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Author

*Unverified author*

R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Tue, 09 Dec 2008 15:04:53 -0700

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/2008/Dec/09/t1228860324h99p9630lb7zy17.htm/, Retrieved Sun, 19 May 2024 10:40:54 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31826, Retrieved Sun, 19 May 2024 10:40:54 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

149

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMPD    [(Partial) Autocorrelation Function] [Identification an...] [2008-12-09 22:04:53] [74a138e5b32af267311b5ad4cd13bf7e] [Current]

Feedback Forum

2008-12-14 14:30:02 [Gert-Jan Geudens] [reply] 
Zeer correct.  
Een correlatiecoeffïenct is de weergave tussen een yt en yt met 1 periode opgeschoven. Als positieve coëfficiënten gevolgd worden door positieve en negatieve coëfficiënten door negatieve, dan is er sprake van autocorrelatie.  
 
We zien hier inderdaad een lineaire trend maar van seizonaliteit is hier geen sprake.  
2008-12-14 14:46:35 [Gert-Jan Geudens] [reply] 
Correctie van onze vorige feedback : 
De student zegt dat er sprake is van seizonaliteit. Dit is uiteraard niet het geval. 
Het antwoord van de student is dus NIET correct.
  2008-12-17 00:12:29 [Gert-Jan Geudens] [reply] 
Foutje in de vorige feedback 
De coëfficiënt bij 12 is significant en dus is er wel seizonaliteit. Het antwoord van de student is dus correct
2008-12-15 14:25:35 [Stefan Temmerman] [reply] 
We zien hier een dalende trend, en ook seizoenaliteit, er moet dus gedifferentieerd worden.

Post a new message

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	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=31826&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=31826&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31826&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	0.818369	7.545	0
2	0.73251	6.7534	0
3	0.773212	7.1287	0
4	0.697013	6.4261	0
5	0.724339	6.6781	0
6	0.802545	7.3991	0
7	0.671675	6.1925	0
8	0.608928	5.614	0
9	0.633891	5.8442	0
10	0.526068	4.8501	3e-06
11	0.568384	5.2402	1e-06
12	0.666154	6.1416	0
13	0.511253	4.7135	5e-06
14	0.431143	3.9749	7.4e-05
15	0.447461	4.1254	4.3e-05
16	0.36899	3.4019	0.000511
17	0.39058	3.601	0.000266
18	0.449448	4.1437	4e-05
19	0.322527	2.9736	0.001915
20	0.267366	2.465	0.007857
21	0.269848	2.4879	0.007402
22	0.165592	1.5267	0.065276
23	0.201059	1.8537	0.033627
24	0.261108	2.4073	0.009118
25	0.128731	1.1868	0.119299
26	0.064027	0.5903	0.278279
27	0.06417	0.5916	0.277839
28	-0.024538	-0.2262	0.410784
29	-0.000894	-0.0082	0.496722
30	0.02227	0.2053	0.418906
31	-0.07538	-0.695	0.244484
32	-0.112856	-1.0405	0.150533
33	-0.13109	-1.2086	0.115086
34	-0.205573	-1.8953	0.030727
35	-0.161718	-1.491	0.069836
36	-0.11447	-1.0554	0.147125
37	-0.208714	-1.9242	0.028835
38	-0.242925	-2.2397	0.013862
39	-0.244265	-2.252	0.013449
40	-0.288937	-2.6639	0.00462
41	-0.262103	-2.4165	0.008906
42	-0.239295	-2.2062	0.015034
43	-0.298603	-2.753	0.00361
44	-0.313575	-2.891	0.002437
45	-0.328383	-3.0275	0.001632
46	-0.383728	-3.5378	0.000328
47	-0.344789	-3.1788	0.001032
48	-0.317905	-2.9309	0.00217
49	-0.365725	-3.3718	0.000563
50	-0.382202	-3.5237	0.000344
51	-0.389896	-3.5947	0.000272
52	-0.402596	-3.7118	0.000183
53	-0.375384	-3.4609	0.000422
54	-0.353106	-3.2555	0.000813
55	-0.373174	-3.4405	0.000451
56	-0.361566	-3.3335	0.000636
57	-0.367765	-3.3906	0.00053
58	-0.378413	-3.4888	0.000386
59	-0.335517	-3.0933	0.001339
60	-0.312428	-2.8804	0.002512

