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R Software Module

rwasp_autocorrelation.wasp

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(Partial) Autocorrelation Function

Date of computation

Wed, 15 Dec 2010 16:52:15 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/15/t1292431801fvyrgwcwxwkban5.htm/, Retrieved Sun, 11 May 2025 16:47:42 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110565, Retrieved Sun, 11 May 2025 16:47:42 +0000

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User-defined keywords

Estimated Impact

242

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 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [Model 1 (d = 0, D...] [2009-11-24 17:27:24] [ee7c2e7343f5b1451e62c5c16ec521f1]
-    D          [(Partial) Autocorrelation Function] [Methode 1 (D=0, d=0)] [2009-11-27 12:01:23] [76ab39dc7a55316678260825bd5ad46c]
-    D            [(Partial) Autocorrelation Function] [methode 1 (d=0 D= 0)] [2009-11-27 20:21:42] [4b453aa14d54730625f8d3de5f1f6d82]
-    D              [(Partial) Autocorrelation Function] [koffie en thee] [2009-12-16 19:04:55] [7773f496f69461f4a67891f0ef752622]
-    D                [(Partial) Autocorrelation Function] [Appelen Jonagold ...] [2009-12-17 16:51:16] [7773f496f69461f4a67891f0ef752622]
- R PD                    [(Partial) Autocorrelation Function] [autocorrelatie] [2010-12-15 16:52:15] [c1f1b5e209adb4577289f490325e36f2] [Current]
-   P                       [(Partial) Autocorrelation Function] [autocorrelation] [2010-12-23 07:12:39] [717f3d787904f94c39256c5c1fc72d4c] 

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Dataseries X:

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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=110565&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=110565&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110565&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	0.937746	7.2638	0
2	0.878736	6.8067	0
3	0.835109	6.4687	0
4	0.772608	5.9846	0
5	0.721038	5.5851	0
6	0.683066	5.291	1e-06
7	0.64734	5.0143	3e-06
8	0.611877	4.7396	7e-06
9	0.565683	4.3818	2.4e-05
10	0.484037	3.7493	0.000201
11	0.42118	3.2624	0.000912
12	0.350725	2.7167	0.004302
13	0.254599	1.9721	0.026606
14	0.198408	1.5369	0.064792
15	0.159548	1.2359	0.110665
16	0.111578	0.8643	0.195438
17	0.065739	0.5092	0.306235
18	0.028567	0.2213	0.412814
19	-0.013486	-0.1045	0.458576
20	-0.05167	-0.4002	0.345203
21	-0.093928	-0.7276	0.234854
22	-0.143171	-1.109	0.135927
23	-0.181604	-1.4067	0.082338
24	-0.211801	-1.6406	0.053056
25	-0.244912	-1.8971	0.031317
26	-0.26814	-2.077	0.021045
27	-0.283117	-2.193	0.016097
28	-0.298401	-2.3114	0.012131
29	-0.303323	-2.3495	0.011053
30	-0.308591	-2.3903	0.009995
31	-0.31764	-2.4604	0.008387
32	-0.32316	-2.5032	0.007524
33	-0.327724	-2.5385	0.006872
34	-0.338458	-2.6217	0.005536
35	-0.339468	-2.6295	0.005423
