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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 computationWed, 29 Dec 2010 12:46:43 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/29/t1293626671r0xhbp7hkfaiugr.htm/, Retrieved Fri, 03 May 2024 11:24:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116766, Retrieved Fri, 03 May 2024 11:24:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact150
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [] [2009-11-24 09:55:25] [fef2f8976fa1eef1b54e2cee317fe737]
-    D          [(Partial) Autocorrelation Function] [] [2009-12-18 11:14:21] [fef2f8976fa1eef1b54e2cee317fe737]
- R               [(Partial) Autocorrelation Function] [Paper: ACF] [2010-12-22 20:09:28] [29e492448d11757ae0fad5ef6e7f8e86]
-    D                [(Partial) Autocorrelation Function] [] [2010-12-29 12:46:43] [e180d4cd19004beeddc12e67012247dc] [Current]
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Dataseries X:
04,031636
03,702076
03,056167
03,280707
02,984728
03,693712
03,226317
02,190349
02,599515
03,080288
02,929672
02,922548
03,234943
02,983081
03,284389
03,806511
03,784579
02,645654
03,092081
03,204859
03,107225
03,466909
02,984404
03,218072
02,827310
03,182049
02,236319
02,033218
01,644804
01,627971
01,677559
02,330828
02,493615
02,257172
02,655517
02,298655
02,600402
03,045230
02,790583
03,227052
02,967479
02,938817
03,277961
03,423985
03,072646
02,754253
02,910431
03,174369
03,068387
03,089543
02,906654
02,931161
03,025660
02,939551
02,691019
03,198120
03,076390
02,863873
03,013802
03,053364
02,864753
03,057062
02,959365
03,252258
03,602988
03,497704
03,296867
03,602417
03,300100
03,401930
03,502591
03,402348
03,498551
03,199823
02,700064
02,801034
02,898628
02,800854
02,399942
02,402724
02,202331
02,102594
01,798293
01,202484
01,400201
01,200832
01,298083
01,099742
01,001377
00,836174




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 2 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116766&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116766&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116766&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 time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8039417.62690
20.6739836.3940
30.5960615.65470
40.5078164.81763e-06
50.4191033.9767.1e-05
60.3055892.89910.002351
70.1595521.51360.06681
80.0793120.75240.22688
90.0611040.57970.281787
10-0.009155-0.08690.465492
11-0.080281-0.76160.22414
12-0.146893-1.39360.083442
13-0.187019-1.77420.039704
14-0.209324-1.98580.025048
15-0.195477-1.85450.033474
16-0.211873-2.010.023713
17-0.242828-2.30370.011772
18-0.198215-1.88040.031641
19-0.185892-1.76350.040603
20-0.15534-1.47370.072028
21-0.126551-1.20060.116535
22-0.123806-1.17450.121642
23-0.115599-1.09670.137856
24-0.115221-1.09310.138638
25-0.110949-1.05260.147681
26-0.106458-1.010.157612
27-0.093563-0.88760.188556
28-0.09721-0.92220.179442
29-0.115193-1.09280.138696
30-0.120702-1.14510.127606
31-0.095556-0.90650.183539
