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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 computationTue, 15 Dec 2009 17:39:56 -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/16/t1260924043ievwwnnbepzfmkk.htm/, Retrieved Tue, 30 Apr 2024 20:02:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68203, Retrieved Tue, 30 Apr 2024 20:02:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact156
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 12:26:39] [b98453cac15ba1066b407e146608df68]
-   PD        [(Partial) Autocorrelation Function] [Shwws8_v1] [2009-11-27 19:33:40] [5f89c040fdf1f8599c99d7f78a662321]
-   PD            [(Partial) Autocorrelation Function] [Paper] [2009-12-16 00:39:56] [93b66894f6318f3da4fcda772f2ffa6f] [Current]
-    D              [(Partial) Autocorrelation Function] [Paper] [2009-12-16 00:52:21] [5f89c040fdf1f8599c99d7f78a662321]
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Dataseries X:
102.1
102.86
102.99
103.73
105.02
104.43
104.63
104.93
105.87
105.66
106.76
106
107.22
107.33
107.11
108.86
107.72
107.88
108.38
107.72
108.41
109.9
111.45
112.18
113.34
113.46
114.06
115.54
116.39
115.94
116.97
115.94
115.91
116.43
116.26
116.35
117.9
117.7
117.53
117.86
117.65
116.51
115.93
115.31
115
115.45
115.83




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=68203&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=68203&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68203&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
10.0017440.01020.495974
20.2306681.3450.093762
30.2044841.19230.120693
4-0.02195-0.1280.449455
50.07740.45130.327313
60.0324680.18930.425483
70.0424860.24770.402915
80.0717230.41820.339211
9-0.076254-0.44460.329701
10-0.126817-0.73950.23235
11-0.133662-0.77940.220574
12-0.415959-2.42540.010375
130.0053130.0310.487734
14-0.25526-1.48840.07293
150.0400390.23350.408401
16-0.122916-0.71670.239222
17-0.138451-0.80730.212553
180.0288390.16820.433728
19-0.118798-0.69270.246599
20-0.029452-0.17170.432333
21-0.026134-0.15240.439892
220.0576530.33620.369403
230.0762040.44430.329806
240.0025340.01480.49415
250.0318570.18580.42687
260.1184360.69060.247255
27-0.100589-0.58650.280698
280.0611080.35630.361903
290.029270.17070.432748
30-0.057375-0.33460.37001
310.028490.16610.434522
32-0.005807-0.03390.486594
33-0.011288-0.06580.473952
34NANANA
35NANANA
36NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.001744 & 0.0102 & 0.495974 \tabularnewline
2 & 0.230668 & 1.345 & 0.093762 \tabularnewline
3 & 0.204484 & 1.1923 & 0.120693 \tabularnewline
4 & -0.02195 & -0.128 & 0.449455 \tabularnewline
5 & 0.0774 & 0.4513 & 0.327313 \tabularnewline
6 & 0.032468 & 0.1893 & 0.425483 \tabularnewline
