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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Sun, 07 Dec 2008 16:16:53 -0700

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/08/t1228691858y5rycn0lmkmu9ns.htm/, Retrieved Thu, 16 May 2024 14:07:44 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30340, Retrieved Thu, 16 May 2024 14:07:44 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

209

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

F     [Standard Deviation-Mean Plot] [step 1] [2008-12-06 12:33:55] [c45c87b96bbf32ffc2144fc37d767b2e]
- RMP   [(Partial) Autocorrelation Function] [acf] [2008-12-07 20:04:18] [c45c87b96bbf32ffc2144fc37d767b2e]
-   P     [(Partial) Autocorrelation Function] [acf] [2008-12-07 20:21:09] [c45c87b96bbf32ffc2144fc37d767b2e]
F   P         [(Partial) Autocorrelation Function] [acf] [2008-12-07 23:16:53] [3dc594a6c62226e1e98766c4d385bfaa] [Current]

Feedback Forum

2008-12-14 20:58:40 [Michaël De Kuyer] [reply] 
Dit is correct.
2008-12-15 20:11:46 [8e2cc0b2ef568da46d009b2f601285b2] [reply] 
De acf is correct besproken, hoewel een foutieve lambda waarde is gebruikt doordat de student een foutieve waarde had gevonden in vraag 1. Toch is de resulterende grafiek correct besproken en beoordeeld. Deze reeks is stationair en zoals de student reeds vermoed zijn er arima processen aanwezig.
2008-12-15 20:19:41 [8e2cc0b2ef568da46d009b2f601285b2] [reply] 
De student heeft correct naar de ARIMA patterns gezocht en goed besproken/toegelicht hoe deze gevonden kunnen worden. Enkel bij de SMA blijkt de student geen process te vinden terwijl er volgens mij toch 1 aanwezig is.

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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=30340&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=30340&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30340&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	0.345924	3.2817	0.000735
2	0.300215	2.8481	0.002725
3	0.342083	3.2453	0.000824
4	0.362999	3.4437	0.000437
5	0.270153	2.5629	0.00602
6	0.256336	2.4318	0.008502
7	0.227627	2.1595	0.016737
8	0.107327	1.0182	0.155658
9	0.264975	2.5138	0.006861
10	0.112258	1.065	0.144869
11	0.088282	0.8375	0.202262
12	-0.127132	-1.2061	0.115474
13	-0.000562	-0.0053	0.49788
14	0.112557	1.0678	0.144231
15	0.028051	0.2661	0.395378
16	-0.022839	-0.2167	0.414479
17	-0.015104	-0.1433	0.44319
18	0.07663	0.727	0.234564
19	-0.030163	-0.2861	0.387712
20	-0.064469	-0.6116	0.271168
21	-0.130208	-1.2353	0.109973
22	-0.097459	-0.9246	0.17883
23	0.014844	0.1408	0.444161
24	-0.139545	-1.3238	0.094454
25	-0.067211	-0.6376	0.262671
26	-0.110706	-1.0503	0.148207
27	-0.120123	-1.1396	0.128742
28	-0.115858	-1.0991	0.137321
29	-0.106312	-1.0086	0.157944
30	-0.194151	-1.8419	0.034393
31	-0.23677	-2.2462	0.013569
32	-0.020224	-0.1919	0.424142
33	-0.049447	-0.4691	0.320069
34	-0.165246	-1.5677	0.060235
35	-0.208971	-1.9825	0.025238
36	-0.072314	-0.686	0.247229

