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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 computationFri, 12 Dec 2008 06:59:06 -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/12/t1229090494wslwifldhabgrp8.htm/, Retrieved Fri, 17 May 2024 00:34:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32745, Retrieved Fri, 17 May 2024 00:34:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact191
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  [Standard Deviation-Mean Plot] [Q5 Standard DMP] [2008-11-29 16:26:32] [aa5573c1db401b164e448aef050955a1]
-   PD    [Standard Deviation-Mean Plot] [Q8 SDMN bouwprod] [2008-11-30 00:14:02] [aa5573c1db401b164e448aef050955a1]
-           [Standard Deviation-Mean Plot] [Q8 SDMN bouwprod] [2008-11-30 00:31:28] [aa5573c1db401b164e448aef050955a1]
-   P         [Standard Deviation-Mean Plot] [Standard Deviatio...] [2008-12-12 12:06:26] [aa5573c1db401b164e448aef050955a1]
- RM            [Variance Reduction Matrix] [VRM Bouwproductie] [2008-12-12 13:22:47] [aa5573c1db401b164e448aef050955a1]
- RMP             [(Partial) Autocorrelation Function] [ACF bouwproductie...] [2008-12-12 13:31:29] [aa5573c1db401b164e448aef050955a1]
-   P               [(Partial) Autocorrelation Function] [ACF bouwproductie...] [2008-12-12 13:45:52] [aa5573c1db401b164e448aef050955a1]
-   P                   [(Partial) Autocorrelation Function] [ACF bouwproductie...] [2008-12-12 13:59:06] [8a1195ff8db4df756ce44b463a631c76] [Current]
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Dataseries X:
82.7
88.9
105.9
100.8
94
105
58.5
87.6
113.1
112.5
89.6
74.5
82.7
90.1
109.4
96
89.2
109.1
49.1
92.9
107.7
103.5
91.1
79.8
71.9
82.9
90.1
100.7
90.7
108.8
44.1
93.6
107.4
96.5
93.6
76.5
76.7
84
103.3
88.5
99
105.9
44.7
94
107.1
104.8
102.5
77.7
85.2
91.3
106.5
92.4
97.5
107
51.1
98.6
102.2
114.3
99.4
72.5
92.3
99.4
85.9
109.4
97.6




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32745&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32745&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32745&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.646359-4.6611.1e-05
20.1396011.00670.159376
30.0118530.08550.466106
40.0546110.39380.347669
5-0.176694-1.27420.104137
60.257531.85710.034484
7-0.218721-1.57720.060405
80.0513390.37020.356366
90.0884170.63760.263271
10-0.07005-0.50510.307798
110.0566230.40830.342359
12-0.088727-0.63980.262548
130.0791030.57040.285425
14-0.132551-0.95580.171788
150.2325591.6770.049772
16-0.242774-1.75070.042951
170.1384430.99830.161372
18-0.036168-0.26080.397633
190.0587520.42370.336778
20-0.121332-0.87490.192816
210.1740371.2550.107545
22-0.282923-2.04020.023213
230.3474262.50530.007702
24-0.25995-1.87450.03324
250.0643430.4640.322299
260.0302540.21820.414077
270.0429480.30970.379012
28-0.111775-0.8060.211951
290.1039360.74950.22847
30-0.041661-0.30040.382527
31-0.072087-0.51980.302695
320.1250130.90150.185745
33-0.070675-0.50960.306229
340.0310770.22410.41178