7 & 0.042486 & 0.2477 & 0.402915 \tabularnewline
8 & 0.071723 & 0.4182 & 0.339211 \tabularnewline
9 & -0.076254 & -0.4446 & 0.329701 \tabularnewline
10 & -0.126817 & -0.7395 & 0.23235 \tabularnewline
11 & -0.133662 & -0.7794 & 0.220574 \tabularnewline
12 & -0.415959 & -2.4254 & 0.010375 \tabularnewline
13 & 0.005313 & 0.031 & 0.487734 \tabularnewline
14 & -0.25526 & -1.4884 & 0.07293 \tabularnewline
15 & 0.040039 & 0.2335 & 0.408401 \tabularnewline
16 & -0.122916 & -0.7167 & 0.239222 \tabularnewline
17 & -0.138451 & -0.8073 & 0.212553 \tabularnewline
18 & 0.028839 & 0.1682 & 0.433728 \tabularnewline
19 & -0.118798 & -0.6927 & 0.246599 \tabularnewline
20 & -0.029452 & -0.1717 & 0.432333 \tabularnewline
21 & -0.026134 & -0.1524 & 0.439892 \tabularnewline
22 & 0.057653 & 0.3362 & 0.369403 \tabularnewline
23 & 0.076204 & 0.4443 & 0.329806 \tabularnewline
24 & 0.002534 & 0.0148 & 0.49415 \tabularnewline
25 & 0.031857 & 0.1858 & 0.42687 \tabularnewline
26 & 0.118436 & 0.6906 & 0.247255 \tabularnewline
27 & -0.100589 & -0.5865 & 0.280698 \tabularnewline
28 & 0.061108 & 0.3563 & 0.361903 \tabularnewline
29 & 0.02927 & 0.1707 & 0.432748 \tabularnewline
30 & -0.057375 & -0.3346 & 0.37001 \tabularnewline
31 & 0.02849 & 0.1661 & 0.434522 \tabularnewline
32 & -0.005807 & -0.0339 & 0.486594 \tabularnewline
33 & -0.011288 & -0.0658 & 0.473952 \tabularnewline
34 & NA & NA & NA \tabularnewline
35 & NA & NA & NA \tabularnewline
36 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68203&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]0.001744[/C][C]0.0102[/C][C]0.495974[/C][/ROW]
[ROW][C]2[/C][C]0.230668[/C][C]1.345[/C][C]0.093762[/C][/ROW]
[ROW][C]3[/C][C]0.204484[/C][C]1.1923[/C][C]0.120693[/C][/ROW]
[ROW][C]4[/C][C]-0.02195[/C][C]-0.128[/C][C]0.449455[/C][/ROW]
[ROW][C]5[/C][C]0.0774[/C][C]0.4513[/C][C]0.327313[/C][/ROW]
[ROW][C]6[/C][C]0.032468[/C][C]0.1893[/C][C]0.425483[/C][/ROW]
[ROW][C]7[/C][C]0.042486[/C][C]0.2477[/C][C]0.402915[/C][/ROW]
[ROW][C]8[/C][C]0.071723[/C][C]0.4182[/C][C]0.339211[/C][/ROW]
[ROW][C]9[/C][C]-0.076254[/C][C]-0.4446[/C][C]0.329701[/C][/ROW]
[ROW][C]10[/C][C]-0.126817[/C][C]-0.7395[/C][C]0.23235[/C][/ROW]
[ROW][C]11[/C][C]-0.133662[/C][C]-0.7794[/C][C]0.220574[/C][/ROW]
[ROW][C]12[/C][C]-0.415959[/C][C]-2.4254[/C][C]0.010375[/C][/ROW]
[ROW][C]13[/C][C]0.005313[/C][C]0.031[/C][C]0.487734[/C][/ROW]
[ROW][C]14[/C][C]-0.25526[/C][C]-1.4884[/C][C]0.07293[/C][/ROW]
[ROW][C]15[/C][C]0.040039[/C][C]0.2335[/C][C]0.408401[/C][/ROW]
[ROW][C]16[/C][C]-0.122916[/C][C]-0.7167[/C][C]0.239222[/C][/ROW]
[ROW][C]17[/C][C]-0.138451[/C][C]-0.8073[/C][C]0.212553[/C][/ROW]
[ROW][C]18[/C][C]0.028839[/C][C]0.1682[/C][C]0.433728[/C][/ROW]
[ROW][C]19[/C][C]-0.118798[/C][C]-0.6927[/C][C]0.246599[/C][/ROW]
