## Free Statistics

of Irreproducible Research!

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 12:43:08 -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/t12590918978d0rhdjlwd4kzw9.htm/, Retrieved Fri, 14 Jun 2024 17:48:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59252, Retrieved Fri, 14 Jun 2024 17:48:07 +0000
QR Codes:

Original text written by user:
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 12:26:39] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [] [2009-11-24 19:43:08] [fc845972e0ebdb725d2fb9537c0c51aa] [Current]
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Dataseries X:
111,4
87,4
96,8
114,1
110,3
103,9
101,6
94,6
95,9
104,7
102,8
98,1
113,9
80,9
95,7
113,2
105,9
108,8
102,3
99
100,7
115,5
100,7
109,9
114,6
85,4
100,5
114,8
116,5
112,9
102
106
105,3
118,8
106,1
109,3
117,2
92,5
104,2
112,5
122,4
113,3
100
110,7
112,8
109,8
117,3
109,1
115,9
96
99,8
116,8
115,7
99,4
94,3
91
93,2
103,1
94,1
91,8
102,7


 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 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=59252&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=59252&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59252&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 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135

 Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 -0.625046 -4.3304 3.8e-05 2 0.030297 0.2099 0.417315 3 0.368488 2.553 0.006958 4 -0.34364 -2.3808 0.010646 5 0.087861 0.6087 0.272791 6 0.151133 1.0471 0.150153 7 -0.260461 -1.8045 0.038712 8 0.190383 1.319 0.096712 9 -0.074048 -0.513 0.305146 10 -0.086344 -0.5982 0.276256 11 0.217552 1.5072 0.069151 12 -0.220404 -1.527 0.066662 13 0.077468 0.5367 0.296972 14 0.059527 0.4124 0.340937 15 -0.046695 -0.3235 0.373857 16 -0.079101 -0.548 0.293106 17 0.149524 1.0359 0.152712 18 -0.070905 -0.4912 0.312746 19 -0.072049 -0.4992 0.30997 20 0.124483 0.8624 0.196366 21 0.007698 0.0533 0.478844 22 -0.250202 -1.7334 0.044718 23 0.382418 2.6495 0.005441 24 -0.281624 -1.9511 0.028445 25 0.030798 0.2134 0.41597 26 0.175242 1.2141 0.115322 27 -0.200091 -1.3863 0.086036 28 0.050788 0.3519 0.363238 29 0.117277 0.8125 0.210252 30 -0.160022 -1.1087 0.13655 31 0.079143 0.5483 0.293008 32 0.025272 0.1751 0.430872 33 -0.126783 -0.8784 0.192057 34 0.166086 1.1507 0.127783 35 -0.155533 -1.0776 0.143308 36 0.039539 0.2739 0.392654

