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Author

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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Mon, 08 Dec 2008 07:09:16 -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/2008/Dec/08/t1228745393m45o8u7o89xrst2.htm/, Retrieved Thu, 16 May 2024 16:42:23 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30501, Retrieved Thu, 16 May 2024 16:42:23 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

ACF

Estimated Impact

149

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMP   [(Partial) Autocorrelation Function] [ARMA processing Q2] [2008-12-08 12:50:33] [c96f3dce3a823a83b6ede18389e1cfd4]
F   PD      [(Partial) Autocorrelation Function] [ARMA processing Q...] [2008-12-08 14:09:16] [3bdbbe597ac6c61989658933956ee6ac] [Current]
-   P         [(Partial) Autocorrelation Function] [ARMA processing Q...] [2008-12-08 14:13:47] [c96f3dce3a823a83b6ede18389e1cfd4] 

Feedback Forum

2008-12-14 11:46:57 [Gert-Jan Geudens] [reply] 
Goede berkeningen al hebben we onze bedenkingen bij de conclusie. Het lijkt ons hier voldoende om enkel niet-seizonaal te differentiëren. Als we de berekening uitbreiden naar 60 lags, zien we wel enkele palen van het hangmatpatroon maar deze liggen op lags 33, 44 , 54,... dus dit is geen seizonaliteit.

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Dataseries X:

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Histogram

Boxplots

8.4
8.4
8.4
8.6
8.9
8.8
8.3
7.5
7.2
7.5
8.8
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.6
8.2
8.1
8
8.6
8.7
8.8
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8.1
8.2
8.1
8.1
7.9
7.9
7.9
8
8
7.9
8
7.7
7.2
7.5
7.3
7
7
7
7.2
7.3
7.1
6.8
6.6
6.2
6.2
6.8
6.9
6.8

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=30501&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=30501&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30501&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	0.886544	6.9241	0
2	0.70831	5.5321	0
3	0.56402	4.4051	2.2e-05
4	0.498033	3.8898	0.000125
5	0.505633	3.9491	0.000103
6	0.525751	4.1062	6.1e-05
7	0.49174	3.8406	0.000147
8	0.428384	3.3458	0.000704
9	0.377418	2.9477	0.002265
10	0.362439	2.8307	0.00314
11	0.356341	2.7831	0.003579
12	0.332892	2.6	0.005839
13	0.242088	1.8908	0.031704
14	0.152835	1.1937	0.118612
15	0.089081	0.6957	0.244616
16	0.048313	0.3773	0.353617
17	0.042044	0.3284	0.371877
18	0.040992	0.3202	0.374972
19	0.004135	0.0323	0.487171
20	-0.04554	-0.3557	0.361654
21	-0.087314	-0.6819	0.248928
22	-0.108496	-0.8474	0.200047
23	-0.120208	-0.9389	0.175755
24	-0.132336	-1.0336	0.152707
25	-0.163377	-1.276	0.103393
26	-0.194066	-1.5157	0.06738
27	-0.213079	-1.6642	0.050601
28	-0.221615	-1.7309	0.044265
29	-0.224037	-1.7498	0.042592
30	-0.227292	-1.7752	0.040426
31	-0.24342	-1.9012	0.031003
32	-0.268529	-2.0973	0.020061
33	-0.278434	-2.1746	0.016772
34	-0.2732	-2.1338	0.018446
35	-0.259285	-2.0251	0.023621
36	-0.239383	-1.8696	0.033168

