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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 computationFri, 04 Dec 2009 05:56:52 -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/04/t1259931491hvs2ihzxdmfyxwf.htm/, Retrieved Sat, 27 Apr 2024 16:56:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63444, Retrieved Sat, 27 Apr 2024 16:56:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact124

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [] [2009-11-27 14:48:46] [b98453cac15ba1066b407e146608df68]
-    D      [(Partial) Autocorrelation Function] [Stap 5 Workshop 5] [2009-12-04 12:56:52] [d79e31a57591875d497c91f296c77132] [Current]
-    D        [(Partial) Autocorrelation Function] [stap 5] [2009-12-04 16:42:59] [4b453aa14d54730625f8d3de5f1f6d82]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
91,98
91,72
90,27
91,89
92,07
92,92
93,34
93,60
92,41
93,60
93,77
93,60
93,60
93,51
92,66
94,20
94,37
94,45
94,62
94,37
93,43
94,79
94,88
94,79
94,62
94,71
93,77
95,73
95,99
95,82
95,47
95,82
94,71
96,33
96,50
96,16
96,33
96,33
95,05
96,84
96,92
97,44
97,78
97,69
96,67
98,29
98,20
98,71
98,54
98,20
96,92
99,06
99,65
99,82
99,99
100,33
99,31
101,10
101,10
100,93
100,85
100,93
99,60
101,88
101,81
102,38
102,74
102,82
101,72
103,47
102,98
102,68
102,90
103,03
101,29
103,69
103,68
104,20
104,08
104,16
103,05
104,66
104,46
104,95
105,85
106,23
104,86
107,44
108,23
108,45
109,39
110,15
109,13
110,28
110,17
109,99
109,26
109,11
107,06
109,53
108,92
109,24
109,12
109,00
107,23
109,49
109,04
109,02

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'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=63444&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=63444&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63444&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'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1357831.32340.094432
20.1783031.73790.042736
30.105181.02520.153944
40.2054582.00260.024038
50.021040.20510.418976
60.0926560.90310.184378
70.0326270.3180.375587
8-0.002198-0.02140.491477
9-0.180457-1.75890.040909
10-0.097348-0.94880.172558
110.0661730.6450.260248
12-0.439656-4.28522.2e-05
13-0.164251-1.60090.056357
14-0.078785-0.76790.222225
15-0.014466-0.1410.444085
16-0.122183-1.19090.118331
17-0.117928-1.14940.126634
18-0.060458-0.58930.278538
190.0239420.23340.407993
20-0.060861-0.59320.277229
210.0505650.49280.311628
220.065170.63520.263412
23-0.084454-0.82320.206242
240.0036120.03520.485995
250.0627230.61140.271213
260.0305080.29740.383423
27-0.002892-0.02820.488786
280.0015550.01520.493972
290.0638650.62250.267558
300.0504720.49190.311947
31-0.038927-0.37940.352612
320.0620260.60460.273459
330.0514540.50150.308586
340.0077120.07520.470119
35-0.05399-0.52620.299978
360.0759640.74040.23044

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.135783 & 1.3234 & 0.094432 \tabularnewline
2 & 0.178303 & 1.7379 & 0.042736 \tabularnewline