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.625046 & -4.3304 & 3.8e-05 \tabularnewline
2 & 0.030297 & 0.2099 & 0.417315 \tabularnewline
3 & 0.368488 & 2.553 & 0.006958 \tabularnewline
4 & -0.34364 & -2.3808 & 0.010646 \tabularnewline
5 & 0.087861 & 0.6087 & 0.272791 \tabularnewline
6 & 0.151133 & 1.0471 & 0.150153 \tabularnewline
7 & -0.260461 & -1.8045 & 0.038712 \tabularnewline
8 & 0.190383 & 1.319 & 0.096712 \tabularnewline
9 & -0.074048 & -0.513 & 0.305146 \tabularnewline
10 & -0.086344 & -0.5982 & 0.276256 \tabularnewline
11 & 0.217552 & 1.5072 & 0.069151 \tabularnewline
12 & -0.220404 & -1.527 & 0.066662 \tabularnewline
13 & 0.077468 & 0.5367 & 0.296972 \tabularnewline
14 & 0.059527 & 0.4124 & 0.340937 \tabularnewline
15 & -0.046695 & -0.3235 & 0.373857 \tabularnewline
16 & -0.079101 & -0.548 & 0.293106 \tabularnewline
17 & 0.149524 & 1.0359 & 0.152712 \tabularnewline
18 & -0.070905 & -0.4912 & 0.312746 \tabularnewline
19 & -0.072049 & -0.4992 & 0.30997 \tabularnewline
20 & 0.124483 & 0.8624 & 0.196366 \tabularnewline
21 & 0.007698 & 0.0533 & 0.478844 \tabularnewline
22 & -0.250202 & -1.7334 & 0.044718 \tabularnewline
23 & 0.382418 & 2.6495 & 0.005441 \tabularnewline
24 & -0.281624 & -1.9511 & 0.028445 \tabularnewline
25 & 0.030798 & 0.2134 & 0.41597 \tabularnewline
26 & 0.175242 & 1.2141 & 0.115322 \tabularnewline
27 & -0.200091 & -1.3863 & 0.086036 \tabularnewline
28 & 0.050788 & 0.3519 & 0.363238 \tabularnewline
29 & 0.117277 & 0.8125 & 0.210252 \tabularnewline
30 & -0.160022 & -1.1087 & 0.13655 \tabularnewline
31 & 0.079143 & 0.5483 & 0.293008 \tabularnewline
32 & 0.025272 & 0.1751 & 0.430872 \tabularnewline
33 & -0.126783 & -0.8784 & 0.192057 \tabularnewline
34 & 0.166086 & 1.1507 & 0.127783 \tabularnewline
35 & -0.155533 & -1.0776 & 0.143308 \tabularnewline
36 & 0.039539 & 0.2739 & 0.392654 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59252&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]-0.625046[/C][C]-4.3304[/C][C]3.8e-05[/C][/ROW]
[ROW][C]2[/C][C]0.030297[/C][C]0.2099[/C][C]0.417315[/C][/ROW]
[ROW][C]3[/C][C]0.368488[/C][C]2.553[/C][C]0.006958[/C][/ROW]
[ROW][C]4[/C][C]-0.34364[/C][C]-2.3808[/C][C]0.010646[/C][/ROW]
[ROW][C]5[/C][C]0.087861[/C][C]0.6087[/C][C]0.272791[/C][/ROW]
[ROW][C]6[/C][C]0.151133[/C][C]1.0471[/C][C]0.150153[/C][/ROW]
[ROW][C]7[/C][C]-0.260461[/C][C]-1.8045[/C][C]0.038712[/C][/ROW]
[ROW][C]8[/C][C]0.190383[/C][C]1.319[/C][C]0.096712[/C][/ROW]
[ROW][C]9[/C][C]-0.074048[/C][C]-0.513[/C][C]0.305146[/C][/ROW]
[ROW][C]10[/C][C]-0.086344[/C][C]-0.5982[/C][C]0.276256[/C][/ROW]
[ROW][C]11[/C][C]0.217552[/C][C]1.5072[/C][C]0.069151[/C][/ROW]
[ROW][C]12[/C][C]-0.220404[/C][C]-1.527[/C][C]0.066662[/C][/ROW]
[ROW][C]13[/C][C]0.077468[/C][C]0.5367[/C][C]0.296972[/C][/ROW]
[ROW][C]14[/C][C]0.059527[/C][C]0.4124[/C][C]0.340937[/C][/ROW]
[ROW][C]15[/C][C]-0.046695[/C][C]-0.3235[/C][C]0.373857[/C][/ROW]
[ROW][C]16[/C][C]-0.079101[/C][C]-0.548[/C][C]0.293106[/C][/ROW]
[ROW][C]17[/C][C]0.149524[/C][C]1.0359[/C][C]0.152712[/C][/ROW]
[ROW][C]18[/C][C]-0.070905[/C][C]-0.4912[/C][C]0.312746[/C][/ROW]
[ROW][C]19[/C][C]-0.072049[/C][C]-0.4992[/C][C]0.30997[/C][/ROW]
[ROW][C]20[/C][C]0.124483[/C][C]0.8624[/C][C]0.196366[/C][/ROW]
[ROW][C]21[/C][C]0.007698[/C][C]0.0533[/C][C]0.478844[/C][/ROW]
[ROW][C]22[/C][C]-0.250202[/C][C]-1.7334[/C][C]0.044718[/C][/ROW]
[ROW][C]23[/C][C]0.382418[/C][C]2.6495[/C][C]0.005441[/C][/ROW]
[ROW][C]24[/C][C]-0.281624[/C][C]-1.9511[/C][C]0.028445[/C][/ROW]
[ROW][C]25[/C][C]0.030798[/C][C]0.2134[/C][C]0.41597[/C][/ROW]
[ROW][C]26[/C][C]0.175242[/C][C]1.2141[/C][C]0.115322[/C][/ROW]
[ROW][C]27[/C][C]-0.200091[/C][C]-1.3863[/C][C]0.086036[/C][/ROW]
[ROW][C]28[/C][C]0.050788[/C][C]0.3519[/C][C]0.363238[/C][/ROW]
[ROW][C]29[/C][C]0.117277[/C][C]0.8125[/C][C]0.210252[/C][/ROW]
[ROW][C]30[/C][C]-0.160022[/C][C]-1.1087[/C][C]0.13655[/C][/ROW]
[ROW][C]31[/C][C]0.079143[/C][C]0.5483[/C][C]0.293008[/C][/ROW]
[ROW][C]32[/C][C]0.025272[/C][C]0.1751[/C][C]0.430872[/C][/ROW]
[ROW][C]33[/C][C]-0.126783[/C][C]-0.8784[/C][C]0.192057[/C][/ROW]
[ROW][C]34[/C][C]0.166086[/C][C]1.1507[/C][C]0.127783[/C][/ROW]
[ROW][C]35[/C][C]-0.155533[/C][C]-1.0776[/C][C]0.143308[/C][/ROW]
[ROW][C]36[/C][C]0.039539[/C][C]0.2739[/C][C]0.392654[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59252&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59252&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 -0.625046 -4.3304 3.8e-05 2 0.030297 0.2099 0.417315 3 0.368488 2.553 0.006958 4 -0.34364 -2.3808 0.010646 5 0.087861 0.6087 0.272791 6 0.151133 1.0471 0.150153 7 -0.260461 -1.8045 0.038712 8 0.190383 1.319 0.096712 9 -0.074048 -0.513 0.305146 10 -0.086344 -0.5982 0.276256 11 0.217552 1.5072 0.069151 12 -0.220404 -1.527 0.066662 13 0.077468 0.5367 0.296972 14 0.059527 0.4124 0.340937 15 -0.046695 -0.3235 0.373857 16 -0.079101 -0.548 0.293106 17 0.149524 1.0359 0.152712 18 -0.070905 -0.4912 0.312746 19 -0.072049 -0.4992 0.30997 20 0.124483 0.8624 0.196366 21 0.007698 0.0533 0.478844 22 -0.250202 -1.7334 0.044718 23 0.382418 2.6495 0.005441 24 -0.281624 -1.9511 0.028445 25 0.030798 0.2134 0.41597 26 0.175242 1.2141 0.115322 27 -0.200091 -1.3863 0.086036 28 0.050788 0.3519 0.363238 29 0.117277 0.8125 0.210252 30 -0.160022 -1.1087 0.13655 31 0.079143 0.5483 0.293008 32 0.025272 0.1751 0.430872 33 -0.126783 -0.8784 0.192057 34 0.166086 1.1507 0.127783 35 -0.155533 -1.0776 0.143308 36 0.039539 0.2739 0.392654