35-0.075791-0.54650.293517
360.1348610.97250.167654

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.646359 & -4.661 & 1.1e-05 \tabularnewline
2 & 0.139601 & 1.0067 & 0.159376 \tabularnewline
3 & 0.011853 & 0.0855 & 0.466106 \tabularnewline
4 & 0.054611 & 0.3938 & 0.347669 \tabularnewline
5 & -0.176694 & -1.2742 & 0.104137 \tabularnewline
6 & 0.25753 & 1.8571 & 0.034484 \tabularnewline
7 & -0.218721 & -1.5772 & 0.060405 \tabularnewline
8 & 0.051339 & 0.3702 & 0.356366 \tabularnewline
9 & 0.088417 & 0.6376 & 0.263271 \tabularnewline
10 & -0.07005 & -0.5051 & 0.307798 \tabularnewline
11 & 0.056623 & 0.4083 & 0.342359 \tabularnewline
12 & -0.088727 & -0.6398 & 0.262548 \tabularnewline
13 & 0.079103 & 0.5704 & 0.285425 \tabularnewline
14 & -0.132551 & -0.9558 & 0.171788 \tabularnewline
15 & 0.232559 & 1.677 & 0.049772 \tabularnewline
16 & -0.242774 & -1.7507 & 0.042951 \tabularnewline
17 & 0.138443 & 0.9983 & 0.161372 \tabularnewline
18 & -0.036168 & -0.2608 & 0.397633 \tabularnewline
19 & 0.058752 & 0.4237 & 0.336778 \tabularnewline
20 & -0.121332 & -0.8749 & 0.192816 \tabularnewline
21 & 0.174037 & 1.255 & 0.107545 \tabularnewline
22 & -0.282923 & -2.0402 & 0.023213 \tabularnewline
23 & 0.347426 & 2.5053 & 0.007702 \tabularnewline
24 & -0.25995 & -1.8745 & 0.03324 \tabularnewline
25 & 0.064343 & 0.464 & 0.322299 \tabularnewline
26 & 0.030254 & 0.2182 & 0.414077 \tabularnewline
27 & 0.042948 & 0.3097 & 0.379012 \tabularnewline
28 & -0.111775 & -0.806 & 0.211951 \tabularnewline
29 & 0.103936 & 0.7495 & 0.22847 \tabularnewline
30 & -0.041661 & -0.3004 & 0.382527 \tabularnewline
31 & -0.072087 & -0.5198 & 0.302695 \tabularnewline
32 & 0.125013 & 0.9015 & 0.185745 \tabularnewline
33 & -0.070675 & -0.5096 & 0.306229 \tabularnewline
34 & 0.031077 & 0.2241 & 0.41178 \tabularnewline
35 & -0.075791 & -0.5465 & 0.293517 \tabularnewline
36 & 0.134861 & 0.9725 & 0.167654 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32745&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]-0.646359[/C][C]-4.661[/C][C]1.1e-05[/C][/ROW]
[ROW][C]2[/C][C]0.139601[/C][C]1.0067[/C][C]0.159376[/C][/ROW]
[ROW][C]3[/C][C]0.011853[/C][C]0.0855[/C][C]0.466106[/C][/ROW]
[ROW][C]4[/C][C]0.054611[/C][C]0.3938[/C][C]0.347669[/C][/ROW]
[ROW][C]5[/C][C]-0.176694[/C][C]-1.2742[/C][C]0.104137[/C][/ROW]
[ROW][C]6[/C][C]0.25753[/C][C]1.8571[/C][C]0.034484[/C][/ROW]
[ROW][C]7[/C][C]-0.218721[/C][C]-1.5772[/C][C]0.060405[/C][/ROW]
[ROW][C]8[/C][C]0.051339[/C][C]0.3702[/C][C]0.356366[/C][/ROW]
[ROW][C]9[/C][C]0.088417[/C][C]0.6376[/C][C]0.263271[/C][/ROW]
[ROW][C]10[/C][C]-0.07005[/C][C]-0.5051[/C][C]0.307798[/C][/ROW]
[ROW][C]11[/C][C]0.056623[/C][C]0.4083[/C][C]0.342359[/C][/ROW]
[ROW][C]12[/C][C]-0.088727[/C][C]-0.6398[/C][C]0.262548[/C][/ROW]
[ROW][C]13[/C][C]0.079103[/C][C]0.5704[/C][C]0.285425[/C][/ROW]
[ROW][C]14[/C][C]-0.132551[/C][C]-0.9558[/C][C]0.171788[/C][/ROW]
[ROW][C]15[/C][C]0.232559[/C][C]1.677[/C][C]0.049772[/C][/ROW]
