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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 computationMon, 08 Dec 2008 13:24:54 -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/08/t1228767932fewwnozjztnfifu.htm/, Retrieved Thu, 16 May 2024 16:32:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30955, Retrieved Thu, 16 May 2024 16:32:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact230

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]
F RMPD  [Cross Correlation Function] [Q7 - zonder trans...] [2008-12-01 20:04:13] [299afd6311e4c20059ea2f05c8dd029d]
F RM D    [Variance Reduction Matrix] [Q8] [2008-12-01 20:20:44] [299afd6311e4c20059ea2f05c8dd029d]
F    D      [Variance Reduction Matrix] [Q8 - 2] [2008-12-01 20:25:07] [299afd6311e4c20059ea2f05c8dd029d]
F RM D        [Standard Deviation-Mean Plot] [Deel 2: Step 1] [2008-12-08 20:09:35] [299afd6311e4c20059ea2f05c8dd029d]
- RM D            [(Partial) Autocorrelation Function] [Deel 2: Step 2 - ...] [2008-12-08 20:24:54] [5e2b1e7aa808f9f0d23fd35605d4968f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
14291.1
14205.3
15859.4
15258.9
15498.6
15106.5
15023.6
12083
15761.3
16943
15070.3
13659.6
14768.9
14725.1
15998.1
15370.6
14956.9
15469.7
15101.8
11703.7
16283.6
16726.5
14968.9
14861
14583.3
15305.8
17903.9
16379.4
15420.3
17870.5
15912.8
13866.5
17823.2
17872
17420.4
16704.4
15991.2
16583.6
19123.5
17838.7
17209.4
18586.5
16258.1
15141.6
19202.1
17746.5
19090.1
18040.3
17515.5
17751.8
21072.4
17170
19439.5
19795.4
17574.9
16165.4
19464.6
19932.1
19961.2
17343.4
18924.2
18574.1
21350.6
18594.6
19823.1
20844.4
19640.2
17735.4
19813.6
22160
20664.3
17877.4

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30955&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30955&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30955&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0757080.58640.279892
20.2236291.73220.044186
30.4899923.79550.000173
40.1463931.1340.130662
50.1609491.24670.108676
60.2726362.11180.019437
7-0.138498-1.07280.143828
80.1170720.90680.18406
90.1255620.97260.167329
10-0.17479-1.35390.090421
11-0.073827-0.57190.284777
12-0.083672-0.64810.25969
13-0.13936-1.07950.142347
140.0048340.03740.485129
15-0.177663-1.37620.086941
16-0.238053-1.84390.035065
170.0722940.560.288785
18-0.141926-1.09940.138002
19-0.107048-0.82920.205143
20-0.058679-0.45450.325546
21-0.002056-0.01590.493672
22-0.198771-1.53970.064449
230.1295511.00350.159825
24-0.159299-1.23390.111021
25-0.173885-1.34690.091538
260.095920.7430.230192
27-0.066181-0.51260.305045
28-0.128549-0.99570.161689
290.0496120.38430.351059
30-0.123481-0.95650.171335
31-0.005094-0.03950.48433
320.0161390.1250.450467
33-0.157694-1.22150.113338
340.0193240.14970.440759
350.0657080.5090.30632
36-0.121003-0.93730.176185

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.075708 & 0.5864 & 0.279892 \tabularnewline
