Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Mon, 05 Dec 2011 09:45:05 -0500

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/2011/Dec/05/t1323096337o0qfv9cv8vyy3si.htm/, Retrieved Fri, 03 May 2024 08:14:31 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=150955, Retrieved Fri, 03 May 2024 08:14:31 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

127

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

-     [Univariate Data Series] [] [2008-12-08 19:22:39] [d2d412c7f4d35ffbf5ee5ee89db327d4]
- RMPD  [(Partial) Autocorrelation Function] [] [2011-12-01 17:46:48] [86f7284edee3dbb8ea5c7e2dec87d892]
- R P       [(Partial) Autocorrelation Function] [] [2011-12-05 14:45:05] [79818163420d1233b8d9d93d595e6c9e] [Current]
-   P         [(Partial) Autocorrelation Function] [] [2011-12-05 15:01:18] [86f7284edee3dbb8ea5c7e2dec87d892] 
- RMP         [ARIMA Forecasting] [] [2011-12-05 16:06:32] [86f7284edee3dbb8ea5c7e2dec87d892] 
- R P           [ARIMA Forecasting] [] [2011-12-16 07:39:11] [86f7284edee3dbb8ea5c7e2dec87d892] 
- RMPD            [Multiple Regression] [] [2011-12-23 12:25:40] [ad2d4c5ace9fa07b356a7b5098237581] 
- R                 [Multiple Regression] [] [2011-12-23 12:45:24] [ad2d4c5ace9fa07b356a7b5098237581] 
- RMPD          [Multiple Regression] [] [2011-12-16 11:27:07] [86f7284edee3dbb8ea5c7e2dec87d892] 
- R               [Multiple Regression] [] [2011-12-17 18:08:25] [74be16979710d4c4e7c6647856088456] 
- RMP         [Univariate Explorative Data Analysis] [] [2011-12-05 16:49:42] [86f7284edee3dbb8ea5c7e2dec87d892] 
- RMP         [Classical Decomposition] [] [2011-12-05 17:18:28] [86f7284edee3dbb8ea5c7e2dec87d892] 

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

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' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=150955&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=150955&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=150955&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' @ jenkins.wessa.net

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.375746	2.8862	0.00272
2	-0.282137	-2.1671	0.017137
3	-0.415974	-3.1952	0.001122
4	-0.29117	-2.2365	0.014556
5	0.032422	0.249	0.402097
6	0.147808	1.1353	0.130413
7	0.047654	0.366	0.357824
8	-0.173242	-1.3307	0.094205
9	-0.332485	-2.5539	0.006628
10	-0.284685	-2.1867	0.016371
11	0.280324	2.1532	0.017701
12	0.782618	6.0114	0
13	0.347714	2.6708	0.004881
14	-0.212006	-1.6284	0.054379
15	-0.360674	-2.7704	0.003738
16	-0.262414	-2.0156	0.0242
17	0.014175	0.1089	0.456832
18	0.107395	0.8249	0.20637
19	0.038196	0.2934	0.385126
20	-0.105335	-0.8091	0.210857
21	-0.241413	-1.8543	0.034346
22	-0.202684	-1.5568	0.062428
23	0.196181	1.5069	0.068587
24	0.563264	4.3265	3e-05
25	0.266037	2.0435	0.02274
26	-0.13445	-1.0327	0.152973
27	-0.272508	-2.0932	0.020321
28	-0.206852	-1.5889	0.058718
29	-0.003883	-0.0298	0.488154
30	0.06998	0.5375	0.296462
31	0.036967	0.284	0.388721
32	-0.066165	-0.5082	0.306597
33	-0.150139	-1.1532	0.126732
34	-0.129663	-0.996	0.161669
35	0.109475	0.8409	0.2019
36	0.361938	2.7801	0.00364

