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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationWed, 03 Dec 2008 14:00:52 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/03/t1228338314y8umokxybw6jb7e.htm/, Retrieved Sun, 19 May 2024 05:38:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28884, Retrieved Sun, 19 May 2024 05:38:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact212

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
- RMPD  [(Partial) Autocorrelation Function] [blok 17 Q6 ACF] [2008-12-02 20:15:24] [6173c35e31b784a490c8cd5476f785d4]
-    D      [(Partial) Autocorrelation Function] [blok 17 Q8 acf x(t)] [2008-12-03 21:00:52] [1237f4df7e9be807e4c0a07b90c45721] [Current]
-   PD        [(Partial) Autocorrelation Function] [blok 17 Q8 acf x(...] [2008-12-03 21:05:57] [6173c35e31b784a490c8cd5476f785d4]
-   P           [(Partial) Autocorrelation Function] [blok 17 Q8 acf x(...] [2008-12-03 21:08:53] [6173c35e31b784a490c8cd5476f785d4]
-   PD            [(Partial) Autocorrelation Function] [blok 17 Q8 acf y(t)] [2008-12-03 21:21:49] [6173c35e31b784a490c8cd5476f785d4]
-   PD              [(Partial) Autocorrelation Function] [blok 17 Q8 acf y(...] [2008-12-03 21:25:22] [6173c35e31b784a490c8cd5476f785d4]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
98,6
98
106,8
96,6
100,1
107,7
91,5
97,8
107,4
117,5
105,6
97,4
99,5
98
104,3
100,6
101,1
103,9
96,9
95,5
108,4
117
103,8
100,8
110,6
104
112,6
107,3
98,9
109,8
104,9
102,2
123,9
124,9
112,7
121,9
100,6
104,3
120,4
107,5
102,9
125,6
107,5
108,8
128,4
121,1
119,5
128,7
108,7
105,5
119,8
111,3
110,6
120,1
97,5
107,7
127,3
117,2
119,8
116,2
111
112,4
130,6
109,1
118,8
123,9
101,6
112,8
128
129,6
125,8
119,5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28884&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]4 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=28884&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28884&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3885153.29670.000761
20.198271.68240.048414
30.4628253.92729.7e-05
40.1270271.07790.142347
50.2253731.91240.029905
60.5223664.43241.6e-05
70.141551.20110.116826
80.1432771.21570.114026
90.3617153.06930.001512
100.0452710.38410.351005
110.2863362.42960.008805
120.5880114.98942e-06
130.1486931.26170.105564
140.1207931.0250.154405
150.2334761.98110.0257
16-0.051773-0.43930.330878
170.129891.10220.137032
180.2537112.15280.017343
19-0.057342-0.48660.314023
200.0111810.09490.462338
210.1023120.86810.194099
22-0.095845-0.81330.209373
230.1529491.29780.099246
240.2813962.38770.00979
25-0.003861-0.03280.486977
26-0.003143-0.02670.489399
270.0158280.13430.446768
28-0.190517-1.61660.05517
29-0.06384-0.54170.294849
300.0106420.09030.464151
31-0.172015-1.45960.074375
32-0.116354-0.98730.163402
33-0.122023-1.03540.151974
34-0.213525-1.81180.037092
35-0.028573-0.24250.404559
360.0984910.83570.203038