2 & 0.223629 & 1.7322 & 0.044186 \tabularnewline
3 & 0.489992 & 3.7955 & 0.000173 \tabularnewline
4 & 0.146393 & 1.134 & 0.130662 \tabularnewline
5 & 0.160949 & 1.2467 & 0.108676 \tabularnewline
6 & 0.272636 & 2.1118 & 0.019437 \tabularnewline
7 & -0.138498 & -1.0728 & 0.143828 \tabularnewline
8 & 0.117072 & 0.9068 & 0.18406 \tabularnewline
9 & 0.125562 & 0.9726 & 0.167329 \tabularnewline
10 & -0.17479 & -1.3539 & 0.090421 \tabularnewline
11 & -0.073827 & -0.5719 & 0.284777 \tabularnewline
12 & -0.083672 & -0.6481 & 0.25969 \tabularnewline
13 & -0.13936 & -1.0795 & 0.142347 \tabularnewline
14 & 0.004834 & 0.0374 & 0.485129 \tabularnewline
15 & -0.177663 & -1.3762 & 0.086941 \tabularnewline
16 & -0.238053 & -1.8439 & 0.035065 \tabularnewline
17 & 0.072294 & 0.56 & 0.288785 \tabularnewline
18 & -0.141926 & -1.0994 & 0.138002 \tabularnewline
19 & -0.107048 & -0.8292 & 0.205143 \tabularnewline
20 & -0.058679 & -0.4545 & 0.325546 \tabularnewline
21 & -0.002056 & -0.0159 & 0.493672 \tabularnewline
22 & -0.198771 & -1.5397 & 0.064449 \tabularnewline
23 & 0.129551 & 1.0035 & 0.159825 \tabularnewline
24 & -0.159299 & -1.2339 & 0.111021 \tabularnewline
25 & -0.173885 & -1.3469 & 0.091538 \tabularnewline
26 & 0.09592 & 0.743 & 0.230192 \tabularnewline
27 & -0.066181 & -0.5126 & 0.305045 \tabularnewline
28 & -0.128549 & -0.9957 & 0.161689 \tabularnewline
29 & 0.049612 & 0.3843 & 0.351059 \tabularnewline
30 & -0.123481 & -0.9565 & 0.171335 \tabularnewline
31 & -0.005094 & -0.0395 & 0.48433 \tabularnewline
32 & 0.016139 & 0.125 & 0.450467 \tabularnewline
33 & -0.157694 & -1.2215 & 0.113338 \tabularnewline
34 & 0.019324 & 0.1497 & 0.440759 \tabularnewline
35 & 0.065708 & 0.509 & 0.30632 \tabularnewline
36 & -0.121003 & -0.9373 & 0.176185 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30955&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]0.075708[/C][C]0.5864[/C][C]0.279892[/C][/ROW]
[ROW][C]2[/C][C]0.223629[/C][C]1.7322[/C][C]0.044186[/C][/ROW]
[ROW][C]3[/C][C]0.489992[/C][C]3.7955[/C][C]0.000173[/C][/ROW]
[ROW][C]4[/C][C]0.146393[/C][C]1.134[/C][C]0.130662[/C][/ROW]
[ROW][C]5[/C][C]0.160949[/C][C]1.2467[/C][C]0.108676[/C][/ROW]
[ROW][C]6[/C][C]0.272636[/C][C]2.1118[/C][C]0.019437[/C][/ROW]
[ROW][C]7[/C][C]-0.138498[/C][C]-1.0728[/C][C]0.143828[/C][/ROW]
[ROW][C]8[/C][C]0.117072[/C][C]0.9068[/C][C]0.18406[/C][/ROW]
[ROW][C]9[/C][C]0.125562[/C][C]0.9726[/C][C]0.167329[/C][/ROW]
[ROW][C]10[/C][C]-0.17479[/C][C]-1.3539[/C][C]0.090421[/C][/ROW]
[ROW][C]11[/C][C]-0.073827[/C][C]-0.5719[/C][C]0.284777[/C][/ROW]
[ROW][C]12[/C][C]-0.083672[/C][C]-0.6481[/C][C]0.25969[/C][/ROW]
[ROW][C]13[/C][C]-0.13936[/C][C]-1.0795[/C][C]0.142347[/C][/ROW]
[ROW][C]14[/C][C]0.004834[/C][C]0.0374[/C][C]0.485129[/C][/ROW]
[ROW][C]15[/C][C]-0.177663[/C][C]-1.3762[/C][C]0.086941[/C][/ROW]
[ROW][C]16[/C][C]-0.238053[/C][C]-1.8439[/C][C]0.035065[/C][/ROW]
[ROW][C]17[/C][C]0.072294[/C][C]0.56[/C][C]0.288785[/C][/ROW]