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.886544 & 6.9241 & 0 \tabularnewline
2 & 0.70831 & 5.5321 & 0 \tabularnewline
3 & 0.56402 & 4.4051 & 2.2e-05 \tabularnewline
4 & 0.498033 & 3.8898 & 0.000125 \tabularnewline
5 & 0.505633 & 3.9491 & 0.000103 \tabularnewline
6 & 0.525751 & 4.1062 & 6.1e-05 \tabularnewline
7 & 0.49174 & 3.8406 & 0.000147 \tabularnewline
8 & 0.428384 & 3.3458 & 0.000704 \tabularnewline
9 & 0.377418 & 2.9477 & 0.002265 \tabularnewline
10 & 0.362439 & 2.8307 & 0.00314 \tabularnewline
11 & 0.356341 & 2.7831 & 0.003579 \tabularnewline
12 & 0.332892 & 2.6 & 0.005839 \tabularnewline
13 & 0.242088 & 1.8908 & 0.031704 \tabularnewline
14 & 0.152835 & 1.1937 & 0.118612 \tabularnewline
15 & 0.089081 & 0.6957 & 0.244616 \tabularnewline
16 & 0.048313 & 0.3773 & 0.353617 \tabularnewline
17 & 0.042044 & 0.3284 & 0.371877 \tabularnewline
18 & 0.040992 & 0.3202 & 0.374972 \tabularnewline
19 & 0.004135 & 0.0323 & 0.487171 \tabularnewline
20 & -0.04554 & -0.3557 & 0.361654 \tabularnewline
21 & -0.087314 & -0.6819 & 0.248928 \tabularnewline
22 & -0.108496 & -0.8474 & 0.200047 \tabularnewline
23 & -0.120208 & -0.9389 & 0.175755 \tabularnewline
24 & -0.132336 & -1.0336 & 0.152707 \tabularnewline
25 & -0.163377 & -1.276 & 0.103393 \tabularnewline
26 & -0.194066 & -1.5157 & 0.06738 \tabularnewline
27 & -0.213079 & -1.6642 & 0.050601 \tabularnewline
28 & -0.221615 & -1.7309 & 0.044265 \tabularnewline
29 & -0.224037 & -1.7498 & 0.042592 \tabularnewline
30 & -0.227292 & -1.7752 & 0.040426 \tabularnewline
31 & -0.24342 & -1.9012 & 0.031003 \tabularnewline
32 & -0.268529 & -2.0973 & 0.020061 \tabularnewline
33 & -0.278434 & -2.1746 & 0.016772 \tabularnewline
34 & -0.2732 & -2.1338 & 0.018446 \tabularnewline
35 & -0.259285 & -2.0251 & 0.023621 \tabularnewline
36 & -0.239383 & -1.8696 & 0.033168 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30501&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]0.886544[/C][C]6.9241[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.70831[/C][C]5.5321[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.56402[/C][C]4.4051[/C][C]2.2e-05[/C][/ROW]
[ROW][C]4[/C][C]0.498033[/C][C]3.8898[/C][C]0.000125[/C][/ROW]
[ROW][C]5[/C][C]0.505633[/C][C]3.9491[/C][C]0.000103[/C][/ROW]
[ROW][C]6[/C][C]0.525751[/C][C]4.1062[/C][C]6.1e-05[/C][/ROW]
[ROW][C]7[/C][C]0.49174[/C][C]3.8406[/C][C]0.000147[/C][/ROW]
[ROW][C]8[/C][C]0.428384[/C][C]3.3458[/C][C]0.000704[/C][/ROW]
[ROW][C]9[/C][C]0.377418[/C][C]2.9477[/C][C]0.002265[/C][/ROW]
[ROW][C]10[/C][C]0.362439[/C][C]2.8307[/C][C]0.00314[/C][/ROW]
[ROW][C]11[/C][C]0.356341[/C][C]2.7831[/C][C]0.003579[/C][/ROW]
[ROW][C]12[/C][C]0.332892[/C][C]2.6[/C][C]0.005839[/C][/ROW]
[ROW][C]13[/C][C]0.242088[/C][C]1.8908[/C][C]0.031704[/C][/ROW]
[ROW][C]14[/C][C]0.152835[/C][C]1.1937[/C][C]0.118612[/C][/ROW]
[ROW][C]15[/C][C]0.089081[/C][C]0.6957[/C][C]0.244616[/C][/ROW]
[ROW][C]16[/C][C]0.048313[/C][C]0.3773[/C][C]0.353617[/C][/ROW]
[ROW][C]17[/C][C]0.042044[/C][C]0.3284[/C][C]0.371877[/C][/ROW]
[ROW][C]18[/C][C]0.040992[/C][C]0.3202[/C][C]0.374972[/C][/ROW]
[ROW][C]19[/C][C]0.004135[/C][C]0.0323[/C][C]0.487171[/C][/ROW]
[ROW][C]20[/C][C]-0.04554[/C][C]-0.3557[/C][C]0.361654[/C][/ROW]
[ROW][C]21[/C][C]-0.087314[/C][C]-0.6819[/C][C]0.248928[/C][/ROW]
[ROW][C]22[/C][C]-0.108496[/C][C]-0.8474[/C][C]0.200047[/C][/ROW]
[ROW][C]23[/C][C]-0.120208[/C][C]-0.9389[/C][C]0.175755[/C][/ROW]
[ROW][C]24[/C][C]-0.132336[/C][C]-1.0336[/C][C]0.152707[/C][/ROW]
[ROW][C]25[/C][C]-0.163377[/C][C]-1.276[/C][C]0.103393[/C][/ROW]
[ROW][C]26[/C][C]-0.194066[/C][C]-1.5157[/C][C]0.06738[/C][/ROW]
[ROW][C]27[/C][C]-0.213079[/C][C]-1.6642[/C][C]0.050601[/C][/ROW]
[ROW][C]28[/C][C]-0.221615[/C][C]-1.7309[/C][C]0.044265[/C][/ROW]
[ROW][C]29[/C][C]-0.224037[/C][C]-1.7498[/C][C]0.042592[/C][/ROW]
[ROW][C]30[/C][C]-0.227292[/C][C]-1.7752[/C][C]0.040426[/C][/ROW]
[ROW][C]31[/C][C]-0.24342[/C][C]-1.9012[/C][C]0.031003[/C][/ROW]
[ROW][C]32[/C][C]-0.268529[/C][C]-2.0973[/C][C]0.020061[/C][/ROW]
[ROW][C]33[/C][C]-0.278434[/C][C]-2.1746[/C][C]0.016772[/C][/ROW]
[ROW][C]34[/C][C]-0.2732[/C][C]-2.1338[/C][C]0.018446[/C][/ROW]
[ROW][C]35[/C][C]-0.259285[/C][C]-2.0251[/C][C]0.023621[/C][/ROW]
[ROW][C]36[/C][C]-0.239383[/C][C]-1.8696[/C][C]0.033168[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30501&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30501&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	0.886544	6.9241	0
2	0.70831	5.5321	0
3	0.56402	4.4051	2.2e-05
4	0.498033	3.8898	0.000125
5	0.505633	3.9491	0.000103
6	0.525751	4.1062	6.1e-05
7	0.49174	3.8406	0.000147
8	0.428384	3.3458	0.000704
9	0.377418	2.9477	0.002265
10	0.362439	2.8307	0.00314
11	0.356341	2.7831	0.003579
12	0.332892	2.6	0.005839
13	0.242088	1.8908	0.031704
14	0.152835	1.1937	0.118612
15	0.089081	0.6957	0.244616
16	0.048313	0.3773	0.353617
17	0.042044	0.3284	0.371877
18	0.040992	0.3202	0.374972
19	0.004135	0.0323	0.487171
20	-0.04554	-0.3557	0.361654
21	-0.087314	-0.6819	0.248928
22	-0.108496	-0.8474	0.200047
23	-0.120208	-0.9389	0.175755
24	-0.132336	-1.0336	0.152707
25	-0.163377	-1.276	0.103393
26	-0.194066	-1.5157	0.06738
27	-0.213079	-1.6642	0.050601
28	-0.221615	-1.7309	0.044265
29	-0.224037	-1.7498	0.042592
30	-0.227292	-1.7752	0.040426
31	-0.24342	-1.9012	0.031003
32	-0.268529	-2.0973	0.020061
33	-0.278434	-2.1746	0.016772
34	-0.2732	-2.1338	0.018446
35	-0.259285	-2.0251	0.023621
36	-0.239383	-1.8696	0.033168