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.818369 & 7.545 & 0 \tabularnewline
2 & 0.73251 & 6.7534 & 0 \tabularnewline
3 & 0.773212 & 7.1287 & 0 \tabularnewline
4 & 0.697013 & 6.4261 & 0 \tabularnewline
5 & 0.724339 & 6.6781 & 0 \tabularnewline
6 & 0.802545 & 7.3991 & 0 \tabularnewline
7 & 0.671675 & 6.1925 & 0 \tabularnewline
8 & 0.608928 & 5.614 & 0 \tabularnewline
9 & 0.633891 & 5.8442 & 0 \tabularnewline
10 & 0.526068 & 4.8501 & 3e-06 \tabularnewline
11 & 0.568384 & 5.2402 & 1e-06 \tabularnewline
12 & 0.666154 & 6.1416 & 0 \tabularnewline
13 & 0.511253 & 4.7135 & 5e-06 \tabularnewline
14 & 0.431143 & 3.9749 & 7.4e-05 \tabularnewline
15 & 0.447461 & 4.1254 & 4.3e-05 \tabularnewline
16 & 0.36899 & 3.4019 & 0.000511 \tabularnewline
17 & 0.39058 & 3.601 & 0.000266 \tabularnewline
18 & 0.449448 & 4.1437 & 4e-05 \tabularnewline
19 & 0.322527 & 2.9736 & 0.001915 \tabularnewline
20 & 0.267366 & 2.465 & 0.007857 \tabularnewline
21 & 0.269848 & 2.4879 & 0.007402 \tabularnewline
22 & 0.165592 & 1.5267 & 0.065276 \tabularnewline
23 & 0.201059 & 1.8537 & 0.033627 \tabularnewline
24 & 0.261108 & 2.4073 & 0.009118 \tabularnewline
25 & 0.128731 & 1.1868 & 0.119299 \tabularnewline
26 & 0.064027 & 0.5903 & 0.278279 \tabularnewline
27 & 0.06417 & 0.5916 & 0.277839 \tabularnewline
28 & -0.024538 & -0.2262 & 0.410784 \tabularnewline
29 & -0.000894 & -0.0082 & 0.496722 \tabularnewline
30 & 0.02227 & 0.2053 & 0.418906 \tabularnewline
31 & -0.07538 & -0.695 & 0.244484 \tabularnewline
32 & -0.112856 & -1.0405 & 0.150533 \tabularnewline
33 & -0.13109 & -1.2086 & 0.115086 \tabularnewline
34 & -0.205573 & -1.8953 & 0.030727 \tabularnewline
35 & -0.161718 & -1.491 & 0.069836 \tabularnewline
36 & -0.11447 & -1.0554 & 0.147125 \tabularnewline
37 & -0.208714 & -1.9242 & 0.028835 \tabularnewline
38 & -0.242925 & -2.2397 & 0.013862 \tabularnewline
39 & -0.244265 & -2.252 & 0.013449 \tabularnewline
40 & -0.288937 & -2.6639 & 0.00462 \tabularnewline
41 & -0.262103 & -2.4165 & 0.008906 \tabularnewline
42 & -0.239295 & -2.2062 & 0.015034 \tabularnewline
43 & -0.298603 & -2.753 & 0.00361 \tabularnewline
44 & -0.313575 & -2.891 & 0.002437 \tabularnewline
45 & -0.328383 & -3.0275 & 0.001632 \tabularnewline
46 & -0.383728 & -3.5378 & 0.000328 \tabularnewline
47 & -0.344789 & -3.1788 & 0.001032 \tabularnewline
48 & -0.317905 & -2.9309 & 0.00217 \tabularnewline
49 & -0.365725 & -3.3718 & 0.000563 \tabularnewline
50 & -0.382202 & -3.5237 & 0.000344 \tabularnewline
51 & -0.389896 & -3.5947 & 0.000272 \tabularnewline
52 & -0.402596 & -3.7118 & 0.000183 \tabularnewline
53 & -0.375384 & -3.4609 & 0.000422 \tabularnewline
54 & -0.353106 & -3.2555 & 0.000813 \tabularnewline
55 & -0.373174 & -3.4405 & 0.000451 \tabularnewline
56 & -0.361566 & -3.3335 & 0.000636 \tabularnewline
57 & -0.367765 & -3.3906 & 0.00053 \tabularnewline
58 & -0.378413 & -3.4888 & 0.000386 \tabularnewline
59 & -0.335517 & -3.0933 & 0.001339 \tabularnewline