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.388515 & 3.2967 & 0.000761 \tabularnewline
2 & 0.19827 & 1.6824 & 0.048414 \tabularnewline
3 & 0.462825 & 3.9272 & 9.7e-05 \tabularnewline
4 & 0.127027 & 1.0779 & 0.142347 \tabularnewline
5 & 0.225373 & 1.9124 & 0.029905 \tabularnewline
6 & 0.522366 & 4.4324 & 1.6e-05 \tabularnewline
7 & 0.14155 & 1.2011 & 0.116826 \tabularnewline
8 & 0.143277 & 1.2157 & 0.114026 \tabularnewline
9 & 0.361715 & 3.0693 & 0.001512 \tabularnewline
10 & 0.045271 & 0.3841 & 0.351005 \tabularnewline
11 & 0.286336 & 2.4296 & 0.008805 \tabularnewline
12 & 0.588011 & 4.9894 & 2e-06 \tabularnewline
13 & 0.148693 & 1.2617 & 0.105564 \tabularnewline
14 & 0.120793 & 1.025 & 0.154405 \tabularnewline
15 & 0.233476 & 1.9811 & 0.0257 \tabularnewline
16 & -0.051773 & -0.4393 & 0.330878 \tabularnewline
17 & 0.12989 & 1.1022 & 0.137032 \tabularnewline
18 & 0.253711 & 2.1528 & 0.017343 \tabularnewline
19 & -0.057342 & -0.4866 & 0.314023 \tabularnewline
20 & 0.011181 & 0.0949 & 0.462338 \tabularnewline
21 & 0.102312 & 0.8681 & 0.194099 \tabularnewline
22 & -0.095845 & -0.8133 & 0.209373 \tabularnewline
23 & 0.152949 & 1.2978 & 0.099246 \tabularnewline
24 & 0.281396 & 2.3877 & 0.00979 \tabularnewline
25 & -0.003861 & -0.0328 & 0.486977 \tabularnewline
26 & -0.003143 & -0.0267 & 0.489399 \tabularnewline
27 & 0.015828 & 0.1343 & 0.446768 \tabularnewline
28 & -0.190517 & -1.6166 & 0.05517 \tabularnewline
29 & -0.06384 & -0.5417 & 0.294849 \tabularnewline
30 & 0.010642 & 0.0903 & 0.464151 \tabularnewline
31 & -0.172015 & -1.4596 & 0.074375 \tabularnewline
32 & -0.116354 & -0.9873 & 0.163402 \tabularnewline
33 & -0.122023 & -1.0354 & 0.151974 \tabularnewline
34 & -0.213525 & -1.8118 & 0.037092 \tabularnewline
35 & -0.028573 & -0.2425 & 0.404559 \tabularnewline
36 & 0.098491 & 0.8357 & 0.203038 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28884&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]0.388515[/C][C]3.2967[/C][C]0.000761[/C][/ROW]
[ROW][C]2[/C][C]0.19827[/C][C]1.6824[/C][C]0.048414[/C][/ROW]
[ROW][C]3[/C][C]0.462825[/C][C]3.9272[/C][C]9.7e-05[/C][/ROW]
[ROW][C]4[/C][C]0.127027[/C][C]1.0779[/C][C]0.142347[/C][/ROW]
[ROW][C]5[/C][C]0.225373[/C][C]1.9124[/C][C]0.029905[/C][/ROW]
[ROW][C]6[/C][C]0.522366[/C][C]4.4324[/C][C]1.6e-05[/C][/ROW]
[ROW][C]7[/C][C]0.14155[/C][C]1.2011[/C][C]0.116826[/C][/ROW]
[ROW][C]8[/C][C]0.143277[/C][C]1.2157[/C][C]0.114026[/C][/ROW]
[ROW][C]9[/C][C]0.361715[/C][C]3.0693[/C][C]0.001512[/C][/ROW]
[ROW][C]10[/C][C]0.045271[/C][C]0.3841[/C][C]0.351005[/C][/ROW]
[ROW][C]11[/C][C]0.286336[/C][C]2.4296[/C][C]0.008805[/C][/ROW]
[ROW][C]12[/C][C]0.588011[/C][C]4.9894[/C][C]2e-06[/C][/ROW]
[ROW][C]13[/C][C]0.148693[/C][C]1.2617[/C][C]0.105564[/C][/ROW]
[ROW][C]14[/C][C]0.120793[/C][C]1.025[/C][C]0.154405[/C][/ROW]
[ROW][C]15[/C][C]0.233476[/C][C]1.9811[/C][C]0.0257[/C][/ROW]
[ROW][C]16[/C][C]-0.051773[/C][C]-0.4393[/C][C]0.330878[/C][/ROW]