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.886544	6.9241	0
2	-0.362782	-2.8334	0.003117
3	0.160794	1.2558	0.106981
4	0.197243	1.5405	0.064303
5	0.178541	1.3944	0.08412
6	-0.015801	-0.1234	0.451094
7	-0.1571	-1.227	0.11227
8	0.093016	0.7265	0.235163
9	0.087242	0.6814	0.249103
10	0.049274	0.3848	0.350847
11	-0.122856	-0.9595	0.170538
12	-0.049078	-0.3833	0.351411
13	-0.254515	-1.9878	0.025662
14	0.175652	1.3719	0.087562
15	-0.119242	-0.9313	0.177682
16	-0.128392	-1.0028	0.159966
17	0.079829	0.6235	0.267644
18	-0.010715	-0.0837	0.466788
19	-0.075007	-0.5858	0.280078
20	-0.035862	-0.2801	0.390177
21	0.005258	0.0411	0.483688
22	0.015948	0.1246	0.45064
23	-0.026895	-0.2101	0.417163
24	-0.052602	-0.4108	0.341318
25	0.016987	0.1327	0.447444
26	-0.007068	-0.0552	0.478078
27	-6e-04	-0.0047	0.498138
28	-0.023467	-0.1833	0.427591
29	-0.086091	-0.6724	0.251936
30	0.034457	0.2691	0.394373
31	0.013347	0.1042	0.458659
32	-0.130908	-1.0224	0.155308
33	0.067745	0.5291	0.299326
34	-0.010341	-0.0808	0.467947
35	0.015369	0.12	0.452423
36	0.014467	0.113	0.455203

