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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, 09 Dec 2009 10:37:39 -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/2009/Dec/09/t1260380305fajqky9t7dexybv.htm/, Retrieved Mon, 29 Apr 2024 02:30:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65079, Retrieved Mon, 29 Apr 2024 02:30:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact131

Tree of Dependent Computations

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]
-   PD        [(Partial) Autocorrelation Function] [ws8_2] [2009-11-24 20:22:15] [8b1aef4e7013bd33fbc2a5833375c5f5]
-   PD          [(Partial) Autocorrelation Function] [SHw WS8] [2009-11-25 19:14:01] [af2352cd9a951bedd08ebe247d0de1a2]
-   PD              [(Partial) Autocorrelation Function] [WS10] [2009-12-09 17:37:39] [d9efc2d105d810fc0b0ac636e31105d1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
627
696
825
677
656
785
412
352
839
729
696
641
695
638
762
635
721
854
418
367
824
687
601
676
740
691
683
594
729
731
386
331
707
715
657
653
642
643
718
654
632
731
392
344
792
852
649
629
685
617
715
715
629
916
531
357
917
828
708
858

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65079&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65079&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65079&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2267441.57090.061384
2-0.002886-0.020.492065
30.1997971.38420.086345
40.0034880.02420.49041
50.205961.42690.080036
60.2378731.6480.052939
70.0642580.44520.329091
80.1879681.30230.099517
90.1023940.70940.240751
100.0565250.39160.348537
110.157041.0880.141013
12-0.088341-0.6120.271699
13-0.13774-0.95430.172358
140.1675051.16050.125791
150.0827390.57320.284581
16-0.112673-0.78060.219429
17-0.047472-0.32890.371832
18-0.055301-0.38310.351656
19-0.155802-1.07940.142895
200.0424920.29440.384864
21-0.024254-0.1680.43363
22-0.112137-0.77690.220513
23-0.173275-1.20050.117921
24-0.272273-1.88640.032652
25-0.057047-0.39520.34721
26-0.030253-0.20960.417434
27-0.180337-1.24940.108787
28-0.010929-0.07570.46998
29-0.049097-0.34020.367612
30-0.175319-1.21460.115222
31-0.093059-0.64470.261085
32-0.141435-0.97990.166027
33-0.081686-0.56590.287036
34-0.007118-0.04930.480437
350.026120.1810.428579
360.0395040.27370.392748

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.226744 & 1.5709 & 0.061384 \tabularnewline
2 & -0.002886 & -0.02 & 0.492065 \tabularnewline
3 & 0.199797 & 1.3842 & 0.086345 \tabularnewline
4 & 0.003488 & 0.0242 & 0.49041 \tabularnewline
5 & 0.20596 & 1.4269 & 0.080036 \tabularnewline
6 & 0.237873 & 1.648 & 0.052939 \tabularnewline
7 & 0.064258 & 0.4452 & 0.329091 \tabularnewline
8 & 0.187968 & 1.3023 & 0.099517 \tabularnewline
9 & 0.102394 & 0.7094 & 0.240751 \tabularnewline
10 & 0.056525 & 0.3916 & 0.348537 \tabularnewline
