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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, 24 Nov 2009 08:33:55 -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/Nov/24/t1259076913kqikd5mo32pxjos.htm/, Retrieved Thu, 12 Sep 2024 16:46:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59122, Retrieved Thu, 12 Sep 2024 16:46:10 +0000
QR Codes:

Original text written by user:Uitleg in Word document
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact190
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]
- R  D          [(Partial) Autocorrelation Function] [Bestedingen consu...] [2009-11-24 15:33:55] [8eb8270f5a1cfdf0409dcfcbf10be18b] [Current]
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Dataseries X:
96.96
93.11
95.62
98.30
96.38
100.82
99.06
94.03
102.07
99.31
98.64
101.82
99.14
97.63
100.06
101.32
101.49
105.43
105.09
99.48
108.53
104.34
106.10
107.35
103.00
104.50
105.17
104.84
106.18
108.86
107.77
102.74
112.63
106.26
108.86
111.38
106.85
107.86
107.94
111.38
111.29
113.72
111.88
109.87
113.72
111.71
114.81
112.05
111.54
110.87
110.87
115.48
111.63
116.24
113.56
106.01
110.45
107.77
108.61
108.19


 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59122&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]3 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=59122&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59122&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 Input view raw input (R code) Raw Output view raw output of R engine Computing time 3 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135

 Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 0.785284 6.0828 0 2 0.765401 5.9288 0 3 0.761673 5.8999 0 4 0.637242 4.9361 3e-06 5 0.671186 5.199 1e-06 6 0.654345 5.0685 2e-06 7 0.588281 4.5568 1.3e-05 8 0.484376 3.752 0.000199 9 0.50575 3.9175 0.000116 10 0.427658 3.3126 0.000785 11 0.375836 2.9112 0.002523 12 0.452412 3.5044 0.000436 13 0.272173 2.1082 0.019597 14 0.24667 1.9107 0.030413 15 0.195546 1.5147 0.067551 16 0.103187 0.7993 0.21364 17 0.115861 0.8975 0.186531 18 0.099114 0.7677 0.222827 19 0.055318 0.4285 0.334913 20 -0.03418 -0.2648 0.396053 21 0.00344 0.0266 0.489416 22 -0.06138 -0.4754 0.318098 23 -0.078771 -0.6102 0.272031 24 -0.020429 -0.1582 0.4374 25 -0.15007 -1.1624 0.12483 26 -0.157671 -1.2213 0.113372 27 -0.19041 -1.4749 0.072732 28 -0.24457 -1.8944 0.031495 29 -0.234553 -1.8168 0.037118 30 -0.23961 -1.856 0.034182 31 -0.264478 -2.0486 0.02244 32 -0.330069 -2.5567 0.006558 33 -0.298684 -2.3136 0.012067 34 -0.339541 -2.6301 0.005415 35 -0.348644 -2.7006 0.004491 36 -0.304441 -2.3582 0.01082

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.785284 & 6.0828 & 0 \tabularnewline
2 & 0.765401 & 5.9288 & 0 \tabularnewline
3 & 0.761673 & 5.8999 & 0 \tabularnewline
4 & 0.637242 & 4.9361 & 3e-06 \tabularnewline
5 & 0.671186 & 5.199 & 1e-06 \tabularnewline
6 & 0.654345 & 5.0685 & 2e-06 \tabularnewline