[ROW][C]16[/C][C]-0.242774[/C][C]-1.7507[/C][C]0.042951[/C][/ROW]
[ROW][C]17[/C][C]0.138443[/C][C]0.9983[/C][C]0.161372[/C][/ROW]
[ROW][C]18[/C][C]-0.036168[/C][C]-0.2608[/C][C]0.397633[/C][/ROW]
[ROW][C]19[/C][C]0.058752[/C][C]0.4237[/C][C]0.336778[/C][/ROW]
[ROW][C]20[/C][C]-0.121332[/C][C]-0.8749[/C][C]0.192816[/C][/ROW]
[ROW][C]21[/C][C]0.174037[/C][C]1.255[/C][C]0.107545[/C][/ROW]
[ROW][C]22[/C][C]-0.282923[/C][C]-2.0402[/C][C]0.023213[/C][/ROW]
[ROW][C]23[/C][C]0.347426[/C][C]2.5053[/C][C]0.007702[/C][/ROW]
[ROW][C]24[/C][C]-0.25995[/C][C]-1.8745[/C][C]0.03324[/C][/ROW]
[ROW][C]25[/C][C]0.064343[/C][C]0.464[/C][C]0.322299[/C][/ROW]
[ROW][C]26[/C][C]0.030254[/C][C]0.2182[/C][C]0.414077[/C][/ROW]
[ROW][C]27[/C][C]0.042948[/C][C]0.3097[/C][C]0.379012[/C][/ROW]
[ROW][C]28[/C][C]-0.111775[/C][C]-0.806[/C][C]0.211951[/C][/ROW]
[ROW][C]29[/C][C]0.103936[/C][C]0.7495[/C][C]0.22847[/C][/ROW]
[ROW][C]30[/C][C]-0.041661[/C][C]-0.3004[/C][C]0.382527[/C][/ROW]
[ROW][C]31[/C][C]-0.072087[/C][C]-0.5198[/C][C]0.302695[/C][/ROW]
[ROW][C]32[/C][C]0.125013[/C][C]0.9015[/C][C]0.185745[/C][/ROW]
[ROW][C]33[/C][C]-0.070675[/C][C]-0.5096[/C][C]0.306229[/C][/ROW]
[ROW][C]34[/C][C]0.031077[/C][C]0.2241[/C][C]0.41178[/C][/ROW]
[ROW][C]35[/C][C]-0.075791[/C][C]-0.5465[/C][C]0.293517[/C][/ROW]
[ROW][C]36[/C][C]0.134861[/C][C]0.9725[/C][C]0.167654[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32745&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32745&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 kACF(k)T-STATP-value
1-0.646359-4.6611.1e-05
20.1396011.00670.159376
30.0118530.08550.466106
40.0546110.39380.347669
5-0.176694-1.27420.104137
60.257531.85710.034484
7-0.218721-1.57720.060405
80.0513390.37020.356366
90.0884170.63760.263271
10-0.07005-0.50510.307798
110.0566230.40830.342359
12-0.088727-0.63980.262548
130.0791030.57040.285425
14-0.132551-0.95580.171788
150.2325591.6770.049772
16-0.242774-1.75070.042951
170.1384430.99830.161372
18-0.036168-0.26080.397633
190.0587520.42370.336778
20-0.121332-0.87490.192816
210.1740371.2550.107545
22-0.282923-2.04020.023213
230.3474262.50530.007702
24-0.25995-1.87450.03324
250.0643430.4640.322299
260.0302540.21820.414077
270.0429480.30970.379012
28-0.111775-0.8060.211951
290.1039360.74950.22847
30-0.041661-0.30040.382527
31-0.072087-0.51980.302695
320.1250130.90150.185745
33-0.070675-0.50960.306229
340.0310770.22410.41178
35-0.075791-0.54650.293517
360.1348610.97250.167654







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.646359-4.6611.1e-05
2-0.47779-3.44540.000568
3-0.364172-2.62610.00566
4-0.133764-0.96460.169608
5-0.302569-2.18190.016831
6-0.045418-0.32750.372296
7-0.074081-0.53420.297737
8-0.203976-1.47090.073673
9-0.092858-0.66960.253036
10-0.060213-0.43420.33297
110.1986881.43280.078956
120.0890320.6420.26184
130.1227170.88490.190136
14-0.152233-1.09780.138681
150.0155470.11210.455584
16-0.061124-0.44080.330603
17-0.108962-0.78570.217793
18-0.05122-0.36940.356683
190.0278730.2010.420743
200.0120510.08690.465542