[ROW][C]20[/C][C]-0.029452[/C][C]-0.1717[/C][C]0.432333[/C][/ROW]
[ROW][C]21[/C][C]-0.026134[/C][C]-0.1524[/C][C]0.439892[/C][/ROW]
[ROW][C]22[/C][C]0.057653[/C][C]0.3362[/C][C]0.369403[/C][/ROW]
[ROW][C]23[/C][C]0.076204[/C][C]0.4443[/C][C]0.329806[/C][/ROW]
[ROW][C]24[/C][C]0.002534[/C][C]0.0148[/C][C]0.49415[/C][/ROW]
[ROW][C]25[/C][C]0.031857[/C][C]0.1858[/C][C]0.42687[/C][/ROW]
[ROW][C]26[/C][C]0.118436[/C][C]0.6906[/C][C]0.247255[/C][/ROW]
[ROW][C]27[/C][C]-0.100589[/C][C]-0.5865[/C][C]0.280698[/C][/ROW]
[ROW][C]28[/C][C]0.061108[/C][C]0.3563[/C][C]0.361903[/C][/ROW]
[ROW][C]29[/C][C]0.02927[/C][C]0.1707[/C][C]0.432748[/C][/ROW]
[ROW][C]30[/C][C]-0.057375[/C][C]-0.3346[/C][C]0.37001[/C][/ROW]
[ROW][C]31[/C][C]0.02849[/C][C]0.1661[/C][C]0.434522[/C][/ROW]
[ROW][C]32[/C][C]-0.005807[/C][C]-0.0339[/C][C]0.486594[/C][/ROW]
[ROW][C]33[/C][C]-0.011288[/C][C]-0.0658[/C][C]0.473952[/C][/ROW]
[ROW][C]34[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]35[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]36[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68203&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68203&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
10.0017440.01020.495974
20.2306681.3450.093762
30.2044841.19230.120693
4-0.02195-0.1280.449455
50.07740.45130.327313
60.0324680.18930.425483
70.0424860.24770.402915
80.0717230.41820.339211
9-0.076254-0.44460.329701
10-0.126817-0.73950.23235
11-0.133662-0.77940.220574
12-0.415959-2.42540.010375
130.0053130.0310.487734
14-0.25526-1.48840.07293
150.0400390.23350.408401
16-0.122916-0.71670.239222
17-0.138451-0.80730.212553
180.0288390.16820.433728
19-0.118798-0.69270.246599
20-0.029452-0.17170.432333
21-0.026134-0.15240.439892
220.0576530.33620.369403
230.0762040.44430.329806
240.0025340.01480.49415
250.0318570.18580.42687
260.1184360.69060.247255
27-0.100589-0.58650.280698
280.0611080.35630.361903
290.029270.17070.432748
30-0.057375-0.33460.37001
310.028490.16610.434522
32-0.005807-0.03390.486594
33-0.011288-0.06580.473952
34NANANA
35NANANA
36NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0017440.01020.495974
20.2306661.3450.093764
30.2152241.2550.109025
4-0.07264-0.42360.337277
5-0.025114-0.14640.44222
60.0146020.08510.466324
70.0558420.32560.373357
80.0559380.32620.373146
9-0.112122-0.65380.258826
10-0.202705-1.1820.12271
11-0.145158-0.84640.201622
12-0.373762-2.17940.018163
130.0762510.44460.329706
14-0.054394-0.31720.376528
150.2092621.22020.115393
16-0.103966-0.60620.274198
17-0.109106-0.63620.264455
180.0560350.32670.372935
190.0682130.39770.346652
200.051670.30130.382517
21-0.133687-0.77950.220532
22-0.052726-0.30740.380192
23-0.025116-0.14650.442215
24-0.170076-0.99170.164174
250.0355080.2070.418606
