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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 computationSun, 06 Dec 2009 09:16:37 -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/06/t1260116243jdbw0ekgfhoscjm.htm/, Retrieved Mon, 06 May 2024 02:06:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64444, Retrieved Mon, 06 May 2024 02:06:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109
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] [] [2009-12-06 16:16:37] [0545e25c765ce26b196961216dc11e13] [Current]
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Dataseries X:
9051
8823
8776
8255
7969
8758
8693
8271
7790
7769
8170
8209
9395
9260
9018
8501
8500
9649
9319
8830
8436
8169
8269
7945
9144
8770
8834
7837
7792
8616
8518
7940
7545
7531
7665
7599
8444
8549
7986
7335
7287
7870
7839
7327
7259
6964
7271
6956
7608
7692
7255
6804
6655
7341
7602
7086
6625
6272
6576
6491
7649
7400
6913
6532
6486
7295
7556
7088
6952
6773
6917
7371
8221
7953
8027
7287
8076
8933
9433
9479
9199
9469
10015
10999
13009
13699
13895
13248
13973
15095
15201
14823
14538
14547
14407




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64444&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64444&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64444&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0639090.57870.282181
20.2749712.490.007398
30.1852231.67730.04865
40.0411430.37260.355218
50.1689081.52950.064992
6-0.063662-0.57650.282934
70.0546160.49460.311113
8-0.013514-0.12240.45145
90.0303510.27480.392064
10-0.151751-1.37420.086568
110.0998080.90380.184375
12-0.253078-2.29170.012243
130.0193980.17570.430498
140.0655940.5940.277082
15-0.114641-1.03810.151134
160.1032770.93520.176213
17-0.021667-0.19620.42247
180.0176570.15990.436679
19-0.013013-0.11780.453241
200.0205010.18560.42659
21-0.02423-0.21940.413436
22-0.050331-0.45580.324881
23-0.056626-0.51280.304745
240.0259010.23450.407573
250.095550.86520.194715
26-0.07267-0.65810.256173
270.0151150.13690.445734
28-0.073904-0.66920.252614
29-0.039309-0.3560.361394
300.0240220.21750.41417
31-0.076417-0.6920.245451
320.034760.31480.376869
33-0.050501-0.45730.324331
340.1067150.96630.168357
35-0.023428-0.21220.416258
36-0.107527-0.97370.166534

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.063909 & 0.5787 & 0.282181 \tabularnewline
2 & 0.274971 & 2.49 & 0.007398 \tabularnewline
3 & 0.185223 & 1.6773 & 0.04865 \tabularnewline
4 & 0.041143 & 0.3726 & 0.355218 \tabularnewline
5 & 0.168908 & 1.5295 & 0.064992 \tabularnewline
6 & -0.063662 & -0.5765 & 0.282934 \tabularnewline
7 & 0.054616 & 0.4946 & 0.311113 \tabularnewline
8 & -0.013514 & -0.1224 & 0.45145 \tabularnewline
9 & 0.030351 & 0.2748 & 0.392064 \tabularnewline
10 & -0.151751 & -1.3742 & 0.086568 \tabularnewline