36	-0.333383	-2.5824	0.006135
37	-0.333909	-2.5864	0.00607
38	-0.329694	-2.5538	0.006607
39	-0.31783	-2.4619	0.008356
40	-0.309234	-2.3953	0.009872
41	-0.298278	-2.3104	0.012159
42	-0.295976	-2.2926	0.012696
43	-0.294495	-2.2811	0.013052
44	-0.287556	-2.2274	0.014842
45	-0.283497	-2.196	0.015986
46	-0.280831	-2.1753	0.016779
47	-0.267882	-2.075	0.021141
48	-0.238464	-1.8471	0.03483
49	-0.219369	-1.6992	0.047229
50	-0.198475	-1.5374	0.064729
51	-0.17371	-1.3456	0.091755
52	-0.153745	-1.1909	0.119191
53	-0.137362	-1.064	0.145795
54	-0.123446	-0.9562	0.171401
55	-0.105481	-0.8171	0.208565
56	-0.083882	-0.6497	0.259167
57	-0.057997	-0.4492	0.327438
58	-0.037791	-0.2927	0.38537
59	-0.016702	-0.1294	0.448747
60	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.937746 & 7.2638 & 0 \tabularnewline
2 & 0.878736 & 6.8067 & 0 \tabularnewline
3 & 0.835109 & 6.4687 & 0 \tabularnewline
4 & 0.772608 & 5.9846 & 0 \tabularnewline
5 & 0.721038 & 5.5851 & 0 \tabularnewline
6 & 0.683066 & 5.291 & 1e-06 \tabularnewline
7 & 0.64734 & 5.0143 & 3e-06 \tabularnewline
8 & 0.611877 & 4.7396 & 7e-06 \tabularnewline
9 & 0.565683 & 4.3818 & 2.4e-05 \tabularnewline
10 & 0.484037 & 3.7493 & 0.000201 \tabularnewline
11 & 0.42118 & 3.2624 & 0.000912 \tabularnewline
12 & 0.350725 & 2.7167 & 0.004302 \tabularnewline
13 & 0.254599 & 1.9721 & 0.026606 \tabularnewline
14 & 0.198408 & 1.5369 & 0.064792 \tabularnewline
15 & 0.159548 & 1.2359 & 0.110665 \tabularnewline
16 & 0.111578 & 0.8643 & 0.195438 \tabularnewline
17 & 0.065739 & 0.5092 & 0.306235 \tabularnewline
18 & 0.028567 & 0.2213 & 0.412814 \tabularnewline
19 & -0.013486 & -0.1045 & 0.458576 \tabularnewline
20 & -0.05167 & -0.4002 & 0.345203 \tabularnewline
21 & -0.093928 & -0.7276 & 0.234854 \tabularnewline
22 & -0.143171 & -1.109 & 0.135927 \tabularnewline
23 & -0.181604 & -1.4067 & 0.082338 \tabularnewline
24 & -0.211801 & -1.6406 & 0.053056 \tabularnewline
25 & -0.244912 & -1.8971 & 0.031317 \tabularnewline
26 & -0.26814 & -2.077 & 0.021045 \tabularnewline
27 & -0.283117 & -2.193 & 0.016097 \tabularnewline
28 & -0.298401 & -2.3114 & 0.012131 \tabularnewline
29 & -0.303323 & -2.3495 & 0.011053 \tabularnewline
30 & -0.308591 & -2.3903 & 0.009995 \tabularnewline
31 & -0.31764 & -2.4604 & 0.008387 \tabularnewline
32 & -0.32316 & -2.5032 & 0.007524 \tabularnewline
33 & -0.327724 & -2.5385 & 0.006872 \tabularnewline
34 & -0.338458 & -2.6217 & 0.005536 \tabularnewline
35 & -0.339468 & -2.6295 & 0.005423 \tabularnewline
36 & -0.333383 & -2.5824 & 0.006135 \tabularnewline
37 & -0.333909 & -2.5864 & 0.00607 \tabularnewline
38 & -0.329694 & -2.5538 & 0.006607 \tabularnewline
39 & -0.31783 & -2.4619 & 0.008356 \tabularnewline
40 & -0.309234 & -2.3953 & 0.009872 \tabularnewline
41 & -0.298278 & -2.3104 & 0.012159 \tabularnewline
42 & -0.295976 & -2.2926 & 0.012696 \tabularnewline
43 & -0.294495 & -2.2811 & 0.013052 \tabularnewline