60 & -0.312428 & -2.8804 & 0.002512 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31826&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]0.818369[/C][C]7.545[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.73251[/C][C]6.7534[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.773212[/C][C]7.1287[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.697013[/C][C]6.4261[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.724339[/C][C]6.6781[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.802545[/C][C]7.3991[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.671675[/C][C]6.1925[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.608928[/C][C]5.614[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.633891[/C][C]5.8442[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.526068[/C][C]4.8501[/C][C]3e-06[/C][/ROW]
[ROW][C]11[/C][C]0.568384[/C][C]5.2402[/C][C]1e-06[/C][/ROW]
[ROW][C]12[/C][C]0.666154[/C][C]6.1416[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.511253[/C][C]4.7135[/C][C]5e-06[/C][/ROW]
[ROW][C]14[/C][C]0.431143[/C][C]3.9749[/C][C]7.4e-05[/C][/ROW]
[ROW][C]15[/C][C]0.447461[/C][C]4.1254[/C][C]4.3e-05[/C][/ROW]
[ROW][C]16[/C][C]0.36899[/C][C]3.4019[/C][C]0.000511[/C][/ROW]
[ROW][C]17[/C][C]0.39058[/C][C]3.601[/C][C]0.000266[/C][/ROW]
[ROW][C]18[/C][C]0.449448[/C][C]4.1437[/C][C]4e-05[/C][/ROW]
[ROW][C]19[/C][C]0.322527[/C][C]2.9736[/C][C]0.001915[/C][/ROW]
[ROW][C]20[/C][C]0.267366[/C][C]2.465[/C][C]0.007857[/C][/ROW]
[ROW][C]21[/C][C]0.269848[/C][C]2.4879[/C][C]0.007402[/C][/ROW]
[ROW][C]22[/C][C]0.165592[/C][C]1.5267[/C][C]0.065276[/C][/ROW]
[ROW][C]23[/C][C]0.201059[/C][C]1.8537[/C][C]0.033627[/C][/ROW]
[ROW][C]24[/C][C]0.261108[/C][C]2.4073[/C][C]0.009118[/C][/ROW]
[ROW][C]25[/C][C]0.128731[/C][C]1.1868[/C][C]0.119299[/C][/ROW]
[ROW][C]26[/C][C]0.064027[/C][C]0.5903[/C][C]0.278279[/C][/ROW]
[ROW][C]27[/C][C]0.06417[/C][C]0.5916[/C][C]0.277839[/C][/ROW]
[ROW][C]28[/C][C]-0.024538[/C][C]-0.2262[/C][C]0.410784[/C][/ROW]
[ROW][C]29[/C][C]-0.000894[/C][C]-0.0082[/C][C]0.496722[/C][/ROW]
[ROW][C]30[/C][C]0.02227[/C][C]0.2053[/C][C]0.418906[/C][/ROW]
[ROW][C]31[/C][C]-0.07538[/C][C]-0.695[/C][C]0.244484[/C][/ROW]
[ROW][C]32[/C][C]-0.112856[/C][C]-1.0405[/C][C]0.150533[/C][/ROW]
[ROW][C]33[/C][C]-0.13109[/C][C]-1.2086[/C][C]0.115086[/C][/ROW]
[ROW][C]34[/C][C]-0.205573[/C][C]-1.8953[/C][C]0.030727[/C][/ROW]
[ROW][C]35[/C][C]-0.161718[/C][C]-1.491[/C][C]0.069836[/C][/ROW]
[ROW][C]36[/C][C]-0.11447[/C][C]-1.0554[/C][C]0.147125[/C][/ROW]
[ROW][C]37[/C][C]-0.208714[/C][C]-1.9242[/C][C]0.028835[/C][/ROW]
[ROW][C]38[/C][C]-0.242925[/C][C]-2.2397[/C][C]0.013862[/C][/ROW]
[ROW][C]39[/C][C]-0.244265[/C][C]-2.252[/C][C]0.013449[/C][/ROW]
[ROW][C]40[/C][C]-0.288937[/C][C]-2.6639[/C][C]0.00462[/C][/ROW]
[ROW][C]41[/C][C]-0.262103[/C][C]-2.4165[/C][C]0.008906[/C][/ROW]
[ROW][C]42[/C][C]-0.239295[/C][C]-2.2062[/C][C]0.015034[/C][/ROW]