11 & 0.099808 & 0.9038 & 0.184375 \tabularnewline
12 & -0.253078 & -2.2917 & 0.012243 \tabularnewline
13 & 0.019398 & 0.1757 & 0.430498 \tabularnewline
14 & 0.065594 & 0.594 & 0.277082 \tabularnewline
15 & -0.114641 & -1.0381 & 0.151134 \tabularnewline
16 & 0.103277 & 0.9352 & 0.176213 \tabularnewline
17 & -0.021667 & -0.1962 & 0.42247 \tabularnewline
18 & 0.017657 & 0.1599 & 0.436679 \tabularnewline
19 & -0.013013 & -0.1178 & 0.453241 \tabularnewline
20 & 0.020501 & 0.1856 & 0.42659 \tabularnewline
21 & -0.02423 & -0.2194 & 0.413436 \tabularnewline
22 & -0.050331 & -0.4558 & 0.324881 \tabularnewline
23 & -0.056626 & -0.5128 & 0.304745 \tabularnewline
24 & 0.025901 & 0.2345 & 0.407573 \tabularnewline
25 & 0.09555 & 0.8652 & 0.194715 \tabularnewline
26 & -0.07267 & -0.6581 & 0.256173 \tabularnewline
27 & 0.015115 & 0.1369 & 0.445734 \tabularnewline
28 & -0.073904 & -0.6692 & 0.252614 \tabularnewline
29 & -0.039309 & -0.356 & 0.361394 \tabularnewline
30 & 0.024022 & 0.2175 & 0.41417 \tabularnewline
31 & -0.076417 & -0.692 & 0.245451 \tabularnewline
32 & 0.03476 & 0.3148 & 0.376869 \tabularnewline
33 & -0.050501 & -0.4573 & 0.324331 \tabularnewline
34 & 0.106715 & 0.9663 & 0.168357 \tabularnewline
35 & -0.023428 & -0.2122 & 0.416258 \tabularnewline
36 & -0.107527 & -0.9737 & 0.166534 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64444&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]0.063909[/C][C]0.5787[/C][C]0.282181[/C][/ROW]
[ROW][C]2[/C][C]0.274971[/C][C]2.49[/C][C]0.007398[/C][/ROW]
[ROW][C]3[/C][C]0.185223[/C][C]1.6773[/C][C]0.04865[/C][/ROW]
[ROW][C]4[/C][C]0.041143[/C][C]0.3726[/C][C]0.355218[/C][/ROW]
[ROW][C]5[/C][C]0.168908[/C][C]1.5295[/C][C]0.064992[/C][/ROW]
[ROW][C]6[/C][C]-0.063662[/C][C]-0.5765[/C][C]0.282934[/C][/ROW]
[ROW][C]7[/C][C]0.054616[/C][C]0.4946[/C][C]0.311113[/C][/ROW]
[ROW][C]8[/C][C]-0.013514[/C][C]-0.1224[/C][C]0.45145[/C][/ROW]
[ROW][C]9[/C][C]0.030351[/C][C]0.2748[/C][C]0.392064[/C][/ROW]
[ROW][C]10[/C][C]-0.151751[/C][C]-1.3742[/C][C]0.086568[/C][/ROW]
[ROW][C]11[/C][C]0.099808[/C][C]0.9038[/C][C]0.184375[/C][/ROW]
[ROW][C]12[/C][C]-0.253078[/C][C]-2.2917[/C][C]0.012243[/C][/ROW]
[ROW][C]13[/C][C]0.019398[/C][C]0.1757[/C][C]0.430498[/C][/ROW]
[ROW][C]14[/C][C]0.065594[/C][C]0.594[/C][C]0.277082[/C][/ROW]
[ROW][C]15[/C][C]-0.114641[/C][C]-1.0381[/C][C]0.151134[/C][/ROW]
[ROW][C]16[/C][C]0.103277[/C][C]0.9352[/C][C]0.176213[/C][/ROW]
[ROW][C]17[/C][C]-0.021667[/C][C]-0.1962[/C][C]0.42247[/C][/ROW]
[ROW][C]18[/C][C]0.017657[/C][C]0.1599[/C][C]0.436679[/C][/ROW]
[ROW][C]19[/C][C]-0.013013[/C][C]-0.1178[/C][C]0.453241[/C][/ROW]
[ROW][C]20[/C][C]0.020501[/C][C]0.1856[/C][C]0.42659[/C][/ROW]
[ROW][C]21[/C][C]-0.02423[/C][C]-0.2194[/C][C]0.413436[/C][/ROW]
[ROW][C]22[/C][C]-0.050331[/C][C]-0.4558[/C][C]0.324881[/C][/ROW]