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.345924 & 3.2817 & 0.000735 \tabularnewline
2 & 0.300215 & 2.8481 & 0.002725 \tabularnewline
3 & 0.342083 & 3.2453 & 0.000824 \tabularnewline
4 & 0.362999 & 3.4437 & 0.000437 \tabularnewline
5 & 0.270153 & 2.5629 & 0.00602 \tabularnewline
6 & 0.256336 & 2.4318 & 0.008502 \tabularnewline
7 & 0.227627 & 2.1595 & 0.016737 \tabularnewline
8 & 0.107327 & 1.0182 & 0.155658 \tabularnewline
9 & 0.264975 & 2.5138 & 0.006861 \tabularnewline
10 & 0.112258 & 1.065 & 0.144869 \tabularnewline
11 & 0.088282 & 0.8375 & 0.202262 \tabularnewline
12 & -0.127132 & -1.2061 & 0.115474 \tabularnewline
13 & -0.000562 & -0.0053 & 0.49788 \tabularnewline
14 & 0.112557 & 1.0678 & 0.144231 \tabularnewline
15 & 0.028051 & 0.2661 & 0.395378 \tabularnewline
16 & -0.022839 & -0.2167 & 0.414479 \tabularnewline
17 & -0.015104 & -0.1433 & 0.44319 \tabularnewline
18 & 0.07663 & 0.727 & 0.234564 \tabularnewline
19 & -0.030163 & -0.2861 & 0.387712 \tabularnewline
20 & -0.064469 & -0.6116 & 0.271168 \tabularnewline
21 & -0.130208 & -1.2353 & 0.109973 \tabularnewline
22 & -0.097459 & -0.9246 & 0.17883 \tabularnewline
23 & 0.014844 & 0.1408 & 0.444161 \tabularnewline
24 & -0.139545 & -1.3238 & 0.094454 \tabularnewline
25 & -0.067211 & -0.6376 & 0.262671 \tabularnewline
26 & -0.110706 & -1.0503 & 0.148207 \tabularnewline
27 & -0.120123 & -1.1396 & 0.128742 \tabularnewline
28 & -0.115858 & -1.0991 & 0.137321 \tabularnewline
29 & -0.106312 & -1.0086 & 0.157944 \tabularnewline
30 & -0.194151 & -1.8419 & 0.034393 \tabularnewline
31 & -0.23677 & -2.2462 & 0.013569 \tabularnewline
32 & -0.020224 & -0.1919 & 0.424142 \tabularnewline
33 & -0.049447 & -0.4691 & 0.320069 \tabularnewline
34 & -0.165246 & -1.5677 & 0.060235 \tabularnewline
35 & -0.208971 & -1.9825 & 0.025238 \tabularnewline
36 & -0.072314 & -0.686 & 0.247229 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30340&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]0.345924[/C][C]3.2817[/C][C]0.000735[/C][/ROW]
[ROW][C]2[/C][C]0.300215[/C][C]2.8481[/C][C]0.002725[/C][/ROW]
[ROW][C]3[/C][C]0.342083[/C][C]3.2453[/C][C]0.000824[/C][/ROW]
[ROW][C]4[/C][C]0.362999[/C][C]3.4437[/C][C]0.000437[/C][/ROW]
[ROW][C]5[/C][C]0.270153[/C][C]2.5629[/C][C]0.00602[/C][/ROW]
[ROW][C]6[/C][C]0.256336[/C][C]2.4318[/C][C]0.008502[/C][/ROW]
[ROW][C]7[/C][C]0.227627[/C][C]2.1595[/C][C]0.016737[/C][/ROW]
[ROW][C]8[/C][C]0.107327[/C][C]1.0182[/C][C]0.155658[/C][/ROW]
[ROW][C]9[/C][C]0.264975[/C][C]2.5138[/C][C]0.006861[/C][/ROW]
[ROW][C]10[/C][C]0.112258[/C][C]1.065[/C][C]0.144869[/C][/ROW]
[ROW][C]11[/C][C]0.088282[/C][C]0.8375[/C][C]0.202262[/C][/ROW]
[ROW][C]12[/C][C]-0.127132[/C][C]-1.2061[/C][C]0.115474[/C][/ROW]
[ROW][C]13[/C][C]-0.000562[/C][C]-0.0053[/C][C]0.49788[/C][/ROW]
[ROW][C]14[/C][C]0.112557[/C][C]1.0678[/C][C]0.144231[/C][/ROW]
[ROW][C]15[/C][C]0.028051[/C][C]0.2661[/C][C]0.395378[/C][/ROW]
[ROW][C]16[/C][C]-0.022839[/C][C]-0.2167[/C][C]0.414479[/C][/ROW]
[ROW][C]17[/C][C]-0.015104[/C][C]-0.1433[/C][C]0.44319[/C][/ROW]
[ROW][C]18[/C][C]0.07663[/C][C]0.727[/C][C]0.234564[/C][/ROW]
[ROW][C]19[/C][C]-0.030163[/C][C]-0.2861[/C][C]0.387712[/C][/ROW]
[ROW][C]20[/C][C]-0.064469[/C][C]-0.6116[/C][C]0.271168[/C][/ROW]
[ROW][C]21[/C][C]-0.130208[/C][C]-1.2353[/C][C]0.109973[/C][/ROW]
[ROW][C]22[/C][C]-0.097459[/C][C]-0.9246[/C][C]0.17883[/C][/ROW]
[ROW][C]23[/C][C]0.014844[/C][C]0.1408[/C][C]0.444161[/C][/ROW]
[ROW][C]24[/C][C]-0.139545[/C][C]-1.3238[/C][C]0.094454[/C][/ROW]
[ROW][C]25[/C][C]-0.067211[/C][C]-0.6376[/C][C]0.262671[/C][/ROW]
[ROW][C]26[/C][C]-0.110706[/C][C]-1.0503[/C][C]0.148207[/C][/ROW]
[ROW][C]27[/C][C]-0.120123[/C][C]-1.1396[/C][C]0.128742[/C][/ROW]
[ROW][C]28[/C][C]-0.115858[/C][C]-1.0991[/C][C]0.137321[/C][/ROW]
[ROW][C]29[/C][C]-0.106312[/C][C]-1.0086[/C][C]0.157944[/C][/ROW]
[ROW][C]30[/C][C]-0.194151[/C][C]-1.8419[/C][C]0.034393[/C][/ROW]
[ROW][C]31[/C][C]-0.23677[/C][C]-2.2462[/C][C]0.013569[/C][/ROW]
[ROW][C]32[/C][C]-0.020224[/C][C]-0.1919[/C][C]0.424142[/C][/ROW]
[ROW][C]33[/C][C]-0.049447[/C][C]-0.4691[/C][C]0.320069[/C][/ROW]
[ROW][C]34[/C][C]-0.165246[/C][C]-1.5677[/C][C]0.060235[/C][/ROW]
[ROW][C]35[/C][C]-0.208971[/C][C]-1.9825[/C][C]0.025238[/C][/ROW]
[ROW][C]36[/C][C]-0.072314[/C][C]-0.686[/C][C]0.247229[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30340&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30340&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	0.345924	3.2817	0.000735
2	0.300215	2.8481	0.002725
3	0.342083	3.2453	0.000824
4	0.362999	3.4437	0.000437
5	0.270153	2.5629	0.00602
6	0.256336	2.4318	0.008502
7	0.227627	2.1595	0.016737
8	0.107327	1.0182	0.155658
9	0.264975	2.5138	0.006861
10	0.112258	1.065	0.144869
11	0.088282	0.8375	0.202262
12	-0.127132	-1.2061	0.115474
13	-0.000562	-0.0053	0.49788
14	0.112557	1.0678	0.144231
15	0.028051	0.2661	0.395378
16	-0.022839	-0.2167	0.414479
17	-0.015104	-0.1433	0.44319
18	0.07663	0.727	0.234564
19	-0.030163	-0.2861	0.387712
20	-0.064469	-0.6116	0.271168
21	-0.130208	-1.2353	0.109973
22	-0.097459	-0.9246	0.17883
23	0.014844	0.1408	0.444161
24	-0.139545	-1.3238	0.094454
25	-0.067211	-0.6376	0.262671
26	-0.110706	-1.0503	0.148207
27	-0.120123	-1.1396	0.128742
28	-0.115858	-1.0991	0.137321
29	-0.106312	-1.0086	0.157944
30	-0.194151	-1.8419	0.034393
31	-0.23677	-2.2462	0.013569
32	-0.020224	-0.1919	0.424142
33	-0.049447	-0.4691	0.320069
34	-0.165246	-1.5677	0.060235
35	-0.208971	-1.9825	0.025238
36	-0.072314	-0.686	0.247229