44 & -0.287556 & -2.2274 & 0.014842 \tabularnewline
45 & -0.283497 & -2.196 & 0.015986 \tabularnewline
46 & -0.280831 & -2.1753 & 0.016779 \tabularnewline
47 & -0.267882 & -2.075 & 0.021141 \tabularnewline
48 & -0.238464 & -1.8471 & 0.03483 \tabularnewline
49 & -0.219369 & -1.6992 & 0.047229 \tabularnewline
50 & -0.198475 & -1.5374 & 0.064729 \tabularnewline
51 & -0.17371 & -1.3456 & 0.091755 \tabularnewline
52 & -0.153745 & -1.1909 & 0.119191 \tabularnewline
53 & -0.137362 & -1.064 & 0.145795 \tabularnewline
54 & -0.123446 & -0.9562 & 0.171401 \tabularnewline
55 & -0.105481 & -0.8171 & 0.208565 \tabularnewline
56 & -0.083882 & -0.6497 & 0.259167 \tabularnewline
57 & -0.057997 & -0.4492 & 0.327438 \tabularnewline
58 & -0.037791 & -0.2927 & 0.38537 \tabularnewline
59 & -0.016702 & -0.1294 & 0.448747 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110565&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]0.937746[/C][C]7.2638[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.878736[/C][C]6.8067[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.835109[/C][C]6.4687[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.772608[/C][C]5.9846[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.721038[/C][C]5.5851[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.683066[/C][C]5.291[/C][C]1e-06[/C][/ROW]
[ROW][C]7[/C][C]0.64734[/C][C]5.0143[/C][C]3e-06[/C][/ROW]
[ROW][C]8[/C][C]0.611877[/C][C]4.7396[/C][C]7e-06[/C][/ROW]
[ROW][C]9[/C][C]0.565683[/C][C]4.3818[/C][C]2.4e-05[/C][/ROW]
[ROW][C]10[/C][C]0.484037[/C][C]3.7493[/C][C]0.000201[/C][/ROW]
[ROW][C]11[/C][C]0.42118[/C][C]3.2624[/C][C]0.000912[/C][/ROW]
[ROW][C]12[/C][C]0.350725[/C][C]2.7167[/C][C]0.004302[/C][/ROW]
[ROW][C]13[/C][C]0.254599[/C][C]1.9721[/C][C]0.026606[/C][/ROW]
[ROW][C]14[/C][C]0.198408[/C][C]1.5369[/C][C]0.064792[/C][/ROW]
[ROW][C]15[/C][C]0.159548[/C][C]1.2359[/C][C]0.110665[/C][/ROW]
[ROW][C]16[/C][C]0.111578[/C][C]0.8643[/C][C]0.195438[/C][/ROW]
[ROW][C]17[/C][C]0.065739[/C][C]0.5092[/C][C]0.306235[/C][/ROW]
[ROW][C]18[/C][C]0.028567[/C][C]0.2213[/C][C]0.412814[/C][/ROW]
[ROW][C]19[/C][C]-0.013486[/C][C]-0.1045[/C][C]0.458576[/C][/ROW]
[ROW][C]20[/C][C]-0.05167[/C][C]-0.4002[/C][C]0.345203[/C][/ROW]
[ROW][C]21[/C][C]-0.093928[/C][C]-0.7276[/C][C]0.234854[/C][/ROW]
[ROW][C]22[/C][C]-0.143171[/C][C]-1.109[/C][C]0.135927[/C][/ROW]
[ROW][C]23[/C][C]-0.181604[/C][C]-1.4067[/C][C]0.082338[/C][/ROW]
[ROW][C]24[/C][C]-0.211801[/C][C]-1.6406[/C][C]0.053056[/C][/ROW]
[ROW][C]25[/C][C]-0.244912[/C][C]-1.8971[/C][C]0.031317[/C][/ROW]
[ROW][C]26[/C][C]-0.26814[/C][C]-2.077[/C][C]0.021045[/C][/ROW]
[ROW][C]27[/C][C]-0.283117[/C][C]-2.193[/C][C]0.016097[/C][/ROW]
[ROW][C]28[/C][C]-0.298401[/C][C]-2.3114[/C][C]0.012131[/C][/ROW]
[ROW][C]29[/C][C]-0.303323[/C][C]-2.3495[/C][C]0.011053[/C][/ROW]
[ROW][C]30[/C][C]-0.308591[/C][C]-2.3903[/C][C]0.009995[/C][/ROW]