[ROW][C]17[/C][C]0.12989[/C][C]1.1022[/C][C]0.137032[/C][/ROW]
[ROW][C]18[/C][C]0.253711[/C][C]2.1528[/C][C]0.017343[/C][/ROW]
[ROW][C]19[/C][C]-0.057342[/C][C]-0.4866[/C][C]0.314023[/C][/ROW]
[ROW][C]20[/C][C]0.011181[/C][C]0.0949[/C][C]0.462338[/C][/ROW]
[ROW][C]21[/C][C]0.102312[/C][C]0.8681[/C][C]0.194099[/C][/ROW]
[ROW][C]22[/C][C]-0.095845[/C][C]-0.8133[/C][C]0.209373[/C][/ROW]
[ROW][C]23[/C][C]0.152949[/C][C]1.2978[/C][C]0.099246[/C][/ROW]
[ROW][C]24[/C][C]0.281396[/C][C]2.3877[/C][C]0.00979[/C][/ROW]
[ROW][C]25[/C][C]-0.003861[/C][C]-0.0328[/C][C]0.486977[/C][/ROW]
[ROW][C]26[/C][C]-0.003143[/C][C]-0.0267[/C][C]0.489399[/C][/ROW]
[ROW][C]27[/C][C]0.015828[/C][C]0.1343[/C][C]0.446768[/C][/ROW]
[ROW][C]28[/C][C]-0.190517[/C][C]-1.6166[/C][C]0.05517[/C][/ROW]
[ROW][C]29[/C][C]-0.06384[/C][C]-0.5417[/C][C]0.294849[/C][/ROW]
[ROW][C]30[/C][C]0.010642[/C][C]0.0903[/C][C]0.464151[/C][/ROW]
[ROW][C]31[/C][C]-0.172015[/C][C]-1.4596[/C][C]0.074375[/C][/ROW]
[ROW][C]32[/C][C]-0.116354[/C][C]-0.9873[/C][C]0.163402[/C][/ROW]
[ROW][C]33[/C][C]-0.122023[/C][C]-1.0354[/C][C]0.151974[/C][/ROW]
[ROW][C]34[/C][C]-0.213525[/C][C]-1.8118[/C][C]0.037092[/C][/ROW]
[ROW][C]35[/C][C]-0.028573[/C][C]-0.2425[/C][C]0.404559[/C][/ROW]
[ROW][C]36[/C][C]0.098491[/C][C]0.8357[/C][C]0.203038[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28884&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28884&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3885153.29670.000761
20.198271.68240.048414
30.4628253.92729.7e-05
40.1270271.07790.142347
50.2253731.91240.029905
60.5223664.43241.6e-05
70.141551.20110.116826
80.1432771.21570.114026
90.3617153.06930.001512
100.0452710.38410.351005
110.2863362.42960.008805
120.5880114.98942e-06
130.1486931.26170.105564
140.1207931.0250.154405
150.2334761.98110.0257
16-0.051773-0.43930.330878
170.129891.10220.137032
180.2537112.15280.017343
19-0.057342-0.48660.314023
200.0111810.09490.462338
210.1023120.86810.194099
22-0.095845-0.81330.209373
230.1529491.29780.099246
240.2813962.38770.00979
25-0.003861-0.03280.486977
26-0.003143-0.02670.489399
270.0158280.13430.446768
28-0.190517-1.61660.05517
29-0.06384-0.54170.294849
300.0106420.09030.464151
31-0.172015-1.45960.074375
32-0.116354-0.98730.163402
33-0.122023-1.03540.151974
34-0.213525-1.81180.037092
35-0.028573-0.24250.404559
360.0984910.83570.203038






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3885153.29670.000761
20.055740.4730.318834
30.4352843.69350.000214
4-0.262431-2.22680.014545
50.3536443.00080.001849
60.2162651.83510.035313
7-0.146054-1.23930.109628
80.0496650.42140.337352
90.063210.53640.296684
10-0.090932-0.77160.221444
110.350662.97550.00199
120.21731.84380.03466
13-0.124435-1.05590.147279
14-0.161261-1.36830.08773
15-0.132946-1.12810.131514
16-0.034076-0.28910.386652
17-0.032377-0.27470.392157
18-0.128215-1.08790.140126
190.0035610.03020.487988
20-0.119771-1.01630.156447
210.0431350.3660.357715