3 & 0.10518 & 1.0252 & 0.153944 \tabularnewline
4 & 0.205458 & 2.0026 & 0.024038 \tabularnewline
5 & 0.02104 & 0.2051 & 0.418976 \tabularnewline
6 & 0.092656 & 0.9031 & 0.184378 \tabularnewline
7 & 0.032627 & 0.318 & 0.375587 \tabularnewline
8 & -0.002198 & -0.0214 & 0.491477 \tabularnewline
9 & -0.180457 & -1.7589 & 0.040909 \tabularnewline
10 & -0.097348 & -0.9488 & 0.172558 \tabularnewline
11 & 0.066173 & 0.645 & 0.260248 \tabularnewline
12 & -0.439656 & -4.2852 & 2.2e-05 \tabularnewline
13 & -0.164251 & -1.6009 & 0.056357 \tabularnewline
14 & -0.078785 & -0.7679 & 0.222225 \tabularnewline
15 & -0.014466 & -0.141 & 0.444085 \tabularnewline
16 & -0.122183 & -1.1909 & 0.118331 \tabularnewline
17 & -0.117928 & -1.1494 & 0.126634 \tabularnewline
18 & -0.060458 & -0.5893 & 0.278538 \tabularnewline
19 & 0.023942 & 0.2334 & 0.407993 \tabularnewline
20 & -0.060861 & -0.5932 & 0.277229 \tabularnewline
21 & 0.050565 & 0.4928 & 0.311628 \tabularnewline
22 & 0.06517 & 0.6352 & 0.263412 \tabularnewline
23 & -0.084454 & -0.8232 & 0.206242 \tabularnewline
24 & 0.003612 & 0.0352 & 0.485995 \tabularnewline
25 & 0.062723 & 0.6114 & 0.271213 \tabularnewline
26 & 0.030508 & 0.2974 & 0.383423 \tabularnewline
27 & -0.002892 & -0.0282 & 0.488786 \tabularnewline
28 & 0.001555 & 0.0152 & 0.493972 \tabularnewline
29 & 0.063865 & 0.6225 & 0.267558 \tabularnewline
30 & 0.050472 & 0.4919 & 0.311947 \tabularnewline
31 & -0.038927 & -0.3794 & 0.352612 \tabularnewline
32 & 0.062026 & 0.6046 & 0.273459 \tabularnewline
33 & 0.051454 & 0.5015 & 0.308586 \tabularnewline
34 & 0.007712 & 0.0752 & 0.470119 \tabularnewline
35 & -0.05399 & -0.5262 & 0.299978 \tabularnewline
36 & 0.075964 & 0.7404 & 0.23044 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63444&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]0.135783[/C][C]1.3234[/C][C]0.094432[/C][/ROW]
[ROW][C]2[/C][C]0.178303[/C][C]1.7379[/C][C]0.042736[/C][/ROW]
[ROW][C]3[/C][C]0.10518[/C][C]1.0252[/C][C]0.153944[/C][/ROW]
[ROW][C]4[/C][C]0.205458[/C][C]2.0026[/C][C]0.024038[/C][/ROW]
[ROW][C]5[/C][C]0.02104[/C][C]0.2051[/C][C]0.418976[/C][/ROW]
[ROW][C]6[/C][C]0.092656[/C][C]0.9031[/C][C]0.184378[/C][/ROW]
[ROW][C]7[/C][C]0.032627[/C][C]0.318[/C][C]0.375587[/C][/ROW]
[ROW][C]8[/C][C]-0.002198[/C][C]-0.0214[/C][C]0.491477[/C][/ROW]
[ROW][C]9[/C][C]-0.180457[/C][C]-1.7589[/C][C]0.040909[/C][/ROW]
[ROW][C]10[/C][C]-0.097348[/C][C]-0.9488[/C][C]0.172558[/C][/ROW]
[ROW][C]11[/C][C]0.066173[/C][C]0.645[/C][C]0.260248[/C][/ROW]
[ROW][C]12[/C][C]-0.439656[/C][C]-4.2852[/C][C]2.2e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.164251[/C][C]-1.6009[/C][C]0.056357[/C][/ROW]
[ROW][C]14[/C][C]-0.078785[/C][C]-0.7679[/C][C]0.222225[/C][/ROW]
[ROW][C]15[/C][C]-0.014466[/C][C]-0.141[/C][C]0.444085[/C][/ROW]
[ROW][C]16[/C][C]-0.122183[/C][C]-1.1909[/C][C]0.118331[/C][/ROW]
[ROW][C]17[/C][C]-0.117928[/C][C]-1.1494[/C][C]0.126634[/C][/ROW]
