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 12:55:17 +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/t129362720488qolyitvomk06r.htm/, Retrieved Sat, 10 May 2025 00:51:49 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116775, Retrieved Sat, 10 May 2025 00:51:49 +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

284

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]
-   PD                [(Partial) Autocorrelation Function] [] [2010-12-29 12:55:17] [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	'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116775&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116775&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116775&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	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.515895	-4.527	1.1e-05
2	0.158576	1.3915	0.084041
3	-0.161575	-1.4178	0.080139
4	0.095075	0.8343	0.203352
5	-0.046465	-0.4077	0.342302
6	-0.074434	-0.6532	0.257801
7	0.198787	1.7444	0.042544
8	-0.170806	-1.4988	0.069005
9	0.196178	1.7215	0.044592
10	-0.27953	-2.4529	0.008217
11	0.441717	3.8761	0.000111
12	-0.462379	-4.0574	5.9e-05
13	0.147046	1.2903	0.1004
14	-0.030961	-0.2717	0.393296
15	0.046583	0.4088	0.341923
16	-0.053914	-0.4731	0.318741
17	0.061148	0.5366	0.296555
18	0.081545	0.7156	0.238214
19	-0.17395	-1.5264	0.065503
20	0.131123	1.1506	0.12673
21	-0.239711	-2.1035	0.019346
22	0.298578	2.62	0.005294
23	-0.186112	-1.6331	0.053263
24	0.103732	0.9102	0.182767
25	-0.022009	-0.1931	0.423683
26	0.010396	0.0912	0.463775
27	-0.059022	-0.5179	0.303
28	0.055211	0.4845	0.314711
29	0.024409	0.2142	0.415483
30	-0.119472	-1.0484	0.148876
31	0.206933	1.8158	0.036645
32	-0.242982	-2.1322	0.018091
33	0.251024	2.2027	0.015303
34	-0.17809	-1.5627	0.061108
35	0.083004	0.7284	0.234303
36	-0.097995	-0.8599	0.196255

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.515895 & -4.527 & 1.1e-05 \tabularnewline
2 & 0.158576 & 1.3915 & 0.084041 \tabularnewline
3 & -0.161575 & -1.4178 & 0.080139 \tabularnewline
4 & 0.095075 & 0.8343 & 0.203352 \tabularnewline
5 & -0.046465 & -0.4077 & 0.342302 \tabularnewline
6 & -0.074434 & -0.6532 & 0.257801 \tabularnewline
7 & 0.198787 & 1.7444 & 0.042544 \tabularnewline
8 & -0.170806 & -1.4988 & 0.069005 \tabularnewline
9 & 0.196178 & 1.7215 & 0.044592 \tabularnewline
10 & -0.27953 & -2.4529 & 0.008217 \tabularnewline
11 & 0.441717 & 3.8761 & 0.000111 \tabularnewline
12 & -0.462379 & -4.0574 & 5.9e-05 \tabularnewline
13 & 0.147046 & 1.2903 & 0.1004 \tabularnewline
14 & -0.030961 & -0.2717 & 0.393296 \tabularnewline
15 & 0.046583 & 0.4088 & 0.341923 \tabularnewline
16 & -0.053914 & -0.4731 & 0.318741 \tabularnewline
17 & 0.061148 & 0.5366 & 0.296555 \tabularnewline
18 & 0.081545 & 0.7156 & 0.238214 \tabularnewline
