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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Fri, 27 Nov 2009 01:53:19 -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/2009/Nov/27/t12593121477lrf7jg820q19a2.htm/, Retrieved Sun, 28 Apr 2024 23:16:45 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60485, Retrieved Sun, 28 Apr 2024 23:16:45 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

187

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 12:26:39] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [workshop 8] [2009-11-27 08:53:19] [a18540c86166a2b66550d1fef0503cc2] [Current]
-   PD            [(Partial) Autocorrelation Function] [workshop 9 - 4] [2009-12-04 09:23:46] [f1a50df816abcbb519e7637ff6b72fa0] 
-   PD              [(Partial) Autocorrelation Function] [WS9.4] [2009-12-04 16:34:14] [d31db4f83c6a129f6d3e47077769e868] 
- RMP                 [ARIMA Backward Selection] [WS9.5] [2009-12-04 17:03:38] [d31db4f83c6a129f6d3e47077769e868] 
-    D              [(Partial) Autocorrelation Function] [WS9] [2009-12-06 14:07:52] [9f35ad889e41dd0c9322ca60d75b9f47] 
-    D              [(Partial) Autocorrelation Function] [WS9] [2009-12-06 14:38:30] [9f35ad889e41dd0c9322ca60d75b9f47] 
-   P                 [(Partial) Autocorrelation Function] [Workshop 9 D=1 en...] [2009-12-09 16:41:04] [aba88da643e3763d32ff92bd8f92a385] 
-   PD            [(Partial) Autocorrelation Function] [workshop 9 - ] [2009-12-04 09:23:46] [f1a50df816abcbb519e7637ff6b72fa0] 
-    D              [(Partial) Autocorrelation Function] [WS9] [2009-12-06 14:42:19] [9f35ad889e41dd0c9322ca60d75b9f47] 
-    D            [(Partial) Autocorrelation Function] [WS9] [2009-12-06 14:20:54] [9f35ad889e41dd0c9322ca60d75b9f47] 

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Dataseries X:

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Histogram

Boxplots

8,6
8,5
8,3
7,8
7,8
8
8,6
8,9
8,9
8,6
8,3
8,3
8,3
8,4
8,5
8,4
8,6
8,5
8,5
8,4
8,5
8,5
8,5
8,5
8,5
8,5
8,5
8,5
8,6
8,4
8,1
8
8
8
8
7,9
7,8
7,8
7,9
8,1
8
7,6
7,3
7
6,8
7
7,1
7,2
7,1
6,9
6,7
6,7
6,6
6,9
7,3
7,5
7,3
7,1
6,9
7,1

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=60485&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=60485&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60485&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	0.567758	3.8924	0.000156
2	-0.048973	-0.3357	0.36928
3	-0.49388	-3.3859	0.000721
4	-0.530444	-3.6365	0.000342
5	-0.226428	-1.5523	0.063648
6	0.132686	0.9097	0.183824
7	0.246599	1.6906	0.048768
8	0.212973	1.4601	0.075462
9	0.032069	0.2199	0.413468
10	-0.075326	-0.5164	0.303994
11	-0.054115	-0.371	0.356154
12	-0.054121	-0.371	0.35614
13	-0.057064	-0.3912	0.348705
14	0.016569	0.1136	0.455022
15	0.007751	0.0531	0.478925
16	0.047241	0.3239	0.373737
17	0.043776	0.3001	0.382708
18	-0.014919	-0.1023	0.459485
19	-0.09803	-0.6721	0.252419
20	-0.073881	-0.5065	0.307437
21	-0.049079	-0.3365	0.369008
22	0.000139	0.001	0.499622
23	-0.003066	-0.021	0.491661
24	0.005873	0.0403	0.484028
25	0.021078	0.1445	0.44286
26	0.021203	0.1454	0.442524
27	-0.067522	-0.4629	0.322784
28	-0.144626	-0.9915	0.163258
29	-0.154098	-1.0564	0.148084
30	-0.044037	-0.3019	0.38203
31	0.161141	1.1047	0.13745
32	0.295749	2.0276	0.024149
33	0.213291	1.4622	0.075164
34	-0.035246	-0.2416	0.405058
35	-0.30513	-2.0919	0.02094
36	-0.384911	-2.6388	0.005625