[ROW][C]23[/C][C]-0.056626[/C][C]-0.5128[/C][C]0.304745[/C][/ROW]
[ROW][C]24[/C][C]0.025901[/C][C]0.2345[/C][C]0.407573[/C][/ROW]
[ROW][C]25[/C][C]0.09555[/C][C]0.8652[/C][C]0.194715[/C][/ROW]
[ROW][C]26[/C][C]-0.07267[/C][C]-0.6581[/C][C]0.256173[/C][/ROW]
[ROW][C]27[/C][C]0.015115[/C][C]0.1369[/C][C]0.445734[/C][/ROW]
[ROW][C]28[/C][C]-0.073904[/C][C]-0.6692[/C][C]0.252614[/C][/ROW]
[ROW][C]29[/C][C]-0.039309[/C][C]-0.356[/C][C]0.361394[/C][/ROW]
[ROW][C]30[/C][C]0.024022[/C][C]0.2175[/C][C]0.41417[/C][/ROW]
[ROW][C]31[/C][C]-0.076417[/C][C]-0.692[/C][C]0.245451[/C][/ROW]
[ROW][C]32[/C][C]0.03476[/C][C]0.3148[/C][C]0.376869[/C][/ROW]
[ROW][C]33[/C][C]-0.050501[/C][C]-0.4573[/C][C]0.324331[/C][/ROW]
[ROW][C]34[/C][C]0.106715[/C][C]0.9663[/C][C]0.168357[/C][/ROW]
[ROW][C]35[/C][C]-0.023428[/C][C]-0.2122[/C][C]0.416258[/C][/ROW]
[ROW][C]36[/C][C]-0.107527[/C][C]-0.9737[/C][C]0.166534[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64444&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64444&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
10.0639090.57870.282181
20.2749712.490.007398
30.1852231.67730.04865
40.0411430.37260.355218
50.1689081.52950.064992
6-0.063662-0.57650.282934
70.0546160.49460.311113
8-0.013514-0.12240.45145
90.0303510.27480.392064
10-0.151751-1.37420.086568
110.0998080.90380.184375
12-0.253078-2.29170.012243
130.0193980.17570.430498
140.0655940.5940.277082
15-0.114641-1.03810.151134
160.1032770.93520.176213
17-0.021667-0.19620.42247
180.0176570.15990.436679
19-0.013013-0.11780.453241
200.0205010.18560.42659
21-0.02423-0.21940.413436
22-0.050331-0.45580.324881
23-0.056626-0.51280.304745
240.0259010.23450.407573
250.095550.86520.194715
26-0.07267-0.65810.256173
270.0151150.13690.445734
28-0.073904-0.66920.252614
29-0.039309-0.3560.361394
300.0240220.21750.41417
31-0.076417-0.6920.245451
320.034760.31480.376869
33-0.050501-0.45730.324331
340.1067150.96630.168357
35-0.023428-0.21220.416258
36-0.107527-0.97370.166534







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0639090.57870.282181
20.2719982.4630.007935
30.168121.52240.065879
4-0.047302-0.42830.334765
50.0828560.75030.227614
6-0.107656-0.97490.166246
7-0.007695-0.06970.472307
8-0.011978-0.10850.456946
90.0553610.50130.308746
10-0.189613-1.7170.044876
110.1387091.25610.10633
12-0.248171-2.24730.013654
130.0753630.68240.248442
140.1433461.29810.098954
15-0.016623-0.15050.440358
16-0.02157-0.19530.42281
170.1008520.91330.181893
18-0.101941-0.92310.179328
19-0.026661-0.24140.404915
200.0473620.42890.334568
21-0.006846-0.0620.475361
22-0.180523-1.63470.052972
230.0644040.58320.28068
240.0294470.26670.395201
250.1243641.12620.131691
26-0.004503-0.04080.483785
27-0.070572-0.63910.262283
28-0.147583-1.33640.092554
290.0541570.49040.312577
300.0356990.32330.373657
31-0.033383-0.30230.381597