32-0.101542-0.96330.168987
33-0.103835-0.98510.163616
34-0.110362-1.0470.148955
35-0.142992-1.35650.08916
36-0.145837-1.38350.084961

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.803941 & 7.6269 & 0 \tabularnewline
2 & 0.673983 & 6.394 & 0 \tabularnewline
3 & 0.596061 & 5.6547 & 0 \tabularnewline
4 & 0.507816 & 4.8176 & 3e-06 \tabularnewline
5 & 0.419103 & 3.976 & 7.1e-05 \tabularnewline
6 & 0.305589 & 2.8991 & 0.002351 \tabularnewline
7 & 0.159552 & 1.5136 & 0.06681 \tabularnewline
8 & 0.079312 & 0.7524 & 0.22688 \tabularnewline
9 & 0.061104 & 0.5797 & 0.281787 \tabularnewline
10 & -0.009155 & -0.0869 & 0.465492 \tabularnewline
11 & -0.080281 & -0.7616 & 0.22414 \tabularnewline
12 & -0.146893 & -1.3936 & 0.083442 \tabularnewline
13 & -0.187019 & -1.7742 & 0.039704 \tabularnewline
14 & -0.209324 & -1.9858 & 0.025048 \tabularnewline
15 & -0.195477 & -1.8545 & 0.033474 \tabularnewline
16 & -0.211873 & -2.01 & 0.023713 \tabularnewline
17 & -0.242828 & -2.3037 & 0.011772 \tabularnewline
18 & -0.198215 & -1.8804 & 0.031641 \tabularnewline
19 & -0.185892 & -1.7635 & 0.040603 \tabularnewline
20 & -0.15534 & -1.4737 & 0.072028 \tabularnewline
21 & -0.126551 & -1.2006 & 0.116535 \tabularnewline
22 & -0.123806 & -1.1745 & 0.121642 \tabularnewline
23 & -0.115599 & -1.0967 & 0.137856 \tabularnewline
24 & -0.115221 & -1.0931 & 0.138638 \tabularnewline
25 & -0.110949 & -1.0526 & 0.147681 \tabularnewline
26 & -0.106458 & -1.01 & 0.157612 \tabularnewline
27 & -0.093563 & -0.8876 & 0.188556 \tabularnewline
28 & -0.09721 & -0.9222 & 0.179442 \tabularnewline
29 & -0.115193 & -1.0928 & 0.138696 \tabularnewline
30 & -0.120702 & -1.1451 & 0.127606 \tabularnewline
31 & -0.095556 & -0.9065 & 0.183539 \tabularnewline
32 & -0.101542 & -0.9633 & 0.168987 \tabularnewline
33 & -0.103835 & -0.9851 & 0.163616 \tabularnewline
34 & -0.110362 & -1.047 & 0.148955 \tabularnewline
35 & -0.142992 & -1.3565 & 0.08916 \tabularnewline
36 & -0.145837 & -1.3835 & 0.084961 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116766&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]0.803941[/C][C]7.6269[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.673983[/C][C]6.394[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.596061[/C][C]5.6547[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.507816[/C][C]4.8176[/C][C]3e-06[/C][/ROW]
[ROW][C]5[/C][C]0.419103[/C][C]3.976[/C][C]7.1e-05[/C][/ROW]
[ROW][C]6[/C][C]0.305589[/C][C]2.8991[/C][C]0.002351[/C][/ROW]
[ROW][C]7[/C][C]0.159552[/C][C]1.5136[/C][C]0.06681[/C][/ROW]
[ROW][C]8[/C][C]0.079312[/C][C]0.7524[/C][C]0.22688[/C][/ROW]
[ROW][C]9[/C][C]0.061104[/C][C]0.5797[/C][C]0.281787[/C][/ROW]
[ROW][C]10[/C][C]-0.009155[/C][C]-0.0869[/C][C]0.465492[/C][/ROW]
[ROW][C]11[/C][C]-0.080281[/C][C]-0.7616[/C][C]0.22414[/C][/ROW]
[ROW][C]12[/C][C]-0.146893[/C][C]-1.3936[/C][C]0.083442[/C][/ROW]
[ROW][C]13[/C][C]-0.187019[/C][C]-1.7742[/C][C]0.039704[/C][/ROW]
[ROW][C]14[/C][C]-0.209324[/C][C]-1.9858[/C][C]0.025048[/C][/ROW]