[ROW][C]43[/C][C]-0.298603[/C][C]-2.753[/C][C]0.00361[/C][/ROW]
[ROW][C]44[/C][C]-0.313575[/C][C]-2.891[/C][C]0.002437[/C][/ROW]
[ROW][C]45[/C][C]-0.328383[/C][C]-3.0275[/C][C]0.001632[/C][/ROW]
[ROW][C]46[/C][C]-0.383728[/C][C]-3.5378[/C][C]0.000328[/C][/ROW]
[ROW][C]47[/C][C]-0.344789[/C][C]-3.1788[/C][C]0.001032[/C][/ROW]
[ROW][C]48[/C][C]-0.317905[/C][C]-2.9309[/C][C]0.00217[/C][/ROW]
[ROW][C]49[/C][C]-0.365725[/C][C]-3.3718[/C][C]0.000563[/C][/ROW]
[ROW][C]50[/C][C]-0.382202[/C][C]-3.5237[/C][C]0.000344[/C][/ROW]
[ROW][C]51[/C][C]-0.389896[/C][C]-3.5947[/C][C]0.000272[/C][/ROW]
[ROW][C]52[/C][C]-0.402596[/C][C]-3.7118[/C][C]0.000183[/C][/ROW]
[ROW][C]53[/C][C]-0.375384[/C][C]-3.4609[/C][C]0.000422[/C][/ROW]
[ROW][C]54[/C][C]-0.353106[/C][C]-3.2555[/C][C]0.000813[/C][/ROW]
[ROW][C]55[/C][C]-0.373174[/C][C]-3.4405[/C][C]0.000451[/C][/ROW]
[ROW][C]56[/C][C]-0.361566[/C][C]-3.3335[/C][C]0.000636[/C][/ROW]
[ROW][C]57[/C][C]-0.367765[/C][C]-3.3906[/C][C]0.00053[/C][/ROW]
[ROW][C]58[/C][C]-0.378413[/C][C]-3.4888[/C][C]0.000386[/C][/ROW]
[ROW][C]59[/C][C]-0.335517[/C][C]-3.0933[/C][C]0.001339[/C][/ROW]
[ROW][C]60[/C][C]-0.312428[/C][C]-2.8804[/C][C]0.002512[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31826&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31826&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	0.818369	7.545	0
2	0.73251	6.7534	0
3	0.773212	7.1287	0
4	0.697013	6.4261	0
5	0.724339	6.6781	0
6	0.802545	7.3991	0
7	0.671675	6.1925	0
8	0.608928	5.614	0
9	0.633891	5.8442	0
10	0.526068	4.8501	3e-06
11	0.568384	5.2402	1e-06
12	0.666154	6.1416	0
13	0.511253	4.7135	5e-06
14	0.431143	3.9749	7.4e-05
15	0.447461	4.1254	4.3e-05
16	0.36899	3.4019	0.000511
17	0.39058	3.601	0.000266
18	0.449448	4.1437	4e-05
19	0.322527	2.9736	0.001915
20	0.267366	2.465	0.007857
21	0.269848	2.4879	0.007402
22	0.165592	1.5267	0.065276
23	0.201059	1.8537	0.033627
24	0.261108	2.4073	0.009118
25	0.128731	1.1868	0.119299
26	0.064027	0.5903	0.278279
27	0.06417	0.5916	0.277839
28	-0.024538	-0.2262	0.410784
29	-0.000894	-0.0082	0.496722
30	0.02227	0.2053	0.418906
31	-0.07538	-0.695	0.244484
32	-0.112856	-1.0405	0.150533
33	-0.13109	-1.2086	0.115086
34	-0.205573	-1.8953	0.030727
35	-0.161718	-1.491	0.069836
36	-0.11447	-1.0554	0.147125
37	-0.208714	-1.9242	0.028835
38	-0.242925	-2.2397	0.013862
39	-0.244265	-2.252	0.013449
40	-0.288937	-2.6639	0.00462
41	-0.262103	-2.4165	0.008906
42	-0.239295	-2.2062	0.015034
43	-0.298603	-2.753	0.00361
44	-0.313575	-2.891	0.002437
45	-0.328383	-3.0275	0.001632
46	-0.383728	-3.5378	0.000328
47	-0.344789	-3.1788	0.001032
48	-0.317905	-2.9309	0.00217
49	-0.365725	-3.3718	0.000563
50	-0.382202	-3.5237	0.000344
51	-0.389896	-3.5947	0.000272
52	-0.402596	-3.7118	0.000183
53	-0.375384	-3.4609	0.000422
54	-0.353106	-3.2555	0.000813
55	-0.373174	-3.4405	0.000451
56	-0.361566	-3.3335	0.000636
57	-0.367765	-3.3906	0.00053
58	-0.378413	-3.4888	0.000386
59	-0.335517	-3.0933	0.001339
60	-0.312428	-2.8804	0.002512