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.375746 & 2.8862 & 0.00272 \tabularnewline
2 & -0.282137 & -2.1671 & 0.017137 \tabularnewline
3 & -0.415974 & -3.1952 & 0.001122 \tabularnewline
4 & -0.29117 & -2.2365 & 0.014556 \tabularnewline
5 & 0.032422 & 0.249 & 0.402097 \tabularnewline
6 & 0.147808 & 1.1353 & 0.130413 \tabularnewline
7 & 0.047654 & 0.366 & 0.357824 \tabularnewline
8 & -0.173242 & -1.3307 & 0.094205 \tabularnewline
9 & -0.332485 & -2.5539 & 0.006628 \tabularnewline
10 & -0.284685 & -2.1867 & 0.016371 \tabularnewline
11 & 0.280324 & 2.1532 & 0.017701 \tabularnewline
12 & 0.782618 & 6.0114 & 0 \tabularnewline
13 & 0.347714 & 2.6708 & 0.004881 \tabularnewline
14 & -0.212006 & -1.6284 & 0.054379 \tabularnewline
15 & -0.360674 & -2.7704 & 0.003738 \tabularnewline
16 & -0.262414 & -2.0156 & 0.0242 \tabularnewline
17 & 0.014175 & 0.1089 & 0.456832 \tabularnewline
18 & 0.107395 & 0.8249 & 0.20637 \tabularnewline
19 & 0.038196 & 0.2934 & 0.385126 \tabularnewline
20 & -0.105335 & -0.8091 & 0.210857 \tabularnewline
21 & -0.241413 & -1.8543 & 0.034346 \tabularnewline
22 & -0.202684 & -1.5568 & 0.062428 \tabularnewline
23 & 0.196181 & 1.5069 & 0.068587 \tabularnewline
24 & 0.563264 & 4.3265 & 3e-05 \tabularnewline
25 & 0.266037 & 2.0435 & 0.02274 \tabularnewline
26 & -0.13445 & -1.0327 & 0.152973 \tabularnewline
27 & -0.272508 & -2.0932 & 0.020321 \tabularnewline
28 & -0.206852 & -1.5889 & 0.058718 \tabularnewline
29 & -0.003883 & -0.0298 & 0.488154 \tabularnewline
30 & 0.06998 & 0.5375 & 0.296462 \tabularnewline
31 & 0.036967 & 0.284 & 0.388721 \tabularnewline
32 & -0.066165 & -0.5082 & 0.306597 \tabularnewline
33 & -0.150139 & -1.1532 & 0.126732 \tabularnewline
34 & -0.129663 & -0.996 & 0.161669 \tabularnewline
35 & 0.109475 & 0.8409 & 0.2019 \tabularnewline
36 & 0.361938 & 2.7801 & 0.00364 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=150955&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]0.375746[/C][C]2.8862[/C][C]0.00272[/C][/ROW]
[ROW][C]2[/C][C]-0.282137[/C][C]-2.1671[/C][C]0.017137[/C][/ROW]
[ROW][C]3[/C][C]-0.415974[/C][C]-3.1952[/C][C]0.001122[/C][/ROW]
[ROW][C]4[/C][C]-0.29117[/C][C]-2.2365[/C][C]0.014556[/C][/ROW]
[ROW][C]5[/C][C]0.032422[/C][C]0.249[/C][C]0.402097[/C][/ROW]
[ROW][C]6[/C][C]0.147808[/C][C]1.1353[/C][C]0.130413[/C][/ROW]
[ROW][C]7[/C][C]0.047654[/C][C]0.366[/C][C]0.357824[/C][/ROW]
[ROW][C]8[/C][C]-0.173242[/C][C]-1.3307[/C][C]0.094205[/C][/ROW]
[ROW][C]9[/C][C]-0.332485[/C][C]-2.5539[/C][C]0.006628[/C][/ROW]
[ROW][C]10[/C][C]-0.284685[/C][C]-2.1867[/C][C]0.016371[/C][/ROW]
[ROW][C]11[/C][C]0.280324[/C][C]2.1532[/C][C]0.017701[/C][/ROW]
[ROW][C]12[/C][C]0.782618[/C][C]6.0114[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.347714[/C][C]2.6708[/C][C]0.004881[/C][/ROW]
[ROW][C]14[/C][C]-0.212006[/C][C]-1.6284[/C][C]0.054379[/C][/ROW]
[ROW][C]15[/C][C]-0.360674[/C][C]-2.7704[/C][C]0.003738[/C][/ROW]
[ROW][C]16[/C][C]-0.262414[/C][C]-2.0156[/C][C]0.0242[/C][/ROW]
[ROW][C]17[/C][C]0.014175[/C][C]0.1089[/C][C]0.456832[/C][/ROW]
[ROW][C]18[/C][C]0.107395[/C][C]0.8249[/C][C]0.20637[/C][/ROW]
[ROW][C]19[/C][C]0.038196[/C][C]0.2934[/C][C]0.385126[/C][/ROW]
[ROW][C]20[/C][C]-0.105335[/C][C]-0.8091[/C][C]0.210857[/C][/ROW]
[ROW][C]21[/C][C]-0.241413[/C][C]-1.8543[/C][C]0.034346[/C][/ROW]
[ROW][C]22[/C][C]-0.202684[/C][C]-1.5568[/C][C]0.062428[/C][/ROW]
[ROW][C]23[/C][C]0.196181[/C][C]1.5069[/C][C]0.068587[/C][/ROW]
[ROW][C]24[/C][C]0.563264[/C][C]4.3265[/C][C]3e-05[/C][/ROW]
[ROW][C]25[/C][C]0.266037[/C][C]2.0435[/C][C]0.02274[/C][/ROW]
[ROW][C]26[/C][C]-0.13445[/C][C]-1.0327[/C][C]0.152973[/C][/ROW]
[ROW][C]27[/C][C]-0.272508[/C][C]-2.0932[/C][C]0.020321[/C][/ROW]
[ROW][C]28[/C][C]-0.206852[/C][C]-1.5889[/C][C]0.058718[/C][/ROW]
[ROW][C]29[/C][C]-0.003883[/C][C]-0.0298[/C][C]0.488154[/C][/ROW]
[ROW][C]30[/C][C]0.06998[/C][C]0.5375[/C][C]0.296462[/C][/ROW]
[ROW][C]31[/C][C]0.036967[/C][C]0.284[/C][C]0.388721[/C][/ROW]
[ROW][C]32[/C][C]-0.066165[/C][C]-0.5082[/C][C]0.306597[/C][/ROW]
[ROW][C]33[/C][C]-0.150139[/C][C]-1.1532[/C][C]0.126732[/C][/ROW]
[ROW][C]34[/C][C]-0.129663[/C][C]-0.996[/C][C]0.161669[/C][/ROW]
[ROW][C]35[/C][C]0.109475[/C][C]0.8409[/C][C]0.2019[/C][/ROW]
[ROW][C]36[/C][C]0.361938[/C][C]2.7801[/C][C]0.00364[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=150955&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=150955&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	0.375746	2.8862	0.00272
2	-0.282137	-2.1671	0.017137
3	-0.415974	-3.1952	0.001122
4	-0.29117	-2.2365	0.014556
5	0.032422	0.249	0.402097
6	0.147808	1.1353	0.130413
7	0.047654	0.366	0.357824
8	-0.173242	-1.3307	0.094205
9	-0.332485	-2.5539	0.006628
10	-0.284685	-2.1867	0.016371
11	0.280324	2.1532	0.017701
12	0.782618	6.0114	0
13	0.347714	2.6708	0.004881
14	-0.212006	-1.6284	0.054379
15	-0.360674	-2.7704	0.003738
16	-0.262414	-2.0156	0.0242
17	0.014175	0.1089	0.456832
18	0.107395	0.8249	0.20637
19	0.038196	0.2934	0.385126
20	-0.105335	-0.8091	0.210857
21	-0.241413	-1.8543	0.034346
22	-0.202684	-1.5568	0.062428
23	0.196181	1.5069	0.068587
24	0.563264	4.3265	3e-05
25	0.266037	2.0435	0.02274
26	-0.13445	-1.0327	0.152973
27	-0.272508	-2.0932	0.020321
28	-0.206852	-1.5889	0.058718
29	-0.003883	-0.0298	0.488154
30	0.06998	0.5375	0.296462
31	0.036967	0.284	0.388721
32	-0.066165	-0.5082	0.306597
33	-0.150139	-1.1532	0.126732
34	-0.129663	-0.996	0.161669
35	0.109475	0.8409	0.2019
36	0.361938	2.7801	0.00364