[ROW][C]31[/C][C]-0.31764[/C][C]-2.4604[/C][C]0.008387[/C][/ROW]
[ROW][C]32[/C][C]-0.32316[/C][C]-2.5032[/C][C]0.007524[/C][/ROW]
[ROW][C]33[/C][C]-0.327724[/C][C]-2.5385[/C][C]0.006872[/C][/ROW]
[ROW][C]34[/C][C]-0.338458[/C][C]-2.6217[/C][C]0.005536[/C][/ROW]
[ROW][C]35[/C][C]-0.339468[/C][C]-2.6295[/C][C]0.005423[/C][/ROW]
[ROW][C]36[/C][C]-0.333383[/C][C]-2.5824[/C][C]0.006135[/C][/ROW]
[ROW][C]37[/C][C]-0.333909[/C][C]-2.5864[/C][C]0.00607[/C][/ROW]
[ROW][C]38[/C][C]-0.329694[/C][C]-2.5538[/C][C]0.006607[/C][/ROW]
[ROW][C]39[/C][C]-0.31783[/C][C]-2.4619[/C][C]0.008356[/C][/ROW]
[ROW][C]40[/C][C]-0.309234[/C][C]-2.3953[/C][C]0.009872[/C][/ROW]
[ROW][C]41[/C][C]-0.298278[/C][C]-2.3104[/C][C]0.012159[/C][/ROW]
[ROW][C]42[/C][C]-0.295976[/C][C]-2.2926[/C][C]0.012696[/C][/ROW]
[ROW][C]43[/C][C]-0.294495[/C][C]-2.2811[/C][C]0.013052[/C][/ROW]
[ROW][C]44[/C][C]-0.287556[/C][C]-2.2274[/C][C]0.014842[/C][/ROW]
[ROW][C]45[/C][C]-0.283497[/C][C]-2.196[/C][C]0.015986[/C][/ROW]
[ROW][C]46[/C][C]-0.280831[/C][C]-2.1753[/C][C]0.016779[/C][/ROW]
[ROW][C]47[/C][C]-0.267882[/C][C]-2.075[/C][C]0.021141[/C][/ROW]
[ROW][C]48[/C][C]-0.238464[/C][C]-1.8471[/C][C]0.03483[/C][/ROW]
[ROW][C]49[/C][C]-0.219369[/C][C]-1.6992[/C][C]0.047229[/C][/ROW]
[ROW][C]50[/C][C]-0.198475[/C][C]-1.5374[/C][C]0.064729[/C][/ROW]
[ROW][C]51[/C][C]-0.17371[/C][C]-1.3456[/C][C]0.091755[/C][/ROW]
[ROW][C]52[/C][C]-0.153745[/C][C]-1.1909[/C][C]0.119191[/C][/ROW]
[ROW][C]53[/C][C]-0.137362[/C][C]-1.064[/C][C]0.145795[/C][/ROW]
[ROW][C]54[/C][C]-0.123446[/C][C]-0.9562[/C][C]0.171401[/C][/ROW]
[ROW][C]55[/C][C]-0.105481[/C][C]-0.8171[/C][C]0.208565[/C][/ROW]
[ROW][C]56[/C][C]-0.083882[/C][C]-0.6497[/C][C]0.259167[/C][/ROW]
[ROW][C]57[/C][C]-0.057997[/C][C]-0.4492[/C][C]0.327438[/C][/ROW]
[ROW][C]58[/C][C]-0.037791[/C][C]-0.2927[/C][C]0.38537[/C][/ROW]
[ROW][C]59[/C][C]-0.016702[/C][C]-0.1294[/C][C]0.448747[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110565&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110565&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	0.937746	7.2638	0
2	0.878736	6.8067	0
3	0.835109	6.4687	0
4	0.772608	5.9846	0
5	0.721038	5.5851	0
6	0.683066	5.291	1e-06
7	0.64734	5.0143	3e-06
8	0.611877	4.7396	7e-06
9	0.565683	4.3818	2.4e-05
10	0.484037	3.7493	0.000201
11	0.42118	3.2624	0.000912
12	0.350725	2.7167	0.004302
13	0.254599	1.9721	0.026606
14	0.198408	1.5369	0.064792
15	0.159548	1.2359	0.110665
16	0.111578	0.8643	0.195438
17	0.065739	0.5092	0.306235
18	0.028567	0.2213	0.412814
19	-0.013486	-0.1045	0.458576
20	-0.05167	-0.4002	0.345203
21	-0.093928	-0.7276	0.234854
22	-0.143171	-1.109	0.135927
23	-0.181604	-1.4067	0.082338
24	-0.211801	-1.6406	0.053056
25	-0.244912	-1.8971	0.031317
26	-0.26814	-2.077	0.021045
27	-0.283117	-2.193	0.016097
28	-0.298401	-2.3114	0.012131
29	-0.303323	-2.3495	0.011053
30	-0.308591	-2.3903	0.009995
31	-0.31764	-2.4604	0.008387