210.1271480.91690.18172
22-0.205474-1.48170.072228
230.1402091.01110.158335
240.0138770.10010.460336
25-0.118423-0.8540.198521
26-0.202137-1.45760.075477
27-0.113315-0.81710.208792
28-0.050585-0.36480.35838
29-0.116236-0.83820.20288
30-0.034504-0.24880.402244
31-0.065012-0.46880.320583
32-0.052563-0.3790.353101
33-0.006822-0.04920.480476
340.0202810.14630.442145
350.045280.32650.372671
36-0.018038-0.13010.448504

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.646359 & -4.661 & 1.1e-05 \tabularnewline
2 & -0.47779 & -3.4454 & 0.000568 \tabularnewline
3 & -0.364172 & -2.6261 & 0.00566 \tabularnewline
4 & -0.133764 & -0.9646 & 0.169608 \tabularnewline
5 & -0.302569 & -2.1819 & 0.016831 \tabularnewline
6 & -0.045418 & -0.3275 & 0.372296 \tabularnewline
7 & -0.074081 & -0.5342 & 0.297737 \tabularnewline
8 & -0.203976 & -1.4709 & 0.073673 \tabularnewline
9 & -0.092858 & -0.6696 & 0.253036 \tabularnewline
10 & -0.060213 & -0.4342 & 0.33297 \tabularnewline
11 & 0.198688 & 1.4328 & 0.078956 \tabularnewline
12 & 0.089032 & 0.642 & 0.26184 \tabularnewline
13 & 0.122717 & 0.8849 & 0.190136 \tabularnewline
14 & -0.152233 & -1.0978 & 0.138681 \tabularnewline
15 & 0.015547 & 0.1121 & 0.455584 \tabularnewline
16 & -0.061124 & -0.4408 & 0.330603 \tabularnewline
17 & -0.108962 & -0.7857 & 0.217793 \tabularnewline
18 & -0.05122 & -0.3694 & 0.356683 \tabularnewline
19 & 0.027873 & 0.201 & 0.420743 \tabularnewline
20 & 0.012051 & 0.0869 & 0.465542 \tabularnewline
21 & 0.127148 & 0.9169 & 0.18172 \tabularnewline
22 & -0.205474 & -1.4817 & 0.072228 \tabularnewline
23 & 0.140209 & 1.0111 & 0.158335 \tabularnewline
24 & 0.013877 & 0.1001 & 0.460336 \tabularnewline
25 & -0.118423 & -0.854 & 0.198521 \tabularnewline
26 & -0.202137 & -1.4576 & 0.075477 \tabularnewline
27 & -0.113315 & -0.8171 & 0.208792 \tabularnewline
28 & -0.050585 & -0.3648 & 0.35838 \tabularnewline
29 & -0.116236 & -0.8382 & 0.20288 \tabularnewline
30 & -0.034504 & -0.2488 & 0.402244 \tabularnewline
31 & -0.065012 & -0.4688 & 0.320583 \tabularnewline
32 & -0.052563 & -0.379 & 0.353101 \tabularnewline
33 & -0.006822 & -0.0492 & 0.480476 \tabularnewline
34 & 0.020281 & 0.1463 & 0.442145 \tabularnewline
35 & 0.04528 & 0.3265 & 0.372671 \tabularnewline
36 & -0.018038 & -0.1301 & 0.448504 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32745&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]-0.646359[/C][C]-4.661[/C][C]1.1e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.47779[/C][C]-3.4454[/C][C]0.000568[/C][/ROW]
[ROW][C]3[/C][C]-0.364172[/C][C]-2.6261[/C][C]0.00566[/C][/ROW]
[ROW][C]4[/C][C]-0.133764[/C][C]-0.9646[/C][C]0.169608[/C][/ROW]
[ROW][C]5[/C][C]-0.302569[/C][C]-2.1819[/C][C]0.016831[/C][/ROW]
[ROW][C]6[/C][C]-0.045418[/C][C]-0.3275[/C][C]0.372296[/C][/ROW]
[ROW][C]7[/C][C]-0.074081[/C][C]-0.5342[/C][C]0.297737[/C][/ROW]
[ROW][C]8[/C][C]-0.203976[/C][C]-1.4709[/C][C]0.073673[/C][/ROW]
[ROW][C]9[/C][C]-0.092858[/C][C]-0.6696[/C][C]0.253036[/C][/ROW]