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.818369	7.545	0
2	0.19009	1.7525	0.041643
3	0.415082	3.8269	0.000124
4	-0.120967	-1.1153	0.133942
5	0.382292	3.5246	0.000343
6	0.248935	2.2951	0.012096
7	-0.317894	-2.9308	0.00217
8	-0.073932	-0.6816	0.248668
9	-0.035211	-0.3246	0.37313
10	-0.241474	-2.2263	0.01432
11	0.273242	2.5192	0.006818
12	0.204505	1.8854	0.031393
13	-0.350915	-3.2353	0.000866
14	-0.149814	-1.3812	0.085416
15	-0.016572	-0.1528	0.439463
16	0.089955	0.8293	0.204617
17	-0.051469	-0.4745	0.318172
18	-0.006152	-0.0567	0.477452
19	-0.010298	-0.0949	0.462291
20	-0.055325	-0.5101	0.305661
21	-0.081867	-0.7548	0.226236
22	-0.017179	-0.1584	0.437265
23	0.034839	0.3212	0.374424
24	-0.08037	-0.741	0.230376
25	-0.072416	-0.6676	0.253085
26	-0.007318	-0.0675	0.473185
27	-0.030903	-0.2849	0.388202
28	-0.101957	-0.94	0.17494
29	0.000886	0.0082	0.496751
30	-0.144069	-1.3283	0.093825
31	0.150647	1.3889	0.084247
32	-0.063109	-0.5818	0.281108
33	-0.053584	-0.494	0.311282
34	0.115603	1.0658	0.144765
35	0.016069	0.1481	0.441288
36	0.03201	0.2951	0.384313
37	-0.022266	-0.2053	0.418921
38	-0.016951	-0.1563	0.43809
39	0.043762	0.4035	0.343809
40	0.023536	0.217	0.414368
41	-0.118657	-1.094	0.138531
42	0.036436	0.3359	0.368877
43	-0.040416	-0.3726	0.355182
44	-0.006038	-0.0557	0.477869
45	-0.03117	-0.2874	0.387263
46	-0.052335	-0.4825	0.315345
47	-0.060499	-0.5578	0.289234
48	-0.070854	-0.6532	0.257683
49	0.124045	1.1436	0.127992
50	-0.019078	-0.1759	0.4304
51	-0.019798	-0.1825	0.4278
52	0.046355	0.4274	0.335094
53	-0.028367	-0.2615	0.397158
54	0.059534	0.5489	0.292265
55	-0.010032	-0.0925	0.463263
56	0.040314	0.3717	0.355529
57	0.036984	0.341	0.366983
58	-0.048249	-0.4448	0.328785
59	0.057412	0.5293	0.298983
60	-0.068967	-0.6358	0.263293