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.375746	2.8862	0.00272
2	-0.492914	-3.7861	0.00018
3	-0.111508	-0.8565	0.197591
4	-0.249525	-1.9166	0.030066
5	0.076201	0.5853	0.280285
6	-0.186013	-1.4288	0.079168
7	-0.056502	-0.434	0.332935
8	-0.330966	-2.5422	0.006831
9	-0.316028	-2.4275	0.009138
10	-0.556146	-4.2718	3.6e-05
11	0.252193	1.9371	0.028761
12	0.347971	2.6728	0.004856
13	-0.189828	-1.4581	0.075059
14	-0.012655	-0.0972	0.461446
15	0.186754	1.4345	0.078356
16	0.008852	0.068	0.47301
17	-0.038518	-0.2959	0.384188
18	-0.060693	-0.4662	0.321398
19	0.05573	0.4281	0.335079
20	-0.130333	-1.0011	0.160432
21	0.085871	0.6596	0.256043
22	0.076623	0.5886	0.279204
23	-0.110361	-0.8477	0.200016
24	-0.133442	-1.025	0.154776
25	0.002898	0.0223	0.491158
26	0.083219	0.6392	0.262578
27	-0.121059	-0.9299	0.178113
28	-0.017397	-0.1336	0.447077
29	-0.016687	-0.1282	0.449222
30	0.018453	0.1417	0.443883
31	-0.033666	-0.2586	0.398425
32	0.014374	0.1104	0.45623
33	0.06363	0.4888	0.313414
34	-0.050214	-0.3857	0.350553
35	-0.12028	-0.9239	0.179654
36	0.020352	0.1563	0.438155