[ROW][C]15[/C][C]-0.195477[/C][C]-1.8545[/C][C]0.033474[/C][/ROW]
[ROW][C]16[/C][C]-0.211873[/C][C]-2.01[/C][C]0.023713[/C][/ROW]
[ROW][C]17[/C][C]-0.242828[/C][C]-2.3037[/C][C]0.011772[/C][/ROW]
[ROW][C]18[/C][C]-0.198215[/C][C]-1.8804[/C][C]0.031641[/C][/ROW]
[ROW][C]19[/C][C]-0.185892[/C][C]-1.7635[/C][C]0.040603[/C][/ROW]
[ROW][C]20[/C][C]-0.15534[/C][C]-1.4737[/C][C]0.072028[/C][/ROW]
[ROW][C]21[/C][C]-0.126551[/C][C]-1.2006[/C][C]0.116535[/C][/ROW]
[ROW][C]22[/C][C]-0.123806[/C][C]-1.1745[/C][C]0.121642[/C][/ROW]
[ROW][C]23[/C][C]-0.115599[/C][C]-1.0967[/C][C]0.137856[/C][/ROW]
[ROW][C]24[/C][C]-0.115221[/C][C]-1.0931[/C][C]0.138638[/C][/ROW]
[ROW][C]25[/C][C]-0.110949[/C][C]-1.0526[/C][C]0.147681[/C][/ROW]
[ROW][C]26[/C][C]-0.106458[/C][C]-1.01[/C][C]0.157612[/C][/ROW]
[ROW][C]27[/C][C]-0.093563[/C][C]-0.8876[/C][C]0.188556[/C][/ROW]
[ROW][C]28[/C][C]-0.09721[/C][C]-0.9222[/C][C]0.179442[/C][/ROW]
[ROW][C]29[/C][C]-0.115193[/C][C]-1.0928[/C][C]0.138696[/C][/ROW]
[ROW][C]30[/C][C]-0.120702[/C][C]-1.1451[/C][C]0.127606[/C][/ROW]
[ROW][C]31[/C][C]-0.095556[/C][C]-0.9065[/C][C]0.183539[/C][/ROW]
[ROW][C]32[/C][C]-0.101542[/C][C]-0.9633[/C][C]0.168987[/C][/ROW]
[ROW][C]33[/C][C]-0.103835[/C][C]-0.9851[/C][C]0.163616[/C][/ROW]
[ROW][C]34[/C][C]-0.110362[/C][C]-1.047[/C][C]0.148955[/C][/ROW]
[ROW][C]35[/C][C]-0.142992[/C][C]-1.3565[/C][C]0.08916[/C][/ROW]
[ROW][C]36[/C][C]-0.145837[/C][C]-1.3835[/C][C]0.084961[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116766&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116766&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
10.8039417.62690
20.6739836.3940
30.5960615.65470
40.5078164.81763e-06
50.4191033.9767.1e-05
60.3055892.89910.002351
70.1595521.51360.06681
80.0793120.75240.22688
90.0611040.57970.281787
10-0.009155-0.08690.465492
11-0.080281-0.76160.22414
12-0.146893-1.39360.083442
13-0.187019-1.77420.039704
14-0.209324-1.98580.025048
15-0.195477-1.85450.033474
16-0.211873-2.010.023713
17-0.242828-2.30370.011772
18-0.198215-1.88040.031641
19-0.185892-1.76350.040603
20-0.15534-1.47370.072028
21-0.126551-1.20060.116535
22-0.123806-1.17450.121642
23-0.115599-1.09670.137856
24-0.115221-1.09310.138638
25-0.110949-1.05260.147681
26-0.106458-1.010.157612
27-0.093563-0.88760.188556
28-0.09721-0.92220.179442
29-0.115193-1.09280.138696
30-0.120702-1.14510.127606
31-0.095556-0.90650.183539
32-0.101542-0.96330.168987
33-0.103835-0.98510.163616
34-0.110362-1.0470.148955
35-0.142992-1.35650.08916
36-0.145837-1.38350.084961







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8039417.62690
20.0782120.7420.230014
30.0959260.910.182618
4-0.032595-0.30920.378932
5-0.040088-0.38030.352305
6-0.132718-1.25910.10563
7-0.201543-1.9120.029528
80.0198040.18790.4257
90.1267131.20210.116239
10-0.088991-0.84420.200387
11-0.056046-0.53170.298122
12-0.083936-0.79630.21398
13-0.020985-0.19910.421325
14-0.048119-0.45650.324567
150.0809790.76820.222181
16-0.009022-0.08560.465992
17-0.075853-0.71960.236817
180.1029960.97710.165569