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.345924	3.2817	0.000735
2	0.205094	1.9457	0.027406
3	0.223624	2.1215	0.018315
4	0.204903	1.9439	0.027517
5	0.052949	0.5023	0.308336
6	0.047576	0.4513	0.326415
7	0.005643	0.0535	0.478713
8	-0.129797	-1.2314	0.110697
9	0.154192	1.4628	0.073504
10	-0.093048	-0.8827	0.189868
11	-0.031251	-0.2965	0.383777
12	-0.303639	-2.8806	0.002481
13	-0.035211	-0.334	0.369562
14	0.183858	1.7442	0.042267
15	0.064474	0.6117	0.271154
16	0.028404	0.2695	0.394094
17	0.014578	0.1383	0.445157
18	0.065861	0.6248	0.266836
19	-0.030303	-0.2875	0.387202
20	-0.167805	-1.5919	0.057453
21	-0.094361	-0.8952	0.186538
22	-0.062021	-0.5884	0.278874
23	0.10427	0.9892	0.162611
24	-0.22031	-2.09	0.019717
25	0.039678	0.3764	0.353747
26	0.079686	0.756	0.225822
27	-0.011299	-0.1072	0.457436
28	0.001038	0.0099	0.496081
29	-0.030259	-0.2871	0.387364
30	-0.008864	-0.0841	0.466586
31	-0.127537	-1.2099	0.114739
32	0.018451	0.175	0.430722
33	0.112902	1.0711	0.143499
34	-0.134805	-1.2789	0.102115
35	-0.053044	-0.5032	0.308019
36	-0.02639	-0.2504	0.401442