320.0429510.38890.349164
33-0.041419-0.37510.35429
340.0549460.49760.310063
350.0175720.15910.436981
36-0.149957-1.35790.089107

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.063909 & 0.5787 & 0.282181 \tabularnewline
2 & 0.271998 & 2.463 & 0.007935 \tabularnewline
3 & 0.16812 & 1.5224 & 0.065879 \tabularnewline
4 & -0.047302 & -0.4283 & 0.334765 \tabularnewline
5 & 0.082856 & 0.7503 & 0.227614 \tabularnewline
6 & -0.107656 & -0.9749 & 0.166246 \tabularnewline
7 & -0.007695 & -0.0697 & 0.472307 \tabularnewline
8 & -0.011978 & -0.1085 & 0.456946 \tabularnewline
9 & 0.055361 & 0.5013 & 0.308746 \tabularnewline
10 & -0.189613 & -1.717 & 0.044876 \tabularnewline
11 & 0.138709 & 1.2561 & 0.10633 \tabularnewline
12 & -0.248171 & -2.2473 & 0.013654 \tabularnewline
13 & 0.075363 & 0.6824 & 0.248442 \tabularnewline
14 & 0.143346 & 1.2981 & 0.098954 \tabularnewline
15 & -0.016623 & -0.1505 & 0.440358 \tabularnewline
16 & -0.02157 & -0.1953 & 0.42281 \tabularnewline
17 & 0.100852 & 0.9133 & 0.181893 \tabularnewline
18 & -0.101941 & -0.9231 & 0.179328 \tabularnewline
19 & -0.026661 & -0.2414 & 0.404915 \tabularnewline
20 & 0.047362 & 0.4289 & 0.334568 \tabularnewline
21 & -0.006846 & -0.062 & 0.475361 \tabularnewline
22 & -0.180523 & -1.6347 & 0.052972 \tabularnewline
23 & 0.064404 & 0.5832 & 0.28068 \tabularnewline
24 & 0.029447 & 0.2667 & 0.395201 \tabularnewline
25 & 0.124364 & 1.1262 & 0.131691 \tabularnewline
26 & -0.004503 & -0.0408 & 0.483785 \tabularnewline
27 & -0.070572 & -0.6391 & 0.262283 \tabularnewline
28 & -0.147583 & -1.3364 & 0.092554 \tabularnewline
29 & 0.054157 & 0.4904 & 0.312577 \tabularnewline
30 & 0.035699 & 0.3233 & 0.373657 \tabularnewline
31 & -0.033383 & -0.3023 & 0.381597 \tabularnewline
32 & 0.042951 & 0.3889 & 0.349164 \tabularnewline
33 & -0.041419 & -0.3751 & 0.35429 \tabularnewline
34 & 0.054946 & 0.4976 & 0.310063 \tabularnewline
35 & 0.017572 & 0.1591 & 0.436981 \tabularnewline
36 & -0.149957 & -1.3579 & 0.089107 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64444&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]0.063909[/C][C]0.5787[/C][C]0.282181[/C][/ROW]
[ROW][C]2[/C][C]0.271998[/C][C]2.463[/C][C]0.007935[/C][/ROW]
[ROW][C]3[/C][C]0.16812[/C][C]1.5224[/C][C]0.065879[/C][/ROW]
[ROW][C]4[/C][C]-0.047302[/C][C]-0.4283[/C][C]0.334765[/C][/ROW]
[ROW][C]5[/C][C]0.082856[/C][C]0.7503[/C][C]0.227614[/C][/ROW]
[ROW][C]6[/C][C]-0.107656[/C][C]-0.9749[/C][C]0.166246[/C][/ROW]
[ROW][C]7[/C][C]-0.007695[/C][C]-0.0697[/C][C]0.472307[/C][/ROW]
[ROW][C]8[/C][C]-0.011978[/C][C]-0.1085[/C][C]0.456946[/C][/ROW]
[ROW][C]9[/C][C]0.055361[/C][C]0.5013[/C][C]0.308746[/C][/ROW]
[ROW][C]10[/C][C]-0.189613[/C][C]-1.717[/C][C]0.044876[/C][/ROW]
[ROW][C]11[/C][C]0.138709[/C][C]1.2561[/C][C]0.10633[/C][/ROW]