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.567758 & 3.8924 & 0.000156 \tabularnewline
2 & -0.048973 & -0.3357 & 0.36928 \tabularnewline
3 & -0.49388 & -3.3859 & 0.000721 \tabularnewline
4 & -0.530444 & -3.6365 & 0.000342 \tabularnewline
5 & -0.226428 & -1.5523 & 0.063648 \tabularnewline
6 & 0.132686 & 0.9097 & 0.183824 \tabularnewline
7 & 0.246599 & 1.6906 & 0.048768 \tabularnewline
8 & 0.212973 & 1.4601 & 0.075462 \tabularnewline
9 & 0.032069 & 0.2199 & 0.413468 \tabularnewline
10 & -0.075326 & -0.5164 & 0.303994 \tabularnewline
11 & -0.054115 & -0.371 & 0.356154 \tabularnewline
12 & -0.054121 & -0.371 & 0.35614 \tabularnewline
13 & -0.057064 & -0.3912 & 0.348705 \tabularnewline
14 & 0.016569 & 0.1136 & 0.455022 \tabularnewline
15 & 0.007751 & 0.0531 & 0.478925 \tabularnewline
16 & 0.047241 & 0.3239 & 0.373737 \tabularnewline
17 & 0.043776 & 0.3001 & 0.382708 \tabularnewline
18 & -0.014919 & -0.1023 & 0.459485 \tabularnewline
19 & -0.09803 & -0.6721 & 0.252419 \tabularnewline
20 & -0.073881 & -0.5065 & 0.307437 \tabularnewline
21 & -0.049079 & -0.3365 & 0.369008 \tabularnewline
22 & 0.000139 & 0.001 & 0.499622 \tabularnewline
23 & -0.003066 & -0.021 & 0.491661 \tabularnewline
24 & 0.005873 & 0.0403 & 0.484028 \tabularnewline
25 & 0.021078 & 0.1445 & 0.44286 \tabularnewline
26 & 0.021203 & 0.1454 & 0.442524 \tabularnewline
27 & -0.067522 & -0.4629 & 0.322784 \tabularnewline
28 & -0.144626 & -0.9915 & 0.163258 \tabularnewline
29 & -0.154098 & -1.0564 & 0.148084 \tabularnewline
30 & -0.044037 & -0.3019 & 0.38203 \tabularnewline
31 & 0.161141 & 1.1047 & 0.13745 \tabularnewline
32 & 0.295749 & 2.0276 & 0.024149 \tabularnewline
33 & 0.213291 & 1.4622 & 0.075164 \tabularnewline
34 & -0.035246 & -0.2416 & 0.405058 \tabularnewline
35 & -0.30513 & -2.0919 & 0.02094 \tabularnewline
36 & -0.384911 & -2.6388 & 0.005625 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60485&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]0.567758[/C][C]3.8924[/C][C]0.000156[/C][/ROW]
[ROW][C]2[/C][C]-0.048973[/C][C]-0.3357[/C][C]0.36928[/C][/ROW]
[ROW][C]3[/C][C]-0.49388[/C][C]-3.3859[/C][C]0.000721[/C][/ROW]
[ROW][C]4[/C][C]-0.530444[/C][C]-3.6365[/C][C]0.000342[/C][/ROW]
[ROW][C]5[/C][C]-0.226428[/C][C]-1.5523[/C][C]0.063648[/C][/ROW]
[ROW][C]6[/C][C]0.132686[/C][C]0.9097[/C][C]0.183824[/C][/ROW]
[ROW][C]7[/C][C]0.246599[/C][C]1.6906[/C][C]0.048768[/C][/ROW]
[ROW][C]8[/C][C]0.212973[/C][C]1.4601[/C][C]0.075462[/C][/ROW]
[ROW][C]9[/C][C]0.032069[/C][C]0.2199[/C][C]0.413468[/C][/ROW]
[ROW][C]10[/C][C]-0.075326[/C][C]-0.5164[/C][C]0.303994[/C][/ROW]
[ROW][C]11[/C][C]-0.054115[/C][C]-0.371[/C][C]0.356154[/C][/ROW]
[ROW][C]12[/C][C]-0.054121[/C][C]-0.371[/C][C]0.35614[/C][/ROW]