7 & 0.588281 & 4.5568 & 1.3e-05 \tabularnewline
8 & 0.484376 & 3.752 & 0.000199 \tabularnewline
9 & 0.50575 & 3.9175 & 0.000116 \tabularnewline
10 & 0.427658 & 3.3126 & 0.000785 \tabularnewline
11 & 0.375836 & 2.9112 & 0.002523 \tabularnewline
12 & 0.452412 & 3.5044 & 0.000436 \tabularnewline
13 & 0.272173 & 2.1082 & 0.019597 \tabularnewline
14 & 0.24667 & 1.9107 & 0.030413 \tabularnewline
15 & 0.195546 & 1.5147 & 0.067551 \tabularnewline
16 & 0.103187 & 0.7993 & 0.21364 \tabularnewline
17 & 0.115861 & 0.8975 & 0.186531 \tabularnewline
18 & 0.099114 & 0.7677 & 0.222827 \tabularnewline
19 & 0.055318 & 0.4285 & 0.334913 \tabularnewline
20 & -0.03418 & -0.2648 & 0.396053 \tabularnewline
21 & 0.00344 & 0.0266 & 0.489416 \tabularnewline
22 & -0.06138 & -0.4754 & 0.318098 \tabularnewline
23 & -0.078771 & -0.6102 & 0.272031 \tabularnewline
24 & -0.020429 & -0.1582 & 0.4374 \tabularnewline
25 & -0.15007 & -1.1624 & 0.12483 \tabularnewline
26 & -0.157671 & -1.2213 & 0.113372 \tabularnewline
27 & -0.19041 & -1.4749 & 0.072732 \tabularnewline
28 & -0.24457 & -1.8944 & 0.031495 \tabularnewline
29 & -0.234553 & -1.8168 & 0.037118 \tabularnewline
30 & -0.23961 & -1.856 & 0.034182 \tabularnewline
31 & -0.264478 & -2.0486 & 0.02244 \tabularnewline
32 & -0.330069 & -2.5567 & 0.006558 \tabularnewline
33 & -0.298684 & -2.3136 & 0.012067 \tabularnewline
34 & -0.339541 & -2.6301 & 0.005415 \tabularnewline
35 & -0.348644 & -2.7006 & 0.004491 \tabularnewline
36 & -0.304441 & -2.3582 & 0.01082 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59122&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]0.785284[/C][C]6.0828[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.765401[/C][C]5.9288[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.761673[/C][C]5.8999[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.637242[/C][C]4.9361[/C][C]3e-06[/C][/ROW]
[ROW][C]5[/C][C]0.671186[/C][C]5.199[/C][C]1e-06[/C][/ROW]
[ROW][C]6[/C][C]0.654345[/C][C]5.0685[/C][C]2e-06[/C][/ROW]
[ROW][C]7[/C][C]0.588281[/C][C]4.5568[/C][C]1.3e-05[/C][/ROW]
[ROW][C]8[/C][C]0.484376[/C][C]3.752[/C][C]0.000199[/C][/ROW]
[ROW][C]9[/C][C]0.50575[/C][C]3.9175[/C][C]0.000116[/C][/ROW]
[ROW][C]10[/C][C]0.427658[/C][C]3.3126[/C][C]0.000785[/C][/ROW]
[ROW][C]11[/C][C]0.375836[/C][C]2.9112[/C][C]0.002523[/C][/ROW]
[ROW][C]12[/C][C]0.452412[/C][C]3.5044[/C][C]0.000436[/C][/ROW]
[ROW][C]13[/C][C]0.272173[/C][C]2.1082[/C][C]0.019597[/C][/ROW]
[ROW][C]14[/C][C]0.24667[/C][C]1.9107[/C][C]0.030413[/C][/ROW]
[ROW][C]15[/C][C]0.195546[/C][C]1.5147[/C][C]0.067551[/C][/ROW]
[ROW][C]16[/C][C]0.103187[/C][C]0.7993[/C][C]0.21364[/C][/ROW]
[ROW][C]17[/C][C]0.115861[/C][C]0.8975[/C][C]0.186531[/C][/ROW]
[ROW][C]18[/C][C]0.099114[/C][C]0.7677[/C][C]0.222827[/C][/ROW]
[ROW][C]19[/C][C]0.055318[/C][C]0.4285[/C][C]0.334913[/C][/ROW]
[ROW][C]20[/C][C]-0.03418[/C][C]-0.2648[/C][C]0.396053[/C][/ROW]
[ROW][C]21[/C][C]0.00344[/C][C]0.0266[/C][C]0.489416[/C][/ROW]
[ROW][C]22[/C][C]-0.06138[/C][C]-0.4754[/C][C]0.318098[/C][/ROW]
