & 6.2444 & 0 \tabularnewline
17 & 0.541358 & 5.9303 & 0 \tabularnewline
18 & 0.515357 & 5.6455 & 0 \tabularnewline
19 & 0.496283 & 5.4365 & 0 \tabularnewline
20 & 0.479717 & 5.255 & 0 \tabularnewline
21 & 0.463209 & 5.0742 & 1e-06 \tabularnewline
22 & 0.446554 & 4.8917 & 2e-06 \tabularnewline
23 & 0.430234 & 4.713 & 3e-06 \tabularnewline
24 & 0.411492 & 4.5077 & 8e-06 \tabularnewline
25 & 0.385218 & 4.2199 & 2.4e-05 \tabularnewline
26 & 0.353704 & 3.8746 & 8.7e-05 \tabularnewline
27 & 0.323297 & 3.5415 & 0.000284 \tabularnewline
28 & 0.296137 & 3.244 & 0.000763 \tabularnewline
29 & 0.271268 & 2.9716 & 0.00179 \tabularnewline
30 & 0.248287 & 2.7198 & 0.003751 \tabularnewline
31 & 0.231061 & 2.5311 & 0.006331 \tabularnewline
32 & 0.215368 & 2.3592 & 0.009964 \tabularnewline
33 & 0.199689 & 2.1875 & 0.015323 \tabularnewline
34 & 0.184341 & 2.0194 & 0.022839 \tabularnewline
35 & 0.169078 & 1.8522 & 0.03323 \tabularnewline
36 & 0.152297 & 1.6683 & 0.048929 \tabularnewline
37 & 0.130468 & 1.4292 & 0.077771 \tabularnewline
38 & 0.103762 & 1.1367 & 0.128973 \tabularnewline
39 & 0.076888 & 0.8423 & 0.200656 \tabularnewline
40 & 0.051856 & 0.5681 & 0.28553 \tabularnewline
41 & 0.030065 & 0.3293 & 0.371235 \tabularnewline
42 & 0.011845 & 0.1298 & 0.448488 \tabularnewline
43 & -0.000504 & -0.0055 & 0.4978 \tabularnewline
44 & -0.011506 & -0.126 & 0.449957 \tabularnewline
45 & -0.02153 & -0.2359 & 0.406974 \tabularnewline
46 & -0.031446 & -0.3445 & 0.365548 \tabularnewline
47 & -0.042088 & -0.4611 & 0.322797 \tabularnewline
48 & -0.053259 & -0.5834 & 0.280352 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295965&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]0.970905[/C][C]10.6357[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.936079[/C][C]10.2542[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.901958[/C][C]9.8805[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.873269[/C][C]9.5662[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.845997[/C][C]9.2674[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.821367[/C][C]8.9976[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.801873[/C][C]8.7841[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.783996[/C][C]8.5882[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.765076[/C][C]8.381[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.745514[/C][C]8.1667[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.725792[/C][C]7.9507[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.703607[/C][C]7.7076[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.672668[/C][C]7.3687[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.636777[/C][C]6.9755[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.601132[/C][C]6.5851[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.57003[/C][C]6.2444[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.541358[/C][C]5.9303[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.515357[/C][C]5.6455[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.496283[/C][C]5.4365[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.479717[/C][C]5.255[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.463209[/C][C]5.0742[/C][C]1e-06[/C][/ROW]