32	-0.32316	-2.5032	0.007524
33	-0.327724	-2.5385	0.006872
34	-0.338458	-2.6217	0.005536
35	-0.339468	-2.6295	0.005423
36	-0.333383	-2.5824	0.006135
37	-0.333909	-2.5864	0.00607
38	-0.329694	-2.5538	0.006607
39	-0.31783	-2.4619	0.008356
40	-0.309234	-2.3953	0.009872
41	-0.298278	-2.3104	0.012159
42	-0.295976	-2.2926	0.012696
43	-0.294495	-2.2811	0.013052
44	-0.287556	-2.2274	0.014842
45	-0.283497	-2.196	0.015986
46	-0.280831	-2.1753	0.016779
47	-0.267882	-2.075	0.021141
48	-0.238464	-1.8471	0.03483
49	-0.219369	-1.6992	0.047229
50	-0.198475	-1.5374	0.064729
51	-0.17371	-1.3456	0.091755
52	-0.153745	-1.1909	0.119191
53	-0.137362	-1.064	0.145795
54	-0.123446	-0.9562	0.171401
55	-0.105481	-0.8171	0.208565
56	-0.083882	-0.6497	0.259167
57	-0.057997	-0.4492	0.327438
58	-0.037791	-0.2927	0.38537
59	-0.016702	-0.1294	0.448747
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.937746	7.2638	0
2	-0.005241	-0.0406	0.483878
3	0.096773	0.7496	0.228213
4	-0.175916	-1.3626	0.089044
5	0.069469	0.5381	0.296248
6	0.049956	0.387	0.350077
7	0.043599	0.3377	0.368378
8	-0.024906	-0.1929	0.423837
9	-0.125265	-0.9703	0.167897
10	-0.339255	-2.6279	0.005447
11	0.105093	0.8141	0.209418
12	-0.156979	-1.216	0.114382
13	-0.179902	-1.3935	0.084303
14	0.173394	1.3431	0.092148
15	0.05855	0.4535	0.325902
16	-0.032899	-0.2548	0.39986
17	-0.074733	-0.5789	0.28242
18	0.051578	0.3995	0.345463
19	0.036916	0.286	0.387949
20	0.00886	0.0686	0.472757
21	-0.009297	-0.072	0.471415
22	-0.07867	-0.6094	0.272287
23	-0.189547	-1.4682	0.073634
24	0.094356	0.7309	0.233849
25	-0.036222	-0.2806	0.390002
26	-0.079121	-0.6129	0.271141
27	0.00081	0.0063	0.497507
28	0.0733	0.5678	0.286151
29	0.068503	0.5306	0.298819
30	-0.055207	-0.4276	0.335225
31	0.00644	0.0499	0.48019
32	0.014505	0.1124	0.45546
33	-0.030305	-0.2347	0.407603
34	-0.040977	-0.3174	0.37602
35	0.008229	0.0637	0.474693
36	-0.099599	-0.7715	0.221722
37	-0.046885	-0.3632	0.358878
38	-0.019683	-0.1525	0.439667
39	0.04172	0.3232	0.373848
40	-0.073655	-0.5705	0.285225
41	0.047886	0.3709	0.356
42	-0.045791	-0.3547	0.36203
43	0.009455	0.0732	0.470932
44	-0.039367	-0.3049	0.380734
45	0.004823	0.0374	0.485161
46	-0.010444	-0.0809	0.467897
47	0.005975	0.0463	0.481619
48	0.159424	1.2349	0.110843
49	-0.073295	-0.5677	0.286164
50	-0.039434	-0.3055	0.38054
51	0.019131	0.1482	0.441345
52	0.056046	0.4341	0.332875
53	-0.047531	-0.3682	0.357021
54	0.020736	0.1606	0.436466
55	-0.030234	-0.2342	0.407817
56	0.006008	0.0465	0.481517
57	-0.021778	-0.1687	0.433303
58	0.033175	0.257	0.399041
59	-0.090775	-0.7031	0.242344
60	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.937746 & 7.2638 & 0 \tabularnewline
2 & -0.005241 & -0.0406 & 0.483878 \tabularnewline
3 & 0.096773 & 0.7496 & 0.228213 \tabularnewline
4 & -0.175916 & -1.3626 & 0.089044 \tabularnewline
5 & 0.069469 & 0.5381 & 0.296248 \tabularnewline
6 & 0.049956 & 0.387 & 0.350077 \tabularnewline