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.886544 & 6.9241 & 0 \tabularnewline
2 & -0.362782 & -2.8334 & 0.003117 \tabularnewline
3 & 0.160794 & 1.2558 & 0.106981 \tabularnewline
4 & 0.197243 & 1.5405 & 0.064303 \tabularnewline
5 & 0.178541 & 1.3944 & 0.08412 \tabularnewline
6 & -0.015801 & -0.1234 & 0.451094 \tabularnewline
7 & -0.1571 & -1.227 & 0.11227 \tabularnewline
8 & 0.093016 & 0.7265 & 0.235163 \tabularnewline
9 & 0.087242 & 0.6814 & 0.249103 \tabularnewline
10 & 0.049274 & 0.3848 & 0.350847 \tabularnewline
11 & -0.122856 & -0.9595 & 0.170538 \tabularnewline
12 & -0.049078 & -0.3833 & 0.351411 \tabularnewline
13 & -0.254515 & -1.9878 & 0.025662 \tabularnewline
14 & 0.175652 & 1.3719 & 0.087562 \tabularnewline
15 & -0.119242 & -0.9313 & 0.177682 \tabularnewline
16 & -0.128392 & -1.0028 & 0.159966 \tabularnewline
17 & 0.079829 & 0.6235 & 0.267644 \tabularnewline
18 & -0.010715 & -0.0837 & 0.466788 \tabularnewline
19 & -0.075007 & -0.5858 & 0.280078 \tabularnewline
20 & -0.035862 & -0.2801 & 0.390177 \tabularnewline
21 & 0.005258 & 0.0411 & 0.483688 \tabularnewline
22 & 0.015948 & 0.1246 & 0.45064 \tabularnewline
23 & -0.026895 & -0.2101 & 0.417163 \tabularnewline
24 & -0.052602 & -0.4108 & 0.341318 \tabularnewline
25 & 0.016987 & 0.1327 & 0.447444 \tabularnewline
26 & -0.007068 & -0.0552 & 0.478078 \tabularnewline
27 & -6e-04 & -0.0047 & 0.498138 \tabularnewline
28 & -0.023467 & -0.1833 & 0.427591 \tabularnewline
29 & -0.086091 & -0.6724 & 0.251936 \tabularnewline
30 & 0.034457 & 0.2691 & 0.394373 \tabularnewline
31 & 0.013347 & 0.1042 & 0.458659 \tabularnewline
32 & -0.130908 & -1.0224 & 0.155308 \tabularnewline
33 & 0.067745 & 0.5291 & 0.299326 \tabularnewline
34 & -0.010341 & -0.0808 & 0.467947 \tabularnewline
35 & 0.015369 & 0.12 & 0.452423 \tabularnewline
36 & 0.014467 & 0.113 & 0.455203 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30501&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]0.886544[/C][C]6.9241[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.362782[/C][C]-2.8334[/C][C]0.003117[/C][/ROW]
[ROW][C]3[/C][C]0.160794[/C][C]1.2558[/C][C]0.106981[/C][/ROW]
[ROW][C]4[/C][C]0.197243[/C][C]1.5405[/C][C]0.064303[/C][/ROW]
[ROW][C]5[/C][C]0.178541[/C][C]1.3944[/C][C]0.08412[/C][/ROW]
[ROW][C]6[/C][C]-0.015801[/C][C]-0.1234[/C][C]0.451094[/C][/ROW]
[ROW][C]7[/C][C]-0.1571[/C][C]-1.227[/C][C]0.11227[/C][/ROW]
[ROW][C]8[/C][C]0.093016[/C][C]0.7265[/C][C]0.235163[/C][/ROW]
[ROW][C]9[/C][C]0.087242[/C][C]0.6814[/C][C]0.249103[/C][/ROW]
[ROW][C]10[/C][C]0.049274[/C][C]0.3848[/C][C]0.350847[/C][/ROW]
[ROW][C]11[/C][C]-0.122856[/C][C]-0.9595[/C][C]0.170538[/C][/ROW]
[ROW][C]12[/C][C]-0.049078[/C][C]-0.3833[/C][C]0.351411[/C][/ROW]
[ROW][C]13[/C][C]-0.254515[/C][C]-1.9878[/C][C]0.025662[/C][/ROW]
[ROW][C]14[/C][C]0.175652[/C][C]1.3719[/C][C]0.087562[/C][/ROW]