[ROW][C]22[/C][C]0.446554[/C][C]4.8917[/C][C]2e-06[/C][/ROW]
[ROW][C]23[/C][C]0.430234[/C][C]4.713[/C][C]3e-06[/C][/ROW]
[ROW][C]24[/C][C]0.411492[/C][C]4.5077[/C][C]8e-06[/C][/ROW]
[ROW][C]25[/C][C]0.385218[/C][C]4.2199[/C][C]2.4e-05[/C][/ROW]
[ROW][C]26[/C][C]0.353704[/C][C]3.8746[/C][C]8.7e-05[/C][/ROW]
[ROW][C]27[/C][C]0.323297[/C][C]3.5415[/C][C]0.000284[/C][/ROW]
[ROW][C]28[/C][C]0.296137[/C][C]3.244[/C][C]0.000763[/C][/ROW]
[ROW][C]29[/C][C]0.271268[/C][C]2.9716[/C][C]0.00179[/C][/ROW]
[ROW][C]30[/C][C]0.248287[/C][C]2.7198[/C][C]0.003751[/C][/ROW]
[ROW][C]31[/C][C]0.231061[/C][C]2.5311[/C][C]0.006331[/C][/ROW]
[ROW][C]32[/C][C]0.215368[/C][C]2.3592[/C][C]0.009964[/C][/ROW]
[ROW][C]33[/C][C]0.199689[/C][C]2.1875[/C][C]0.015323[/C][/ROW]
[ROW][C]34[/C][C]0.184341[/C][C]2.0194[/C][C]0.022839[/C][/ROW]
[ROW][C]35[/C][C]0.169078[/C][C]1.8522[/C][C]0.03323[/C][/ROW]
[ROW][C]36[/C][C]0.152297[/C][C]1.6683[/C][C]0.048929[/C][/ROW]
[ROW][C]37[/C][C]0.130468[/C][C]1.4292[/C][C]0.077771[/C][/ROW]
[ROW][C]38[/C][C]0.103762[/C][C]1.1367[/C][C]0.128973[/C][/ROW]
[ROW][C]39[/C][C]0.076888[/C][C]0.8423[/C][C]0.200656[/C][/ROW]
[ROW][C]40[/C][C]0.051856[/C][C]0.5681[/C][C]0.28553[/C][/ROW]
[ROW][C]41[/C][C]0.030065[/C][C]0.3293[/C][C]0.371235[/C][/ROW]
[ROW][C]42[/C][C]0.011845[/C][C]0.1298[/C][C]0.448488[/C][/ROW]
[ROW][C]43[/C][C]-0.000504[/C][C]-0.0055[/C][C]0.4978[/C][/ROW]
[ROW][C]44[/C][C]-0.011506[/C][C]-0.126[/C][C]0.449957[/C][/ROW]
[ROW][C]45[/C][C]-0.02153[/C][C]-0.2359[/C][C]0.406974[/C][/ROW]
[ROW][C]46[/C][C]-0.031446[/C][C]-0.3445[/C][C]0.365548[/C][/ROW]
[ROW][C]47[/C][C]-0.042088[/C][C]-0.4611[/C][C]0.322797[/C][/ROW]
[ROW][C]48[/C][C]-0.053259[/C][C]-0.5834[/C][C]0.280352[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295965&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295965&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	0.970905	10.6357	0
2	0.936079	10.2542	0
3	0.901958	9.8805	0
4	0.873269	9.5662	0
5	0.845997	9.2674	0
6	0.821367	8.9976	0
7	0.801873	8.7841	0
8	0.783996	8.5882	0
9	0.765076	8.381	0
10	0.745514	8.1667	0
11	0.725792	7.9507	0
12	0.703607	7.7076	0
13	0.672668	7.3687	0
14	0.636777	6.9755	0
15	0.601132	6.5851	0
16	0.57003	6.2444	0
17	0.541358	5.9303	0
18	0.515357	5.6455	0
19	0.496283	5.4365	0
20	0.479717	5.255	0
21	0.463209	5.0742	1e-06
22	0.446554	4.8917	2e-06
23	0.430234	4.713	3e-06
24	0.411492	4.5077	8e-06
25	0.385218	4.2199	2.4e-05
26	0.353704	3.8746	8.7e-05
27	0.323297	3.5415	0.000284
28	0.296137	3.244	0.000763
29	0.271268	2.9716	0.00179
30	0.248287	2.7198	0.003751
31	0.231061	2.5311	0.006331
32	0.215368	2.3592	0.009964
33	0.199689	2.1875	0.015323
34	0.184341	2.0194	0.022839
35	0.169078	1.8522	0.03323
36	0.152297	1.6683	0.048929
37	0.130468	1.4292	0.077771
38	0.103762	1.1367	0.128973
39	0.076888	0.8423	0.200656
40	0.051856	0.5681	0.28553
41	0.030065	0.3293	0.371235
