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

Wed, 29 Dec 2010 12:52:24 +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/29/t1293627108c58flurhqvvp95i.htm/, Retrieved Fri, 09 May 2025 23:39:12 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116774, Retrieved Fri, 09 May 2025 23:39:12 +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

229

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] [] [2009-11-24 09:55:25] [fef2f8976fa1eef1b54e2cee317fe737]
-    D          [(Partial) Autocorrelation Function] [] [2009-12-18 11:14:21] [fef2f8976fa1eef1b54e2cee317fe737]
- R               [(Partial) Autocorrelation Function] [Paper: ACF] [2010-12-22 20:09:28] [29e492448d11757ae0fad5ef6e7f8e86]
-    D                [(Partial) Autocorrelation Function] [] [2010-12-29 12:52:24] [e180d4cd19004beeddc12e67012247dc] [Current]

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	2 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116774&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116774&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116774&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	'RServer@AstonUniversity' @ vre.aston.ac.uk

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.560767	5.3199	0
2	0.461969	4.3826	1.6e-05
3	0.376285	3.5698	0.000288
4	0.399723	3.7921	0.000135
5	0.323917	3.0729	0.001402
6	0.210442	1.9964	0.024455
7	0.255335	2.4223	0.008713
8	0.187219	1.7761	0.039547
9	0.210061	1.9928	0.024655
10	0.054047	0.5127	0.304695
11	0.087621	0.8312	0.204016
12	-0.064818	-0.6149	0.27008
13	-0.095318	-0.9043	0.184134
14	-0.152669	-1.4483	0.075497
15	-0.169849	-1.6113	0.055305
16	-0.119221	-1.131	0.130523
17	-0.139763	-1.3259	0.094114
18	-0.18842	-1.7875	0.038611
19	-0.284417	-2.6982	0.004162
20	-0.222369	-2.1096	0.018835
21	-0.206262	-1.9568	0.026737
22	-0.202727	-1.9232	0.028806
23	-0.254073	-2.4104	0.008986
24	-0.228585	-2.1685	0.016377
25	-0.182608	-1.7324	0.043317
26	-0.198851	-1.8865	0.031228
27	-0.22658	-2.1495	0.017138
28	-0.143215	-1.3587	0.088826
29	-0.198831	-1.8863	0.031241
30	-0.241025	-2.2866	0.012284
31	-0.203283	-1.9285	0.028472
32	-0.185347	-1.7584	0.041043
33	-0.138359	-1.3126	0.09633
34	-0.234157	-2.2214	0.014416
35	-0.20783	-1.9716	0.02586
36	-0.238558	-2.2632	0.013015