7 & 0.043599 & 0.3377 & 0.368378 \tabularnewline
8 & -0.024906 & -0.1929 & 0.423837 \tabularnewline
9 & -0.125265 & -0.9703 & 0.167897 \tabularnewline
10 & -0.339255 & -2.6279 & 0.005447 \tabularnewline
11 & 0.105093 & 0.8141 & 0.209418 \tabularnewline
12 & -0.156979 & -1.216 & 0.114382 \tabularnewline
13 & -0.179902 & -1.3935 & 0.084303 \tabularnewline
14 & 0.173394 & 1.3431 & 0.092148 \tabularnewline
15 & 0.05855 & 0.4535 & 0.325902 \tabularnewline
16 & -0.032899 & -0.2548 & 0.39986 \tabularnewline
17 & -0.074733 & -0.5789 & 0.28242 \tabularnewline
18 & 0.051578 & 0.3995 & 0.345463 \tabularnewline
19 & 0.036916 & 0.286 & 0.387949 \tabularnewline
20 & 0.00886 & 0.0686 & 0.472757 \tabularnewline
21 & -0.009297 & -0.072 & 0.471415 \tabularnewline
22 & -0.07867 & -0.6094 & 0.272287 \tabularnewline
23 & -0.189547 & -1.4682 & 0.073634 \tabularnewline
24 & 0.094356 & 0.7309 & 0.233849 \tabularnewline
25 & -0.036222 & -0.2806 & 0.390002 \tabularnewline
26 & -0.079121 & -0.6129 & 0.271141 \tabularnewline
27 & 0.00081 & 0.0063 & 0.497507 \tabularnewline
28 & 0.0733 & 0.5678 & 0.286151 \tabularnewline
29 & 0.068503 & 0.5306 & 0.298819 \tabularnewline
30 & -0.055207 & -0.4276 & 0.335225 \tabularnewline
31 & 0.00644 & 0.0499 & 0.48019 \tabularnewline
32 & 0.014505 & 0.1124 & 0.45546 \tabularnewline
33 & -0.030305 & -0.2347 & 0.407603 \tabularnewline
34 & -0.040977 & -0.3174 & 0.37602 \tabularnewline
35 & 0.008229 & 0.0637 & 0.474693 \tabularnewline
36 & -0.099599 & -0.7715 & 0.221722 \tabularnewline
37 & -0.046885 & -0.3632 & 0.358878 \tabularnewline
38 & -0.019683 & -0.1525 & 0.439667 \tabularnewline
39 & 0.04172 & 0.3232 & 0.373848 \tabularnewline
40 & -0.073655 & -0.5705 & 0.285225 \tabularnewline
41 & 0.047886 & 0.3709 & 0.356 \tabularnewline
42 & -0.045791 & -0.3547 & 0.36203 \tabularnewline
43 & 0.009455 & 0.0732 & 0.470932 \tabularnewline
44 & -0.039367 & -0.3049 & 0.380734 \tabularnewline
45 & 0.004823 & 0.0374 & 0.485161 \tabularnewline
46 & -0.010444 & -0.0809 & 0.467897 \tabularnewline
47 & 0.005975 & 0.0463 & 0.481619 \tabularnewline
48 & 0.159424 & 1.2349 & 0.110843 \tabularnewline
49 & -0.073295 & -0.5677 & 0.286164 \tabularnewline
50 & -0.039434 & -0.3055 & 0.38054 \tabularnewline
51 & 0.019131 & 0.1482 & 0.441345 \tabularnewline
52 & 0.056046 & 0.4341 & 0.332875 \tabularnewline
53 & -0.047531 & -0.3682 & 0.357021 \tabularnewline
54 & 0.020736 & 0.1606 & 0.436466 \tabularnewline
55 & -0.030234 & -0.2342 & 0.407817 \tabularnewline
56 & 0.006008 & 0.0465 & 0.481517 \tabularnewline
57 & -0.021778 & -0.1687 & 0.433303 \tabularnewline
58 & 0.033175 & 0.257 & 0.399041 \tabularnewline
59 & -0.090775 & -0.7031 & 0.242344 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110565&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]0.937746[/C][C]7.2638[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.005241[/C][C]-0.0406[/C][C]0.483878[/C][/ROW]