19 & -0.17395 & -1.5264 & 0.065503 \tabularnewline
20 & 0.131123 & 1.1506 & 0.12673 \tabularnewline
21 & -0.239711 & -2.1035 & 0.019346 \tabularnewline
22 & 0.298578 & 2.62 & 0.005294 \tabularnewline
23 & -0.186112 & -1.6331 & 0.053263 \tabularnewline
24 & 0.103732 & 0.9102 & 0.182767 \tabularnewline
25 & -0.022009 & -0.1931 & 0.423683 \tabularnewline
26 & 0.010396 & 0.0912 & 0.463775 \tabularnewline
27 & -0.059022 & -0.5179 & 0.303 \tabularnewline
28 & 0.055211 & 0.4845 & 0.314711 \tabularnewline
29 & 0.024409 & 0.2142 & 0.415483 \tabularnewline
30 & -0.119472 & -1.0484 & 0.148876 \tabularnewline
31 & 0.206933 & 1.8158 & 0.036645 \tabularnewline
32 & -0.242982 & -2.1322 & 0.018091 \tabularnewline
33 & 0.251024 & 2.2027 & 0.015303 \tabularnewline
34 & -0.17809 & -1.5627 & 0.061108 \tabularnewline
35 & 0.083004 & 0.7284 & 0.234303 \tabularnewline
36 & -0.097995 & -0.8599 & 0.196255 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116775&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]-0.515895[/C][C]-4.527[/C][C]1.1e-05[/C][/ROW]
[ROW][C]2[/C][C]0.158576[/C][C]1.3915[/C][C]0.084041[/C][/ROW]
[ROW][C]3[/C][C]-0.161575[/C][C]-1.4178[/C][C]0.080139[/C][/ROW]
[ROW][C]4[/C][C]0.095075[/C][C]0.8343[/C][C]0.203352[/C][/ROW]
[ROW][C]5[/C][C]-0.046465[/C][C]-0.4077[/C][C]0.342302[/C][/ROW]
[ROW][C]6[/C][C]-0.074434[/C][C]-0.6532[/C][C]0.257801[/C][/ROW]
[ROW][C]7[/C][C]0.198787[/C][C]1.7444[/C][C]0.042544[/C][/ROW]
[ROW][C]8[/C][C]-0.170806[/C][C]-1.4988[/C][C]0.069005[/C][/ROW]
[ROW][C]9[/C][C]0.196178[/C][C]1.7215[/C][C]0.044592[/C][/ROW]
[ROW][C]10[/C][C]-0.27953[/C][C]-2.4529[/C][C]0.008217[/C][/ROW]
[ROW][C]11[/C][C]0.441717[/C][C]3.8761[/C][C]0.000111[/C][/ROW]
[ROW][C]12[/C][C]-0.462379[/C][C]-4.0574[/C][C]5.9e-05[/C][/ROW]
[ROW][C]13[/C][C]0.147046[/C][C]1.2903[/C][C]0.1004[/C][/ROW]
[ROW][C]14[/C][C]-0.030961[/C][C]-0.2717[/C][C]0.393296[/C][/ROW]
[ROW][C]15[/C][C]0.046583[/C][C]0.4088[/C][C]0.341923[/C][/ROW]
[ROW][C]16[/C][C]-0.053914[/C][C]-0.4731[/C][C]0.318741[/C][/ROW]
[ROW][C]17[/C][C]0.061148[/C][C]0.5366[/C][C]0.296555[/C][/ROW]
[ROW][C]18[/C][C]0.081545[/C][C]0.7156[/C][C]0.238214[/C][/ROW]
[ROW][C]19[/C][C]-0.17395[/C][C]-1.5264[/C][C]0.065503[/C][/ROW]
[ROW][C]20[/C][C]0.131123[/C][C]1.1506[/C][C]0.12673[/C][/ROW]
[ROW][C]21[/C][C]-0.239711[/C][C]-2.1035[/C][C]0.019346[/C][/ROW]
[ROW][C]22[/C][C]0.298578[/C][C]2.62[/C][C]0.005294[/C][/ROW]
[ROW][C]23[/C][C]-0.186112[/C][C]-1.6331[/C][C]0.053263[/C][/ROW]
[ROW][C]24[/C][C]0.103732[/C][C]0.9102[/C][C]0.182767[/C][/ROW]
[ROW][C]25[/C][C]-0.022009[/C][C]-0.1931[/C][C]0.423683[/C][/ROW]
[ROW][C]26[/C][C]0.010396[/C][C]0.0912[/C][C]0.463775[/C][/ROW]
[ROW][C]27[/C][C]-0.059022[/C][C]-0.5179[/C][C]0.303[/C][/ROW]
[ROW][C]28[/C][C]0.055211[/C][C]0.4845[/C][C]0.314711[/C][/ROW]