[ROW][C]15[/C][C]-0.119242[/C][C]-0.9313[/C][C]0.177682[/C][/ROW]
[ROW][C]16[/C][C]-0.128392[/C][C]-1.0028[/C][C]0.159966[/C][/ROW]
[ROW][C]17[/C][C]0.079829[/C][C]0.6235[/C][C]0.267644[/C][/ROW]
[ROW][C]18[/C][C]-0.010715[/C][C]-0.0837[/C][C]0.466788[/C][/ROW]
[ROW][C]19[/C][C]-0.075007[/C][C]-0.5858[/C][C]0.280078[/C][/ROW]
[ROW][C]20[/C][C]-0.035862[/C][C]-0.2801[/C][C]0.390177[/C][/ROW]
[ROW][C]21[/C][C]0.005258[/C][C]0.0411[/C][C]0.483688[/C][/ROW]
[ROW][C]22[/C][C]0.015948[/C][C]0.1246[/C][C]0.45064[/C][/ROW]
[ROW][C]23[/C][C]-0.026895[/C][C]-0.2101[/C][C]0.417163[/C][/ROW]
[ROW][C]24[/C][C]-0.052602[/C][C]-0.4108[/C][C]0.341318[/C][/ROW]
[ROW][C]25[/C][C]0.016987[/C][C]0.1327[/C][C]0.447444[/C][/ROW]
[ROW][C]26[/C][C]-0.007068[/C][C]-0.0552[/C][C]0.478078[/C][/ROW]
[ROW][C]27[/C][C]-6e-04[/C][C]-0.0047[/C][C]0.498138[/C][/ROW]
[ROW][C]28[/C][C]-0.023467[/C][C]-0.1833[/C][C]0.427591[/C][/ROW]
[ROW][C]29[/C][C]-0.086091[/C][C]-0.6724[/C][C]0.251936[/C][/ROW]
[ROW][C]30[/C][C]0.034457[/C][C]0.2691[/C][C]0.394373[/C][/ROW]
[ROW][C]31[/C][C]0.013347[/C][C]0.1042[/C][C]0.458659[/C][/ROW]
[ROW][C]32[/C][C]-0.130908[/C][C]-1.0224[/C][C]0.155308[/C][/ROW]
[ROW][C]33[/C][C]0.067745[/C][C]0.5291[/C][C]0.299326[/C][/ROW]
[ROW][C]34[/C][C]-0.010341[/C][C]-0.0808[/C][C]0.467947[/C][/ROW]
[ROW][C]35[/C][C]0.015369[/C][C]0.12[/C][C]0.452423[/C][/ROW]
[ROW][C]36[/C][C]0.014467[/C][C]0.113[/C][C]0.455203[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30501&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30501&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	0.886544	6.9241	0
2	-0.362782	-2.8334	0.003117
3	0.160794	1.2558	0.106981
4	0.197243	1.5405	0.064303
5	0.178541	1.3944	0.08412
6	-0.015801	-0.1234	0.451094
7	-0.1571	-1.227	0.11227
8	0.093016	0.7265	0.235163
9	0.087242	0.6814	0.249103
10	0.049274	0.3848	0.350847
11	-0.122856	-0.9595	0.170538
12	-0.049078	-0.3833	0.351411
13	-0.254515	-1.9878	0.025662
14	0.175652	1.3719	0.087562
15	-0.119242	-0.9313	0.177682
16	-0.128392	-1.0028	0.159966
17	0.079829	0.6235	0.267644
18	-0.010715	-0.0837	0.466788
19	-0.075007	-0.5858	0.280078
20	-0.035862	-0.2801	0.390177
21	0.005258	0.0411	0.483688
22	0.015948	0.1246	0.45064
23	-0.026895	-0.2101	0.417163
24	-0.052602	-0.4108	0.341318
25	0.016987	0.1327	0.447444
26	-0.007068	-0.0552	0.478078
27	-6e-04	-0.0047	0.498138
28	-0.023467	-0.1833	0.427591
29	-0.086091	-0.6724	0.251936
30	0.034457	0.2691	0.394373
31	0.013347	0.1042	0.458659
32	-0.130908	-1.0224	0.155308
33	0.067745	0.5291	0.299326
34	-0.010341	-0.0808	0.467947
35	0.015369	0.12	0.452423
36	0.014467	0.113	0.455203

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

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

Parameters (R input):

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