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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

Wed, 16 Dec 2009 12:08:43 -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/Dec/16/t12609906133xgqosgyhl5nti6.htm/, Retrieved Tue, 30 Apr 2024 13:48:21 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68546, Retrieved Tue, 30 Apr 2024 13:48:21 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

105

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]
-   PD                [(Partial) Autocorrelation Function] [koffie en thee] [2009-12-16 19:08:43] [5c2088b06970f9a7d6fea063ee8d5871] [Current]

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Dataseries X:

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Histogram

Boxplots

8.32
8.27
8.28
8.32
8.3
8.26
8.29
8.17
8.04
8
7.98
7.97
7.92
7.96
7.99
7.93
7.97
7.95
7.96
7.97
7.9
7.76
7.74
7.72
7.68
7.72
7.71
7.71
7.68
7.7
7.69
7.66
7.61
7.33
7.24
7.14

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=68546&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=68546&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68546&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	0.254125	1.5034	0.07085
2	0.093328	0.5521	0.292183
3	0.031488	0.1863	0.426649
4	-0.163515	-0.9674	0.17
5	-0.177492	-1.0501	0.150444
6	-0.170498	-1.0087	0.160025
7	-0.06984	-0.4132	0.340998
8	-0.199544	-1.1805	0.122878
9	-0.05167	-0.3057	0.380828
10	-0.03417	-0.2022	0.420484
11	0.046102	0.2727	0.393326
12	0.26671	1.5779	0.061795
13	0.280068	1.6569	0.053239
14	0.087914	0.5201	0.303132
15	-0.088117	-0.5213	0.302718
16	0.009996	0.0591	0.476591
17	-0.202139	-1.1959	0.119893
18	-0.12514	-0.7403	0.232017
19	-0.159078	-0.9411	0.176547
20	-0.131679	-0.779	0.220601
21	-0.052437	-0.3102	0.379117
22	-0.082658	-0.489	0.313943
23	0.021213	0.1255	0.450425
24	0.028267	0.1672	0.434075
25	0.189152	1.119	0.135372
26	0.211602	1.2519	0.109462
27	-0.001866	-0.011	0.495627
28	0.027534	0.1629	0.435771
29	-0.061319	-0.3628	0.359481
30	-0.136352	-0.8067	0.212653
31	-0.110023	-0.6509	0.25968
32	-0.023588	-0.1395	0.444908
33	-0.014008	-0.0829	0.467212
34	0.007634	0.0452	0.482118
35	NA	NA	NA
36	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.254125 & 1.5034 & 0.07085 \tabularnewline
2 & 0.093328 & 0.5521 & 0.292183 \tabularnewline
3 & 0.031488 & 0.1863 & 0.426649 \tabularnewline
4 & -0.163515 & -0.9674 & 0.17 \tabularnewline
5 & -0.177492 & -1.0501 & 0.150444 \tabularnewline
6 & -0.170498 & -1.0087 & 0.160025 \tabularnewline
7 & -0.06984 & -0.4132 & 0.340998 \tabularnewline
8 & -0.199544 & -1.1805 & 0.122878 \tabularnewline
9 & -0.05167 & -0.3057 & 0.380828 \tabularnewline
10 & -0.03417 & -0.2022 & 0.420484 \tabularnewline
11 & 0.046102 & 0.2727 & 0.393326 \tabularnewline
12 & 0.26671 & 1.5779 & 0.061795 \tabularnewline