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.818369 & 7.545 & 0 \tabularnewline
2 & 0.19009 & 1.7525 & 0.041643 \tabularnewline
3 & 0.415082 & 3.8269 & 0.000124 \tabularnewline
4 & -0.120967 & -1.1153 & 0.133942 \tabularnewline
5 & 0.382292 & 3.5246 & 0.000343 \tabularnewline
6 & 0.248935 & 2.2951 & 0.012096 \tabularnewline
7 & -0.317894 & -2.9308 & 0.00217 \tabularnewline
8 & -0.073932 & -0.6816 & 0.248668 \tabularnewline
9 & -0.035211 & -0.3246 & 0.37313 \tabularnewline
10 & -0.241474 & -2.2263 & 0.01432 \tabularnewline
11 & 0.273242 & 2.5192 & 0.006818 \tabularnewline
12 & 0.204505 & 1.8854 & 0.031393 \tabularnewline
13 & -0.350915 & -3.2353 & 0.000866 \tabularnewline
14 & -0.149814 & -1.3812 & 0.085416 \tabularnewline
15 & -0.016572 & -0.1528 & 0.439463 \tabularnewline
16 & 0.089955 & 0.8293 & 0.204617 \tabularnewline
17 & -0.051469 & -0.4745 & 0.318172 \tabularnewline
18 & -0.006152 & -0.0567 & 0.477452 \tabularnewline
19 & -0.010298 & -0.0949 & 0.462291 \tabularnewline
20 & -0.055325 & -0.5101 & 0.305661 \tabularnewline
21 & -0.081867 & -0.7548 & 0.226236 \tabularnewline
22 & -0.017179 & -0.1584 & 0.437265 \tabularnewline
23 & 0.034839 & 0.3212 & 0.374424 \tabularnewline
24 & -0.08037 & -0.741 & 0.230376 \tabularnewline
25 & -0.072416 & -0.6676 & 0.253085 \tabularnewline
26 & -0.007318 & -0.0675 & 0.473185 \tabularnewline
27 & -0.030903 & -0.2849 & 0.388202 \tabularnewline
28 & -0.101957 & -0.94 & 0.17494 \tabularnewline
29 & 0.000886 & 0.0082 & 0.496751 \tabularnewline
30 & -0.144069 & -1.3283 & 0.093825 \tabularnewline
31 & 0.150647 & 1.3889 & 0.084247 \tabularnewline
32 & -0.063109 & -0.5818 & 0.281108 \tabularnewline
33 & -0.053584 & -0.494 & 0.311282 \tabularnewline
34 & 0.115603 & 1.0658 & 0.144765 \tabularnewline
35 & 0.016069 & 0.1481 & 0.441288 \tabularnewline
36 & 0.03201 & 0.2951 & 0.384313 \tabularnewline
37 & -0.022266 & -0.2053 & 0.418921 \tabularnewline
38 & -0.016951 & -0.1563 & 0.43809 \tabularnewline
39 & 0.043762 & 0.4035 & 0.343809 \tabularnewline
40 & 0.023536 & 0.217 & 0.414368 \tabularnewline
41 & -0.118657 & -1.094 & 0.138531 \tabularnewline
42 & 0.036436 & 0.3359 & 0.368877 \tabularnewline
43 & -0.040416 & -0.3726 & 0.355182 \tabularnewline
44 & -0.006038 & -0.0557 & 0.477869 \tabularnewline
45 & -0.03117 & -0.2874 & 0.387263 \tabularnewline
46 & -0.052335 & -0.4825 & 0.315345 \tabularnewline
47 & -0.060499 & -0.5578 & 0.289234 \tabularnewline
48 & -0.070854 & -0.6532 & 0.257683 \tabularnewline
49 & 0.124045 & 1.1436 & 0.127992 \tabularnewline
50 & -0.019078 & -0.1759 & 0.4304 \tabularnewline
51 & -0.019798 & -0.1825 & 0.4278 \tabularnewline
52 & 0.046355 & 0.4274 & 0.335094 \tabularnewline
53 & -0.028367 & -0.2615 & 0.397158 \tabularnewline
54 & 0.059534 & 0.5489 & 0.292265 \tabularnewline
55 & -0.010032 & -0.0925 & 0.463263 \tabularnewline
56 & 0.040314 & 0.3717 & 0.355529 \tabularnewline
57 & 0.036984 & 0.341 & 0.366983 \tabularnewline
58 & -0.048249 & -0.4448 & 0.328785 \tabularnewline
59 & 0.057412 & 0.5293 & 0.298983 \tabularnewline