11 & 0.15704 & 1.088 & 0.141013 \tabularnewline
12 & -0.088341 & -0.612 & 0.271699 \tabularnewline
13 & -0.13774 & -0.9543 & 0.172358 \tabularnewline
14 & 0.167505 & 1.1605 & 0.125791 \tabularnewline
15 & 0.082739 & 0.5732 & 0.284581 \tabularnewline
16 & -0.112673 & -0.7806 & 0.219429 \tabularnewline
17 & -0.047472 & -0.3289 & 0.371832 \tabularnewline
18 & -0.055301 & -0.3831 & 0.351656 \tabularnewline
19 & -0.155802 & -1.0794 & 0.142895 \tabularnewline
20 & 0.042492 & 0.2944 & 0.384864 \tabularnewline
21 & -0.024254 & -0.168 & 0.43363 \tabularnewline
22 & -0.112137 & -0.7769 & 0.220513 \tabularnewline
23 & -0.173275 & -1.2005 & 0.117921 \tabularnewline
24 & -0.272273 & -1.8864 & 0.032652 \tabularnewline
25 & -0.057047 & -0.3952 & 0.34721 \tabularnewline
26 & -0.030253 & -0.2096 & 0.417434 \tabularnewline
27 & -0.180337 & -1.2494 & 0.108787 \tabularnewline
28 & -0.010929 & -0.0757 & 0.46998 \tabularnewline
29 & -0.049097 & -0.3402 & 0.367612 \tabularnewline
30 & -0.175319 & -1.2146 & 0.115222 \tabularnewline
31 & -0.093059 & -0.6447 & 0.261085 \tabularnewline
32 & -0.141435 & -0.9799 & 0.166027 \tabularnewline
33 & -0.081686 & -0.5659 & 0.287036 \tabularnewline
34 & -0.007118 & -0.0493 & 0.480437 \tabularnewline
35 & 0.02612 & 0.181 & 0.428579 \tabularnewline
36 & 0.039504 & 0.2737 & 0.392748 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65079&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]0.226744[/C][C]1.5709[/C][C]0.061384[/C][/ROW]
[ROW][C]2[/C][C]-0.002886[/C][C]-0.02[/C][C]0.492065[/C][/ROW]
[ROW][C]3[/C][C]0.199797[/C][C]1.3842[/C][C]0.086345[/C][/ROW]
[ROW][C]4[/C][C]0.003488[/C][C]0.0242[/C][C]0.49041[/C][/ROW]
[ROW][C]5[/C][C]0.20596[/C][C]1.4269[/C][C]0.080036[/C][/ROW]
[ROW][C]6[/C][C]0.237873[/C][C]1.648[/C][C]0.052939[/C][/ROW]
[ROW][C]7[/C][C]0.064258[/C][C]0.4452[/C][C]0.329091[/C][/ROW]
[ROW][C]8[/C][C]0.187968[/C][C]1.3023[/C][C]0.099517[/C][/ROW]
[ROW][C]9[/C][C]0.102394[/C][C]0.7094[/C][C]0.240751[/C][/ROW]
[ROW][C]10[/C][C]0.056525[/C][C]0.3916[/C][C]0.348537[/C][/ROW]
[ROW][C]11[/C][C]0.15704[/C][C]1.088[/C][C]0.141013[/C][/ROW]
[ROW][C]12[/C][C]-0.088341[/C][C]-0.612[/C][C]0.271699[/C][/ROW]
[ROW][C]13[/C][C]-0.13774[/C][C]-0.9543[/C][C]0.172358[/C][/ROW]
[ROW][C]14[/C][C]0.167505[/C][C]1.1605[/C][C]0.125791[/C][/ROW]
[ROW][C]15[/C][C]0.082739[/C][C]0.5732[/C][C]0.284581[/C][/ROW]
[ROW][C]16[/C][C]-0.112673[/C][C]-0.7806[/C][C]0.219429[/C][/ROW]
[ROW][C]17[/C][C]-0.047472[/C][C]-0.3289[/C][C]0.371832[/C][/ROW]
[ROW][C]18[/C][C]-0.055301[/C][C]-0.3831[/C][C]0.351656[/C][/ROW]
[ROW][C]19[/C][C]-0.155802[/C][C]-1.0794[/C][C]0.142895[/C][/ROW]
[ROW][C]20[/C][C]0.042492[/C][C]0.2944[/C][C]0.384864[/C][/ROW]
[ROW][C]21[/C][C]-0.024254[/C][C]-0.168[/C][C]0.43363[/C][/ROW]
[ROW][C]22[/C][C]-0.112137[/C][C]-0.7769[/C][C]0.220513[/C][/ROW]
[ROW][C]23[/C][C]-0.173275[/C][C]-1.2005[/C][C]0.117921[/C][/ROW]