[ROW][C]18[/C][C]-0.060458[/C][C]-0.5893[/C][C]0.278538[/C][/ROW]
[ROW][C]19[/C][C]0.023942[/C][C]0.2334[/C][C]0.407993[/C][/ROW]
[ROW][C]20[/C][C]-0.060861[/C][C]-0.5932[/C][C]0.277229[/C][/ROW]
[ROW][C]21[/C][C]0.050565[/C][C]0.4928[/C][C]0.311628[/C][/ROW]
[ROW][C]22[/C][C]0.06517[/C][C]0.6352[/C][C]0.263412[/C][/ROW]
[ROW][C]23[/C][C]-0.084454[/C][C]-0.8232[/C][C]0.206242[/C][/ROW]
[ROW][C]24[/C][C]0.003612[/C][C]0.0352[/C][C]0.485995[/C][/ROW]
[ROW][C]25[/C][C]0.062723[/C][C]0.6114[/C][C]0.271213[/C][/ROW]
[ROW][C]26[/C][C]0.030508[/C][C]0.2974[/C][C]0.383423[/C][/ROW]
[ROW][C]27[/C][C]-0.002892[/C][C]-0.0282[/C][C]0.488786[/C][/ROW]
[ROW][C]28[/C][C]0.001555[/C][C]0.0152[/C][C]0.493972[/C][/ROW]
[ROW][C]29[/C][C]0.063865[/C][C]0.6225[/C][C]0.267558[/C][/ROW]
[ROW][C]30[/C][C]0.050472[/C][C]0.4919[/C][C]0.311947[/C][/ROW]
[ROW][C]31[/C][C]-0.038927[/C][C]-0.3794[/C][C]0.352612[/C][/ROW]
[ROW][C]32[/C][C]0.062026[/C][C]0.6046[/C][C]0.273459[/C][/ROW]
[ROW][C]33[/C][C]0.051454[/C][C]0.5015[/C][C]0.308586[/C][/ROW]
[ROW][C]34[/C][C]0.007712[/C][C]0.0752[/C][C]0.470119[/C][/ROW]
[ROW][C]35[/C][C]-0.05399[/C][C]-0.5262[/C][C]0.299978[/C][/ROW]
[ROW][C]36[/C][C]0.075964[/C][C]0.7404[/C][C]0.23044[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63444&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63444&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
10.1357831.32340.094432
20.1783031.73790.042736
30.105181.02520.153944
40.2054582.00260.024038
50.021040.20510.418976
60.0926560.90310.184378
70.0326270.3180.375587
8-0.002198-0.02140.491477
9-0.180457-1.75890.040909
10-0.097348-0.94880.172558
110.0661730.6450.260248
12-0.439656-4.28522.2e-05
13-0.164251-1.60090.056357
14-0.078785-0.76790.222225
15-0.014466-0.1410.444085
16-0.122183-1.19090.118331
17-0.117928-1.14940.126634
18-0.060458-0.58930.278538
190.0239420.23340.407993
20-0.060861-0.59320.277229
210.0505650.49280.311628
220.065170.63520.263412
23-0.084454-0.82320.206242
240.0036120.03520.485995
250.0627230.61140.271213
260.0305080.29740.383423
27-0.002892-0.02820.488786
280.0015550.01520.493972
290.0638650.62250.267558
300.0504720.49190.311947
31-0.038927-0.37940.352612
320.0620260.60460.273459
330.0514540.50150.308586
340.0077120.07520.470119
35-0.05399-0.52620.299978
360.0759640.74040.23044






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1357831.32340.094432
20.1628691.58750.057867
30.0657210.64060.261673
40.1660681.61860.054422
5-0.046177-0.45010.32684
60.0364270.35510.361669
7-0.004009-0.03910.484457
8-0.05764-0.56180.287785
9-0.19632-1.91350.029348
10-0.088777-0.86530.194529
110.1504021.46590.072984
12-0.464296-4.52549e-06
13-0.021241-0.2070.418215
140.1155331.12610.131485
150.0378810.36920.356395
160.0632350.61630.269573
17-0.151865-1.48020.071065
180.0382670.3730.354998
190.0958510.93420.176273
20-0.014421-0.14060.44426
21-0.097812-0.95340.171415
22-0.048141-0.46920.319992