60 & -0.068967 & -0.6358 & 0.263293 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31826&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]0.818369[/C][C]7.545[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.19009[/C][C]1.7525[/C][C]0.041643[/C][/ROW]
[ROW][C]3[/C][C]0.415082[/C][C]3.8269[/C][C]0.000124[/C][/ROW]
[ROW][C]4[/C][C]-0.120967[/C][C]-1.1153[/C][C]0.133942[/C][/ROW]
[ROW][C]5[/C][C]0.382292[/C][C]3.5246[/C][C]0.000343[/C][/ROW]
[ROW][C]6[/C][C]0.248935[/C][C]2.2951[/C][C]0.012096[/C][/ROW]
[ROW][C]7[/C][C]-0.317894[/C][C]-2.9308[/C][C]0.00217[/C][/ROW]
[ROW][C]8[/C][C]-0.073932[/C][C]-0.6816[/C][C]0.248668[/C][/ROW]
[ROW][C]9[/C][C]-0.035211[/C][C]-0.3246[/C][C]0.37313[/C][/ROW]
[ROW][C]10[/C][C]-0.241474[/C][C]-2.2263[/C][C]0.01432[/C][/ROW]
[ROW][C]11[/C][C]0.273242[/C][C]2.5192[/C][C]0.006818[/C][/ROW]
[ROW][C]12[/C][C]0.204505[/C][C]1.8854[/C][C]0.031393[/C][/ROW]
[ROW][C]13[/C][C]-0.350915[/C][C]-3.2353[/C][C]0.000866[/C][/ROW]
[ROW][C]14[/C][C]-0.149814[/C][C]-1.3812[/C][C]0.085416[/C][/ROW]
[ROW][C]15[/C][C]-0.016572[/C][C]-0.1528[/C][C]0.439463[/C][/ROW]
[ROW][C]16[/C][C]0.089955[/C][C]0.8293[/C][C]0.204617[/C][/ROW]
[ROW][C]17[/C][C]-0.051469[/C][C]-0.4745[/C][C]0.318172[/C][/ROW]
[ROW][C]18[/C][C]-0.006152[/C][C]-0.0567[/C][C]0.477452[/C][/ROW]
[ROW][C]19[/C][C]-0.010298[/C][C]-0.0949[/C][C]0.462291[/C][/ROW]
[ROW][C]20[/C][C]-0.055325[/C][C]-0.5101[/C][C]0.305661[/C][/ROW]
[ROW][C]21[/C][C]-0.081867[/C][C]-0.7548[/C][C]0.226236[/C][/ROW]
[ROW][C]22[/C][C]-0.017179[/C][C]-0.1584[/C][C]0.437265[/C][/ROW]
[ROW][C]23[/C][C]0.034839[/C][C]0.3212[/C][C]0.374424[/C][/ROW]
[ROW][C]24[/C][C]-0.08037[/C][C]-0.741[/C][C]0.230376[/C][/ROW]
[ROW][C]25[/C][C]-0.072416[/C][C]-0.6676[/C][C]0.253085[/C][/ROW]
[ROW][C]26[/C][C]-0.007318[/C][C]-0.0675[/C][C]0.473185[/C][/ROW]
[ROW][C]27[/C][C]-0.030903[/C][C]-0.2849[/C][C]0.388202[/C][/ROW]
[ROW][C]28[/C][C]-0.101957[/C][C]-0.94[/C][C]0.17494[/C][/ROW]
[ROW][C]29[/C][C]0.000886[/C][C]0.0082[/C][C]0.496751[/C][/ROW]
[ROW][C]30[/C][C]-0.144069[/C][C]-1.3283[/C][C]0.093825[/C][/ROW]
[ROW][C]31[/C][C]0.150647[/C][C]1.3889[/C][C]0.084247[/C][/ROW]
[ROW][C]32[/C][C]-0.063109[/C][C]-0.5818[/C][C]0.281108[/C][/ROW]
[ROW][C]33[/C][C]-0.053584[/C][C]-0.494[/C][C]0.311282[/C][/ROW]
[ROW][C]34[/C][C]0.115603[/C][C]1.0658[/C][C]0.144765[/C][/ROW]
[ROW][C]35[/C][C]0.016069[/C][C]0.1481[/C][C]0.441288[/C][/ROW]
[ROW][C]36[/C][C]0.03201[/C][C]0.2951[/C][C]0.384313[/C][/ROW]
[ROW][C]37[/C][C]-0.022266[/C][C]-0.2053[/C][C]0.418921[/C][/ROW]
[ROW][C]38[/C][C]-0.016951[/C][C]-0.1563[/C][C]0.43809[/C][/ROW]
[ROW][C]39[/C][C]0.043762[/C][C]0.4035[/C][C]0.343809[/C][/ROW]
[ROW][C]40[/C][C]0.023536[/C][C]0.217[/C][C]0.414368[/C][/ROW]
[ROW][C]41[/C][C]-0.118657[/C][C]-1.094[/C][C]0.138531[/C][/ROW]
[ROW][C]42[/C][C]0.036436[/C][C]0.3359[/C][C]0.368877[/C][/ROW]
[ROW][C]43[/C][C]-0.040416[/C][C]-0.3726[/C][C]0.355182[/C][/ROW]
[ROW][C]44[/C][C]-0.006038[/C][C]-0.0557[/C][C]0.477869[/C][/ROW]
[ROW][C]45[/C][C]-0.03117[/C][C]-0.2874[/C][C]0.387263[/C][/ROW]