260.0434790.25350.400696
270.0002710.00160.499373
28-0.169683-0.98940.164725
29-0.033279-0.19410.423646
30-0.019879-0.11590.454202
31-0.000131-8e-040.499697
320.0603750.3520.363489
33-0.099583-0.58070.282648
34NANANA
35NANANA
36NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.001744 & 0.0102 & 0.495974 \tabularnewline
2 & 0.230666 & 1.345 & 0.093764 \tabularnewline
3 & 0.215224 & 1.255 & 0.109025 \tabularnewline
4 & -0.07264 & -0.4236 & 0.337277 \tabularnewline
5 & -0.025114 & -0.1464 & 0.44222 \tabularnewline
6 & 0.014602 & 0.0851 & 0.466324 \tabularnewline
7 & 0.055842 & 0.3256 & 0.373357 \tabularnewline
8 & 0.055938 & 0.3262 & 0.373146 \tabularnewline
9 & -0.112122 & -0.6538 & 0.258826 \tabularnewline
10 & -0.202705 & -1.182 & 0.12271 \tabularnewline
11 & -0.145158 & -0.8464 & 0.201622 \tabularnewline
12 & -0.373762 & -2.1794 & 0.018163 \tabularnewline
13 & 0.076251 & 0.4446 & 0.329706 \tabularnewline
14 & -0.054394 & -0.3172 & 0.376528 \tabularnewline
15 & 0.209262 & 1.2202 & 0.115393 \tabularnewline
16 & -0.103966 & -0.6062 & 0.274198 \tabularnewline
17 & -0.109106 & -0.6362 & 0.264455 \tabularnewline
18 & 0.056035 & 0.3267 & 0.372935 \tabularnewline
19 & 0.068213 & 0.3977 & 0.346652 \tabularnewline
20 & 0.05167 & 0.3013 & 0.382517 \tabularnewline
21 & -0.133687 & -0.7795 & 0.220532 \tabularnewline
22 & -0.052726 & -0.3074 & 0.380192 \tabularnewline
23 & -0.025116 & -0.1465 & 0.442215 \tabularnewline
24 & -0.170076 & -0.9917 & 0.164174 \tabularnewline
25 & 0.035508 & 0.207 & 0.418606 \tabularnewline
26 & 0.043479 & 0.2535 & 0.400696 \tabularnewline
27 & 0.000271 & 0.0016 & 0.499373 \tabularnewline
28 & -0.169683 & -0.9894 & 0.164725 \tabularnewline
29 & -0.033279 & -0.1941 & 0.423646 \tabularnewline
30 & -0.019879 & -0.1159 & 0.454202 \tabularnewline
31 & -0.000131 & -8e-04 & 0.499697 \tabularnewline
32 & 0.060375 & 0.352 & 0.363489 \tabularnewline
33 & -0.099583 & -0.5807 & 0.282648 \tabularnewline
34 & NA & NA & NA \tabularnewline
35 & NA & NA & NA \tabularnewline
36 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68203&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]0.001744[/C][C]0.0102[/C][C]0.495974[/C][/ROW]
[ROW][C]2[/C][C]0.230666[/C][C]1.345[/C][C]0.093764[/C][/ROW]
[ROW][C]3[/C][C]0.215224[/C][C]1.255[/C][C]0.109025[/C][/ROW]
[ROW][C]4[/C][C]-0.07264[/C][C]-0.4236[/C][C]0.337277[/C][/ROW]
[ROW][C]5[/C][C]-0.025114[/C][C]-0.1464[/C][C]0.44222[/C][/ROW]
[ROW][C]6[/C][C]0.014602[/C][C]0.0851[/C][C]0.466324[/C][/ROW]
[ROW][C]7[/C][C]0.055842[/C][C]0.3256[/C][C]0.373357[/C][/ROW]
[ROW][C]8[/C][C]0.055938[/C][C]0.3262[/C][C]0.373146[/C][/ROW]
[ROW][C]9[/C][C]-0.112122[/C][C]-0.6538[/C][C]0.258826[/C][/ROW]
[ROW][C]10[/C][C]-0.202705[/C][C]-1.182[/C][C]0.12271[/C][/ROW]