19-0.079762-0.75670.225605
200.0379680.36020.359774
21-0.004422-0.0420.483314
22-0.037517-0.35590.361367
23-0.021715-0.2060.418624
24-0.126912-1.2040.115874
250.0085750.08130.467674
260.0031690.03010.488043
270.010780.10230.459385
28-0.009935-0.09430.462559
29-0.094537-0.89690.186093
30-0.020186-0.19150.424281
310.0368610.34970.363694
32-0.041275-0.39160.348151
330.0043580.04130.483558
34-0.03904-0.37040.35599
35-0.088443-0.8390.201835
36-0.067487-0.64020.261823

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.803941 & 7.6269 & 0 \tabularnewline
2 & 0.078212 & 0.742 & 0.230014 \tabularnewline
3 & 0.095926 & 0.91 & 0.182618 \tabularnewline
4 & -0.032595 & -0.3092 & 0.378932 \tabularnewline
5 & -0.040088 & -0.3803 & 0.352305 \tabularnewline
6 & -0.132718 & -1.2591 & 0.10563 \tabularnewline
7 & -0.201543 & -1.912 & 0.029528 \tabularnewline
8 & 0.019804 & 0.1879 & 0.4257 \tabularnewline
9 & 0.126713 & 1.2021 & 0.116239 \tabularnewline
10 & -0.088991 & -0.8442 & 0.200387 \tabularnewline
11 & -0.056046 & -0.5317 & 0.298122 \tabularnewline
12 & -0.083936 & -0.7963 & 0.21398 \tabularnewline
13 & -0.020985 & -0.1991 & 0.421325 \tabularnewline
14 & -0.048119 & -0.4565 & 0.324567 \tabularnewline
15 & 0.080979 & 0.7682 & 0.222181 \tabularnewline
16 & -0.009022 & -0.0856 & 0.465992 \tabularnewline
17 & -0.075853 & -0.7196 & 0.236817 \tabularnewline
18 & 0.102996 & 0.9771 & 0.165569 \tabularnewline
19 & -0.079762 & -0.7567 & 0.225605 \tabularnewline
20 & 0.037968 & 0.3602 & 0.359774 \tabularnewline
21 & -0.004422 & -0.042 & 0.483314 \tabularnewline
22 & -0.037517 & -0.3559 & 0.361367 \tabularnewline
23 & -0.021715 & -0.206 & 0.418624 \tabularnewline
24 & -0.126912 & -1.204 & 0.115874 \tabularnewline
25 & 0.008575 & 0.0813 & 0.467674 \tabularnewline
26 & 0.003169 & 0.0301 & 0.488043 \tabularnewline
27 & 0.01078 & 0.1023 & 0.459385 \tabularnewline
28 & -0.009935 & -0.0943 & 0.462559 \tabularnewline
29 & -0.094537 & -0.8969 & 0.186093 \tabularnewline
30 & -0.020186 & -0.1915 & 0.424281 \tabularnewline
31 & 0.036861 & 0.3497 & 0.363694 \tabularnewline
32 & -0.041275 & -0.3916 & 0.348151 \tabularnewline
33 & 0.004358 & 0.0413 & 0.483558 \tabularnewline
34 & -0.03904 & -0.3704 & 0.35599 \tabularnewline
35 & -0.088443 & -0.839 & 0.201835 \tabularnewline
36 & -0.067487 & -0.6402 & 0.261823 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116766&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]0.803941[/C][C]7.6269[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.078212[/C][C]0.742[/C][C]0.230014[/C][/ROW]
[ROW][C]3[/C][C]0.095926[/C][C]0.91[/C][C]0.182618[/C][/ROW]
[ROW][C]4[/C][C]-0.032595[/C][C]-0.3092[/C][C]0.378932[/C][/ROW]
[ROW][C]5[/C][C]-0.040088[/C][C]-0.3803[/C][C]0.352305[/C][/ROW]
[ROW][C]6[/C][C]-0.132718[/C][C]-1.2591[/C][C]0.10563[/C][/ROW]
[ROW][C]7[/C][C]-0.201543[/C][C]-1.912[/C][C]0.029528[/C][/ROW]
[ROW][C]8[/C][C]0.019804[/C][C]0.1879[/C][C]0.4257[/C][/ROW]
[ROW][C]9[/C][C]0.126713[/C][C]1.2021[/C][C]0.116239[/C][/ROW]