13 & 0.280068 & 1.6569 & 0.053239 \tabularnewline
14 & 0.087914 & 0.5201 & 0.303132 \tabularnewline
15 & -0.088117 & -0.5213 & 0.302718 \tabularnewline
16 & 0.009996 & 0.0591 & 0.476591 \tabularnewline
17 & -0.202139 & -1.1959 & 0.119893 \tabularnewline
18 & -0.12514 & -0.7403 & 0.232017 \tabularnewline
19 & -0.159078 & -0.9411 & 0.176547 \tabularnewline
20 & -0.131679 & -0.779 & 0.220601 \tabularnewline
21 & -0.052437 & -0.3102 & 0.379117 \tabularnewline
22 & -0.082658 & -0.489 & 0.313943 \tabularnewline
23 & 0.021213 & 0.1255 & 0.450425 \tabularnewline
24 & 0.028267 & 0.1672 & 0.434075 \tabularnewline
25 & 0.189152 & 1.119 & 0.135372 \tabularnewline
26 & 0.211602 & 1.2519 & 0.109462 \tabularnewline
27 & -0.001866 & -0.011 & 0.495627 \tabularnewline
28 & 0.027534 & 0.1629 & 0.435771 \tabularnewline
29 & -0.061319 & -0.3628 & 0.359481 \tabularnewline
30 & -0.136352 & -0.8067 & 0.212653 \tabularnewline
31 & -0.110023 & -0.6509 & 0.25968 \tabularnewline
32 & -0.023588 & -0.1395 & 0.444908 \tabularnewline
33 & -0.014008 & -0.0829 & 0.467212 \tabularnewline
34 & 0.007634 & 0.0452 & 0.482118 \tabularnewline
35 & NA & NA & NA \tabularnewline
36 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68546&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]0.254125[/C][C]1.5034[/C][C]0.07085[/C][/ROW]
[ROW][C]2[/C][C]0.093328[/C][C]0.5521[/C][C]0.292183[/C][/ROW]
[ROW][C]3[/C][C]0.031488[/C][C]0.1863[/C][C]0.426649[/C][/ROW]
[ROW][C]4[/C][C]-0.163515[/C][C]-0.9674[/C][C]0.17[/C][/ROW]
[ROW][C]5[/C][C]-0.177492[/C][C]-1.0501[/C][C]0.150444[/C][/ROW]
[ROW][C]6[/C][C]-0.170498[/C][C]-1.0087[/C][C]0.160025[/C][/ROW]
[ROW][C]7[/C][C]-0.06984[/C][C]-0.4132[/C][C]0.340998[/C][/ROW]
[ROW][C]8[/C][C]-0.199544[/C][C]-1.1805[/C][C]0.122878[/C][/ROW]
[ROW][C]9[/C][C]-0.05167[/C][C]-0.3057[/C][C]0.380828[/C][/ROW]
[ROW][C]10[/C][C]-0.03417[/C][C]-0.2022[/C][C]0.420484[/C][/ROW]
[ROW][C]11[/C][C]0.046102[/C][C]0.2727[/C][C]0.393326[/C][/ROW]
[ROW][C]12[/C][C]0.26671[/C][C]1.5779[/C][C]0.061795[/C][/ROW]
[ROW][C]13[/C][C]0.280068[/C][C]1.6569[/C][C]0.053239[/C][/ROW]
[ROW][C]14[/C][C]0.087914[/C][C]0.5201[/C][C]0.303132[/C][/ROW]
[ROW][C]15[/C][C]-0.088117[/C][C]-0.5213[/C][C]0.302718[/C][/ROW]
[ROW][C]16[/C][C]0.009996[/C][C]0.0591[/C][C]0.476591[/C][/ROW]
[ROW][C]17[/C][C]-0.202139[/C][C]-1.1959[/C][C]0.119893[/C][/ROW]
[ROW][C]18[/C][C]-0.12514[/C][C]-0.7403[/C][C]0.232017[/C][/ROW]
[ROW][C]19[/C][C]-0.159078[/C][C]-0.9411[/C][C]0.176547[/C][/ROW]
[ROW][C]20[/C][C]-0.131679[/C][C]-0.779[/C][C]0.220601[/C][/ROW]
[ROW][C]21[/C][C]-0.052437[/C][C]-0.3102[/C][C]0.379117[/C][/ROW]
[ROW][C]22[/C][C]-0.082658[/C][C]-0.489[/C][C]0.313943[/C][/ROW]
[ROW][C]23[/C][C]0.021213[/C][C]0.1255[/C][C]0.450425[/C][/ROW]
[ROW][C]24[/C][C]0.028267[/C][C]0.1672[/C][C]0.434075[/C][/ROW]