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.560767 & 5.3199 & 0 \tabularnewline
2 & 0.461969 & 4.3826 & 1.6e-05 \tabularnewline
3 & 0.376285 & 3.5698 & 0.000288 \tabularnewline
4 & 0.399723 & 3.7921 & 0.000135 \tabularnewline
5 & 0.323917 & 3.0729 & 0.001402 \tabularnewline
6 & 0.210442 & 1.9964 & 0.024455 \tabularnewline
7 & 0.255335 & 2.4223 & 0.008713 \tabularnewline
8 & 0.187219 & 1.7761 & 0.039547 \tabularnewline
9 & 0.210061 & 1.9928 & 0.024655 \tabularnewline
10 & 0.054047 & 0.5127 & 0.304695 \tabularnewline
11 & 0.087621 & 0.8312 & 0.204016 \tabularnewline
12 & -0.064818 & -0.6149 & 0.27008 \tabularnewline
13 & -0.095318 & -0.9043 & 0.184134 \tabularnewline
14 & -0.152669 & -1.4483 & 0.075497 \tabularnewline
15 & -0.169849 & -1.6113 & 0.055305 \tabularnewline
16 & -0.119221 & -1.131 & 0.130523 \tabularnewline
17 & -0.139763 & -1.3259 & 0.094114 \tabularnewline
18 & -0.18842 & -1.7875 & 0.038611 \tabularnewline
19 & -0.284417 & -2.6982 & 0.004162 \tabularnewline
20 & -0.222369 & -2.1096 & 0.018835 \tabularnewline
21 & -0.206262 & -1.9568 & 0.026737 \tabularnewline
22 & -0.202727 & -1.9232 & 0.028806 \tabularnewline
23 & -0.254073 & -2.4104 & 0.008986 \tabularnewline
24 & -0.228585 & -2.1685 & 0.016377 \tabularnewline
25 & -0.182608 & -1.7324 & 0.043317 \tabularnewline
26 & -0.198851 & -1.8865 & 0.031228 \tabularnewline
27 & -0.22658 & -2.1495 & 0.017138 \tabularnewline
28 & -0.143215 & -1.3587 & 0.088826 \tabularnewline
29 & -0.198831 & -1.8863 & 0.031241 \tabularnewline
30 & -0.241025 & -2.2866 & 0.012284 \tabularnewline
31 & -0.203283 & -1.9285 & 0.028472 \tabularnewline
32 & -0.185347 & -1.7584 & 0.041043 \tabularnewline
33 & -0.138359 & -1.3126 & 0.09633 \tabularnewline
34 & -0.234157 & -2.2214 & 0.014416 \tabularnewline
35 & -0.20783 & -1.9716 & 0.02586 \tabularnewline
36 & -0.238558 & -2.2632 & 0.013015 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116774&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]0.560767[/C][C]5.3199[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.461969[/C][C]4.3826[/C][C]1.6e-05[/C][/ROW]
[ROW][C]3[/C][C]0.376285[/C][C]3.5698[/C][C]0.000288[/C][/ROW]
[ROW][C]4[/C][C]0.399723[/C][C]3.7921[/C][C]0.000135[/C][/ROW]
[ROW][C]5[/C][C]0.323917[/C][C]3.0729[/C][C]0.001402[/C][/ROW]
[ROW][C]6[/C][C]0.210442[/C][C]1.9964[/C][C]0.024455[/C][/ROW]
[ROW][C]7[/C][C]0.255335[/C][C]2.4223[/C][C]0.008713[/C][/ROW]
[ROW][C]8[/C][C]0.187219[/C][C]1.7761[/C][C]0.039547[/C][/ROW]
[ROW][C]9[/C][C]0.210061[/C][C]1.9928[/C][C]0.024655[/C][/ROW]
[ROW][C]10[/C][C]0.054047[/C][C]0.5127[/C][C]0.304695[/C][/ROW]
[ROW][C]11[/C][C]0.087621[/C][C]0.8312[/C][C]0.204016[/C][/ROW]
[ROW][C]12[/C][C]-0.064818[/C][C]-0.6149[/C][C]0.27008[/C][/ROW]
[ROW][C]13[/C][C]-0.095318[/C][C]-0.9043[/C][C]0.184134[/C][/ROW]
[ROW][C]14[/C][C]-0.152669[/C][C]-1.4483[/C][C]0.075497[/C][/ROW]
[ROW][C]15[/C][C]-0.169849[/C][C]-1.6113[/C][C]0.055305[/C][/ROW]
[ROW][C]16[/C][C]-0.119221[/C][C]-1.131[/C][C]0.130523[/C][/ROW]
[ROW][C]17[/C][C]-0.139763[/C][C]-1.3259[/C][C]0.094114[/C][/ROW]
[ROW][C]18[/C][C]-0.18842[/C][C]-1.7875[/C][C]0.038611[/C][/ROW]
[ROW][C]19[/C][C]-0.284417[/C][C]-2.6982[/C][C]0.004162[/C][/ROW]
[ROW][C]20[/C][C]-0.222369[/C][C]-2.1096[/C][C]0.018835[/C][/ROW]
[ROW][C]21[/C][C]-0.206262[/C][C]-1.9568[/C][C]0.026737[/C][/ROW]
[ROW][C]22[/C][C]-0.202727[/C][C]-1.9232[/C][C]0.028806[/C][/ROW]
[ROW][C]23[/C][C]-0.254073[/C][C]-2.4104[/C][C]0.008986[/C][/ROW]
[ROW][C]24[/C][C]-0.228585[/C][C]-2.1685[/C][C]0.016377[/C][/ROW]
[ROW][C]25[/C][C]-0.182608[/C][C]-1.7324[/C][C]0.043317[/C][/ROW]
[ROW][C]26[/C][C]-0.198851[/C][C]-1.8865[/C][C]0.031228[/C][/ROW]
[ROW][C]27[/C][C]-0.22658[/C][C]-2.1495[/C][C]0.017138[/C][/ROW]
[ROW][C]28[/C][C]-0.143215[/C][C]-1.3587[/C][C]0.088826[/C][/ROW]
[ROW][C]29[/C][C]-0.198831[/C][C]-1.8863[/C][C]0.031241[/C][/ROW]
[ROW][C]30[/C][C]-0.241025[/C][C]-2.2866[/C][C]0.012284[/C][/ROW]
[ROW][C]31[/C][C]-0.203283[/C][C]-1.9285[/C][C]0.028472[/C][/ROW]
[ROW][C]32[/C][C]-0.185347[/C][C]-1.7584[/C][C]0.041043[/C][/ROW]
[ROW][C]33[/C][C]-0.138359[/C][C]-1.3126[/C][C]0.09633[/C][/ROW]
[ROW][C]34[/C][C]-0.234157[/C][C]-2.2214[/C][C]0.014416[/C][/ROW]
[ROW][C]35[/C][C]-0.20783[/C][C]-1.9716[/C][C]0.02586[/C][/ROW]
[ROW][C]36[/C][C]-0.238558[/C][C]-2.2632[/C][C]0.013015[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116774&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116774&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	0.560767	5.3199	0
2	0.461969	4.3826	1.6e-05
3	0.376285	3.5698	0.000288
4	0.399723	3.7921	0.000135
5	0.323917	3.0729	0.001402
6	0.210442	1.9964	0.024455
7	0.255335	2.4223	0.008713
8	0.187219	1.7761	0.039547
9	0.210061	1.9928	0.024655
10	0.054047	0.5127	0.304695
11	0.087621	0.8312	0.204016
12	-0.064818	-0.6149	0.27008
13	-0.095318	-0.9043	0.184134
14	-0.152669	-1.4483	0.075497
15	-0.169849	-1.6113	0.055305
16	-0.119221	-1.131	0.130523
17	-0.139763	-1.3259	0.094114
18	-0.18842	-1.7875	0.038611
19	-0.284417	-2.6982	0.004162
20	-0.222369	-2.1096	0.018835
21	-0.206262	-1.9568	0.026737
22	-0.202727	-1.9232	0.028806
23	-0.254073	-2.4104	0.008986
24	-0.228585	-2.1685	0.016377
25	-0.182608	-1.7324	0.043317
26	-0.198851	-1.8865	0.031228
27	-0.22658	-2.1495	0.017138
28	-0.143215	-1.3587	0.088826
29	-0.198831	-1.8863	0.031241
30	-0.241025	-2.2866	0.012284
31	-0.203283	-1.9285	0.028472
32	-0.185347	-1.7584	0.041043
33	-0.138359	-1.3126	0.09633
34	-0.234157	-2.2214	0.014416
35	-0.20783	-1.9716	0.02586
36	-0.238558	-2.2632	0.013015