[ROW][C]3[/C][C]0.096773[/C][C]0.7496[/C][C]0.228213[/C][/ROW]
[ROW][C]4[/C][C]-0.175916[/C][C]-1.3626[/C][C]0.089044[/C][/ROW]
[ROW][C]5[/C][C]0.069469[/C][C]0.5381[/C][C]0.296248[/C][/ROW]
[ROW][C]6[/C][C]0.049956[/C][C]0.387[/C][C]0.350077[/C][/ROW]
[ROW][C]7[/C][C]0.043599[/C][C]0.3377[/C][C]0.368378[/C][/ROW]
[ROW][C]8[/C][C]-0.024906[/C][C]-0.1929[/C][C]0.423837[/C][/ROW]
[ROW][C]9[/C][C]-0.125265[/C][C]-0.9703[/C][C]0.167897[/C][/ROW]
[ROW][C]10[/C][C]-0.339255[/C][C]-2.6279[/C][C]0.005447[/C][/ROW]
[ROW][C]11[/C][C]0.105093[/C][C]0.8141[/C][C]0.209418[/C][/ROW]
[ROW][C]12[/C][C]-0.156979[/C][C]-1.216[/C][C]0.114382[/C][/ROW]
[ROW][C]13[/C][C]-0.179902[/C][C]-1.3935[/C][C]0.084303[/C][/ROW]
[ROW][C]14[/C][C]0.173394[/C][C]1.3431[/C][C]0.092148[/C][/ROW]
[ROW][C]15[/C][C]0.05855[/C][C]0.4535[/C][C]0.325902[/C][/ROW]
[ROW][C]16[/C][C]-0.032899[/C][C]-0.2548[/C][C]0.39986[/C][/ROW]
[ROW][C]17[/C][C]-0.074733[/C][C]-0.5789[/C][C]0.28242[/C][/ROW]
[ROW][C]18[/C][C]0.051578[/C][C]0.3995[/C][C]0.345463[/C][/ROW]
[ROW][C]19[/C][C]0.036916[/C][C]0.286[/C][C]0.387949[/C][/ROW]
[ROW][C]20[/C][C]0.00886[/C][C]0.0686[/C][C]0.472757[/C][/ROW]
[ROW][C]21[/C][C]-0.009297[/C][C]-0.072[/C][C]0.471415[/C][/ROW]
[ROW][C]22[/C][C]-0.07867[/C][C]-0.6094[/C][C]0.272287[/C][/ROW]
[ROW][C]23[/C][C]-0.189547[/C][C]-1.4682[/C][C]0.073634[/C][/ROW]
[ROW][C]24[/C][C]0.094356[/C][C]0.7309[/C][C]0.233849[/C][/ROW]
[ROW][C]25[/C][C]-0.036222[/C][C]-0.2806[/C][C]0.390002[/C][/ROW]
[ROW][C]26[/C][C]-0.079121[/C][C]-0.6129[/C][C]0.271141[/C][/ROW]
[ROW][C]27[/C][C]0.00081[/C][C]0.0063[/C][C]0.497507[/C][/ROW]
[ROW][C]28[/C][C]0.0733[/C][C]0.5678[/C][C]0.286151[/C][/ROW]
[ROW][C]29[/C][C]0.068503[/C][C]0.5306[/C][C]0.298819[/C][/ROW]
[ROW][C]30[/C][C]-0.055207[/C][C]-0.4276[/C][C]0.335225[/C][/ROW]
[ROW][C]31[/C][C]0.00644[/C][C]0.0499[/C][C]0.48019[/C][/ROW]
[ROW][C]32[/C][C]0.014505[/C][C]0.1124[/C][C]0.45546[/C][/ROW]
[ROW][C]33[/C][C]-0.030305[/C][C]-0.2347[/C][C]0.407603[/C][/ROW]
[ROW][C]34[/C][C]-0.040977[/C][C]-0.3174[/C][C]0.37602[/C][/ROW]
[ROW][C]35[/C][C]0.008229[/C][C]0.0637[/C][C]0.474693[/C][/ROW]
[ROW][C]36[/C][C]-0.099599[/C][C]-0.7715[/C][C]0.221722[/C][/ROW]
[ROW][C]37[/C][C]-0.046885[/C][C]-0.3632[/C][C]0.358878[/C][/ROW]
[ROW][C]38[/C][C]-0.019683[/C][C]-0.1525[/C][C]0.439667[/C][/ROW]
[ROW][C]39[/C][C]0.04172[/C][C]0.3232[/C][C]0.373848[/C][/ROW]
[ROW][C]40[/C][C]-0.073655[/C][C]-0.5705[/C][C]0.285225[/C][/ROW]
[ROW][C]41[/C][C]0.047886[/C][C]0.3709[/C][C]0.356[/C][/ROW]
[ROW][C]42[/C][C]-0.045791[/C][C]-0.3547[/C][C]0.36203[/C][/ROW]
[ROW][C]43[/C][C]0.009455[/C][C]0.0732[/C][C]0.470932[/C][/ROW]
[ROW][C]44[/C][C]-0.039367[/C][C]-0.3049[/C][C]0.380734[/C][/ROW]
[ROW][C]45[/C][C]0.004823[/C][C]0.0374[/C][C]0.485161[/C][/ROW]
[ROW][C]46[/C][C]-0.010444[/C][C]-0.0809[/C][C]0.467897[/C][/ROW]