[ROW][C]25[/C][C]0.189152[/C][C]1.119[/C][C]0.135372[/C][/ROW]
[ROW][C]26[/C][C]0.211602[/C][C]1.2519[/C][C]0.109462[/C][/ROW]
[ROW][C]27[/C][C]-0.001866[/C][C]-0.011[/C][C]0.495627[/C][/ROW]
[ROW][C]28[/C][C]0.027534[/C][C]0.1629[/C][C]0.435771[/C][/ROW]
[ROW][C]29[/C][C]-0.061319[/C][C]-0.3628[/C][C]0.359481[/C][/ROW]
[ROW][C]30[/C][C]-0.136352[/C][C]-0.8067[/C][C]0.212653[/C][/ROW]
[ROW][C]31[/C][C]-0.110023[/C][C]-0.6509[/C][C]0.25968[/C][/ROW]
[ROW][C]32[/C][C]-0.023588[/C][C]-0.1395[/C][C]0.444908[/C][/ROW]
[ROW][C]33[/C][C]-0.014008[/C][C]-0.0829[/C][C]0.467212[/C][/ROW]
[ROW][C]34[/C][C]0.007634[/C][C]0.0452[/C][C]0.482118[/C][/ROW]
[ROW][C]35[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]36[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68546&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68546&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	0.254125	1.5034	0.07085
2	0.093328	0.5521	0.292183
3	0.031488	0.1863	0.426649
4	-0.163515	-0.9674	0.17
5	-0.177492	-1.0501	0.150444
6	-0.170498	-1.0087	0.160025
7	-0.06984	-0.4132	0.340998
8	-0.199544	-1.1805	0.122878
9	-0.05167	-0.3057	0.380828
10	-0.03417	-0.2022	0.420484
11	0.046102	0.2727	0.393326
12	0.26671	1.5779	0.061795
13	0.280068	1.6569	0.053239
14	0.087914	0.5201	0.303132
15	-0.088117	-0.5213	0.302718
16	0.009996	0.0591	0.476591
17	-0.202139	-1.1959	0.119893
18	-0.12514	-0.7403	0.232017
19	-0.159078	-0.9411	0.176547
20	-0.131679	-0.779	0.220601
21	-0.052437	-0.3102	0.379117
22	-0.082658	-0.489	0.313943
23	0.021213	0.1255	0.450425
24	0.028267	0.1672	0.434075
25	0.189152	1.119	0.135372
26	0.211602	1.2519	0.109462
27	-0.001866	-0.011	0.495627
28	0.027534	0.1629	0.435771
29	-0.061319	-0.3628	0.359481
30	-0.136352	-0.8067	0.212653
31	-0.110023	-0.6509	0.25968
32	-0.023588	-0.1395	0.444908
33	-0.014008	-0.0829	0.467212
34	0.007634	0.0452	0.482118
35	NA	NA	NA
36	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.254125	1.5034	0.07085
2	0.030733	0.1818	0.428387
3	0.000738	0.0044	0.498271
4	-0.186519	-1.1035	0.138679
5	-0.105646	-0.625	0.268008
6	-0.093377	-0.5524	0.292085
7	0.019632	0.1161	0.4541
8	-0.212895	-1.2595	0.108091
9	0.006093	0.036	0.485725
10	-0.073834	-0.4368	0.332466
11	0.061255	0.3624	0.35962
12	0.200055	1.1835	0.122286
13	0.161875	0.9577	0.1724
14	-0.104538	-0.6185	0.27014
15	-0.161559	-0.9558	0.172866
16	0.084238	0.4984	0.310675
17	-0.11014	-0.6516	0.259459
18	0.025786	0.1526	0.439813
19	-0.173937	-1.029	0.155264
20	-0.0127	-0.0751	0.470268
21	0.00488	0.0289	0.488566
22	-0.043725	-0.2587	0.398699
23	-0.061152	-0.3618	0.359845
24	-0.058945	-0.3487	0.364694
25	0.023332	0.138	0.445503
26	0.14197	0.8399	0.203331
27	-0.11175	-0.6611	0.256431
28	0.000608	0.0036	0.498575
29	-0.066008	-0.3905	0.349263
30	-0.037507	-0.2219	0.412843
31	0.039723	0.235	0.407788
32	0.038382	0.2271	0.410844