[ROW][C]46[/C][C]-0.052335[/C][C]-0.4825[/C][C]0.315345[/C][/ROW]
[ROW][C]47[/C][C]-0.060499[/C][C]-0.5578[/C][C]0.289234[/C][/ROW]
[ROW][C]48[/C][C]-0.070854[/C][C]-0.6532[/C][C]0.257683[/C][/ROW]
[ROW][C]49[/C][C]0.124045[/C][C]1.1436[/C][C]0.127992[/C][/ROW]
[ROW][C]50[/C][C]-0.019078[/C][C]-0.1759[/C][C]0.4304[/C][/ROW]
[ROW][C]51[/C][C]-0.019798[/C][C]-0.1825[/C][C]0.4278[/C][/ROW]
[ROW][C]52[/C][C]0.046355[/C][C]0.4274[/C][C]0.335094[/C][/ROW]
[ROW][C]53[/C][C]-0.028367[/C][C]-0.2615[/C][C]0.397158[/C][/ROW]
[ROW][C]54[/C][C]0.059534[/C][C]0.5489[/C][C]0.292265[/C][/ROW]
[ROW][C]55[/C][C]-0.010032[/C][C]-0.0925[/C][C]0.463263[/C][/ROW]
[ROW][C]56[/C][C]0.040314[/C][C]0.3717[/C][C]0.355529[/C][/ROW]
[ROW][C]57[/C][C]0.036984[/C][C]0.341[/C][C]0.366983[/C][/ROW]
[ROW][C]58[/C][C]-0.048249[/C][C]-0.4448[/C][C]0.328785[/C][/ROW]
[ROW][C]59[/C][C]0.057412[/C][C]0.5293[/C][C]0.298983[/C][/ROW]
[ROW][C]60[/C][C]-0.068967[/C][C]-0.6358[/C][C]0.263293[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31826&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31826&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	0.818369	7.545	0
2	0.19009	1.7525	0.041643
3	0.415082	3.8269	0.000124
4	-0.120967	-1.1153	0.133942
5	0.382292	3.5246	0.000343
6	0.248935	2.2951	0.012096
7	-0.317894	-2.9308	0.00217
8	-0.073932	-0.6816	0.248668
9	-0.035211	-0.3246	0.37313
10	-0.241474	-2.2263	0.01432
11	0.273242	2.5192	0.006818
12	0.204505	1.8854	0.031393
13	-0.350915	-3.2353	0.000866
14	-0.149814	-1.3812	0.085416
15	-0.016572	-0.1528	0.439463
16	0.089955	0.8293	0.204617
17	-0.051469	-0.4745	0.318172
18	-0.006152	-0.0567	0.477452
19	-0.010298	-0.0949	0.462291
20	-0.055325	-0.5101	0.305661
21	-0.081867	-0.7548	0.226236
22	-0.017179	-0.1584	0.437265
23	0.034839	0.3212	0.374424
24	-0.08037	-0.741	0.230376
25	-0.072416	-0.6676	0.253085
26	-0.007318	-0.0675	0.473185
27	-0.030903	-0.2849	0.388202
28	-0.101957	-0.94	0.17494
29	0.000886	0.0082	0.496751
30	-0.144069	-1.3283	0.093825
31	0.150647	1.3889	0.084247
32	-0.063109	-0.5818	0.281108
33	-0.053584	-0.494	0.311282
34	0.115603	1.0658	0.144765
35	0.016069	0.1481	0.441288
36	0.03201	0.2951	0.384313
37	-0.022266	-0.2053	0.418921
38	-0.016951	-0.1563	0.43809
39	0.043762	0.4035	0.343809
40	0.023536	0.217	0.414368
41	-0.118657	-1.094	0.138531
42	0.036436	0.3359	0.368877
43	-0.040416	-0.3726	0.355182
44	-0.006038	-0.0557	0.477869
45	-0.03117	-0.2874	0.387263
46	-0.052335	-0.4825	0.315345
47	-0.060499	-0.5578	0.289234
48	-0.070854	-0.6532	0.257683
49	0.124045	1.1436	0.127992
50	-0.019078	-0.1759	0.4304
51	-0.019798	-0.1825	0.4278
52	0.046355	0.4274	0.335094
53	-0.028367	-0.2615	0.397158
54	0.059534	0.5489	0.292265
55	-0.010032	-0.0925	0.463263
56	0.040314	0.3717	0.355529
57	0.036984	0.341	0.366983
58	-0.048249	-0.4448	0.328785
59	0.057412	0.5293	0.298983
60	-0.068967	-0.6358	0.263293

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;

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 (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='lags',ylab='ACF')
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