[ROW][C]12[/C][C]-0.248171[/C][C]-2.2473[/C][C]0.013654[/C][/ROW]
[ROW][C]13[/C][C]0.075363[/C][C]0.6824[/C][C]0.248442[/C][/ROW]
[ROW][C]14[/C][C]0.143346[/C][C]1.2981[/C][C]0.098954[/C][/ROW]
[ROW][C]15[/C][C]-0.016623[/C][C]-0.1505[/C][C]0.440358[/C][/ROW]
[ROW][C]16[/C][C]-0.02157[/C][C]-0.1953[/C][C]0.42281[/C][/ROW]
[ROW][C]17[/C][C]0.100852[/C][C]0.9133[/C][C]0.181893[/C][/ROW]
[ROW][C]18[/C][C]-0.101941[/C][C]-0.9231[/C][C]0.179328[/C][/ROW]
[ROW][C]19[/C][C]-0.026661[/C][C]-0.2414[/C][C]0.404915[/C][/ROW]
[ROW][C]20[/C][C]0.047362[/C][C]0.4289[/C][C]0.334568[/C][/ROW]
[ROW][C]21[/C][C]-0.006846[/C][C]-0.062[/C][C]0.475361[/C][/ROW]
[ROW][C]22[/C][C]-0.180523[/C][C]-1.6347[/C][C]0.052972[/C][/ROW]
[ROW][C]23[/C][C]0.064404[/C][C]0.5832[/C][C]0.28068[/C][/ROW]
[ROW][C]24[/C][C]0.029447[/C][C]0.2667[/C][C]0.395201[/C][/ROW]
[ROW][C]25[/C][C]0.124364[/C][C]1.1262[/C][C]0.131691[/C][/ROW]
[ROW][C]26[/C][C]-0.004503[/C][C]-0.0408[/C][C]0.483785[/C][/ROW]
[ROW][C]27[/C][C]-0.070572[/C][C]-0.6391[/C][C]0.262283[/C][/ROW]
[ROW][C]28[/C][C]-0.147583[/C][C]-1.3364[/C][C]0.092554[/C][/ROW]
[ROW][C]29[/C][C]0.054157[/C][C]0.4904[/C][C]0.312577[/C][/ROW]
[ROW][C]30[/C][C]0.035699[/C][C]0.3233[/C][C]0.373657[/C][/ROW]
[ROW][C]31[/C][C]-0.033383[/C][C]-0.3023[/C][C]0.381597[/C][/ROW]
[ROW][C]32[/C][C]0.042951[/C][C]0.3889[/C][C]0.349164[/C][/ROW]
[ROW][C]33[/C][C]-0.041419[/C][C]-0.3751[/C][C]0.35429[/C][/ROW]
[ROW][C]34[/C][C]0.054946[/C][C]0.4976[/C][C]0.310063[/C][/ROW]
[ROW][C]35[/C][C]0.017572[/C][C]0.1591[/C][C]0.436981[/C][/ROW]
[ROW][C]36[/C][C]-0.149957[/C][C]-1.3579[/C][C]0.089107[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64444&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64444&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
10.0639090.57870.282181
20.2719982.4630.007935
30.168121.52240.065879
4-0.047302-0.42830.334765
50.0828560.75030.227614
6-0.107656-0.97490.166246
7-0.007695-0.06970.472307
8-0.011978-0.10850.456946
90.0553610.50130.308746
10-0.189613-1.7170.044876
110.1387091.25610.10633
12-0.248171-2.24730.013654
130.0753630.68240.248442
140.1433461.29810.098954
15-0.016623-0.15050.440358
16-0.02157-0.19530.42281
170.1008520.91330.181893
18-0.101941-0.92310.179328
19-0.026661-0.24140.404915
200.0473620.42890.334568
21-0.006846-0.0620.475361
22-0.180523-1.63470.052972
230.0644040.58320.28068
240.0294470.26670.395201
250.1243641.12620.131691
26-0.004503-0.04080.483785
27-0.070572-0.63910.262283
28-0.147583-1.33640.092554
290.0541570.49040.312577
300.0356990.32330.373657
31-0.033383-0.30230.381597
320.0429510.38890.349164
33-0.041419-0.37510.35429
340.0549460.49760.310063
350.0175720.15910.436981
36-0.149957-1.35790.089107



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; 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')