[ROW][C]18[/C][C]-0.141926[/C][C]-1.0994[/C][C]0.138002[/C][/ROW]
[ROW][C]19[/C][C]-0.107048[/C][C]-0.8292[/C][C]0.205143[/C][/ROW]
[ROW][C]20[/C][C]-0.058679[/C][C]-0.4545[/C][C]0.325546[/C][/ROW]
[ROW][C]21[/C][C]-0.002056[/C][C]-0.0159[/C][C]0.493672[/C][/ROW]
[ROW][C]22[/C][C]-0.198771[/C][C]-1.5397[/C][C]0.064449[/C][/ROW]
[ROW][C]23[/C][C]0.129551[/C][C]1.0035[/C][C]0.159825[/C][/ROW]
[ROW][C]24[/C][C]-0.159299[/C][C]-1.2339[/C][C]0.111021[/C][/ROW]
[ROW][C]25[/C][C]-0.173885[/C][C]-1.3469[/C][C]0.091538[/C][/ROW]
[ROW][C]26[/C][C]0.09592[/C][C]0.743[/C][C]0.230192[/C][/ROW]
[ROW][C]27[/C][C]-0.066181[/C][C]-0.5126[/C][C]0.305045[/C][/ROW]
[ROW][C]28[/C][C]-0.128549[/C][C]-0.9957[/C][C]0.161689[/C][/ROW]
[ROW][C]29[/C][C]0.049612[/C][C]0.3843[/C][C]0.351059[/C][/ROW]
[ROW][C]30[/C][C]-0.123481[/C][C]-0.9565[/C][C]0.171335[/C][/ROW]
[ROW][C]31[/C][C]-0.005094[/C][C]-0.0395[/C][C]0.48433[/C][/ROW]
[ROW][C]32[/C][C]0.016139[/C][C]0.125[/C][C]0.450467[/C][/ROW]
[ROW][C]33[/C][C]-0.157694[/C][C]-1.2215[/C][C]0.113338[/C][/ROW]
[ROW][C]34[/C][C]0.019324[/C][C]0.1497[/C][C]0.440759[/C][/ROW]
[ROW][C]35[/C][C]0.065708[/C][C]0.509[/C][C]0.30632[/C][/ROW]
[ROW][C]36[/C][C]-0.121003[/C][C]-0.9373[/C][C]0.176185[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30955&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30955&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
10.0757080.58640.279892
20.2236291.73220.044186
30.4899923.79550.000173
40.1463931.1340.130662
50.1609491.24670.108676
60.2726362.11180.019437
7-0.138498-1.07280.143828
80.1170720.90680.18406
90.1255620.97260.167329
10-0.17479-1.35390.090421
11-0.073827-0.57190.284777
12-0.083672-0.64810.25969
13-0.13936-1.07950.142347
140.0048340.03740.485129
15-0.177663-1.37620.086941
16-0.238053-1.84390.035065
170.0722940.560.288785
18-0.141926-1.09940.138002
19-0.107048-0.82920.205143
20-0.058679-0.45450.325546
21-0.002056-0.01590.493672
22-0.198771-1.53970.064449
230.1295511.00350.159825
24-0.159299-1.23390.111021
25-0.173885-1.34690.091538
260.095920.7430.230192
27-0.066181-0.51260.305045
28-0.128549-0.99570.161689
290.0496120.38430.351059
30-0.123481-0.95650.171335
31-0.005094-0.03950.48433
320.0161390.1250.450467
33-0.157694-1.22150.113338
340.0193240.14970.440759
350.0657080.5090.30632
36-0.121003-0.93730.176185






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0757080.58640.279892
20.2191531.69760.047387
30.4861833.7660.00019
40.1248570.96710.168679
5-0.034257-0.26540.395824
6-0.008351-0.06470.47432
7-0.372786-2.88760.002696
8-0.091101-0.70570.241563
90.0928680.71940.237358
100.0232270.17990.428912
11-0.107878-0.83560.203343
12-0.199123-1.54240.064117
13-0.000484-0.00370.498512
140.202121.56560.061349
150.0763720.59160.278178
16-0.178873-1.38550.085507
17-0.017709-0.13720.445676
18-0.038351-0.29710.383721
190.0988750.76590.223374
20-0.024991-0.19360.423579
210.1512631.17170.122979
22-0.363237-2.81360.003307