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.560767	5.3199	0
2	0.215171	2.0413	0.022075
3	0.080008	0.759	0.224912
4	0.173324	1.6443	0.051802
5	0.006581	0.0624	0.475177
6	-0.104434	-0.9907	0.162232
7	0.126239	1.1976	0.117108
8	-0.052271	-0.4959	0.310593
9	0.059838	0.5677	0.285836
10	-0.161995	-1.5368	0.063922
11	0.033572	0.3185	0.375425
12	-0.22216	-2.1076	0.018924
13	-0.06534	-0.6199	0.268456
14	-0.080095	-0.7599	0.224665
15	-0.028048	-0.2661	0.39539
16	0.059598	0.5654	0.286604
17	0.053989	0.5122	0.304887
18	-0.145252	-1.378	0.085813
19	-0.100919	-0.9574	0.170466
20	0.002344	0.0222	0.491153
21	0.073979	0.7018	0.2423
22	-0.013081	-0.1241	0.450759
23	-0.029928	-0.2839	0.38856
24	-0.046865	-0.4446	0.328838
25	-0.01962	-0.1861	0.426382
26	-0.053241	-0.5051	0.307366
27	-0.079411	-0.7534	0.226599
28	0.125242	1.1881	0.118951
29	-0.157095	-1.4903	0.069817
30	-0.10856	-1.0299	0.15291
31	-0.002353	-0.0223	0.491119
32	-0.0821	-0.7789	0.21905
33	0.001309	0.0124	0.495059
34	-0.135716	-1.2875	0.100608
35	-0.039111	-0.371	0.355741
36	-0.113675	-1.0784	0.141864