[ROW][C]11[/C][C]-0.145158[/C][C]-0.8464[/C][C]0.201622[/C][/ROW]
[ROW][C]12[/C][C]-0.373762[/C][C]-2.1794[/C][C]0.018163[/C][/ROW]
[ROW][C]13[/C][C]0.076251[/C][C]0.4446[/C][C]0.329706[/C][/ROW]
[ROW][C]14[/C][C]-0.054394[/C][C]-0.3172[/C][C]0.376528[/C][/ROW]
[ROW][C]15[/C][C]0.209262[/C][C]1.2202[/C][C]0.115393[/C][/ROW]
[ROW][C]16[/C][C]-0.103966[/C][C]-0.6062[/C][C]0.274198[/C][/ROW]
[ROW][C]17[/C][C]-0.109106[/C][C]-0.6362[/C][C]0.264455[/C][/ROW]
[ROW][C]18[/C][C]0.056035[/C][C]0.3267[/C][C]0.372935[/C][/ROW]
[ROW][C]19[/C][C]0.068213[/C][C]0.3977[/C][C]0.346652[/C][/ROW]
[ROW][C]20[/C][C]0.05167[/C][C]0.3013[/C][C]0.382517[/C][/ROW]
[ROW][C]21[/C][C]-0.133687[/C][C]-0.7795[/C][C]0.220532[/C][/ROW]
[ROW][C]22[/C][C]-0.052726[/C][C]-0.3074[/C][C]0.380192[/C][/ROW]
[ROW][C]23[/C][C]-0.025116[/C][C]-0.1465[/C][C]0.442215[/C][/ROW]
[ROW][C]24[/C][C]-0.170076[/C][C]-0.9917[/C][C]0.164174[/C][/ROW]
[ROW][C]25[/C][C]0.035508[/C][C]0.207[/C][C]0.418606[/C][/ROW]
[ROW][C]26[/C][C]0.043479[/C][C]0.2535[/C][C]0.400696[/C][/ROW]
[ROW][C]27[/C][C]0.000271[/C][C]0.0016[/C][C]0.499373[/C][/ROW]
[ROW][C]28[/C][C]-0.169683[/C][C]-0.9894[/C][C]0.164725[/C][/ROW]
[ROW][C]29[/C][C]-0.033279[/C][C]-0.1941[/C][C]0.423646[/C][/ROW]
[ROW][C]30[/C][C]-0.019879[/C][C]-0.1159[/C][C]0.454202[/C][/ROW]
[ROW][C]31[/C][C]-0.000131[/C][C]-8e-04[/C][C]0.499697[/C][/ROW]
[ROW][C]32[/C][C]0.060375[/C][C]0.352[/C][C]0.363489[/C][/ROW]
[ROW][C]33[/C][C]-0.099583[/C][C]-0.5807[/C][C]0.282648[/C][/ROW]
[ROW][C]34[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]35[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]36[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68203&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68203&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
10.0017440.01020.495974
20.2306661.3450.093764
30.2152241.2550.109025
4-0.07264-0.42360.337277
5-0.025114-0.14640.44222
60.0146020.08510.466324
70.0558420.32560.373357
80.0559380.32620.373146
9-0.112122-0.65380.258826
10-0.202705-1.1820.12271
11-0.145158-0.84640.201622
12-0.373762-2.17940.018163
130.0762510.44460.329706
14-0.054394-0.31720.376528
150.2092621.22020.115393
16-0.103966-0.60620.274198
17-0.109106-0.63620.264455
180.0560350.32670.372935
190.0682130.39770.346652
200.051670.30130.382517
21-0.133687-0.77950.220532
22-0.052726-0.30740.380192
23-0.025116-0.14650.442215
24-0.170076-0.99170.164174
250.0355080.2070.418606
260.0434790.25350.400696
270.0002710.00160.499373
28-0.169683-0.98940.164725
29-0.033279-0.19410.423646
30-0.019879-0.11590.454202
31-0.000131-8e-040.499697
320.0603750.3520.363489
33-0.099583-0.58070.282648
34NANANA
35NANANA
36NANANA



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