[ROW][C]24[/C][C]-0.272273[/C][C]-1.8864[/C][C]0.032652[/C][/ROW]
[ROW][C]25[/C][C]-0.057047[/C][C]-0.3952[/C][C]0.34721[/C][/ROW]
[ROW][C]26[/C][C]-0.030253[/C][C]-0.2096[/C][C]0.417434[/C][/ROW]
[ROW][C]27[/C][C]-0.180337[/C][C]-1.2494[/C][C]0.108787[/C][/ROW]
[ROW][C]28[/C][C]-0.010929[/C][C]-0.0757[/C][C]0.46998[/C][/ROW]
[ROW][C]29[/C][C]-0.049097[/C][C]-0.3402[/C][C]0.367612[/C][/ROW]
[ROW][C]30[/C][C]-0.175319[/C][C]-1.2146[/C][C]0.115222[/C][/ROW]
[ROW][C]31[/C][C]-0.093059[/C][C]-0.6447[/C][C]0.261085[/C][/ROW]
[ROW][C]32[/C][C]-0.141435[/C][C]-0.9799[/C][C]0.166027[/C][/ROW]
[ROW][C]33[/C][C]-0.081686[/C][C]-0.5659[/C][C]0.287036[/C][/ROW]
[ROW][C]34[/C][C]-0.007118[/C][C]-0.0493[/C][C]0.480437[/C][/ROW]
[ROW][C]35[/C][C]0.02612[/C][C]0.181[/C][C]0.428579[/C][/ROW]
[ROW][C]36[/C][C]0.039504[/C][C]0.2737[/C][C]0.392748[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65079&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65079&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
10.2267441.57090.061384
2-0.002886-0.020.492065
30.1997971.38420.086345
40.0034880.02420.49041
50.205961.42690.080036
60.2378731.6480.052939
70.0642580.44520.329091
80.1879681.30230.099517
90.1023940.70940.240751
100.0565250.39160.348537
110.157041.0880.141013
12-0.088341-0.6120.271699
13-0.13774-0.95430.172358
140.1675051.16050.125791
150.0827390.57320.284581
16-0.112673-0.78060.219429
17-0.047472-0.32890.371832
18-0.055301-0.38310.351656
19-0.155802-1.07940.142895
200.0424920.29440.384864
21-0.024254-0.1680.43363
22-0.112137-0.77690.220513
23-0.173275-1.20050.117921
24-0.272273-1.88640.032652
25-0.057047-0.39520.34721
26-0.030253-0.20960.417434
27-0.180337-1.24940.108787
28-0.010929-0.07570.46998
29-0.049097-0.34020.367612
30-0.175319-1.21460.115222
31-0.093059-0.64470.261085
32-0.141435-0.97990.166027
33-0.081686-0.56590.287036
34-0.007118-0.04930.480437
350.026120.1810.428579
360.0395040.27370.392748






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2267441.57090.061384
2-0.057242-0.39660.346716
30.2257781.56420.062166
4-0.109782-0.76060.225311
50.2880081.99540.025847
60.0630950.43710.331988
70.0667370.46240.322953
80.1104980.76560.223846
90.0001550.00110.499575
100.0423420.29340.385258
110.0273920.18980.425141
12-0.194526-1.34770.092039
13-0.154056-1.06730.145581
140.1336720.92610.179512
150.0034470.02390.490522
16-0.184704-1.27970.103406
17-0.049742-0.34460.365943
180.0369540.2560.399512
19-0.172723-1.19670.118659
200.1250290.86620.195338
21-0.033419-0.23150.408941
22-0.008179-0.05670.477523
23-0.211875-1.46790.074325
24-0.10254-0.71040.240441
25-0.004017-0.02780.488956
260.001850.01280.494914
270.0148440.10280.459258
280.0619790.42940.334776
29-0.015032-0.10410.458745
300.002690.01860.492605
31-0.04022-0.27870.390853
32-0.055707-0.3860.350619
330.1187660.82280.207335