[ROW][C]23[/C][C]-0.078771[/C][C]-0.6102[/C][C]0.272031[/C][/ROW]
[ROW][C]24[/C][C]-0.020429[/C][C]-0.1582[/C][C]0.4374[/C][/ROW]
[ROW][C]25[/C][C]-0.15007[/C][C]-1.1624[/C][C]0.12483[/C][/ROW]
[ROW][C]26[/C][C]-0.157671[/C][C]-1.2213[/C][C]0.113372[/C][/ROW]
[ROW][C]27[/C][C]-0.19041[/C][C]-1.4749[/C][C]0.072732[/C][/ROW]
[ROW][C]28[/C][C]-0.24457[/C][C]-1.8944[/C][C]0.031495[/C][/ROW]
[ROW][C]29[/C][C]-0.234553[/C][C]-1.8168[/C][C]0.037118[/C][/ROW]
[ROW][C]30[/C][C]-0.23961[/C][C]-1.856[/C][C]0.034182[/C][/ROW]
[ROW][C]31[/C][C]-0.264478[/C][C]-2.0486[/C][C]0.02244[/C][/ROW]
[ROW][C]32[/C][C]-0.330069[/C][C]-2.5567[/C][C]0.006558[/C][/ROW]
[ROW][C]33[/C][C]-0.298684[/C][C]-2.3136[/C][C]0.012067[/C][/ROW]
[ROW][C]34[/C][C]-0.339541[/C][C]-2.6301[/C][C]0.005415[/C][/ROW]
[ROW][C]35[/C][C]-0.348644[/C][C]-2.7006[/C][C]0.004491[/C][/ROW]
[ROW][C]36[/C][C]-0.304441[/C][C]-2.3582[/C][C]0.01082[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59122&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59122&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 k ACF(k) T-STAT P-value 1 0.785284 6.0828 0 2 0.765401 5.9288 0 3 0.761673 5.8999 0 4 0.637242 4.9361 3e-06 5 0.671186 5.199 1e-06 6 0.654345 5.0685 2e-06 7 0.588281 4.5568 1.3e-05 8 0.484376 3.752 0.000199 9 0.50575 3.9175 0.000116 10 0.427658 3.3126 0.000785 11 0.375836 2.9112 0.002523 12 0.452412 3.5044 0.000436 13 0.272173 2.1082 0.019597 14 0.24667 1.9107 0.030413 15 0.195546 1.5147 0.067551 16 0.103187 0.7993 0.21364 17 0.115861 0.8975 0.186531 18 0.099114 0.7677 0.222827 19 0.055318 0.4285 0.334913 20 -0.03418 -0.2648 0.396053 21 0.00344 0.0266 0.489416 22 -0.06138 -0.4754 0.318098 23 -0.078771 -0.6102 0.272031 24 -0.020429 -0.1582 0.4374 25 -0.15007 -1.1624 0.12483 26 -0.157671 -1.2213 0.113372 27 -0.19041 -1.4749 0.072732 28 -0.24457 -1.8944 0.031495 29 -0.234553 -1.8168 0.037118 30 -0.23961 -1.856 0.034182 31 -0.264478 -2.0486 0.02244 32 -0.330069 -2.5567 0.006558 33 -0.298684 -2.3136 0.012067 34 -0.339541 -2.6301 0.005415 35 -0.348644 -2.7006 0.004491 36 -0.304441 -2.3582 0.01082

 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.785284 6.0828 0 2 0.387996 3.0054 0.001934 3 0.273743 2.1204 0.019058 4 -0.196398 -1.5213 0.066719 5 0.183345 1.4202 0.080364 6 0.116635 0.9035 0.184949 7 -0.034332 -0.2659 0.395601 8 -0.43129 -3.3408 0.000721 9 0.222454 1.7231 0.045009 10 -0.002504 -0.0194 0.492295 11 -0.048848 -0.3784 0.353244 12 0.120439 0.9329 0.1773 13 -0.325834 -2.5239 0.007136 14 -0.033197 -0.2571 0.398975 15 -0.180117 -1.3952 0.084053 16 0.097847 0.7579 0.225732 17 -0.001687 -0.0131 0.494808 18 0.121542 0.9415 0.175122 19 -0.067505 -0.5229 0.301487 20 -0.061401 -0.4756 0.318039 21 0.11483 0.8895 0.188651 22 0.013548 0.1049 0.458385 23 -0.006331 -0.049 0.480526 24 -0.104429 -0.8089 0.210883 25 -0.053705 -0.416 0.339448 26 -0.100788 -0.7807 0.219023 27 -0.007204 -0.0558 0.477842 28 -0.084626 -0.6555 0.257323 29 0.001925 0.0149 0.494075 30 -0.051867 -0.4018 0.344643 31 0.000978 0.0076 0.49699 32 -0.037813 -0.2929 0.385304 33 -0.034651 -0.2684 0.394655 34 0.072907 0.5647 0.287179 35 -0.095143 -0.737 0.232006 36 -0.003217 -0.0249 0.490101