[ROW][C]47[/C][C]0.005975[/C][C]0.0463[/C][C]0.481619[/C][/ROW]
[ROW][C]48[/C][C]0.159424[/C][C]1.2349[/C][C]0.110843[/C][/ROW]
[ROW][C]49[/C][C]-0.073295[/C][C]-0.5677[/C][C]0.286164[/C][/ROW]
[ROW][C]50[/C][C]-0.039434[/C][C]-0.3055[/C][C]0.38054[/C][/ROW]
[ROW][C]51[/C][C]0.019131[/C][C]0.1482[/C][C]0.441345[/C][/ROW]
[ROW][C]52[/C][C]0.056046[/C][C]0.4341[/C][C]0.332875[/C][/ROW]
[ROW][C]53[/C][C]-0.047531[/C][C]-0.3682[/C][C]0.357021[/C][/ROW]
[ROW][C]54[/C][C]0.020736[/C][C]0.1606[/C][C]0.436466[/C][/ROW]
[ROW][C]55[/C][C]-0.030234[/C][C]-0.2342[/C][C]0.407817[/C][/ROW]
[ROW][C]56[/C][C]0.006008[/C][C]0.0465[/C][C]0.481517[/C][/ROW]
[ROW][C]57[/C][C]-0.021778[/C][C]-0.1687[/C][C]0.433303[/C][/ROW]
[ROW][C]58[/C][C]0.033175[/C][C]0.257[/C][C]0.399041[/C][/ROW]
[ROW][C]59[/C][C]-0.090775[/C][C]-0.7031[/C][C]0.242344[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110565&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110565&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	0.937746	7.2638	0
2	-0.005241	-0.0406	0.483878
3	0.096773	0.7496	0.228213
4	-0.175916	-1.3626	0.089044
5	0.069469	0.5381	0.296248
6	0.049956	0.387	0.350077
7	0.043599	0.3377	0.368378
8	-0.024906	-0.1929	0.423837
9	-0.125265	-0.9703	0.167897
10	-0.339255	-2.6279	0.005447
11	0.105093	0.8141	0.209418
12	-0.156979	-1.216	0.114382
13	-0.179902	-1.3935	0.084303
14	0.173394	1.3431	0.092148
15	0.05855	0.4535	0.325902
16	-0.032899	-0.2548	0.39986
17	-0.074733	-0.5789	0.28242
18	0.051578	0.3995	0.345463
19	0.036916	0.286	0.387949
20	0.00886	0.0686	0.472757
21	-0.009297	-0.072	0.471415
22	-0.07867	-0.6094	0.272287
23	-0.189547	-1.4682	0.073634
24	0.094356	0.7309	0.233849
25	-0.036222	-0.2806	0.390002
26	-0.079121	-0.6129	0.271141
27	0.00081	0.0063	0.497507
28	0.0733	0.5678	0.286151
29	0.068503	0.5306	0.298819
30	-0.055207	-0.4276	0.335225
31	0.00644	0.0499	0.48019
32	0.014505	0.1124	0.45546
33	-0.030305	-0.2347	0.407603
34	-0.040977	-0.3174	0.37602
35	0.008229	0.0637	0.474693
36	-0.099599	-0.7715	0.221722
37	-0.046885	-0.3632	0.358878
38	-0.019683	-0.1525	0.439667
39	0.04172	0.3232	0.373848
40	-0.073655	-0.5705	0.285225
41	0.047886	0.3709	0.356
42	-0.045791	-0.3547	0.36203
43	0.009455	0.0732	0.470932
44	-0.039367	-0.3049	0.380734
45	0.004823	0.0374	0.485161
46	-0.010444	-0.0809	0.467897
47	0.005975	0.0463	0.481619
48	0.159424	1.2349	0.110843
49	-0.073295	-0.5677	0.286164
50	-0.039434	-0.3055	0.38054
51	0.019131	0.1482	0.441345
52	0.056046	0.4341	0.332875
53	-0.047531	-0.3682	0.357021
54	0.020736	0.1606	0.436466
55	-0.030234	-0.2342	0.407817
56	0.006008	0.0465	0.481517
57	-0.021778	-0.1687	0.433303
58	0.033175	0.257	0.399041
59	-0.090775	-0.7031	0.242344
60	NA	NA	NA

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 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; 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)
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