42	0.011845	0.1298	0.448488
43	-0.000504	-0.0055	0.4978
44	-0.011506	-0.126	0.449957
45	-0.02153	-0.2359	0.406974
46	-0.031446	-0.3445	0.365548
47	-0.042088	-0.4611	0.322797
48	-0.053259	-0.5834	0.280352

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.970905	10.6357	0
2	-0.114681	-1.2563	0.105729
3	0.004101	0.0449	0.482122
4	0.074655	0.8178	0.207546
5	-0.008505	-0.0932	0.462965
6	0.031057	0.3402	0.367147
7	0.077377	0.8476	0.199168
8	0.003404	0.0373	0.485158
9	-0.023327	-0.2555	0.399375
10	-0.001094	-0.012	0.495229
11	-0.006365	-0.0697	0.472265
12	-0.051296	-0.5619	0.287609
13	-0.152897	-1.6749	0.048278
14	-0.078823	-0.8635	0.194802
15	-0.017262	-0.1891	0.425168
16	0.028224	0.3092	0.37886
17	-0.006932	-0.0759	0.469797
18	0.009018	0.0988	0.460734
19	0.086071	0.9429	0.173824
20	0.005579	0.0611	0.475687
21	0.000647	0.0071	0.49718
22	0.022797	0.2497	0.401612
23	0.010019	0.1098	0.456393
24	-0.037829	-0.4144	0.339663
25	-0.102882	-1.127	0.130993
26	-0.069699	-0.7635	0.223328
27	-0.000416	-0.0046	0.498186
28	-0.007965	-0.0873	0.465308
29	-0.017754	-0.1945	0.423061
30	-0.013452	-0.1474	0.441546
31	0.043367	0.4751	0.317803
32	-0.023565	-0.2581	0.39837
33	-0.004003	-0.0439	0.482548
34	0.029266	0.3206	0.374539
35	-0.001534	-0.0168	0.493311
36	-0.018685	-0.2047	0.419081
37	-0.044102	-0.4831	0.314949
38	-0.058006	-0.6354	0.263179
39	-0.019713	-0.2159	0.414698
40	-0.02455	-0.2689	0.394222
41	0.000197	0.0022	0.499142
42	0.012768	0.1399	0.444499
43	0.03488	0.3821	0.351533
44	-0.028257	-0.3095	0.378723
45	0.01738	0.1904	0.424664
46	0.018593	0.2037	0.419475
47	-0.0166	-0.1818	0.428006
48	0.006562	0.0719	0.471408

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.970905 & 10.6357 & 0 \tabularnewline
2 & -0.114681 & -1.2563 & 0.105729 \tabularnewline
3 & 0.004101 & 0.0449 & 0.482122 \tabularnewline
4 & 0.074655 & 0.8178 & 0.207546 \tabularnewline
5 & -0.008505 & -0.0932 & 0.462965 \tabularnewline
6 & 0.031057 & 0.3402 & 0.367147 \tabularnewline
7 & 0.077377 & 0.8476 & 0.199168 \tabularnewline
8 & 0.003404 & 0.0373 & 0.485158 \tabularnewline
9 & -0.023327 & -0.2555 & 0.399375 \tabularnewline
10 & -0.001094 & -0.012 & 0.495229 \tabularnewline
11 & -0.006365 & -0.0697 & 0.472265 \tabularnewline
12 & -0.051296 & -0.5619 & 0.287609 \tabularnewline
13 & -0.152897 & -1.6749 & 0.048278 \tabularnewline
14 & -0.078823 & -0.8635 & 0.194802 \tabularnewline
15 & -0.017262 & -0.1891 & 0.425168 \tabularnewline
16 & 0.028224 & 0.3092 & 0.37886 \tabularnewline
17 & -0.006932 & -0.0759 & 0.469797 \tabularnewline
18 & 0.009018 & 0.0988 & 0.460734 \tabularnewline
19 & 0.086071 & 0.9429 & 0.173824 \tabularnewline
20 & 0.005579 & 0.0611 & 0.475687 \tabularnewline
21 & 0.000647 & 0.0071 & 0.49718 \tabularnewline
22 & 0.022797 & 0.2497 & 0.401612 \tabularnewline
23 & 0.010019 & 0.1098 & 0.456393 \tabularnewline
24 & -0.037829 & -0.4144 & 0.339663 \tabularnewline
25 & -0.102882 & -1.127 & 0.130993 \tabularnewline
26 & -0.069699 & -0.7635 & 0.223328 \tabularnewline
27 & -0.000416 & -0.0046 & 0.498186 \tabularnewline