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.375746 & 2.8862 & 0.00272 \tabularnewline
2 & -0.492914 & -3.7861 & 0.00018 \tabularnewline
3 & -0.111508 & -0.8565 & 0.197591 \tabularnewline
4 & -0.249525 & -1.9166 & 0.030066 \tabularnewline
5 & 0.076201 & 0.5853 & 0.280285 \tabularnewline
6 & -0.186013 & -1.4288 & 0.079168 \tabularnewline
7 & -0.056502 & -0.434 & 0.332935 \tabularnewline
8 & -0.330966 & -2.5422 & 0.006831 \tabularnewline
9 & -0.316028 & -2.4275 & 0.009138 \tabularnewline
10 & -0.556146 & -4.2718 & 3.6e-05 \tabularnewline
11 & 0.252193 & 1.9371 & 0.028761 \tabularnewline
12 & 0.347971 & 2.6728 & 0.004856 \tabularnewline
13 & -0.189828 & -1.4581 & 0.075059 \tabularnewline
14 & -0.012655 & -0.0972 & 0.461446 \tabularnewline
15 & 0.186754 & 1.4345 & 0.078356 \tabularnewline
16 & 0.008852 & 0.068 & 0.47301 \tabularnewline
17 & -0.038518 & -0.2959 & 0.384188 \tabularnewline
18 & -0.060693 & -0.4662 & 0.321398 \tabularnewline
19 & 0.05573 & 0.4281 & 0.335079 \tabularnewline
20 & -0.130333 & -1.0011 & 0.160432 \tabularnewline
21 & 0.085871 & 0.6596 & 0.256043 \tabularnewline
22 & 0.076623 & 0.5886 & 0.279204 \tabularnewline
23 & -0.110361 & -0.8477 & 0.200016 \tabularnewline
24 & -0.133442 & -1.025 & 0.154776 \tabularnewline
25 & 0.002898 & 0.0223 & 0.491158 \tabularnewline
26 & 0.083219 & 0.6392 & 0.262578 \tabularnewline
27 & -0.121059 & -0.9299 & 0.178113 \tabularnewline
28 & -0.017397 & -0.1336 & 0.447077 \tabularnewline
29 & -0.016687 & -0.1282 & 0.449222 \tabularnewline
30 & 0.018453 & 0.1417 & 0.443883 \tabularnewline
31 & -0.033666 & -0.2586 & 0.398425 \tabularnewline
32 & 0.014374 & 0.1104 & 0.45623 \tabularnewline
33 & 0.06363 & 0.4888 & 0.313414 \tabularnewline
34 & -0.050214 & -0.3857 & 0.350553 \tabularnewline
35 & -0.12028 & -0.9239 & 0.179654 \tabularnewline
36 & 0.020352 & 0.1563 & 0.438155 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=150955&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]0.375746[/C][C]2.8862[/C][C]0.00272[/C][/ROW]
[ROW][C]2[/C][C]-0.492914[/C][C]-3.7861[/C][C]0.00018[/C][/ROW]
[ROW][C]3[/C][C]-0.111508[/C][C]-0.8565[/C][C]0.197591[/C][/ROW]
[ROW][C]4[/C][C]-0.249525[/C][C]-1.9166[/C][C]0.030066[/C][/ROW]
[ROW][C]5[/C][C]0.076201[/C][C]0.5853[/C][C]0.280285[/C][/ROW]
[ROW][C]6[/C][C]-0.186013[/C][C]-1.4288[/C][C]0.079168[/C][/ROW]
[ROW][C]7[/C][C]-0.056502[/C][C]-0.434[/C][C]0.332935[/C][/ROW]
[ROW][C]8[/C][C]-0.330966[/C][C]-2.5422[/C][C]0.006831[/C][/ROW]
[ROW][C]9[/C][C]-0.316028[/C][C]-2.4275[/C][C]0.009138[/C][/ROW]
[ROW][C]10[/C][C]-0.556146[/C][C]-4.2718[/C][C]3.6e-05[/C][/ROW]
[ROW][C]11[/C][C]0.252193[/C][C]1.9371[/C][C]0.028761[/C][/ROW]
[ROW][C]12[/C][C]0.347971[/C][C]2.6728[/C][C]0.004856[/C][/ROW]
[ROW][C]13[/C][C]-0.189828[/C][C]-1.4581[/C][C]0.075059[/C][/ROW]
[ROW][C]14[/C][C]-0.012655[/C][C]-0.0972[/C][C]0.461446[/C][/ROW]