33	0.009207	0.0545	0.478437
34	-0.013582	-0.0804	0.468208
35	NA	NA	NA
36	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.254125 & 1.5034 & 0.07085 \tabularnewline
2 & 0.030733 & 0.1818 & 0.428387 \tabularnewline
3 & 0.000738 & 0.0044 & 0.498271 \tabularnewline
4 & -0.186519 & -1.1035 & 0.138679 \tabularnewline
5 & -0.105646 & -0.625 & 0.268008 \tabularnewline
6 & -0.093377 & -0.5524 & 0.292085 \tabularnewline
7 & 0.019632 & 0.1161 & 0.4541 \tabularnewline
8 & -0.212895 & -1.2595 & 0.108091 \tabularnewline
9 & 0.006093 & 0.036 & 0.485725 \tabularnewline
10 & -0.073834 & -0.4368 & 0.332466 \tabularnewline
11 & 0.061255 & 0.3624 & 0.35962 \tabularnewline
12 & 0.200055 & 1.1835 & 0.122286 \tabularnewline
13 & 0.161875 & 0.9577 & 0.1724 \tabularnewline
14 & -0.104538 & -0.6185 & 0.27014 \tabularnewline
15 & -0.161559 & -0.9558 & 0.172866 \tabularnewline
16 & 0.084238 & 0.4984 & 0.310675 \tabularnewline
17 & -0.11014 & -0.6516 & 0.259459 \tabularnewline
18 & 0.025786 & 0.1526 & 0.439813 \tabularnewline
19 & -0.173937 & -1.029 & 0.155264 \tabularnewline
20 & -0.0127 & -0.0751 & 0.470268 \tabularnewline
21 & 0.00488 & 0.0289 & 0.488566 \tabularnewline
22 & -0.043725 & -0.2587 & 0.398699 \tabularnewline
23 & -0.061152 & -0.3618 & 0.359845 \tabularnewline
24 & -0.058945 & -0.3487 & 0.364694 \tabularnewline
25 & 0.023332 & 0.138 & 0.445503 \tabularnewline
26 & 0.14197 & 0.8399 & 0.203331 \tabularnewline
27 & -0.11175 & -0.6611 & 0.256431 \tabularnewline
28 & 0.000608 & 0.0036 & 0.498575 \tabularnewline
29 & -0.066008 & -0.3905 & 0.349263 \tabularnewline
30 & -0.037507 & -0.2219 & 0.412843 \tabularnewline
31 & 0.039723 & 0.235 & 0.407788 \tabularnewline
32 & 0.038382 & 0.2271 & 0.410844 \tabularnewline
33 & 0.009207 & 0.0545 & 0.478437 \tabularnewline
34 & -0.013582 & -0.0804 & 0.468208 \tabularnewline
35 & NA & NA & NA \tabularnewline
36 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68546&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]0.254125[/C][C]1.5034[/C][C]0.07085[/C][/ROW]
[ROW][C]2[/C][C]0.030733[/C][C]0.1818[/C][C]0.428387[/C][/ROW]
[ROW][C]3[/C][C]0.000738[/C][C]0.0044[/C][C]0.498271[/C][/ROW]
[ROW][C]4[/C][C]-0.186519[/C][C]-1.1035[/C][C]0.138679[/C][/ROW]
[ROW][C]5[/C][C]-0.105646[/C][C]-0.625[/C][C]0.268008[/C][/ROW]
[ROW][C]6[/C][C]-0.093377[/C][C]-0.5524[/C][C]0.292085[/C][/ROW]
[ROW][C]7[/C][C]0.019632[/C][C]0.1161[/C][C]0.4541[/C][/ROW]
[ROW][C]8[/C][C]-0.212895[/C][C]-1.2595[/C][C]0.108091[/C][/ROW]
[ROW][C]9[/C][C]0.006093[/C][C]0.036[/C][C]0.485725[/C][/ROW]
[ROW][C]10[/C][C]-0.073834[/C][C]-0.4368[/C][C]0.332466[/C][/ROW]
[ROW][C]11[/C][C]0.061255[/C][C]0.3624[/C][C]0.35962[/C][/ROW]
[ROW][C]12[/C][C]0.200055[/C][C]1.1835[/C][C]0.122286[/C][/ROW]
[ROW][C]13[/C][C]0.161875[/C][C]0.9577[/C][C]0.1724[/C][/ROW]