23-0.025851-0.20020.420984
24-0.025508-0.19760.422019
25-0.019019-0.14730.441688
260.0977540.75720.225946
27-0.017866-0.13840.445198
280.0362640.28090.389875
29-0.062487-0.4840.315067
30-0.034911-0.27040.393883
310.0306880.23770.406457
32-0.058737-0.4550.325386
33-0.09494-0.73540.232479
340.010520.08150.467663
350.1396221.08150.1419
36-0.027257-0.21110.416751

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.075708 & 0.5864 & 0.279892 \tabularnewline
2 & 0.219153 & 1.6976 & 0.047387 \tabularnewline
3 & 0.486183 & 3.766 & 0.00019 \tabularnewline
4 & 0.124857 & 0.9671 & 0.168679 \tabularnewline
5 & -0.034257 & -0.2654 & 0.395824 \tabularnewline
6 & -0.008351 & -0.0647 & 0.47432 \tabularnewline
7 & -0.372786 & -2.8876 & 0.002696 \tabularnewline
8 & -0.091101 & -0.7057 & 0.241563 \tabularnewline
9 & 0.092868 & 0.7194 & 0.237358 \tabularnewline
10 & 0.023227 & 0.1799 & 0.428912 \tabularnewline
11 & -0.107878 & -0.8356 & 0.203343 \tabularnewline
12 & -0.199123 & -1.5424 & 0.064117 \tabularnewline
13 & -0.000484 & -0.0037 & 0.498512 \tabularnewline
14 & 0.20212 & 1.5656 & 0.061349 \tabularnewline
15 & 0.076372 & 0.5916 & 0.278178 \tabularnewline
16 & -0.178873 & -1.3855 & 0.085507 \tabularnewline
17 & -0.017709 & -0.1372 & 0.445676 \tabularnewline
18 & -0.038351 & -0.2971 & 0.383721 \tabularnewline
19 & 0.098875 & 0.7659 & 0.223374 \tabularnewline
20 & -0.024991 & -0.1936 & 0.423579 \tabularnewline
21 & 0.151263 & 1.1717 & 0.122979 \tabularnewline
22 & -0.363237 & -2.8136 & 0.003307 \tabularnewline
23 & -0.025851 & -0.2002 & 0.420984 \tabularnewline
24 & -0.025508 & -0.1976 & 0.422019 \tabularnewline
25 & -0.019019 & -0.1473 & 0.441688 \tabularnewline
26 & 0.097754 & 0.7572 & 0.225946 \tabularnewline
27 & -0.017866 & -0.1384 & 0.445198 \tabularnewline
28 & 0.036264 & 0.2809 & 0.389875 \tabularnewline
29 & -0.062487 & -0.484 & 0.315067 \tabularnewline
30 & -0.034911 & -0.2704 & 0.393883 \tabularnewline
31 & 0.030688 & 0.2377 & 0.406457 \tabularnewline
32 & -0.058737 & -0.455 & 0.325386 \tabularnewline
33 & -0.09494 & -0.7354 & 0.232479 \tabularnewline
34 & 0.01052 & 0.0815 & 0.467663 \tabularnewline
35 & 0.139622 & 1.0815 & 0.1419 \tabularnewline
36 & -0.027257 & -0.2111 & 0.416751 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30955&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]0.075708[/C][C]0.5864[/C][C]0.279892[/C][/ROW]
[ROW][C]2[/C][C]0.219153[/C][C]1.6976[/C][C]0.047387[/C][/ROW]
[ROW][C]3[/C][C]0.486183[/C][C]3.766[/C][C]0.00019[/C][/ROW]
[ROW][C]4[/C][C]0.124857[/C][C]0.9671[/C][C]0.168679[/C][/ROW]
[ROW][C]5[/C][C]-0.034257[/C][C]-0.2654[/C][C]0.395824[/C][/ROW]
[ROW][C]6[/C][C]-0.008351[/C][C]-0.0647[/C][C]0.47432[/C][/ROW]
[ROW][C]7[/C][C]-0.372786[/C][C]-2.8876[/C][C]0.002696[/C][/ROW]
[ROW][C]8[/C][C]-0.091101[/C][C]-0.7057[/C][C]0.241563[/C][/ROW]
[ROW][C]9[/C][C]0.092868[/C][C]0.7194[/C][C]0.237358[/C][/ROW]