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.560767 & 5.3199 & 0 \tabularnewline
2 & 0.215171 & 2.0413 & 0.022075 \tabularnewline
3 & 0.080008 & 0.759 & 0.224912 \tabularnewline
4 & 0.173324 & 1.6443 & 0.051802 \tabularnewline
5 & 0.006581 & 0.0624 & 0.475177 \tabularnewline
6 & -0.104434 & -0.9907 & 0.162232 \tabularnewline
7 & 0.126239 & 1.1976 & 0.117108 \tabularnewline
8 & -0.052271 & -0.4959 & 0.310593 \tabularnewline
9 & 0.059838 & 0.5677 & 0.285836 \tabularnewline
10 & -0.161995 & -1.5368 & 0.063922 \tabularnewline
11 & 0.033572 & 0.3185 & 0.375425 \tabularnewline
12 & -0.22216 & -2.1076 & 0.018924 \tabularnewline
13 & -0.06534 & -0.6199 & 0.268456 \tabularnewline
14 & -0.080095 & -0.7599 & 0.224665 \tabularnewline
15 & -0.028048 & -0.2661 & 0.39539 \tabularnewline
16 & 0.059598 & 0.5654 & 0.286604 \tabularnewline
17 & 0.053989 & 0.5122 & 0.304887 \tabularnewline
18 & -0.145252 & -1.378 & 0.085813 \tabularnewline
19 & -0.100919 & -0.9574 & 0.170466 \tabularnewline
20 & 0.002344 & 0.0222 & 0.491153 \tabularnewline
21 & 0.073979 & 0.7018 & 0.2423 \tabularnewline
22 & -0.013081 & -0.1241 & 0.450759 \tabularnewline
23 & -0.029928 & -0.2839 & 0.38856 \tabularnewline
24 & -0.046865 & -0.4446 & 0.328838 \tabularnewline
25 & -0.01962 & -0.1861 & 0.426382 \tabularnewline
26 & -0.053241 & -0.5051 & 0.307366 \tabularnewline
27 & -0.079411 & -0.7534 & 0.226599 \tabularnewline
28 & 0.125242 & 1.1881 & 0.118951 \tabularnewline
29 & -0.157095 & -1.4903 & 0.069817 \tabularnewline
30 & -0.10856 & -1.0299 & 0.15291 \tabularnewline
31 & -0.002353 & -0.0223 & 0.491119 \tabularnewline
32 & -0.0821 & -0.7789 & 0.21905 \tabularnewline
33 & 0.001309 & 0.0124 & 0.495059 \tabularnewline
34 & -0.135716 & -1.2875 & 0.100608 \tabularnewline
35 & -0.039111 & -0.371 & 0.355741 \tabularnewline
36 & -0.113675 & -1.0784 & 0.141864 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116774&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]0.560767[/C][C]5.3199[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.215171[/C][C]2.0413[/C][C]0.022075[/C][/ROW]
[ROW][C]3[/C][C]0.080008[/C][C]0.759[/C][C]0.224912[/C][/ROW]
[ROW][C]4[/C][C]0.173324[/C][C]1.6443[/C][C]0.051802[/C][/ROW]
[ROW][C]5[/C][C]0.006581[/C][C]0.0624[/C][C]0.475177[/C][/ROW]
[ROW][C]6[/C][C]-0.104434[/C][C]-0.9907[/C][C]0.162232[/C][/ROW]
[ROW][C]7[/C][C]0.126239[/C][C]1.1976[/C][C]0.117108[/C][/ROW]
[ROW][C]8[/C][C]-0.052271[/C][C]-0.4959[/C][C]0.310593[/C][/ROW]
[ROW][C]9[/C][C]0.059838[/C][C]0.5677[/C][C]0.285836[/C][/ROW]
[ROW][C]10[/C][C]-0.161995[/C][C]-1.5368[/C][C]0.063922[/C][/ROW]
[ROW][C]11[/C][C]0.033572[/C][C]0.3185[/C][C]0.375425[/C][/ROW]
[ROW][C]12[/C][C]-0.22216[/C][C]-2.1076[/C][C]0.018924[/C][/ROW]
[ROW][C]13[/C][C]-0.06534[/C][C]-0.6199[/C][C]0.268456[/C][/ROW]
[ROW][C]14[/C][C]-0.080095[/C][C]-0.7599[/C][C]0.224665[/C][/ROW]