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.785284 & 6.0828 & 0 \tabularnewline
2 & 0.387996 & 3.0054 & 0.001934 \tabularnewline
3 & 0.273743 & 2.1204 & 0.019058 \tabularnewline
4 & -0.196398 & -1.5213 & 0.066719 \tabularnewline
5 & 0.183345 & 1.4202 & 0.080364 \tabularnewline
6 & 0.116635 & 0.9035 & 0.184949 \tabularnewline
7 & -0.034332 & -0.2659 & 0.395601 \tabularnewline
8 & -0.43129 & -3.3408 & 0.000721 \tabularnewline
9 & 0.222454 & 1.7231 & 0.045009 \tabularnewline
10 & -0.002504 & -0.0194 & 0.492295 \tabularnewline
11 & -0.048848 & -0.3784 & 0.353244 \tabularnewline
12 & 0.120439 & 0.9329 & 0.1773 \tabularnewline
13 & -0.325834 & -2.5239 & 0.007136 \tabularnewline
14 & -0.033197 & -0.2571 & 0.398975 \tabularnewline
15 & -0.180117 & -1.3952 & 0.084053 \tabularnewline
16 & 0.097847 & 0.7579 & 0.225732 \tabularnewline
17 & -0.001687 & -0.0131 & 0.494808 \tabularnewline
18 & 0.121542 & 0.9415 & 0.175122 \tabularnewline
19 & -0.067505 & -0.5229 & 0.301487 \tabularnewline
20 & -0.061401 & -0.4756 & 0.318039 \tabularnewline
21 & 0.11483 & 0.8895 & 0.188651 \tabularnewline
22 & 0.013548 & 0.1049 & 0.458385 \tabularnewline
23 & -0.006331 & -0.049 & 0.480526 \tabularnewline
24 & -0.104429 & -0.8089 & 0.210883 \tabularnewline
25 & -0.053705 & -0.416 & 0.339448 \tabularnewline
26 & -0.100788 & -0.7807 & 0.219023 \tabularnewline
27 & -0.007204 & -0.0558 & 0.477842 \tabularnewline
28 & -0.084626 & -0.6555 & 0.257323 \tabularnewline
29 & 0.001925 & 0.0149 & 0.494075 \tabularnewline
30 & -0.051867 & -0.4018 & 0.344643 \tabularnewline
31 & 0.000978 & 0.0076 & 0.49699 \tabularnewline
32 & -0.037813 & -0.2929 & 0.385304 \tabularnewline
33 & -0.034651 & -0.2684 & 0.394655 \tabularnewline
34 & 0.072907 & 0.5647 & 0.287179 \tabularnewline
35 & -0.095143 & -0.737 & 0.232006 \tabularnewline
36 & -0.003217 & -0.0249 & 0.490101 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59122&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]0.785284[/C][C]6.0828[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.387996[/C][C]3.0054[/C][C]0.001934[/C][/ROW]
[ROW][C]3[/C][C]0.273743[/C][C]2.1204[/C][C]0.019058[/C][/ROW]
[ROW][C]4[/C][C]-0.196398[/C][C]-1.5213[/C][C]0.066719[/C][/ROW]
[ROW][C]5[/C][C]0.183345[/C][C]1.4202[/C][C]0.080364[/C][/ROW]
[ROW][C]6[/C][C]0.116635[/C][C]0.9035[/C][C]0.184949[/C][/ROW]
[ROW][C]7[/C][C]-0.034332[/C][C]-0.2659[/C][C]0.395601[/C][/ROW]
[ROW][C]8[/C][C]-0.43129[/C][C]-3.3408[/C][C]0.000721[/C][/ROW]
[ROW][C]9[/C][C]0.222454[/C][C]1.7231[/C][C]0.045009[/C][/ROW]
[ROW][C]10[/C][C]-0.002504[/C][C]-0.0194[/C][C]0.492295[/C][/ROW]
[ROW][C]11[/C][C]-0.048848[/C][C]-0.3784[/C][C]0.353244[/C][/ROW]
[ROW][C]12[/C][C]0.120439[/C][C]0.9329[/C][C]0.1773[/C][/ROW]