220.027420.23270.408339
230.0701010.59480.276913
240.0278380.23620.406968
250.0356610.30260.381537
26-0.137151-1.16380.124181
270.0355850.30190.381782
28-0.177967-1.51010.067697
29-0.095036-0.80640.211331
30-0.043923-0.37270.355233
310.0515650.43750.331513
32-0.025519-0.21650.41459
33-0.073142-0.62060.268402
34-0.012124-0.10290.459175
350.0218360.18530.426764
360.1451371.23150.111067

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.388515 & 3.2967 & 0.000761 \tabularnewline
2 & 0.05574 & 0.473 & 0.318834 \tabularnewline
3 & 0.435284 & 3.6935 & 0.000214 \tabularnewline
4 & -0.262431 & -2.2268 & 0.014545 \tabularnewline
5 & 0.353644 & 3.0008 & 0.001849 \tabularnewline
6 & 0.216265 & 1.8351 & 0.035313 \tabularnewline
7 & -0.146054 & -1.2393 & 0.109628 \tabularnewline
8 & 0.049665 & 0.4214 & 0.337352 \tabularnewline
9 & 0.06321 & 0.5364 & 0.296684 \tabularnewline
10 & -0.090932 & -0.7716 & 0.221444 \tabularnewline
11 & 0.35066 & 2.9755 & 0.00199 \tabularnewline
12 & 0.2173 & 1.8438 & 0.03466 \tabularnewline
13 & -0.124435 & -1.0559 & 0.147279 \tabularnewline
14 & -0.161261 & -1.3683 & 0.08773 \tabularnewline
15 & -0.132946 & -1.1281 & 0.131514 \tabularnewline
16 & -0.034076 & -0.2891 & 0.386652 \tabularnewline
17 & -0.032377 & -0.2747 & 0.392157 \tabularnewline
18 & -0.128215 & -1.0879 & 0.140126 \tabularnewline
19 & 0.003561 & 0.0302 & 0.487988 \tabularnewline
20 & -0.119771 & -1.0163 & 0.156447 \tabularnewline
21 & 0.043135 & 0.366 & 0.357715 \tabularnewline
22 & 0.02742 & 0.2327 & 0.408339 \tabularnewline
23 & 0.070101 & 0.5948 & 0.276913 \tabularnewline
24 & 0.027838 & 0.2362 & 0.406968 \tabularnewline
25 & 0.035661 & 0.3026 & 0.381537 \tabularnewline
26 & -0.137151 & -1.1638 & 0.124181 \tabularnewline
27 & 0.035585 & 0.3019 & 0.381782 \tabularnewline
28 & -0.177967 & -1.5101 & 0.067697 \tabularnewline
29 & -0.095036 & -0.8064 & 0.211331 \tabularnewline
30 & -0.043923 & -0.3727 & 0.355233 \tabularnewline
31 & 0.051565 & 0.4375 & 0.331513 \tabularnewline
32 & -0.025519 & -0.2165 & 0.41459 \tabularnewline
33 & -0.073142 & -0.6206 & 0.268402 \tabularnewline
34 & -0.012124 & -0.1029 & 0.459175 \tabularnewline
35 & 0.021836 & 0.1853 & 0.426764 \tabularnewline
36 & 0.145137 & 1.2315 & 0.111067 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28884&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]0.388515[/C][C]3.2967[/C][C]0.000761[/C][/ROW]
[ROW][C]2[/C][C]0.05574[/C][C]0.473[/C][C]0.318834[/C][/ROW]
[ROW][C]3[/C][C]0.435284[/C][C]3.6935[/C][C]0.000214[/C][/ROW]
[ROW][C]4[/C][C]-0.262431[/C][C]-2.2268[/C][C]0.014545[/C][/ROW]
[ROW][C]5[/C][C]0.353644[/C][C]3.0008[/C][C]0.001849[/C][/ROW]
[ROW][C]6[/C][C]0.216265[/C][C]1.8351[/C][C]0.035313[/C][/ROW]
[ROW][C]7[/C][C]-0.146054[/C][C]-1.2393[/C][C]0.109628[/C][/ROW]
[ROW][C]8[/C][C]0.049665[/C][C]0.4214[/C][C]0.337352[/C][/ROW]
[ROW][C]9[/C][C]0.06321[/C][C]0.5364[/C][C]0.296684[/C][/ROW]