28 & -0.007965 & -0.0873 & 0.465308 \tabularnewline
29 & -0.017754 & -0.1945 & 0.423061 \tabularnewline
30 & -0.013452 & -0.1474 & 0.441546 \tabularnewline
31 & 0.043367 & 0.4751 & 0.317803 \tabularnewline
32 & -0.023565 & -0.2581 & 0.39837 \tabularnewline
33 & -0.004003 & -0.0439 & 0.482548 \tabularnewline
34 & 0.029266 & 0.3206 & 0.374539 \tabularnewline
35 & -0.001534 & -0.0168 & 0.493311 \tabularnewline
36 & -0.018685 & -0.2047 & 0.419081 \tabularnewline
37 & -0.044102 & -0.4831 & 0.314949 \tabularnewline
38 & -0.058006 & -0.6354 & 0.263179 \tabularnewline
39 & -0.019713 & -0.2159 & 0.414698 \tabularnewline
40 & -0.02455 & -0.2689 & 0.394222 \tabularnewline
41 & 0.000197 & 0.0022 & 0.499142 \tabularnewline
42 & 0.012768 & 0.1399 & 0.444499 \tabularnewline
43 & 0.03488 & 0.3821 & 0.351533 \tabularnewline
44 & -0.028257 & -0.3095 & 0.378723 \tabularnewline
45 & 0.01738 & 0.1904 & 0.424664 \tabularnewline
46 & 0.018593 & 0.2037 & 0.419475 \tabularnewline
47 & -0.0166 & -0.1818 & 0.428006 \tabularnewline
48 & 0.006562 & 0.0719 & 0.471408 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295965&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]0.970905[/C][C]10.6357[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.114681[/C][C]-1.2563[/C][C]0.105729[/C][/ROW]
[ROW][C]3[/C][C]0.004101[/C][C]0.0449[/C][C]0.482122[/C][/ROW]
[ROW][C]4[/C][C]0.074655[/C][C]0.8178[/C][C]0.207546[/C][/ROW]
[ROW][C]5[/C][C]-0.008505[/C][C]-0.0932[/C][C]0.462965[/C][/ROW]
[ROW][C]6[/C][C]0.031057[/C][C]0.3402[/C][C]0.367147[/C][/ROW]
[ROW][C]7[/C][C]0.077377[/C][C]0.8476[/C][C]0.199168[/C][/ROW]
[ROW][C]8[/C][C]0.003404[/C][C]0.0373[/C][C]0.485158[/C][/ROW]
[ROW][C]9[/C][C]-0.023327[/C][C]-0.2555[/C][C]0.399375[/C][/ROW]
[ROW][C]10[/C][C]-0.001094[/C][C]-0.012[/C][C]0.495229[/C][/ROW]
[ROW][C]11[/C][C]-0.006365[/C][C]-0.0697[/C][C]0.472265[/C][/ROW]
[ROW][C]12[/C][C]-0.051296[/C][C]-0.5619[/C][C]0.287609[/C][/ROW]
[ROW][C]13[/C][C]-0.152897[/C][C]-1.6749[/C][C]0.048278[/C][/ROW]
[ROW][C]14[/C][C]-0.078823[/C][C]-0.8635[/C][C]0.194802[/C][/ROW]
[ROW][C]15[/C][C]-0.017262[/C][C]-0.1891[/C][C]0.425168[/C][/ROW]
[ROW][C]16[/C][C]0.028224[/C][C]0.3092[/C][C]0.37886[/C][/ROW]
[ROW][C]17[/C][C]-0.006932[/C][C]-0.0759[/C][C]0.469797[/C][/ROW]
[ROW][C]18[/C][C]0.009018[/C][C]0.0988[/C][C]0.460734[/C][/ROW]
[ROW][C]19[/C][C]0.086071[/C][C]0.9429[/C][C]0.173824[/C][/ROW]
[ROW][C]20[/C][C]0.005579[/C][C]0.0611[/C][C]0.475687[/C][/ROW]
[ROW][C]21[/C][C]0.000647[/C][C]0.0071[/C][C]0.49718[/C][/ROW]
[ROW][C]22[/C][C]0.022797[/C][C]0.2497[/C][C]0.401612[/C][/ROW]
[ROW][C]23[/C][C]0.010019[/C][C]0.1098[/C][C]0.456393[/C][/ROW]
[ROW][C]24[/C][C]-0.037829[/C][C]-0.4144[/C][C]0.339663[/C][/ROW]
[ROW][C]25[/C][C]-0.102882[/C][C]-1.127[/C][C]0.130993[/C][/ROW]
[ROW][C]26[/C][C]-0.069699[/C][C]-0.7635[/C][C]0.223328[/C][/ROW]
[ROW][C]27[/C][C]-0.000416[/C][C]-0.0046[/C][C]0.498186[/C][/ROW]
[ROW][C]28[/C][C]-0.007965[/C][C]-0.0873[/C][C]0.465308[/C][/ROW]
[ROW][C]29[/C][C]-0.017754[/C][C]-0.1945[/C][C]0.423061[/C][/ROW]