[ROW][C]29[/C][C]0.024409[/C][C]0.2142[/C][C]0.415483[/C][/ROW]
[ROW][C]30[/C][C]-0.119472[/C][C]-1.0484[/C][C]0.148876[/C][/ROW]
[ROW][C]31[/C][C]0.206933[/C][C]1.8158[/C][C]0.036645[/C][/ROW]
[ROW][C]32[/C][C]-0.242982[/C][C]-2.1322[/C][C]0.018091[/C][/ROW]
[ROW][C]33[/C][C]0.251024[/C][C]2.2027[/C][C]0.015303[/C][/ROW]
[ROW][C]34[/C][C]-0.17809[/C][C]-1.5627[/C][C]0.061108[/C][/ROW]
[ROW][C]35[/C][C]0.083004[/C][C]0.7284[/C][C]0.234303[/C][/ROW]
[ROW][C]36[/C][C]-0.097995[/C][C]-0.8599[/C][C]0.196255[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116775&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116775&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	-0.515895	-4.527	1.1e-05
2	0.158576	1.3915	0.084041
3	-0.161575	-1.4178	0.080139
4	0.095075	0.8343	0.203352
5	-0.046465	-0.4077	0.342302
6	-0.074434	-0.6532	0.257801
7	0.198787	1.7444	0.042544
8	-0.170806	-1.4988	0.069005
9	0.196178	1.7215	0.044592
10	-0.27953	-2.4529	0.008217
11	0.441717	3.8761	0.000111
12	-0.462379	-4.0574	5.9e-05
13	0.147046	1.2903	0.1004
14	-0.030961	-0.2717	0.393296
15	0.046583	0.4088	0.341923
16	-0.053914	-0.4731	0.318741
17	0.061148	0.5366	0.296555
18	0.081545	0.7156	0.238214
19	-0.17395	-1.5264	0.065503
20	0.131123	1.1506	0.12673
21	-0.239711	-2.1035	0.019346
22	0.298578	2.62	0.005294
23	-0.186112	-1.6331	0.053263
24	0.103732	0.9102	0.182767
25	-0.022009	-0.1931	0.423683
26	0.010396	0.0912	0.463775
27	-0.059022	-0.5179	0.303
28	0.055211	0.4845	0.314711
29	0.024409	0.2142	0.415483
30	-0.119472	-1.0484	0.148876
31	0.206933	1.8158	0.036645
32	-0.242982	-2.1322	0.018091
33	0.251024	2.2027	0.015303
34	-0.17809	-1.5627	0.061108
35	0.083004	0.7284	0.234303
36	-0.097995	-0.8599	0.196255

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.515895	-4.527	1.1e-05
2	-0.146586	-1.2863	0.101099
3	-0.199695	-1.7523	0.04185
4	-0.096127	-0.8435	0.200777
5	-0.059967	-0.5262	0.300128
6	-0.190562	-1.6722	0.049275
7	0.099665	0.8746	0.192266
8	-0.02995	-0.2628	0.396701
9	0.130671	1.1466	0.127543
10	-0.128667	-1.129	0.131191
11	0.348482	3.0579	0.001532
12	-0.133622	-1.1725	0.122301
13	-0.182912	-1.605	0.056289
14	-0.063438	-0.5567	0.289685
15	-0.061901	-0.5432	0.294288
16	-0.169691	-1.489	0.070282
17	0.083715	0.7346	0.232409
18	0.011319	0.0993	0.460571
19	-0.002494	-0.0219	0.4913
20	0.011967	0.105	0.45832
21	-0.129763	-1.1387	0.129187
22	-0.025197	-0.2211	0.412799
23	0.190591	1.6724	0.049249
24	-0.015126	-0.1327	0.447376
25	-0.025014	-0.2195	0.413422
26	0.037467	0.3288	0.371612
27	-0.066329	-0.582	0.281121
28	-0.019763	-0.1734	0.431387
29	0.070932	0.6224	0.267749
30	-0.034654	-0.3041	0.38094
31	0.14656	1.2861	0.101138
32	-0.051269	-0.4499	0.32703
33	-0.024484	-0.2148	0.415228
34	-0.009631	-0.0845	0.466434
35	0.057366	0.5034	0.308065
36	-0.140756	-1.2351	0.110268

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.515895 & -4.527 & 1.1e-05 \tabularnewline