[ROW][C]10[/C][C]-0.088991[/C][C]-0.8442[/C][C]0.200387[/C][/ROW]
[ROW][C]11[/C][C]-0.056046[/C][C]-0.5317[/C][C]0.298122[/C][/ROW]
[ROW][C]12[/C][C]-0.083936[/C][C]-0.7963[/C][C]0.21398[/C][/ROW]
[ROW][C]13[/C][C]-0.020985[/C][C]-0.1991[/C][C]0.421325[/C][/ROW]
[ROW][C]14[/C][C]-0.048119[/C][C]-0.4565[/C][C]0.324567[/C][/ROW]
[ROW][C]15[/C][C]0.080979[/C][C]0.7682[/C][C]0.222181[/C][/ROW]
[ROW][C]16[/C][C]-0.009022[/C][C]-0.0856[/C][C]0.465992[/C][/ROW]
[ROW][C]17[/C][C]-0.075853[/C][C]-0.7196[/C][C]0.236817[/C][/ROW]
[ROW][C]18[/C][C]0.102996[/C][C]0.9771[/C][C]0.165569[/C][/ROW]
[ROW][C]19[/C][C]-0.079762[/C][C]-0.7567[/C][C]0.225605[/C][/ROW]
[ROW][C]20[/C][C]0.037968[/C][C]0.3602[/C][C]0.359774[/C][/ROW]
[ROW][C]21[/C][C]-0.004422[/C][C]-0.042[/C][C]0.483314[/C][/ROW]
[ROW][C]22[/C][C]-0.037517[/C][C]-0.3559[/C][C]0.361367[/C][/ROW]
[ROW][C]23[/C][C]-0.021715[/C][C]-0.206[/C][C]0.418624[/C][/ROW]
[ROW][C]24[/C][C]-0.126912[/C][C]-1.204[/C][C]0.115874[/C][/ROW]
[ROW][C]25[/C][C]0.008575[/C][C]0.0813[/C][C]0.467674[/C][/ROW]
[ROW][C]26[/C][C]0.003169[/C][C]0.0301[/C][C]0.488043[/C][/ROW]
[ROW][C]27[/C][C]0.01078[/C][C]0.1023[/C][C]0.459385[/C][/ROW]
[ROW][C]28[/C][C]-0.009935[/C][C]-0.0943[/C][C]0.462559[/C][/ROW]
[ROW][C]29[/C][C]-0.094537[/C][C]-0.8969[/C][C]0.186093[/C][/ROW]
[ROW][C]30[/C][C]-0.020186[/C][C]-0.1915[/C][C]0.424281[/C][/ROW]
[ROW][C]31[/C][C]0.036861[/C][C]0.3497[/C][C]0.363694[/C][/ROW]
[ROW][C]32[/C][C]-0.041275[/C][C]-0.3916[/C][C]0.348151[/C][/ROW]
[ROW][C]33[/C][C]0.004358[/C][C]0.0413[/C][C]0.483558[/C][/ROW]
[ROW][C]34[/C][C]-0.03904[/C][C]-0.3704[/C][C]0.35599[/C][/ROW]
[ROW][C]35[/C][C]-0.088443[/C][C]-0.839[/C][C]0.201835[/C][/ROW]
[ROW][C]36[/C][C]-0.067487[/C][C]-0.6402[/C][C]0.261823[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116766&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116766&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
10.8039417.62690
20.0782120.7420.230014
30.0959260.910.182618
4-0.032595-0.30920.378932
5-0.040088-0.38030.352305
6-0.132718-1.25910.10563
7-0.201543-1.9120.029528
80.0198040.18790.4257
90.1267131.20210.116239
10-0.088991-0.84420.200387
11-0.056046-0.53170.298122
12-0.083936-0.79630.21398
13-0.020985-0.19910.421325
14-0.048119-0.45650.324567
150.0809790.76820.222181
16-0.009022-0.08560.465992
17-0.075853-0.71960.236817
180.1029960.97710.165569
19-0.079762-0.75670.225605
200.0379680.36020.359774
21-0.004422-0.0420.483314
22-0.037517-0.35590.361367
23-0.021715-0.2060.418624
24-0.126912-1.2040.115874
250.0085750.08130.467674
260.0031690.03010.488043
270.010780.10230.459385
28-0.009935-0.09430.462559
29-0.094537-0.89690.186093
30-0.020186-0.19150.424281
310.0368610.34970.363694
32-0.041275-0.39160.348151
330.0043580.04130.483558
34-0.03904-0.37040.35599
35-0.088443-0.8390.201835
36-0.067487-0.64020.261823



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ; par8 = ;
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 (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')