[ROW][C]13[/C][C]-0.057064[/C][C]-0.3912[/C][C]0.348705[/C][/ROW]
[ROW][C]14[/C][C]0.016569[/C][C]0.1136[/C][C]0.455022[/C][/ROW]
[ROW][C]15[/C][C]0.007751[/C][C]0.0531[/C][C]0.478925[/C][/ROW]
[ROW][C]16[/C][C]0.047241[/C][C]0.3239[/C][C]0.373737[/C][/ROW]
[ROW][C]17[/C][C]0.043776[/C][C]0.3001[/C][C]0.382708[/C][/ROW]
[ROW][C]18[/C][C]-0.014919[/C][C]-0.1023[/C][C]0.459485[/C][/ROW]
[ROW][C]19[/C][C]-0.09803[/C][C]-0.6721[/C][C]0.252419[/C][/ROW]
[ROW][C]20[/C][C]-0.073881[/C][C]-0.5065[/C][C]0.307437[/C][/ROW]
[ROW][C]21[/C][C]-0.049079[/C][C]-0.3365[/C][C]0.369008[/C][/ROW]
[ROW][C]22[/C][C]0.000139[/C][C]0.001[/C][C]0.499622[/C][/ROW]
[ROW][C]23[/C][C]-0.003066[/C][C]-0.021[/C][C]0.491661[/C][/ROW]
[ROW][C]24[/C][C]0.005873[/C][C]0.0403[/C][C]0.484028[/C][/ROW]
[ROW][C]25[/C][C]0.021078[/C][C]0.1445[/C][C]0.44286[/C][/ROW]
[ROW][C]26[/C][C]0.021203[/C][C]0.1454[/C][C]0.442524[/C][/ROW]
[ROW][C]27[/C][C]-0.067522[/C][C]-0.4629[/C][C]0.322784[/C][/ROW]
[ROW][C]28[/C][C]-0.144626[/C][C]-0.9915[/C][C]0.163258[/C][/ROW]
[ROW][C]29[/C][C]-0.154098[/C][C]-1.0564[/C][C]0.148084[/C][/ROW]
[ROW][C]30[/C][C]-0.044037[/C][C]-0.3019[/C][C]0.38203[/C][/ROW]
[ROW][C]31[/C][C]0.161141[/C][C]1.1047[/C][C]0.13745[/C][/ROW]
[ROW][C]32[/C][C]0.295749[/C][C]2.0276[/C][C]0.024149[/C][/ROW]
[ROW][C]33[/C][C]0.213291[/C][C]1.4622[/C][C]0.075164[/C][/ROW]
[ROW][C]34[/C][C]-0.035246[/C][C]-0.2416[/C][C]0.405058[/C][/ROW]
[ROW][C]35[/C][C]-0.30513[/C][C]-2.0919[/C][C]0.02094[/C][/ROW]
[ROW][C]36[/C][C]-0.384911[/C][C]-2.6388[/C][C]0.005625[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60485&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60485&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	0.567758	3.8924	0.000156
2	-0.048973	-0.3357	0.36928
3	-0.49388	-3.3859	0.000721
4	-0.530444	-3.6365	0.000342
5	-0.226428	-1.5523	0.063648
6	0.132686	0.9097	0.183824
7	0.246599	1.6906	0.048768
8	0.212973	1.4601	0.075462
9	0.032069	0.2199	0.413468
10	-0.075326	-0.5164	0.303994
11	-0.054115	-0.371	0.356154
12	-0.054121	-0.371	0.35614
13	-0.057064	-0.3912	0.348705
14	0.016569	0.1136	0.455022
15	0.007751	0.0531	0.478925
16	0.047241	0.3239	0.373737
17	0.043776	0.3001	0.382708
18	-0.014919	-0.1023	0.459485
19	-0.09803	-0.6721	0.252419
20	-0.073881	-0.5065	0.307437
21	-0.049079	-0.3365	0.369008
22	0.000139	0.001	0.499622
23	-0.003066	-0.021	0.491661
24	0.005873	0.0403	0.484028
25	0.021078	0.1445	0.44286
26	0.021203	0.1454	0.442524
27	-0.067522	-0.4629	0.322784
28	-0.144626	-0.9915	0.163258
29	-0.154098	-1.0564	0.148084
30	-0.044037	-0.3019	0.38203
31	0.161141	1.1047	0.13745
32	0.295749	2.0276	0.024149
33	0.213291	1.4622	0.075164
34	-0.035246	-0.2416	0.405058
35	-0.30513	-2.0919	0.02094
36	-0.384911	-2.6388	0.005625