2 & -0.146586 & -1.2863 & 0.101099 \tabularnewline
3 & -0.199695 & -1.7523 & 0.04185 \tabularnewline
4 & -0.096127 & -0.8435 & 0.200777 \tabularnewline
5 & -0.059967 & -0.5262 & 0.300128 \tabularnewline
6 & -0.190562 & -1.6722 & 0.049275 \tabularnewline
7 & 0.099665 & 0.8746 & 0.192266 \tabularnewline
8 & -0.02995 & -0.2628 & 0.396701 \tabularnewline
9 & 0.130671 & 1.1466 & 0.127543 \tabularnewline
10 & -0.128667 & -1.129 & 0.131191 \tabularnewline
11 & 0.348482 & 3.0579 & 0.001532 \tabularnewline
12 & -0.133622 & -1.1725 & 0.122301 \tabularnewline
13 & -0.182912 & -1.605 & 0.056289 \tabularnewline
14 & -0.063438 & -0.5567 & 0.289685 \tabularnewline
15 & -0.061901 & -0.5432 & 0.294288 \tabularnewline
16 & -0.169691 & -1.489 & 0.070282 \tabularnewline
17 & 0.083715 & 0.7346 & 0.232409 \tabularnewline
18 & 0.011319 & 0.0993 & 0.460571 \tabularnewline
19 & -0.002494 & -0.0219 & 0.4913 \tabularnewline
20 & 0.011967 & 0.105 & 0.45832 \tabularnewline
21 & -0.129763 & -1.1387 & 0.129187 \tabularnewline
22 & -0.025197 & -0.2211 & 0.412799 \tabularnewline
23 & 0.190591 & 1.6724 & 0.049249 \tabularnewline
24 & -0.015126 & -0.1327 & 0.447376 \tabularnewline
25 & -0.025014 & -0.2195 & 0.413422 \tabularnewline
26 & 0.037467 & 0.3288 & 0.371612 \tabularnewline
27 & -0.066329 & -0.582 & 0.281121 \tabularnewline
28 & -0.019763 & -0.1734 & 0.431387 \tabularnewline
29 & 0.070932 & 0.6224 & 0.267749 \tabularnewline
30 & -0.034654 & -0.3041 & 0.38094 \tabularnewline
31 & 0.14656 & 1.2861 & 0.101138 \tabularnewline
32 & -0.051269 & -0.4499 & 0.32703 \tabularnewline
33 & -0.024484 & -0.2148 & 0.415228 \tabularnewline
34 & -0.009631 & -0.0845 & 0.466434 \tabularnewline
35 & 0.057366 & 0.5034 & 0.308065 \tabularnewline
36 & -0.140756 & -1.2351 & 0.110268 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116775&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]-0.515895[/C][C]-4.527[/C][C]1.1e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.146586[/C][C]-1.2863[/C][C]0.101099[/C][/ROW]
[ROW][C]3[/C][C]-0.199695[/C][C]-1.7523[/C][C]0.04185[/C][/ROW]
[ROW][C]4[/C][C]-0.096127[/C][C]-0.8435[/C][C]0.200777[/C][/ROW]
[ROW][C]5[/C][C]-0.059967[/C][C]-0.5262[/C][C]0.300128[/C][/ROW]
[ROW][C]6[/C][C]-0.190562[/C][C]-1.6722[/C][C]0.049275[/C][/ROW]
[ROW][C]7[/C][C]0.099665[/C][C]0.8746[/C][C]0.192266[/C][/ROW]
[ROW][C]8[/C][C]-0.02995[/C][C]-0.2628[/C][C]0.396701[/C][/ROW]
[ROW][C]9[/C][C]0.130671[/C][C]1.1466[/C][C]0.127543[/C][/ROW]
[ROW][C]10[/C][C]-0.128667[/C][C]-1.129[/C][C]0.131191[/C][/ROW]
[ROW][C]11[/C][C]0.348482[/C][C]3.0579[/C][C]0.001532[/C][/ROW]
[ROW][C]12[/C][C]-0.133622[/C][C]-1.1725[/C][C]0.122301[/C][/ROW]
[ROW][C]13[/C][C]-0.182912[/C][C]-1.605[/C][C]0.056289[/C][/ROW]
[ROW][C]14[/C][C]-0.063438[/C][C]-0.5567[/C][C]0.289685[/C][/ROW]