[ROW][C]15[/C][C]0.186754[/C][C]1.4345[/C][C]0.078356[/C][/ROW]
[ROW][C]16[/C][C]0.008852[/C][C]0.068[/C][C]0.47301[/C][/ROW]
[ROW][C]17[/C][C]-0.038518[/C][C]-0.2959[/C][C]0.384188[/C][/ROW]
[ROW][C]18[/C][C]-0.060693[/C][C]-0.4662[/C][C]0.321398[/C][/ROW]
[ROW][C]19[/C][C]0.05573[/C][C]0.4281[/C][C]0.335079[/C][/ROW]
[ROW][C]20[/C][C]-0.130333[/C][C]-1.0011[/C][C]0.160432[/C][/ROW]
[ROW][C]21[/C][C]0.085871[/C][C]0.6596[/C][C]0.256043[/C][/ROW]
[ROW][C]22[/C][C]0.076623[/C][C]0.5886[/C][C]0.279204[/C][/ROW]
[ROW][C]23[/C][C]-0.110361[/C][C]-0.8477[/C][C]0.200016[/C][/ROW]
[ROW][C]24[/C][C]-0.133442[/C][C]-1.025[/C][C]0.154776[/C][/ROW]
[ROW][C]25[/C][C]0.002898[/C][C]0.0223[/C][C]0.491158[/C][/ROW]
[ROW][C]26[/C][C]0.083219[/C][C]0.6392[/C][C]0.262578[/C][/ROW]
[ROW][C]27[/C][C]-0.121059[/C][C]-0.9299[/C][C]0.178113[/C][/ROW]
[ROW][C]28[/C][C]-0.017397[/C][C]-0.1336[/C][C]0.447077[/C][/ROW]
[ROW][C]29[/C][C]-0.016687[/C][C]-0.1282[/C][C]0.449222[/C][/ROW]
[ROW][C]30[/C][C]0.018453[/C][C]0.1417[/C][C]0.443883[/C][/ROW]
[ROW][C]31[/C][C]-0.033666[/C][C]-0.2586[/C][C]0.398425[/C][/ROW]
[ROW][C]32[/C][C]0.014374[/C][C]0.1104[/C][C]0.45623[/C][/ROW]
[ROW][C]33[/C][C]0.06363[/C][C]0.4888[/C][C]0.313414[/C][/ROW]
[ROW][C]34[/C][C]-0.050214[/C][C]-0.3857[/C][C]0.350553[/C][/ROW]
[ROW][C]35[/C][C]-0.12028[/C][C]-0.9239[/C][C]0.179654[/C][/ROW]
[ROW][C]36[/C][C]0.020352[/C][C]0.1563[/C][C]0.438155[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=150955&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=150955&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	0.375746	2.8862	0.00272
2	-0.492914	-3.7861	0.00018
3	-0.111508	-0.8565	0.197591
4	-0.249525	-1.9166	0.030066
5	0.076201	0.5853	0.280285
6	-0.186013	-1.4288	0.079168
7	-0.056502	-0.434	0.332935
8	-0.330966	-2.5422	0.006831
9	-0.316028	-2.4275	0.009138
10	-0.556146	-4.2718	3.6e-05
11	0.252193	1.9371	0.028761
12	0.347971	2.6728	0.004856
13	-0.189828	-1.4581	0.075059
14	-0.012655	-0.0972	0.461446
15	0.186754	1.4345	0.078356
16	0.008852	0.068	0.47301
17	-0.038518	-0.2959	0.384188
18	-0.060693	-0.4662	0.321398
19	0.05573	0.4281	0.335079
20	-0.130333	-1.0011	0.160432
21	0.085871	0.6596	0.256043
22	0.076623	0.5886	0.279204
23	-0.110361	-0.8477	0.200016
24	-0.133442	-1.025	0.154776
25	0.002898	0.0223	0.491158
26	0.083219	0.6392	0.262578
27	-0.121059	-0.9299	0.178113
28	-0.017397	-0.1336	0.447077
29	-0.016687	-0.1282	0.449222
30	0.018453	0.1417	0.443883
31	-0.033666	-0.2586	0.398425
32	0.014374	0.1104	0.45623
33	0.06363	0.4888	0.313414
34	-0.050214	-0.3857	0.350553
35	-0.12028	-0.9239	0.179654
36	0.020352	0.1563	0.438155

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 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 36 ; par2 = 1 ; par3 = 1 ; 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)
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