[ROW][C]15[/C][C]-0.028048[/C][C]-0.2661[/C][C]0.39539[/C][/ROW]
[ROW][C]16[/C][C]0.059598[/C][C]0.5654[/C][C]0.286604[/C][/ROW]
[ROW][C]17[/C][C]0.053989[/C][C]0.5122[/C][C]0.304887[/C][/ROW]
[ROW][C]18[/C][C]-0.145252[/C][C]-1.378[/C][C]0.085813[/C][/ROW]
[ROW][C]19[/C][C]-0.100919[/C][C]-0.9574[/C][C]0.170466[/C][/ROW]
[ROW][C]20[/C][C]0.002344[/C][C]0.0222[/C][C]0.491153[/C][/ROW]
[ROW][C]21[/C][C]0.073979[/C][C]0.7018[/C][C]0.2423[/C][/ROW]
[ROW][C]22[/C][C]-0.013081[/C][C]-0.1241[/C][C]0.450759[/C][/ROW]
[ROW][C]23[/C][C]-0.029928[/C][C]-0.2839[/C][C]0.38856[/C][/ROW]
[ROW][C]24[/C][C]-0.046865[/C][C]-0.4446[/C][C]0.328838[/C][/ROW]
[ROW][C]25[/C][C]-0.01962[/C][C]-0.1861[/C][C]0.426382[/C][/ROW]
[ROW][C]26[/C][C]-0.053241[/C][C]-0.5051[/C][C]0.307366[/C][/ROW]
[ROW][C]27[/C][C]-0.079411[/C][C]-0.7534[/C][C]0.226599[/C][/ROW]
[ROW][C]28[/C][C]0.125242[/C][C]1.1881[/C][C]0.118951[/C][/ROW]
[ROW][C]29[/C][C]-0.157095[/C][C]-1.4903[/C][C]0.069817[/C][/ROW]
[ROW][C]30[/C][C]-0.10856[/C][C]-1.0299[/C][C]0.15291[/C][/ROW]
[ROW][C]31[/C][C]-0.002353[/C][C]-0.0223[/C][C]0.491119[/C][/ROW]
[ROW][C]32[/C][C]-0.0821[/C][C]-0.7789[/C][C]0.21905[/C][/ROW]
[ROW][C]33[/C][C]0.001309[/C][C]0.0124[/C][C]0.495059[/C][/ROW]
[ROW][C]34[/C][C]-0.135716[/C][C]-1.2875[/C][C]0.100608[/C][/ROW]
[ROW][C]35[/C][C]-0.039111[/C][C]-0.371[/C][C]0.355741[/C][/ROW]
[ROW][C]36[/C][C]-0.113675[/C][C]-1.0784[/C][C]0.141864[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116774&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116774&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	0.560767	5.3199	0
2	0.215171	2.0413	0.022075
3	0.080008	0.759	0.224912
4	0.173324	1.6443	0.051802
5	0.006581	0.0624	0.475177
6	-0.104434	-0.9907	0.162232
7	0.126239	1.1976	0.117108
8	-0.052271	-0.4959	0.310593
9	0.059838	0.5677	0.285836
10	-0.161995	-1.5368	0.063922
11	0.033572	0.3185	0.375425
12	-0.22216	-2.1076	0.018924
13	-0.06534	-0.6199	0.268456
14	-0.080095	-0.7599	0.224665
15	-0.028048	-0.2661	0.39539
16	0.059598	0.5654	0.286604
17	0.053989	0.5122	0.304887
18	-0.145252	-1.378	0.085813
19	-0.100919	-0.9574	0.170466
20	0.002344	0.0222	0.491153
21	0.073979	0.7018	0.2423
22	-0.013081	-0.1241	0.450759
23	-0.029928	-0.2839	0.38856
24	-0.046865	-0.4446	0.328838
25	-0.01962	-0.1861	0.426382
26	-0.053241	-0.5051	0.307366
27	-0.079411	-0.7534	0.226599
28	0.125242	1.1881	0.118951
29	-0.157095	-1.4903	0.069817
30	-0.10856	-1.0299	0.15291
31	-0.002353	-0.0223	0.491119
32	-0.0821	-0.7789	0.21905
33	0.001309	0.0124	0.495059
34	-0.135716	-1.2875	0.100608
35	-0.039111	-0.371	0.355741
36	-0.113675	-1.0784	0.141864

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 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;

Parameters (R input):

par1 = 36 ; 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