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.567758	3.8924	0.000156
2	-0.547955	-3.7566	0.000237
3	-0.294683	-2.0202	0.024539
4	-0.053076	-0.3639	0.358794
5	0.030311	0.2078	0.418142
6	-0.019409	-0.1331	0.447358
7	-0.172605	-1.1833	0.121316
8	0.124849	0.8559	0.198193
9	-0.092121	-0.6315	0.26537
10	0.07473	0.5123	0.305412
11	0.073423	0.5034	0.30853
12	-0.161102	-1.1045	0.137508
13	0.008119	0.0557	0.477924
14	0.151754	1.0404	0.151744
15	-0.144565	-0.9911	0.16336
16	0.079697	0.5464	0.293697
17	-0.037441	-0.2567	0.399271
18	-0.039542	-0.2711	0.393756
19	-0.119974	-0.8225	0.207472
20	0.12849	0.8809	0.191432
21	-0.111557	-0.7648	0.224107
22	-0.156389	-1.0722	0.144563
23	0.025786	0.1768	0.430221
24	0.027946	0.1916	0.424446
25	-0.087694	-0.6012	0.275297
26	-0.02356	-0.1615	0.436189
27	-0.179114	-1.2279	0.112792
28	-0.172938	-1.1856	0.12087
29	0.043648	0.2992	0.383039
30	0.004561	0.0313	0.487595
31	0.04756	0.3261	0.372916
32	0.029937	0.2052	0.419136
33	0.039121	0.2682	0.39486
34	-0.169143	-1.1596	0.126037
35	-0.075531	-0.5178	0.303509
36	-0.059967	-0.4111	0.341429