[ROW][C]15[/C][C]-0.061901[/C][C]-0.5432[/C][C]0.294288[/C][/ROW]
[ROW][C]16[/C][C]-0.169691[/C][C]-1.489[/C][C]0.070282[/C][/ROW]
[ROW][C]17[/C][C]0.083715[/C][C]0.7346[/C][C]0.232409[/C][/ROW]
[ROW][C]18[/C][C]0.011319[/C][C]0.0993[/C][C]0.460571[/C][/ROW]
[ROW][C]19[/C][C]-0.002494[/C][C]-0.0219[/C][C]0.4913[/C][/ROW]
[ROW][C]20[/C][C]0.011967[/C][C]0.105[/C][C]0.45832[/C][/ROW]
[ROW][C]21[/C][C]-0.129763[/C][C]-1.1387[/C][C]0.129187[/C][/ROW]
[ROW][C]22[/C][C]-0.025197[/C][C]-0.2211[/C][C]0.412799[/C][/ROW]
[ROW][C]23[/C][C]0.190591[/C][C]1.6724[/C][C]0.049249[/C][/ROW]
[ROW][C]24[/C][C]-0.015126[/C][C]-0.1327[/C][C]0.447376[/C][/ROW]
[ROW][C]25[/C][C]-0.025014[/C][C]-0.2195[/C][C]0.413422[/C][/ROW]
[ROW][C]26[/C][C]0.037467[/C][C]0.3288[/C][C]0.371612[/C][/ROW]
[ROW][C]27[/C][C]-0.066329[/C][C]-0.582[/C][C]0.281121[/C][/ROW]
[ROW][C]28[/C][C]-0.019763[/C][C]-0.1734[/C][C]0.431387[/C][/ROW]
[ROW][C]29[/C][C]0.070932[/C][C]0.6224[/C][C]0.267749[/C][/ROW]
[ROW][C]30[/C][C]-0.034654[/C][C]-0.3041[/C][C]0.38094[/C][/ROW]
[ROW][C]31[/C][C]0.14656[/C][C]1.2861[/C][C]0.101138[/C][/ROW]
[ROW][C]32[/C][C]-0.051269[/C][C]-0.4499[/C][C]0.32703[/C][/ROW]
[ROW][C]33[/C][C]-0.024484[/C][C]-0.2148[/C][C]0.415228[/C][/ROW]
[ROW][C]34[/C][C]-0.009631[/C][C]-0.0845[/C][C]0.466434[/C][/ROW]
[ROW][C]35[/C][C]0.057366[/C][C]0.5034[/C][C]0.308065[/C][/ROW]
[ROW][C]36[/C][C]-0.140756[/C][C]-1.2351[/C][C]0.110268[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116775&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116775&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	-0.515895	-4.527	1.1e-05
2	-0.146586	-1.2863	0.101099
3	-0.199695	-1.7523	0.04185
4	-0.096127	-0.8435	0.200777
5	-0.059967	-0.5262	0.300128
6	-0.190562	-1.6722	0.049275
7	0.099665	0.8746	0.192266
8	-0.02995	-0.2628	0.396701
9	0.130671	1.1466	0.127543
10	-0.128667	-1.129	0.131191
11	0.348482	3.0579	0.001532
12	-0.133622	-1.1725	0.122301
13	-0.182912	-1.605	0.056289
14	-0.063438	-0.5567	0.289685
15	-0.061901	-0.5432	0.294288
16	-0.169691	-1.489	0.070282
17	0.083715	0.7346	0.232409
18	0.011319	0.0993	0.460571
19	-0.002494	-0.0219	0.4913
20	0.011967	0.105	0.45832
21	-0.129763	-1.1387	0.129187
22	-0.025197	-0.2211	0.412799
23	0.190591	1.6724	0.049249
24	-0.015126	-0.1327	0.447376
25	-0.025014	-0.2195	0.413422
26	0.037467	0.3288	0.371612
27	-0.066329	-0.582	0.281121
28	-0.019763	-0.1734	0.431387
29	0.070932	0.6224	0.267749
30	-0.034654	-0.3041	0.38094
31	0.14656	1.2861	0.101138
32	-0.051269	-0.4499	0.32703
33	-0.024484	-0.2148	0.415228
34	-0.009631	-0.0845	0.466434
35	0.057366	0.5034	0.308065
36	-0.140756	-1.2351	0.110268

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 = 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 ; 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