340.0095130.06590.473862
350.0859440.59540.277173
36-0.068176-0.47230.319413

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.226744 & 1.5709 & 0.061384 \tabularnewline
2 & -0.057242 & -0.3966 & 0.346716 \tabularnewline
3 & 0.225778 & 1.5642 & 0.062166 \tabularnewline
4 & -0.109782 & -0.7606 & 0.225311 \tabularnewline
5 & 0.288008 & 1.9954 & 0.025847 \tabularnewline
6 & 0.063095 & 0.4371 & 0.331988 \tabularnewline
7 & 0.066737 & 0.4624 & 0.322953 \tabularnewline
8 & 0.110498 & 0.7656 & 0.223846 \tabularnewline
9 & 0.000155 & 0.0011 & 0.499575 \tabularnewline
10 & 0.042342 & 0.2934 & 0.385258 \tabularnewline
11 & 0.027392 & 0.1898 & 0.425141 \tabularnewline
12 & -0.194526 & -1.3477 & 0.092039 \tabularnewline
13 & -0.154056 & -1.0673 & 0.145581 \tabularnewline
14 & 0.133672 & 0.9261 & 0.179512 \tabularnewline
15 & 0.003447 & 0.0239 & 0.490522 \tabularnewline
16 & -0.184704 & -1.2797 & 0.103406 \tabularnewline
17 & -0.049742 & -0.3446 & 0.365943 \tabularnewline
18 & 0.036954 & 0.256 & 0.399512 \tabularnewline
19 & -0.172723 & -1.1967 & 0.118659 \tabularnewline
20 & 0.125029 & 0.8662 & 0.195338 \tabularnewline
21 & -0.033419 & -0.2315 & 0.408941 \tabularnewline
22 & -0.008179 & -0.0567 & 0.477523 \tabularnewline
23 & -0.211875 & -1.4679 & 0.074325 \tabularnewline
24 & -0.10254 & -0.7104 & 0.240441 \tabularnewline
25 & -0.004017 & -0.0278 & 0.488956 \tabularnewline
26 & 0.00185 & 0.0128 & 0.494914 \tabularnewline
27 & 0.014844 & 0.1028 & 0.459258 \tabularnewline
28 & 0.061979 & 0.4294 & 0.334776 \tabularnewline
29 & -0.015032 & -0.1041 & 0.458745 \tabularnewline
30 & 0.00269 & 0.0186 & 0.492605 \tabularnewline
31 & -0.04022 & -0.2787 & 0.390853 \tabularnewline
32 & -0.055707 & -0.386 & 0.350619 \tabularnewline
33 & 0.118766 & 0.8228 & 0.207335 \tabularnewline
34 & 0.009513 & 0.0659 & 0.473862 \tabularnewline
35 & 0.085944 & 0.5954 & 0.277173 \tabularnewline
36 & -0.068176 & -0.4723 & 0.319413 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65079&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]0.226744[/C][C]1.5709[/C][C]0.061384[/C][/ROW]
[ROW][C]2[/C][C]-0.057242[/C][C]-0.3966[/C][C]0.346716[/C][/ROW]
[ROW][C]3[/C][C]0.225778[/C][C]1.5642[/C][C]0.062166[/C][/ROW]
[ROW][C]4[/C][C]-0.109782[/C][C]-0.7606[/C][C]0.225311[/C][/ROW]
[ROW][C]5[/C][C]0.288008[/C][C]1.9954[/C][C]0.025847[/C][/ROW]
[ROW][C]6[/C][C]0.063095[/C][C]0.4371[/C][C]0.331988[/C][/ROW]
[ROW][C]7[/C][C]0.066737[/C][C]0.4624[/C][C]0.322953[/C][/ROW]
[ROW][C]8[/C][C]0.110498[/C][C]0.7656[/C][C]0.223846[/C][/ROW]
[ROW][C]9[/C][C]0.000155[/C][C]0.0011[/C][C]0.499575[/C][/ROW]
[ROW][C]10[/C][C]0.042342[/C][C]0.2934[/C][C]0.385258[/C][/ROW]
[ROW][C]11[/C][C]0.027392[/C][C]0.1898[/C][C]0.425141[/C][/ROW]
[ROW][C]12[/C][C]-0.194526[/C][C]-1.3477[/C][C]0.092039[/C][/ROW]
[ROW][C]13[/C][C]-0.154056[/C][C]-1.0673[/C][C]0.145581[/C][/ROW]