[ROW][C]10[/C][C]-0.090932[/C][C]-0.7716[/C][C]0.221444[/C][/ROW]
[ROW][C]11[/C][C]0.35066[/C][C]2.9755[/C][C]0.00199[/C][/ROW]
[ROW][C]12[/C][C]0.2173[/C][C]1.8438[/C][C]0.03466[/C][/ROW]
[ROW][C]13[/C][C]-0.124435[/C][C]-1.0559[/C][C]0.147279[/C][/ROW]
[ROW][C]14[/C][C]-0.161261[/C][C]-1.3683[/C][C]0.08773[/C][/ROW]
[ROW][C]15[/C][C]-0.132946[/C][C]-1.1281[/C][C]0.131514[/C][/ROW]
[ROW][C]16[/C][C]-0.034076[/C][C]-0.2891[/C][C]0.386652[/C][/ROW]
[ROW][C]17[/C][C]-0.032377[/C][C]-0.2747[/C][C]0.392157[/C][/ROW]
[ROW][C]18[/C][C]-0.128215[/C][C]-1.0879[/C][C]0.140126[/C][/ROW]
[ROW][C]19[/C][C]0.003561[/C][C]0.0302[/C][C]0.487988[/C][/ROW]
[ROW][C]20[/C][C]-0.119771[/C][C]-1.0163[/C][C]0.156447[/C][/ROW]
[ROW][C]21[/C][C]0.043135[/C][C]0.366[/C][C]0.357715[/C][/ROW]
[ROW][C]22[/C][C]0.02742[/C][C]0.2327[/C][C]0.408339[/C][/ROW]
[ROW][C]23[/C][C]0.070101[/C][C]0.5948[/C][C]0.276913[/C][/ROW]
[ROW][C]24[/C][C]0.027838[/C][C]0.2362[/C][C]0.406968[/C][/ROW]
[ROW][C]25[/C][C]0.035661[/C][C]0.3026[/C][C]0.381537[/C][/ROW]
[ROW][C]26[/C][C]-0.137151[/C][C]-1.1638[/C][C]0.124181[/C][/ROW]
[ROW][C]27[/C][C]0.035585[/C][C]0.3019[/C][C]0.381782[/C][/ROW]
[ROW][C]28[/C][C]-0.177967[/C][C]-1.5101[/C][C]0.067697[/C][/ROW]
[ROW][C]29[/C][C]-0.095036[/C][C]-0.8064[/C][C]0.211331[/C][/ROW]
[ROW][C]30[/C][C]-0.043923[/C][C]-0.3727[/C][C]0.355233[/C][/ROW]
[ROW][C]31[/C][C]0.051565[/C][C]0.4375[/C][C]0.331513[/C][/ROW]
[ROW][C]32[/C][C]-0.025519[/C][C]-0.2165[/C][C]0.41459[/C][/ROW]
[ROW][C]33[/C][C]-0.073142[/C][C]-0.6206[/C][C]0.268402[/C][/ROW]
[ROW][C]34[/C][C]-0.012124[/C][C]-0.1029[/C][C]0.459175[/C][/ROW]
[ROW][C]35[/C][C]0.021836[/C][C]0.1853[/C][C]0.426764[/C][/ROW]
[ROW][C]36[/C][C]0.145137[/C][C]1.2315[/C][C]0.111067[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28884&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28884&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3885153.29670.000761
20.055740.4730.318834
30.4352843.69350.000214
4-0.262431-2.22680.014545
50.3536443.00080.001849
60.2162651.83510.035313
7-0.146054-1.23930.109628
80.0496650.42140.337352
90.063210.53640.296684
10-0.090932-0.77160.221444
110.350662.97550.00199
120.21731.84380.03466
13-0.124435-1.05590.147279
14-0.161261-1.36830.08773
15-0.132946-1.12810.131514
16-0.034076-0.28910.386652
17-0.032377-0.27470.392157
18-0.128215-1.08790.140126
190.0035610.03020.487988
20-0.119771-1.01630.156447
210.0431350.3660.357715
220.027420.23270.408339
230.0701010.59480.276913
240.0278380.23620.406968
250.0356610.30260.381537
26-0.137151-1.16380.124181
270.0355850.30190.381782
28-0.177967-1.51010.067697
29-0.095036-0.80640.211331
30-0.043923-0.37270.355233
310.0515650.43750.331513
32-0.025519-0.21650.41459
33-0.073142-0.62060.268402
34-0.012124-0.10290.459175
350.0218360.18530.426764
360.1451371.23150.111067


Figures (Output of Computation)

Input Parameters & R Code

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')