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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 computationThu, 03 Dec 2009 15:29:45 -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/03/t1259879656zn00wjz4xqeumiy.htm/, Retrieved Thu, 28 Mar 2024 12:48:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63138, Retrieved Thu, 28 Mar 2024 12:48:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsbhschhwstvws8
Estimated Impact108
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] [WS 8.3] [2009-11-27 19:44:23] [4a2be4899cba879e4eea9daa25281df8]
-   P             [(Partial) Autocorrelation Function] [Workshop 8] [2009-12-03 22:29:45] [682632737e024f9e62885141c5f654cd] [Current]
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Dataseries X:
100.00
94.97
107.50
124.27
107.06
79.71
163.41
144.83
166.82
154.26
132.60
157.51
104.02
106.03
113.23
117.64
113.34
66.62
185.99
174.57
208.19
163.81
162.46
148.16
113.41
105.63
111.79
132.36
110.75
67.37
178.29
156.38
189.71
152.80
150.80
160.40
127.25
108.47
117.09
147.25
116.19
75.83
181.94
179.12
183.15
197.90
155.42
162.54
125.90
105.50
121.11
137.51
97.20
69.74
152.58
146.59
161.16
152.84
121.95
140.12




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=63138&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=63138&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63138&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
1-0.512617-3.03270.002272
20.2136051.26370.107345
3-0.064657-0.38250.352196
4-0.080713-0.47750.317986
5-0.097427-0.57640.284022
60.1286050.76080.225926
7-0.078537-0.46460.322536
80.1291980.76430.224892
9-0.103788-0.6140.271588
100.1223880.72410.236921
11-0.019134-0.11320.455261
12-0.249457-1.47580.074468
130.0842990.49870.310549
14-0.064402-0.3810.352751
15-0.047771-0.28260.389568
160.1671610.98890.164741
17-0.07707-0.4560.325621
180.0798830.47260.319719
19-0.053979-0.31930.375682
20-0.077525-0.45860.324663
210.1590630.9410.17657
22-0.252322-1.49280.07223
230.2523021.49260.072246
24-0.104118-0.6160.27095
250.0689190.40770.342977
260.0056880.03360.486674
270.1125340.66580.254965
28-0.219687-1.29970.101102
290.1437610.85050.200414
30-0.097918-0.57930.283051
310.0035270.02090.491736
320.0647860.38330.351916
33-0.026656-0.15770.437801
34-0.00794-0.0470.4814
35NANANA
36NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.512617 & -3.0327 & 0.002272 \tabularnewline
2 & 0.213605 & 1.2637 & 0.107345 \tabularnewline
3 & -0.064657 & -0.3825 & 0.352196 \tabularnewline
4 & -0.080713 & -0.4775 & 0.317986 \tabularnewline
5 & -0.097427 & -0.5764 & 0.284022 \tabularnewline
6 & 0.128605 & 0.7608 & 0.225926 \tabularnewline
7 & -0.078537 & -0.4646 & 0.322536 \tabularnewline
8 & 0.129198 & 0.7643 & 0.224892 \tabularnewline