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.345924 & 3.2817 & 0.000735 \tabularnewline
2 & 0.205094 & 1.9457 & 0.027406 \tabularnewline
3 & 0.223624 & 2.1215 & 0.018315 \tabularnewline
4 & 0.204903 & 1.9439 & 0.027517 \tabularnewline
5 & 0.052949 & 0.5023 & 0.308336 \tabularnewline
6 & 0.047576 & 0.4513 & 0.326415 \tabularnewline
7 & 0.005643 & 0.0535 & 0.478713 \tabularnewline
8 & -0.129797 & -1.2314 & 0.110697 \tabularnewline
9 & 0.154192 & 1.4628 & 0.073504 \tabularnewline
10 & -0.093048 & -0.8827 & 0.189868 \tabularnewline
11 & -0.031251 & -0.2965 & 0.383777 \tabularnewline
12 & -0.303639 & -2.8806 & 0.002481 \tabularnewline
13 & -0.035211 & -0.334 & 0.369562 \tabularnewline
14 & 0.183858 & 1.7442 & 0.042267 \tabularnewline
15 & 0.064474 & 0.6117 & 0.271154 \tabularnewline
16 & 0.028404 & 0.2695 & 0.394094 \tabularnewline
17 & 0.014578 & 0.1383 & 0.445157 \tabularnewline
18 & 0.065861 & 0.6248 & 0.266836 \tabularnewline
19 & -0.030303 & -0.2875 & 0.387202 \tabularnewline
20 & -0.167805 & -1.5919 & 0.057453 \tabularnewline
21 & -0.094361 & -0.8952 & 0.186538 \tabularnewline
22 & -0.062021 & -0.5884 & 0.278874 \tabularnewline
23 & 0.10427 & 0.9892 & 0.162611 \tabularnewline
24 & -0.22031 & -2.09 & 0.019717 \tabularnewline
25 & 0.039678 & 0.3764 & 0.353747 \tabularnewline
26 & 0.079686 & 0.756 & 0.225822 \tabularnewline
27 & -0.011299 & -0.1072 & 0.457436 \tabularnewline
28 & 0.001038 & 0.0099 & 0.496081 \tabularnewline
29 & -0.030259 & -0.2871 & 0.387364 \tabularnewline
30 & -0.008864 & -0.0841 & 0.466586 \tabularnewline
31 & -0.127537 & -1.2099 & 0.114739 \tabularnewline
32 & 0.018451 & 0.175 & 0.430722 \tabularnewline
33 & 0.112902 & 1.0711 & 0.143499 \tabularnewline
34 & -0.134805 & -1.2789 & 0.102115 \tabularnewline
35 & -0.053044 & -0.5032 & 0.308019 \tabularnewline
36 & -0.02639 & -0.2504 & 0.401442 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30340&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]0.345924[/C][C]3.2817[/C][C]0.000735[/C][/ROW]
[ROW][C]2[/C][C]0.205094[/C][C]1.9457[/C][C]0.027406[/C][/ROW]
[ROW][C]3[/C][C]0.223624[/C][C]2.1215[/C][C]0.018315[/C][/ROW]
[ROW][C]4[/C][C]0.204903[/C][C]1.9439[/C][C]0.027517[/C][/ROW]
[ROW][C]5[/C][C]0.052949[/C][C]0.5023[/C][C]0.308336[/C][/ROW]
[ROW][C]6[/C][C]0.047576[/C][C]0.4513[/C][C]0.326415[/C][/ROW]
[ROW][C]7[/C][C]0.005643[/C][C]0.0535[/C][C]0.478713[/C][/ROW]
[ROW][C]8[/C][C]-0.129797[/C][C]-1.2314[/C][C]0.110697[/C][/ROW]
[ROW][C]9[/C][C]0.154192[/C][C]1.4628[/C][C]0.073504[/C][/ROW]
[ROW][C]10[/C][C]-0.093048[/C][C]-0.8827[/C][C]0.189868[/C][/ROW]
[ROW][C]11[/C][C]-0.031251[/C][C]-0.2965[/C][C]0.383777[/C][/ROW]
[ROW][C]12[/C][C]-0.303639[/C][C]-2.8806[/C][C]0.002481[/C][/ROW]
[ROW][C]13[/C][C]-0.035211[/C][C]-0.334[/C][C]0.369562[/C][/ROW]
[ROW][C]14[/C][C]0.183858[/C][C]1.7442[/C][C]0.042267[/C][/ROW]
[ROW][C]15[/C][C]0.064474[/C][C]0.6117[/C][C]0.271154[/C][/ROW]