[ROW][C]10[/C][C]-0.060213[/C][C]-0.4342[/C][C]0.33297[/C][/ROW]
[ROW][C]11[/C][C]0.198688[/C][C]1.4328[/C][C]0.078956[/C][/ROW]
[ROW][C]12[/C][C]0.089032[/C][C]0.642[/C][C]0.26184[/C][/ROW]
[ROW][C]13[/C][C]0.122717[/C][C]0.8849[/C][C]0.190136[/C][/ROW]
[ROW][C]14[/C][C]-0.152233[/C][C]-1.0978[/C][C]0.138681[/C][/ROW]
[ROW][C]15[/C][C]0.015547[/C][C]0.1121[/C][C]0.455584[/C][/ROW]
[ROW][C]16[/C][C]-0.061124[/C][C]-0.4408[/C][C]0.330603[/C][/ROW]
[ROW][C]17[/C][C]-0.108962[/C][C]-0.7857[/C][C]0.217793[/C][/ROW]
[ROW][C]18[/C][C]-0.05122[/C][C]-0.3694[/C][C]0.356683[/C][/ROW]
[ROW][C]19[/C][C]0.027873[/C][C]0.201[/C][C]0.420743[/C][/ROW]
[ROW][C]20[/C][C]0.012051[/C][C]0.0869[/C][C]0.465542[/C][/ROW]
[ROW][C]21[/C][C]0.127148[/C][C]0.9169[/C][C]0.18172[/C][/ROW]
[ROW][C]22[/C][C]-0.205474[/C][C]-1.4817[/C][C]0.072228[/C][/ROW]
[ROW][C]23[/C][C]0.140209[/C][C]1.0111[/C][C]0.158335[/C][/ROW]
[ROW][C]24[/C][C]0.013877[/C][C]0.1001[/C][C]0.460336[/C][/ROW]
[ROW][C]25[/C][C]-0.118423[/C][C]-0.854[/C][C]0.198521[/C][/ROW]
[ROW][C]26[/C][C]-0.202137[/C][C]-1.4576[/C][C]0.075477[/C][/ROW]
[ROW][C]27[/C][C]-0.113315[/C][C]-0.8171[/C][C]0.208792[/C][/ROW]
[ROW][C]28[/C][C]-0.050585[/C][C]-0.3648[/C][C]0.35838[/C][/ROW]
[ROW][C]29[/C][C]-0.116236[/C][C]-0.8382[/C][C]0.20288[/C][/ROW]
[ROW][C]30[/C][C]-0.034504[/C][C]-0.2488[/C][C]0.402244[/C][/ROW]
[ROW][C]31[/C][C]-0.065012[/C][C]-0.4688[/C][C]0.320583[/C][/ROW]
[ROW][C]32[/C][C]-0.052563[/C][C]-0.379[/C][C]0.353101[/C][/ROW]
[ROW][C]33[/C][C]-0.006822[/C][C]-0.0492[/C][C]0.480476[/C][/ROW]
[ROW][C]34[/C][C]0.020281[/C][C]0.1463[/C][C]0.442145[/C][/ROW]
[ROW][C]35[/C][C]0.04528[/C][C]0.3265[/C][C]0.372671[/C][/ROW]
[ROW][C]36[/C][C]-0.018038[/C][C]-0.1301[/C][C]0.448504[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32745&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32745&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 kPACF(k)T-STATP-value
1-0.646359-4.6611.1e-05
2-0.47779-3.44540.000568
3-0.364172-2.62610.00566
4-0.133764-0.96460.169608
5-0.302569-2.18190.016831
6-0.045418-0.32750.372296
7-0.074081-0.53420.297737
8-0.203976-1.47090.073673
9-0.092858-0.66960.253036
10-0.060213-0.43420.33297
110.1986881.43280.078956
120.0890320.6420.26184
130.1227170.88490.190136
14-0.152233-1.09780.138681
150.0155470.11210.455584
16-0.061124-0.44080.330603
17-0.108962-0.78570.217793
18-0.05122-0.36940.356683
190.0278730.2010.420743
200.0120510.08690.465542
210.1271480.91690.18172
22-0.205474-1.48170.072228
230.1402091.01110.158335
240.0138770.10010.460336
25-0.118423-0.8540.198521
26-0.202137-1.45760.075477
27-0.113315-0.81710.208792
28-0.050585-0.36480.35838
29-0.116236-0.83820.20288
30-0.034504-0.24880.402244
31-0.065012-0.46880.320583
32-0.052563-0.3790.353101
33-0.006822-0.04920.480476
340.0202810.14630.442145
350.045280.32650.372671
36-0.018038-0.13010.448504



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; 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')