9 & -0.103788 & -0.614 & 0.271588 \tabularnewline
10 & 0.122388 & 0.7241 & 0.236921 \tabularnewline
11 & -0.019134 & -0.1132 & 0.455261 \tabularnewline
12 & -0.249457 & -1.4758 & 0.074468 \tabularnewline
13 & 0.084299 & 0.4987 & 0.310549 \tabularnewline
14 & -0.064402 & -0.381 & 0.352751 \tabularnewline
15 & -0.047771 & -0.2826 & 0.389568 \tabularnewline
16 & 0.167161 & 0.9889 & 0.164741 \tabularnewline
17 & -0.07707 & -0.456 & 0.325621 \tabularnewline
18 & 0.079883 & 0.4726 & 0.319719 \tabularnewline
19 & -0.053979 & -0.3193 & 0.375682 \tabularnewline
20 & -0.077525 & -0.4586 & 0.324663 \tabularnewline
21 & 0.159063 & 0.941 & 0.17657 \tabularnewline
22 & -0.252322 & -1.4928 & 0.07223 \tabularnewline
23 & 0.252302 & 1.4926 & 0.072246 \tabularnewline
24 & -0.104118 & -0.616 & 0.27095 \tabularnewline
25 & 0.068919 & 0.4077 & 0.342977 \tabularnewline
26 & 0.005688 & 0.0336 & 0.486674 \tabularnewline
27 & 0.112534 & 0.6658 & 0.254965 \tabularnewline
28 & -0.219687 & -1.2997 & 0.101102 \tabularnewline
29 & 0.143761 & 0.8505 & 0.200414 \tabularnewline
30 & -0.097918 & -0.5793 & 0.283051 \tabularnewline
31 & 0.003527 & 0.0209 & 0.491736 \tabularnewline
32 & 0.064786 & 0.3833 & 0.351916 \tabularnewline
33 & -0.026656 & -0.1577 & 0.437801 \tabularnewline
34 & -0.00794 & -0.047 & 0.4814 \tabularnewline
35 & NA & NA & NA \tabularnewline
36 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63138&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]-0.512617[/C][C]-3.0327[/C][C]0.002272[/C][/ROW]
[ROW][C]2[/C][C]0.213605[/C][C]1.2637[/C][C]0.107345[/C][/ROW]
[ROW][C]3[/C][C]-0.064657[/C][C]-0.3825[/C][C]0.352196[/C][/ROW]
[ROW][C]4[/C][C]-0.080713[/C][C]-0.4775[/C][C]0.317986[/C][/ROW]
[ROW][C]5[/C][C]-0.097427[/C][C]-0.5764[/C][C]0.284022[/C][/ROW]
[ROW][C]6[/C][C]0.128605[/C][C]0.7608[/C][C]0.225926[/C][/ROW]
[ROW][C]7[/C][C]-0.078537[/C][C]-0.4646[/C][C]0.322536[/C][/ROW]
[ROW][C]8[/C][C]0.129198[/C][C]0.7643[/C][C]0.224892[/C][/ROW]
[ROW][C]9[/C][C]-0.103788[/C][C]-0.614[/C][C]0.271588[/C][/ROW]
[ROW][C]10[/C][C]0.122388[/C][C]0.7241[/C][C]0.236921[/C][/ROW]
[ROW][C]11[/C][C]-0.019134[/C][C]-0.1132[/C][C]0.455261[/C][/ROW]
[ROW][C]12[/C][C]-0.249457[/C][C]-1.4758[/C][C]0.074468[/C][/ROW]
[ROW][C]13[/C][C]0.084299[/C][C]0.4987[/C][C]0.310549[/C][/ROW]
[ROW][C]14[/C][C]-0.064402[/C][C]-0.381[/C][C]0.352751[/C][/ROW]
[ROW][C]15[/C][C]-0.047771[/C][C]-0.2826[/C][C]0.389568[/C][/ROW]
[ROW][C]16[/C][C]0.167161[/C][C]0.9889[/C][C]0.164741[/C][/ROW]
[ROW][C]17[/C][C]-0.07707[/C][C]-0.456[/C][C]0.325621[/C][/ROW]
[ROW][C]18[/C][C]0.079883[/C][C]0.4726[/C][C]0.319719[/C][/ROW]
[ROW][C]19[/C][C]-0.053979[/C][C]-0.3193[/C][C]0.375682[/C][/ROW]
[ROW][C]20[/C][C]-0.077525[/C][C]-0.4586[/C][C]0.324663[/C][/ROW]