[ROW][C]14[/C][C]-0.104538[/C][C]-0.6185[/C][C]0.27014[/C][/ROW]
[ROW][C]15[/C][C]-0.161559[/C][C]-0.9558[/C][C]0.172866[/C][/ROW]
[ROW][C]16[/C][C]0.084238[/C][C]0.4984[/C][C]0.310675[/C][/ROW]
[ROW][C]17[/C][C]-0.11014[/C][C]-0.6516[/C][C]0.259459[/C][/ROW]
[ROW][C]18[/C][C]0.025786[/C][C]0.1526[/C][C]0.439813[/C][/ROW]
[ROW][C]19[/C][C]-0.173937[/C][C]-1.029[/C][C]0.155264[/C][/ROW]
[ROW][C]20[/C][C]-0.0127[/C][C]-0.0751[/C][C]0.470268[/C][/ROW]
[ROW][C]21[/C][C]0.00488[/C][C]0.0289[/C][C]0.488566[/C][/ROW]
[ROW][C]22[/C][C]-0.043725[/C][C]-0.2587[/C][C]0.398699[/C][/ROW]
[ROW][C]23[/C][C]-0.061152[/C][C]-0.3618[/C][C]0.359845[/C][/ROW]
[ROW][C]24[/C][C]-0.058945[/C][C]-0.3487[/C][C]0.364694[/C][/ROW]
[ROW][C]25[/C][C]0.023332[/C][C]0.138[/C][C]0.445503[/C][/ROW]
[ROW][C]26[/C][C]0.14197[/C][C]0.8399[/C][C]0.203331[/C][/ROW]
[ROW][C]27[/C][C]-0.11175[/C][C]-0.6611[/C][C]0.256431[/C][/ROW]
[ROW][C]28[/C][C]0.000608[/C][C]0.0036[/C][C]0.498575[/C][/ROW]
[ROW][C]29[/C][C]-0.066008[/C][C]-0.3905[/C][C]0.349263[/C][/ROW]
[ROW][C]30[/C][C]-0.037507[/C][C]-0.2219[/C][C]0.412843[/C][/ROW]
[ROW][C]31[/C][C]0.039723[/C][C]0.235[/C][C]0.407788[/C][/ROW]
[ROW][C]32[/C][C]0.038382[/C][C]0.2271[/C][C]0.410844[/C][/ROW]
[ROW][C]33[/C][C]0.009207[/C][C]0.0545[/C][C]0.478437[/C][/ROW]
[ROW][C]34[/C][C]-0.013582[/C][C]-0.0804[/C][C]0.468208[/C][/ROW]
[ROW][C]35[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]36[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68546&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68546&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	0.254125	1.5034	0.07085
2	0.030733	0.1818	0.428387
3	0.000738	0.0044	0.498271
4	-0.186519	-1.1035	0.138679
5	-0.105646	-0.625	0.268008
6	-0.093377	-0.5524	0.292085
7	0.019632	0.1161	0.4541
8	-0.212895	-1.2595	0.108091
9	0.006093	0.036	0.485725
10	-0.073834	-0.4368	0.332466
11	0.061255	0.3624	0.35962
12	0.200055	1.1835	0.122286
13	0.161875	0.9577	0.1724
14	-0.104538	-0.6185	0.27014
15	-0.161559	-0.9558	0.172866
16	0.084238	0.4984	0.310675
17	-0.11014	-0.6516	0.259459
18	0.025786	0.1526	0.439813
19	-0.173937	-1.029	0.155264
20	-0.0127	-0.0751	0.470268
21	0.00488	0.0289	0.488566
22	-0.043725	-0.2587	0.398699
23	-0.061152	-0.3618	0.359845
24	-0.058945	-0.3487	0.364694
25	0.023332	0.138	0.445503
26	0.14197	0.8399	0.203331
27	-0.11175	-0.6611	0.256431
28	0.000608	0.0036	0.498575
29	-0.066008	-0.3905	0.349263
30	-0.037507	-0.2219	0.412843
31	0.039723	0.235	0.407788
32	0.038382	0.2271	0.410844
33	0.009207	0.0545	0.478437
34	-0.013582	-0.0804	0.468208
35	NA	NA	NA
36	NA	NA	NA

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 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;

Parameters (R input):

par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; 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