[ROW][C]30[/C][C]-0.013452[/C][C]-0.1474[/C][C]0.441546[/C][/ROW]
[ROW][C]31[/C][C]0.043367[/C][C]0.4751[/C][C]0.317803[/C][/ROW]
[ROW][C]32[/C][C]-0.023565[/C][C]-0.2581[/C][C]0.39837[/C][/ROW]
[ROW][C]33[/C][C]-0.004003[/C][C]-0.0439[/C][C]0.482548[/C][/ROW]
[ROW][C]34[/C][C]0.029266[/C][C]0.3206[/C][C]0.374539[/C][/ROW]
[ROW][C]35[/C][C]-0.001534[/C][C]-0.0168[/C][C]0.493311[/C][/ROW]
[ROW][C]36[/C][C]-0.018685[/C][C]-0.2047[/C][C]0.419081[/C][/ROW]
[ROW][C]37[/C][C]-0.044102[/C][C]-0.4831[/C][C]0.314949[/C][/ROW]
[ROW][C]38[/C][C]-0.058006[/C][C]-0.6354[/C][C]0.263179[/C][/ROW]
[ROW][C]39[/C][C]-0.019713[/C][C]-0.2159[/C][C]0.414698[/C][/ROW]
[ROW][C]40[/C][C]-0.02455[/C][C]-0.2689[/C][C]0.394222[/C][/ROW]
[ROW][C]41[/C][C]0.000197[/C][C]0.0022[/C][C]0.499142[/C][/ROW]
[ROW][C]42[/C][C]0.012768[/C][C]0.1399[/C][C]0.444499[/C][/ROW]
[ROW][C]43[/C][C]0.03488[/C][C]0.3821[/C][C]0.351533[/C][/ROW]
[ROW][C]44[/C][C]-0.028257[/C][C]-0.3095[/C][C]0.378723[/C][/ROW]
[ROW][C]45[/C][C]0.01738[/C][C]0.1904[/C][C]0.424664[/C][/ROW]
[ROW][C]46[/C][C]0.018593[/C][C]0.2037[/C][C]0.419475[/C][/ROW]
[ROW][C]47[/C][C]-0.0166[/C][C]-0.1818[/C][C]0.428006[/C][/ROW]
[ROW][C]48[/C][C]0.006562[/C][C]0.0719[/C][C]0.471408[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295965&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295965&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	0.970905	10.6357	0
2	-0.114681	-1.2563	0.105729
3	0.004101	0.0449	0.482122
4	0.074655	0.8178	0.207546
5	-0.008505	-0.0932	0.462965
6	0.031057	0.3402	0.367147
7	0.077377	0.8476	0.199168
8	0.003404	0.0373	0.485158
9	-0.023327	-0.2555	0.399375
10	-0.001094	-0.012	0.495229
11	-0.006365	-0.0697	0.472265
12	-0.051296	-0.5619	0.287609
13	-0.152897	-1.6749	0.048278
14	-0.078823	-0.8635	0.194802
15	-0.017262	-0.1891	0.425168
16	0.028224	0.3092	0.37886
17	-0.006932	-0.0759	0.469797
18	0.009018	0.0988	0.460734
19	0.086071	0.9429	0.173824
20	0.005579	0.0611	0.475687
21	0.000647	0.0071	0.49718
22	0.022797	0.2497	0.401612
23	0.010019	0.1098	0.456393
24	-0.037829	-0.4144	0.339663
25	-0.102882	-1.127	0.130993
26	-0.069699	-0.7635	0.223328
27	-0.000416	-0.0046	0.498186
28	-0.007965	-0.0873	0.465308
29	-0.017754	-0.1945	0.423061
30	-0.013452	-0.1474	0.441546
31	0.043367	0.4751	0.317803
32	-0.023565	-0.2581	0.39837
33	-0.004003	-0.0439	0.482548
34	0.029266	0.3206	0.374539
35	-0.001534	-0.0168	0.493311
36	-0.018685	-0.2047	0.419081
37	-0.044102	-0.4831	0.314949
38	-0.058006	-0.6354	0.263179
39	-0.019713	-0.2159	0.414698
40	-0.02455	-0.2689	0.394222
41	0.000197	0.0022	0.499142
42	0.012768	0.1399	0.444499
43	0.03488	0.3821	0.351533
44	-0.028257	-0.3095	0.378723
45	0.01738	0.1904	0.424664
46	0.018593	0.2037	0.419475
47	-0.0166	-0.1818	0.428006
48	0.006562	0.0719	0.471408

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;

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 (par8 != '') par8 <- as.numeric(par8)
x <- na.omit(x)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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