[ROW][C]21[/C][C]0.159063[/C][C]0.941[/C][C]0.17657[/C][/ROW]
[ROW][C]22[/C][C]-0.252322[/C][C]-1.4928[/C][C]0.07223[/C][/ROW]
[ROW][C]23[/C][C]0.252302[/C][C]1.4926[/C][C]0.072246[/C][/ROW]
[ROW][C]24[/C][C]-0.104118[/C][C]-0.616[/C][C]0.27095[/C][/ROW]
[ROW][C]25[/C][C]0.068919[/C][C]0.4077[/C][C]0.342977[/C][/ROW]
[ROW][C]26[/C][C]0.005688[/C][C]0.0336[/C][C]0.486674[/C][/ROW]
[ROW][C]27[/C][C]0.112534[/C][C]0.6658[/C][C]0.254965[/C][/ROW]
[ROW][C]28[/C][C]-0.219687[/C][C]-1.2997[/C][C]0.101102[/C][/ROW]
[ROW][C]29[/C][C]0.143761[/C][C]0.8505[/C][C]0.200414[/C][/ROW]
[ROW][C]30[/C][C]-0.097918[/C][C]-0.5793[/C][C]0.283051[/C][/ROW]
[ROW][C]31[/C][C]0.003527[/C][C]0.0209[/C][C]0.491736[/C][/ROW]
[ROW][C]32[/C][C]0.064786[/C][C]0.3833[/C][C]0.351916[/C][/ROW]
[ROW][C]33[/C][C]-0.026656[/C][C]-0.1577[/C][C]0.437801[/C][/ROW]
[ROW][C]34[/C][C]-0.00794[/C][C]-0.047[/C][C]0.4814[/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=63138&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63138&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
1-0.512617-3.03270.002272
20.2136051.26370.107345
3-0.064657-0.38250.352196
4-0.080713-0.47750.317986
5-0.097427-0.57640.284022
60.1286050.76080.225926
7-0.078537-0.46460.322536
80.1291980.76430.224892
9-0.103788-0.6140.271588
100.1223880.72410.236921
11-0.019134-0.11320.455261
12-0.249457-1.47580.074468
130.0842990.49870.310549
14-0.064402-0.3810.352751
15-0.047771-0.28260.389568
160.1671610.98890.164741
17-0.07707-0.4560.325621
180.0798830.47260.319719
19-0.053979-0.31930.375682
20-0.077525-0.45860.324663
210.1590630.9410.17657
22-0.252322-1.49280.07223
230.2523021.49260.072246
24-0.104118-0.6160.27095
250.0689190.40770.342977
260.0056880.03360.486674
270.1125340.66580.254965
28-0.219687-1.29970.101102
290.1437610.85050.200414
30-0.097918-0.57930.283051
310.0035270.02090.491736
320.0647860.38330.351916
33-0.026656-0.15770.437801
34-0.00794-0.0470.4814
35NANANA
36NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.512617-3.03270.002272
2-0.066698-0.39460.34777
30.0244610.14470.442884
4-0.125471-0.74230.231431
5-0.277016-1.63880.055102
6-0.030701-0.18160.42846
70.0196710.11640.454011
80.0905090.53550.29786
9-0.071954-0.42570.336472
100.0451760.26730.395416
110.162410.96080.171614
12-0.286171-1.6930.049669
13-0.309132-1.82890.037977
14-0.131339-0.7770.221186
15-0.102985-0.60930.273142
16-0.044391-0.26260.397191
17-0.171942-1.01720.158014
18-0.018862-0.11160.455892
190.0200690.11870.453083
20-0.169271-1.00140.161748
210.0629530.37240.355907
22-0.122757-0.72620.23626
230.10050.59460.277978
24-0.110064-0.65110.259602
25-0.122328-0.72370.23703
26-0.059332-0.3510.363842
270.0945690.55950.2897
28-0.096694-0.5720.285472
29-0.199599-1.18080.122813