[ROW][C]16[/C][C]0.028404[/C][C]0.2695[/C][C]0.394094[/C][/ROW]
[ROW][C]17[/C][C]0.014578[/C][C]0.1383[/C][C]0.445157[/C][/ROW]
[ROW][C]18[/C][C]0.065861[/C][C]0.6248[/C][C]0.266836[/C][/ROW]
[ROW][C]19[/C][C]-0.030303[/C][C]-0.2875[/C][C]0.387202[/C][/ROW]
[ROW][C]20[/C][C]-0.167805[/C][C]-1.5919[/C][C]0.057453[/C][/ROW]
[ROW][C]21[/C][C]-0.094361[/C][C]-0.8952[/C][C]0.186538[/C][/ROW]
[ROW][C]22[/C][C]-0.062021[/C][C]-0.5884[/C][C]0.278874[/C][/ROW]
[ROW][C]23[/C][C]0.10427[/C][C]0.9892[/C][C]0.162611[/C][/ROW]
[ROW][C]24[/C][C]-0.22031[/C][C]-2.09[/C][C]0.019717[/C][/ROW]
[ROW][C]25[/C][C]0.039678[/C][C]0.3764[/C][C]0.353747[/C][/ROW]
[ROW][C]26[/C][C]0.079686[/C][C]0.756[/C][C]0.225822[/C][/ROW]
[ROW][C]27[/C][C]-0.011299[/C][C]-0.1072[/C][C]0.457436[/C][/ROW]
[ROW][C]28[/C][C]0.001038[/C][C]0.0099[/C][C]0.496081[/C][/ROW]
[ROW][C]29[/C][C]-0.030259[/C][C]-0.2871[/C][C]0.387364[/C][/ROW]
[ROW][C]30[/C][C]-0.008864[/C][C]-0.0841[/C][C]0.466586[/C][/ROW]
[ROW][C]31[/C][C]-0.127537[/C][C]-1.2099[/C][C]0.114739[/C][/ROW]
[ROW][C]32[/C][C]0.018451[/C][C]0.175[/C][C]0.430722[/C][/ROW]
[ROW][C]33[/C][C]0.112902[/C][C]1.0711[/C][C]0.143499[/C][/ROW]
[ROW][C]34[/C][C]-0.134805[/C][C]-1.2789[/C][C]0.102115[/C][/ROW]
[ROW][C]35[/C][C]-0.053044[/C][C]-0.5032[/C][C]0.308019[/C][/ROW]
[ROW][C]36[/C][C]-0.02639[/C][C]-0.2504[/C][C]0.401442[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30340&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30340&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	0.345924	3.2817	0.000735
2	0.205094	1.9457	0.027406
3	0.223624	2.1215	0.018315
4	0.204903	1.9439	0.027517
5	0.052949	0.5023	0.308336
6	0.047576	0.4513	0.326415
7	0.005643	0.0535	0.478713
8	-0.129797	-1.2314	0.110697
9	0.154192	1.4628	0.073504
10	-0.093048	-0.8827	0.189868
11	-0.031251	-0.2965	0.383777
12	-0.303639	-2.8806	0.002481
13	-0.035211	-0.334	0.369562
14	0.183858	1.7442	0.042267
15	0.064474	0.6117	0.271154
16	0.028404	0.2695	0.394094
17	0.014578	0.1383	0.445157
18	0.065861	0.6248	0.266836
19	-0.030303	-0.2875	0.387202
20	-0.167805	-1.5919	0.057453
21	-0.094361	-0.8952	0.186538
22	-0.062021	-0.5884	0.278874
23	0.10427	0.9892	0.162611
24	-0.22031	-2.09	0.019717
25	0.039678	0.3764	0.353747
26	0.079686	0.756	0.225822
27	-0.011299	-0.1072	0.457436
28	0.001038	0.0099	0.496081
29	-0.030259	-0.2871	0.387364
30	-0.008864	-0.0841	0.466586
31	-0.127537	-1.2099	0.114739
32	0.018451	0.175	0.430722
33	0.112902	1.0711	0.143499
34	-0.134805	-1.2789	0.102115
35	-0.053044	-0.5032	0.308019
36	-0.02639	-0.2504	0.401442

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 36 ; par2 = -0.1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;

Parameters (R input):

par1 = 36 ; par2 = -0.1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;

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 (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='lags',ylab='ACF')
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