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.567758 & 3.8924 & 0.000156 \tabularnewline
2 & -0.547955 & -3.7566 & 0.000237 \tabularnewline
3 & -0.294683 & -2.0202 & 0.024539 \tabularnewline
4 & -0.053076 & -0.3639 & 0.358794 \tabularnewline
5 & 0.030311 & 0.2078 & 0.418142 \tabularnewline
6 & -0.019409 & -0.1331 & 0.447358 \tabularnewline
7 & -0.172605 & -1.1833 & 0.121316 \tabularnewline
8 & 0.124849 & 0.8559 & 0.198193 \tabularnewline
9 & -0.092121 & -0.6315 & 0.26537 \tabularnewline
10 & 0.07473 & 0.5123 & 0.305412 \tabularnewline
11 & 0.073423 & 0.5034 & 0.30853 \tabularnewline
12 & -0.161102 & -1.1045 & 0.137508 \tabularnewline
13 & 0.008119 & 0.0557 & 0.477924 \tabularnewline
14 & 0.151754 & 1.0404 & 0.151744 \tabularnewline
15 & -0.144565 & -0.9911 & 0.16336 \tabularnewline
16 & 0.079697 & 0.5464 & 0.293697 \tabularnewline
17 & -0.037441 & -0.2567 & 0.399271 \tabularnewline
18 & -0.039542 & -0.2711 & 0.393756 \tabularnewline
19 & -0.119974 & -0.8225 & 0.207472 \tabularnewline
20 & 0.12849 & 0.8809 & 0.191432 \tabularnewline
21 & -0.111557 & -0.7648 & 0.224107 \tabularnewline
22 & -0.156389 & -1.0722 & 0.144563 \tabularnewline
23 & 0.025786 & 0.1768 & 0.430221 \tabularnewline
24 & 0.027946 & 0.1916 & 0.424446 \tabularnewline
25 & -0.087694 & -0.6012 & 0.275297 \tabularnewline
26 & -0.02356 & -0.1615 & 0.436189 \tabularnewline
27 & -0.179114 & -1.2279 & 0.112792 \tabularnewline
28 & -0.172938 & -1.1856 & 0.12087 \tabularnewline
29 & 0.043648 & 0.2992 & 0.383039 \tabularnewline
30 & 0.004561 & 0.0313 & 0.487595 \tabularnewline
31 & 0.04756 & 0.3261 & 0.372916 \tabularnewline
32 & 0.029937 & 0.2052 & 0.419136 \tabularnewline
33 & 0.039121 & 0.2682 & 0.39486 \tabularnewline
34 & -0.169143 & -1.1596 & 0.126037 \tabularnewline
35 & -0.075531 & -0.5178 & 0.303509 \tabularnewline
36 & -0.059967 & -0.4111 & 0.341429 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60485&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]0.567758[/C][C]3.8924[/C][C]0.000156[/C][/ROW]
[ROW][C]2[/C][C]-0.547955[/C][C]-3.7566[/C][C]0.000237[/C][/ROW]
[ROW][C]3[/C][C]-0.294683[/C][C]-2.0202[/C][C]0.024539[/C][/ROW]
[ROW][C]4[/C][C]-0.053076[/C][C]-0.3639[/C][C]0.358794[/C][/ROW]
[ROW][C]5[/C][C]0.030311[/C][C]0.2078[/C][C]0.418142[/C][/ROW]
[ROW][C]6[/C][C]-0.019409[/C][C]-0.1331[/C][C]0.447358[/C][/ROW]
[ROW][C]7[/C][C]-0.172605[/C][C]-1.1833[/C][C]0.121316[/C][/ROW]
[ROW][C]8[/C][C]0.124849[/C][C]0.8559[/C][C]0.198193[/C][/ROW]
[ROW][C]9[/C][C]-0.092121[/C][C]-0.6315[/C][C]0.26537[/C][/ROW]
[ROW][C]10[/C][C]0.07473[/C][C]0.5123[/C][C]0.305412[/C][/ROW]
[ROW][C]11[/C][C]0.073423[/C][C]0.5034[/C][C]0.30853[/C][/ROW]
[ROW][C]12[/C][C]-0.161102[/C][C]-1.1045[/C][C]0.137508[/C][/ROW]
[ROW][C]13[/C][C]0.008119[/C][C]0.0557[/C][C]0.477924[/C][/ROW]
[ROW][C]14[/C][C]0.151754[/C][C]1.0404[/C][C]0.151744[/C][/ROW]