300.0496120.29350.385433
31-0.060791-0.35960.360638
32-0.070811-0.41890.338916
33-0.083821-0.49590.311534
34-0.155635-0.92070.181743
35NANANA
36NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.512617 & -3.0327 & 0.002272 \tabularnewline
2 & -0.066698 & -0.3946 & 0.34777 \tabularnewline
3 & 0.024461 & 0.1447 & 0.442884 \tabularnewline
4 & -0.125471 & -0.7423 & 0.231431 \tabularnewline
5 & -0.277016 & -1.6388 & 0.055102 \tabularnewline
6 & -0.030701 & -0.1816 & 0.42846 \tabularnewline
7 & 0.019671 & 0.1164 & 0.454011 \tabularnewline
8 & 0.090509 & 0.5355 & 0.29786 \tabularnewline
9 & -0.071954 & -0.4257 & 0.336472 \tabularnewline
10 & 0.045176 & 0.2673 & 0.395416 \tabularnewline
11 & 0.16241 & 0.9608 & 0.171614 \tabularnewline
12 & -0.286171 & -1.693 & 0.049669 \tabularnewline
13 & -0.309132 & -1.8289 & 0.037977 \tabularnewline
14 & -0.131339 & -0.777 & 0.221186 \tabularnewline
15 & -0.102985 & -0.6093 & 0.273142 \tabularnewline
16 & -0.044391 & -0.2626 & 0.397191 \tabularnewline
17 & -0.171942 & -1.0172 & 0.158014 \tabularnewline
18 & -0.018862 & -0.1116 & 0.455892 \tabularnewline
19 & 0.020069 & 0.1187 & 0.453083 \tabularnewline
20 & -0.169271 & -1.0014 & 0.161748 \tabularnewline
21 & 0.062953 & 0.3724 & 0.355907 \tabularnewline
22 & -0.122757 & -0.7262 & 0.23626 \tabularnewline
23 & 0.1005 & 0.5946 & 0.277978 \tabularnewline
24 & -0.110064 & -0.6511 & 0.259602 \tabularnewline
25 & -0.122328 & -0.7237 & 0.23703 \tabularnewline
26 & -0.059332 & -0.351 & 0.363842 \tabularnewline
27 & 0.094569 & 0.5595 & 0.2897 \tabularnewline
28 & -0.096694 & -0.572 & 0.285472 \tabularnewline
29 & -0.199599 & -1.1808 & 0.122813 \tabularnewline
30 & 0.049612 & 0.2935 & 0.385433 \tabularnewline
31 & -0.060791 & -0.3596 & 0.360638 \tabularnewline
32 & -0.070811 & -0.4189 & 0.338916 \tabularnewline
33 & -0.083821 & -0.4959 & 0.311534 \tabularnewline
34 & -0.155635 & -0.9207 & 0.181743 \tabularnewline
35 & NA & NA & NA \tabularnewline
36 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63138&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]-0.512617[/C][C]-3.0327[/C][C]0.002272[/C][/ROW]
[ROW][C]2[/C][C]-0.066698[/C][C]-0.3946[/C][C]0.34777[/C][/ROW]
[ROW][C]3[/C][C]0.024461[/C][C]0.1447[/C][C]0.442884[/C][/ROW]
[ROW][C]4[/C][C]-0.125471[/C][C]-0.7423[/C][C]0.231431[/C][/ROW]
[ROW][C]5[/C][C]-0.277016[/C][C]-1.6388[/C][C]0.055102[/C][/ROW]
[ROW][C]6[/C][C]-0.030701[/C][C]-0.1816[/C][C]0.42846[/C][/ROW]
[ROW][C]7[/C][C]0.019671[/C][C]0.1164[/C][C]0.454011[/C][/ROW]
[ROW][C]8[/C][C]0.090509[/C][C]0.5355[/C][C]0.29786[/C][/ROW]
[ROW][C]9[/C][C]-0.071954[/C][C]-0.4257[/C][C]0.336472[/C][/ROW]
[ROW][C]10[/C][C]0.045176[/C][C]0.2673[/C][C]0.395416[/C][/ROW]
[ROW][C]11[/C][C]0.16241[/C][C]0.9608[/C][C]0.171614[/C][/ROW]