[ROW][C]14[/C][C]0.133672[/C][C]0.9261[/C][C]0.179512[/C][/ROW]
[ROW][C]15[/C][C]0.003447[/C][C]0.0239[/C][C]0.490522[/C][/ROW]
[ROW][C]16[/C][C]-0.184704[/C][C]-1.2797[/C][C]0.103406[/C][/ROW]
[ROW][C]17[/C][C]-0.049742[/C][C]-0.3446[/C][C]0.365943[/C][/ROW]
[ROW][C]18[/C][C]0.036954[/C][C]0.256[/C][C]0.399512[/C][/ROW]
[ROW][C]19[/C][C]-0.172723[/C][C]-1.1967[/C][C]0.118659[/C][/ROW]
[ROW][C]20[/C][C]0.125029[/C][C]0.8662[/C][C]0.195338[/C][/ROW]
[ROW][C]21[/C][C]-0.033419[/C][C]-0.2315[/C][C]0.408941[/C][/ROW]
[ROW][C]22[/C][C]-0.008179[/C][C]-0.0567[/C][C]0.477523[/C][/ROW]
[ROW][C]23[/C][C]-0.211875[/C][C]-1.4679[/C][C]0.074325[/C][/ROW]
[ROW][C]24[/C][C]-0.10254[/C][C]-0.7104[/C][C]0.240441[/C][/ROW]
[ROW][C]25[/C][C]-0.004017[/C][C]-0.0278[/C][C]0.488956[/C][/ROW]
[ROW][C]26[/C][C]0.00185[/C][C]0.0128[/C][C]0.494914[/C][/ROW]
[ROW][C]27[/C][C]0.014844[/C][C]0.1028[/C][C]0.459258[/C][/ROW]
[ROW][C]28[/C][C]0.061979[/C][C]0.4294[/C][C]0.334776[/C][/ROW]
[ROW][C]29[/C][C]-0.015032[/C][C]-0.1041[/C][C]0.458745[/C][/ROW]
[ROW][C]30[/C][C]0.00269[/C][C]0.0186[/C][C]0.492605[/C][/ROW]
[ROW][C]31[/C][C]-0.04022[/C][C]-0.2787[/C][C]0.390853[/C][/ROW]
[ROW][C]32[/C][C]-0.055707[/C][C]-0.386[/C][C]0.350619[/C][/ROW]
[ROW][C]33[/C][C]0.118766[/C][C]0.8228[/C][C]0.207335[/C][/ROW]
[ROW][C]34[/C][C]0.009513[/C][C]0.0659[/C][C]0.473862[/C][/ROW]
[ROW][C]35[/C][C]0.085944[/C][C]0.5954[/C][C]0.277173[/C][/ROW]
[ROW][C]36[/C][C]-0.068176[/C][C]-0.4723[/C][C]0.319413[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65079&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65079&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
10.2267441.57090.061384
2-0.057242-0.39660.346716
30.2257781.56420.062166
4-0.109782-0.76060.225311
50.2880081.99540.025847
60.0630950.43710.331988
70.0667370.46240.322953
80.1104980.76560.223846
90.0001550.00110.499575
100.0423420.29340.385258
110.0273920.18980.425141
12-0.194526-1.34770.092039
13-0.154056-1.06730.145581
140.1336720.92610.179512
150.0034470.02390.490522
16-0.184704-1.27970.103406
17-0.049742-0.34460.365943
180.0369540.2560.399512
19-0.172723-1.19670.118659
200.1250290.86620.195338
21-0.033419-0.23150.408941
22-0.008179-0.05670.477523
23-0.211875-1.46790.074325
24-0.10254-0.71040.240441
25-0.004017-0.02780.488956
260.001850.01280.494914
270.0148440.10280.459258
280.0619790.42940.334776
29-0.015032-0.10410.458745
300.002690.01860.492605
31-0.04022-0.27870.390853
32-0.055707-0.3860.350619
330.1187660.82280.207335
340.0095130.06590.473862
350.0859440.59540.277173
36-0.068176-0.47230.319413


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
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 (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='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
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')