[ROW][C]15[/C][C]-0.144565[/C][C]-0.9911[/C][C]0.16336[/C][/ROW]
[ROW][C]16[/C][C]0.079697[/C][C]0.5464[/C][C]0.293697[/C][/ROW]
[ROW][C]17[/C][C]-0.037441[/C][C]-0.2567[/C][C]0.399271[/C][/ROW]
[ROW][C]18[/C][C]-0.039542[/C][C]-0.2711[/C][C]0.393756[/C][/ROW]
[ROW][C]19[/C][C]-0.119974[/C][C]-0.8225[/C][C]0.207472[/C][/ROW]
[ROW][C]20[/C][C]0.12849[/C][C]0.8809[/C][C]0.191432[/C][/ROW]
[ROW][C]21[/C][C]-0.111557[/C][C]-0.7648[/C][C]0.224107[/C][/ROW]
[ROW][C]22[/C][C]-0.156389[/C][C]-1.0722[/C][C]0.144563[/C][/ROW]
[ROW][C]23[/C][C]0.025786[/C][C]0.1768[/C][C]0.430221[/C][/ROW]
[ROW][C]24[/C][C]0.027946[/C][C]0.1916[/C][C]0.424446[/C][/ROW]
[ROW][C]25[/C][C]-0.087694[/C][C]-0.6012[/C][C]0.275297[/C][/ROW]
[ROW][C]26[/C][C]-0.02356[/C][C]-0.1615[/C][C]0.436189[/C][/ROW]
[ROW][C]27[/C][C]-0.179114[/C][C]-1.2279[/C][C]0.112792[/C][/ROW]
[ROW][C]28[/C][C]-0.172938[/C][C]-1.1856[/C][C]0.12087[/C][/ROW]
[ROW][C]29[/C][C]0.043648[/C][C]0.2992[/C][C]0.383039[/C][/ROW]
[ROW][C]30[/C][C]0.004561[/C][C]0.0313[/C][C]0.487595[/C][/ROW]
[ROW][C]31[/C][C]0.04756[/C][C]0.3261[/C][C]0.372916[/C][/ROW]
[ROW][C]32[/C][C]0.029937[/C][C]0.2052[/C][C]0.419136[/C][/ROW]
[ROW][C]33[/C][C]0.039121[/C][C]0.2682[/C][C]0.39486[/C][/ROW]
[ROW][C]34[/C][C]-0.169143[/C][C]-1.1596[/C][C]0.126037[/C][/ROW]
[ROW][C]35[/C][C]-0.075531[/C][C]-0.5178[/C][C]0.303509[/C][/ROW]
[ROW][C]36[/C][C]-0.059967[/C][C]-0.4111[/C][C]0.341429[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60485&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60485&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	0.567758	3.8924	0.000156
2	-0.547955	-3.7566	0.000237
3	-0.294683	-2.0202	0.024539
4	-0.053076	-0.3639	0.358794
5	0.030311	0.2078	0.418142
6	-0.019409	-0.1331	0.447358
7	-0.172605	-1.1833	0.121316
8	0.124849	0.8559	0.198193
9	-0.092121	-0.6315	0.26537
10	0.07473	0.5123	0.305412
11	0.073423	0.5034	0.30853
12	-0.161102	-1.1045	0.137508
13	0.008119	0.0557	0.477924
14	0.151754	1.0404	0.151744
15	-0.144565	-0.9911	0.16336
16	0.079697	0.5464	0.293697
17	-0.037441	-0.2567	0.399271
18	-0.039542	-0.2711	0.393756
19	-0.119974	-0.8225	0.207472
20	0.12849	0.8809	0.191432
21	-0.111557	-0.7648	0.224107
22	-0.156389	-1.0722	0.144563
23	0.025786	0.1768	0.430221
24	0.027946	0.1916	0.424446
25	-0.087694	-0.6012	0.275297
26	-0.02356	-0.1615	0.436189
27	-0.179114	-1.2279	0.112792
28	-0.172938	-1.1856	0.12087
29	0.043648	0.2992	0.383039
30	0.004561	0.0313	0.487595
31	0.04756	0.3261	0.372916
32	0.029937	0.2052	0.419136
33	0.039121	0.2682	0.39486
34	-0.169143	-1.1596	0.126037
35	-0.075531	-0.5178	0.303509
36	-0.059967	-0.4111	0.341429

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;

Parameters (R input):

par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; 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