230.0620860.60510.273263
24-0.208495-2.03220.022465
25-0.012315-0.120.452354
260.0057540.05610.477698
270.0385230.37550.354071
280.0886220.86380.194941
29-0.100004-0.97470.166087
300.0406160.39590.346544
310.0385340.37560.354033
320.0786330.76640.222664
33-0.032855-0.32020.374749
34-0.037354-0.36410.358302
35-0.089474-0.87210.192681
36-0.001476-0.01440.494277

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.135783 & 1.3234 & 0.094432 \tabularnewline
2 & 0.162869 & 1.5875 & 0.057867 \tabularnewline
3 & 0.065721 & 0.6406 & 0.261673 \tabularnewline
4 & 0.166068 & 1.6186 & 0.054422 \tabularnewline
5 & -0.046177 & -0.4501 & 0.32684 \tabularnewline
6 & 0.036427 & 0.3551 & 0.361669 \tabularnewline
7 & -0.004009 & -0.0391 & 0.484457 \tabularnewline
8 & -0.05764 & -0.5618 & 0.287785 \tabularnewline
9 & -0.19632 & -1.9135 & 0.029348 \tabularnewline
10 & -0.088777 & -0.8653 & 0.194529 \tabularnewline
11 & 0.150402 & 1.4659 & 0.072984 \tabularnewline
12 & -0.464296 & -4.5254 & 9e-06 \tabularnewline
13 & -0.021241 & -0.207 & 0.418215 \tabularnewline
14 & 0.115533 & 1.1261 & 0.131485 \tabularnewline
15 & 0.037881 & 0.3692 & 0.356395 \tabularnewline
16 & 0.063235 & 0.6163 & 0.269573 \tabularnewline
17 & -0.151865 & -1.4802 & 0.071065 \tabularnewline
18 & 0.038267 & 0.373 & 0.354998 \tabularnewline
19 & 0.095851 & 0.9342 & 0.176273 \tabularnewline
20 & -0.014421 & -0.1406 & 0.44426 \tabularnewline
21 & -0.097812 & -0.9534 & 0.171415 \tabularnewline
22 & -0.048141 & -0.4692 & 0.319992 \tabularnewline
23 & 0.062086 & 0.6051 & 0.273263 \tabularnewline
24 & -0.208495 & -2.0322 & 0.022465 \tabularnewline
25 & -0.012315 & -0.12 & 0.452354 \tabularnewline
26 & 0.005754 & 0.0561 & 0.477698 \tabularnewline
27 & 0.038523 & 0.3755 & 0.354071 \tabularnewline
28 & 0.088622 & 0.8638 & 0.194941 \tabularnewline
29 & -0.100004 & -0.9747 & 0.166087 \tabularnewline
30 & 0.040616 & 0.3959 & 0.346544 \tabularnewline
31 & 0.038534 & 0.3756 & 0.354033 \tabularnewline
32 & 0.078633 & 0.7664 & 0.222664 \tabularnewline
33 & -0.032855 & -0.3202 & 0.374749 \tabularnewline
34 & -0.037354 & -0.3641 & 0.358302 \tabularnewline
35 & -0.089474 & -0.8721 & 0.192681 \tabularnewline
36 & -0.001476 & -0.0144 & 0.494277 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63444&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]0.135783[/C][C]1.3234[/C][C]0.094432[/C][/ROW]
[ROW][C]2[/C][C]0.162869[/C][C]1.5875[/C][C]0.057867[/C][/ROW]
[ROW][C]3[/C][C]0.065721[/C][C]0.6406[/C][C]0.261673[/C][/ROW]
[ROW][C]4[/C][C]0.166068[/C][C]1.6186[/C][C]0.054422[/C][/ROW]
[ROW][C]5[/C][C]-0.046177[/C][C]-0.4501[/C][C]0.32684[/C][/ROW]
[ROW][C]6[/C][C]0.036427[/C][C]0.3551[/C][C]0.361669[/C][/ROW]
[ROW][C]7[/C][C]-0.004009[/C][C]-0.0391[/C][C]0.484457[/C][/ROW]
[ROW][C]8[/C][C]-0.05764[/C][C]-0.5618[/C][C]0.287785[/C][/ROW]
[ROW][C]9[/C][C]-0.19632[/C][C]-1.9135[/C][C]0.029348[/C][/ROW]
[ROW][C]10[/C][C]-0.088777[/C][C]-0.8653[/C][C]0.194529[/C][/ROW]