[ROW][C]10[/C][C]0.023227[/C][C]0.1799[/C][C]0.428912[/C][/ROW]
[ROW][C]11[/C][C]-0.107878[/C][C]-0.8356[/C][C]0.203343[/C][/ROW]
[ROW][C]12[/C][C]-0.199123[/C][C]-1.5424[/C][C]0.064117[/C][/ROW]
[ROW][C]13[/C][C]-0.000484[/C][C]-0.0037[/C][C]0.498512[/C][/ROW]
[ROW][C]14[/C][C]0.20212[/C][C]1.5656[/C][C]0.061349[/C][/ROW]
[ROW][C]15[/C][C]0.076372[/C][C]0.5916[/C][C]0.278178[/C][/ROW]
[ROW][C]16[/C][C]-0.178873[/C][C]-1.3855[/C][C]0.085507[/C][/ROW]
[ROW][C]17[/C][C]-0.017709[/C][C]-0.1372[/C][C]0.445676[/C][/ROW]
[ROW][C]18[/C][C]-0.038351[/C][C]-0.2971[/C][C]0.383721[/C][/ROW]
[ROW][C]19[/C][C]0.098875[/C][C]0.7659[/C][C]0.223374[/C][/ROW]
[ROW][C]20[/C][C]-0.024991[/C][C]-0.1936[/C][C]0.423579[/C][/ROW]
[ROW][C]21[/C][C]0.151263[/C][C]1.1717[/C][C]0.122979[/C][/ROW]
[ROW][C]22[/C][C]-0.363237[/C][C]-2.8136[/C][C]0.003307[/C][/ROW]
[ROW][C]23[/C][C]-0.025851[/C][C]-0.2002[/C][C]0.420984[/C][/ROW]
[ROW][C]24[/C][C]-0.025508[/C][C]-0.1976[/C][C]0.422019[/C][/ROW]
[ROW][C]25[/C][C]-0.019019[/C][C]-0.1473[/C][C]0.441688[/C][/ROW]
[ROW][C]26[/C][C]0.097754[/C][C]0.7572[/C][C]0.225946[/C][/ROW]
[ROW][C]27[/C][C]-0.017866[/C][C]-0.1384[/C][C]0.445198[/C][/ROW]
[ROW][C]28[/C][C]0.036264[/C][C]0.2809[/C][C]0.389875[/C][/ROW]
[ROW][C]29[/C][C]-0.062487[/C][C]-0.484[/C][C]0.315067[/C][/ROW]
[ROW][C]30[/C][C]-0.034911[/C][C]-0.2704[/C][C]0.393883[/C][/ROW]
[ROW][C]31[/C][C]0.030688[/C][C]0.2377[/C][C]0.406457[/C][/ROW]
[ROW][C]32[/C][C]-0.058737[/C][C]-0.455[/C][C]0.325386[/C][/ROW]
[ROW][C]33[/C][C]-0.09494[/C][C]-0.7354[/C][C]0.232479[/C][/ROW]
[ROW][C]34[/C][C]0.01052[/C][C]0.0815[/C][C]0.467663[/C][/ROW]
[ROW][C]35[/C][C]0.139622[/C][C]1.0815[/C][C]0.1419[/C][/ROW]
[ROW][C]36[/C][C]-0.027257[/C][C]-0.2111[/C][C]0.416751[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30955&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30955&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
10.0757080.58640.279892
20.2191531.69760.047387
30.4861833.7660.00019
40.1248570.96710.168679
5-0.034257-0.26540.395824
6-0.008351-0.06470.47432
7-0.372786-2.88760.002696
8-0.091101-0.70570.241563
90.0928680.71940.237358
100.0232270.17990.428912
11-0.107878-0.83560.203343
12-0.199123-1.54240.064117
13-0.000484-0.00370.498512
140.202121.56560.061349
150.0763720.59160.278178
16-0.178873-1.38550.085507
17-0.017709-0.13720.445676
18-0.038351-0.29710.383721
190.0988750.76590.223374
20-0.024991-0.19360.423579
210.1512631.17170.122979
22-0.363237-2.81360.003307
23-0.025851-0.20020.420984
24-0.025508-0.19760.422019
25-0.019019-0.14730.441688
260.0977540.75720.225946
27-0.017866-0.13840.445198
280.0362640.28090.389875
29-0.062487-0.4840.315067
30-0.034911-0.27040.393883
310.0306880.23770.406457
32-0.058737-0.4550.325386
33-0.09494-0.73540.232479
340.010520.08150.467663
350.1396221.08150.1419
36-0.027257-0.21110.416751


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 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')