[ROW][C]12[/C][C]-0.286171[/C][C]-1.693[/C][C]0.049669[/C][/ROW]
[ROW][C]13[/C][C]-0.309132[/C][C]-1.8289[/C][C]0.037977[/C][/ROW]
[ROW][C]14[/C][C]-0.131339[/C][C]-0.777[/C][C]0.221186[/C][/ROW]
[ROW][C]15[/C][C]-0.102985[/C][C]-0.6093[/C][C]0.273142[/C][/ROW]
[ROW][C]16[/C][C]-0.044391[/C][C]-0.2626[/C][C]0.397191[/C][/ROW]
[ROW][C]17[/C][C]-0.171942[/C][C]-1.0172[/C][C]0.158014[/C][/ROW]
[ROW][C]18[/C][C]-0.018862[/C][C]-0.1116[/C][C]0.455892[/C][/ROW]
[ROW][C]19[/C][C]0.020069[/C][C]0.1187[/C][C]0.453083[/C][/ROW]
[ROW][C]20[/C][C]-0.169271[/C][C]-1.0014[/C][C]0.161748[/C][/ROW]
[ROW][C]21[/C][C]0.062953[/C][C]0.3724[/C][C]0.355907[/C][/ROW]
[ROW][C]22[/C][C]-0.122757[/C][C]-0.7262[/C][C]0.23626[/C][/ROW]
[ROW][C]23[/C][C]0.1005[/C][C]0.5946[/C][C]0.277978[/C][/ROW]
[ROW][C]24[/C][C]-0.110064[/C][C]-0.6511[/C][C]0.259602[/C][/ROW]
[ROW][C]25[/C][C]-0.122328[/C][C]-0.7237[/C][C]0.23703[/C][/ROW]
[ROW][C]26[/C][C]-0.059332[/C][C]-0.351[/C][C]0.363842[/C][/ROW]
[ROW][C]27[/C][C]0.094569[/C][C]0.5595[/C][C]0.2897[/C][/ROW]
[ROW][C]28[/C][C]-0.096694[/C][C]-0.572[/C][C]0.285472[/C][/ROW]
[ROW][C]29[/C][C]-0.199599[/C][C]-1.1808[/C][C]0.122813[/C][/ROW]
[ROW][C]30[/C][C]0.049612[/C][C]0.2935[/C][C]0.385433[/C][/ROW]
[ROW][C]31[/C][C]-0.060791[/C][C]-0.3596[/C][C]0.360638[/C][/ROW]
[ROW][C]32[/C][C]-0.070811[/C][C]-0.4189[/C][C]0.338916[/C][/ROW]
[ROW][C]33[/C][C]-0.083821[/C][C]-0.4959[/C][C]0.311534[/C][/ROW]
[ROW][C]34[/C][C]-0.155635[/C][C]-0.9207[/C][C]0.181743[/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=63138&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63138&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
1-0.512617-3.03270.002272
2-0.066698-0.39460.34777
30.0244610.14470.442884
4-0.125471-0.74230.231431
5-0.277016-1.63880.055102
6-0.030701-0.18160.42846
70.0196710.11640.454011
80.0905090.53550.29786
9-0.071954-0.42570.336472
100.0451760.26730.395416
110.162410.96080.171614
12-0.286171-1.6930.049669
13-0.309132-1.82890.037977
14-0.131339-0.7770.221186
15-0.102985-0.60930.273142
16-0.044391-0.26260.397191
17-0.171942-1.01720.158014
18-0.018862-0.11160.455892
190.0200690.11870.453083
20-0.169271-1.00140.161748
210.0629530.37240.355907
22-0.122757-0.72620.23626
230.10050.59460.277978
24-0.110064-0.65110.259602
25-0.122328-0.72370.23703
26-0.059332-0.3510.363842
270.0945690.55950.2897
28-0.096694-0.5720.285472
29-0.199599-1.18080.122813
300.0496120.29350.385433
31-0.060791-0.35960.360638
32-0.070811-0.41890.338916
33-0.083821-0.49590.311534
34-0.155635-0.92070.181743
35NANANA
36NANANA



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 2 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 2 ; 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')