[ROW][C]11[/C][C]0.150402[/C][C]1.4659[/C][C]0.072984[/C][/ROW]
[ROW][C]12[/C][C]-0.464296[/C][C]-4.5254[/C][C]9e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.021241[/C][C]-0.207[/C][C]0.418215[/C][/ROW]
[ROW][C]14[/C][C]0.115533[/C][C]1.1261[/C][C]0.131485[/C][/ROW]
[ROW][C]15[/C][C]0.037881[/C][C]0.3692[/C][C]0.356395[/C][/ROW]
[ROW][C]16[/C][C]0.063235[/C][C]0.6163[/C][C]0.269573[/C][/ROW]
[ROW][C]17[/C][C]-0.151865[/C][C]-1.4802[/C][C]0.071065[/C][/ROW]
[ROW][C]18[/C][C]0.038267[/C][C]0.373[/C][C]0.354998[/C][/ROW]
[ROW][C]19[/C][C]0.095851[/C][C]0.9342[/C][C]0.176273[/C][/ROW]
[ROW][C]20[/C][C]-0.014421[/C][C]-0.1406[/C][C]0.44426[/C][/ROW]
[ROW][C]21[/C][C]-0.097812[/C][C]-0.9534[/C][C]0.171415[/C][/ROW]
[ROW][C]22[/C][C]-0.048141[/C][C]-0.4692[/C][C]0.319992[/C][/ROW]
[ROW][C]23[/C][C]0.062086[/C][C]0.6051[/C][C]0.273263[/C][/ROW]
[ROW][C]24[/C][C]-0.208495[/C][C]-2.0322[/C][C]0.022465[/C][/ROW]
[ROW][C]25[/C][C]-0.012315[/C][C]-0.12[/C][C]0.452354[/C][/ROW]
[ROW][C]26[/C][C]0.005754[/C][C]0.0561[/C][C]0.477698[/C][/ROW]
[ROW][C]27[/C][C]0.038523[/C][C]0.3755[/C][C]0.354071[/C][/ROW]
[ROW][C]28[/C][C]0.088622[/C][C]0.8638[/C][C]0.194941[/C][/ROW]
[ROW][C]29[/C][C]-0.100004[/C][C]-0.9747[/C][C]0.166087[/C][/ROW]
[ROW][C]30[/C][C]0.040616[/C][C]0.3959[/C][C]0.346544[/C][/ROW]
[ROW][C]31[/C][C]0.038534[/C][C]0.3756[/C][C]0.354033[/C][/ROW]
[ROW][C]32[/C][C]0.078633[/C][C]0.7664[/C][C]0.222664[/C][/ROW]
[ROW][C]33[/C][C]-0.032855[/C][C]-0.3202[/C][C]0.374749[/C][/ROW]
[ROW][C]34[/C][C]-0.037354[/C][C]-0.3641[/C][C]0.358302[/C][/ROW]
[ROW][C]35[/C][C]-0.089474[/C][C]-0.8721[/C][C]0.192681[/C][/ROW]
[ROW][C]36[/C][C]-0.001476[/C][C]-0.0144[/C][C]0.494277[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63444&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63444&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
10.1357831.32340.094432
20.1628691.58750.057867
30.0657210.64060.261673
40.1660681.61860.054422
5-0.046177-0.45010.32684
60.0364270.35510.361669
7-0.004009-0.03910.484457
8-0.05764-0.56180.287785
9-0.19632-1.91350.029348
10-0.088777-0.86530.194529
110.1504021.46590.072984
12-0.464296-4.52549e-06
13-0.021241-0.2070.418215
140.1155331.12610.131485
150.0378810.36920.356395
160.0632350.61630.269573
17-0.151865-1.48020.071065
180.0382670.3730.354998
190.0958510.93420.176273
20-0.014421-0.14060.44426
21-0.097812-0.95340.171415
22-0.048141-0.46920.319992
230.0620860.60510.273263
24-0.208495-2.03220.022465
25-0.012315-0.120.452354
260.0057540.05610.477698
270.0385230.37550.354071
280.0886220.86380.194941
29-0.100004-0.97470.166087
300.0406160.39590.346544
310.0385340.37560.354033
320.0786330.76640.222664
33-0.032855-0.32020.374749
34-0.037354-0.36410.358302
35-0.089474-0.87210.192681
36-0.001476-0.01440.494277


Figures (Output of Computation)

Input Parameters & R Code

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')