[ROW][C]13[/C][C]-0.325834[/C][C]-2.5239[/C][C]0.007136[/C][/ROW]
[ROW][C]14[/C][C]-0.033197[/C][C]-0.2571[/C][C]0.398975[/C][/ROW]
[ROW][C]15[/C][C]-0.180117[/C][C]-1.3952[/C][C]0.084053[/C][/ROW]
[ROW][C]16[/C][C]0.097847[/C][C]0.7579[/C][C]0.225732[/C][/ROW]
[ROW][C]17[/C][C]-0.001687[/C][C]-0.0131[/C][C]0.494808[/C][/ROW]
[ROW][C]18[/C][C]0.121542[/C][C]0.9415[/C][C]0.175122[/C][/ROW]
[ROW][C]19[/C][C]-0.067505[/C][C]-0.5229[/C][C]0.301487[/C][/ROW]
[ROW][C]20[/C][C]-0.061401[/C][C]-0.4756[/C][C]0.318039[/C][/ROW]
[ROW][C]21[/C][C]0.11483[/C][C]0.8895[/C][C]0.188651[/C][/ROW]
[ROW][C]22[/C][C]0.013548[/C][C]0.1049[/C][C]0.458385[/C][/ROW]
[ROW][C]23[/C][C]-0.006331[/C][C]-0.049[/C][C]0.480526[/C][/ROW]
[ROW][C]24[/C][C]-0.104429[/C][C]-0.8089[/C][C]0.210883[/C][/ROW]
[ROW][C]25[/C][C]-0.053705[/C][C]-0.416[/C][C]0.339448[/C][/ROW]
[ROW][C]26[/C][C]-0.100788[/C][C]-0.7807[/C][C]0.219023[/C][/ROW]
[ROW][C]27[/C][C]-0.007204[/C][C]-0.0558[/C][C]0.477842[/C][/ROW]
[ROW][C]28[/C][C]-0.084626[/C][C]-0.6555[/C][C]0.257323[/C][/ROW]
[ROW][C]29[/C][C]0.001925[/C][C]0.0149[/C][C]0.494075[/C][/ROW]
[ROW][C]30[/C][C]-0.051867[/C][C]-0.4018[/C][C]0.344643[/C][/ROW]
[ROW][C]31[/C][C]0.000978[/C][C]0.0076[/C][C]0.49699[/C][/ROW]
[ROW][C]32[/C][C]-0.037813[/C][C]-0.2929[/C][C]0.385304[/C][/ROW]
[ROW][C]33[/C][C]-0.034651[/C][C]-0.2684[/C][C]0.394655[/C][/ROW]
[ROW][C]34[/C][C]0.072907[/C][C]0.5647[/C][C]0.287179[/C][/ROW]
[ROW][C]35[/C][C]-0.095143[/C][C]-0.737[/C][C]0.232006[/C][/ROW]
[ROW][C]36[/C][C]-0.003217[/C][C]-0.0249[/C][C]0.490101[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59122&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59122&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 k PACF(k) T-STAT P-value 1 0.785284 6.0828 0 2 0.387996 3.0054 0.001934 3 0.273743 2.1204 0.019058 4 -0.196398 -1.5213 0.066719 5 0.183345 1.4202 0.080364 6 0.116635 0.9035 0.184949 7 -0.034332 -0.2659 0.395601 8 -0.43129 -3.3408 0.000721 9 0.222454 1.7231 0.045009 10 -0.002504 -0.0194 0.492295 11 -0.048848 -0.3784 0.353244 12 0.120439 0.9329 0.1773 13 -0.325834 -2.5239 0.007136 14 -0.033197 -0.2571 0.398975 15 -0.180117 -1.3952 0.084053 16 0.097847 0.7579 0.225732 17 -0.001687 -0.0131 0.494808 18 0.121542 0.9415 0.175122 19 -0.067505 -0.5229 0.301487 20 -0.061401 -0.4756 0.318039 21 0.11483 0.8895 0.188651 22 0.013548 0.1049 0.458385 23 -0.006331 -0.049 0.480526 24 -0.104429 -0.8089 0.210883 25 -0.053705 -0.416 0.339448 26 -0.100788 -0.7807 0.219023 27 -0.007204 -0.0558 0.477842 28 -0.084626 -0.6555 0.257323 29 0.001925 0.0149 0.494075 30 -0.051867 -0.4018 0.344643 31 0.000978 0.0076 0.49699 32 -0.037813 -0.2929 0.385304 33 -0.034651 -0.2684 0.394655 34 0.072907 0.5647 0.287179 35 -0.095143 -0.737 0.232006 36 -0.003217 -0.0249 0.490101

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]*sqrtna<-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]*sqrtna<-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')