 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 -0.625046 -4.3304 3.8e-05 2 -0.591457 -4.0977 8e-05 3 0.073045 0.5061 0.307562 4 0.173487 1.202 0.11764 5 0.041209 0.2855 0.388243 6 0.028295 0.196 0.422706 7 -0.148304 -1.0275 0.154673 8 -0.056163 -0.3891 0.349457 9 -0.109857 -0.7611 0.225157 10 -0.154453 -1.0701 0.144968 11 0.120242 0.8331 0.204469 12 0.078353 0.5428 0.294873 13 -0.00299 -0.0207 0.491778 14 -0.155323 -1.0761 0.143628 15 0.100148 0.6938 0.245562 16 -0.073828 -0.5115 0.305675 17 -0.073587 -0.5098 0.306255 18 0.072782 0.5042 0.308197 19 0.011984 0.083 0.467087 20 -0.020889 -0.1447 0.442767 21 0.148156 1.0265 0.154911 22 -0.260099 -1.802 0.038912 23 0.064976 0.4502 0.327308 24 -0.008812 -0.0611 0.475786 25 0.029366 0.2035 0.419819 26 -0.024155 -0.1673 0.4339 27 0.101917 0.7061 0.24177 28 -0.092648 -0.6419 0.262001 29 -0.088628 -0.614 0.271047 30 0.080206 0.5557 0.290504 31 -0.003887 -0.0269 0.489314 32 -0.061863 -0.4286 0.335066 33 -0.034708 -0.2405 0.405497 34 -0.07086 -0.4909 0.312855 35 -0.086905 -0.6021 0.274972 36 -0.1199 -0.8307 0.205131

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.625046 & -4.3304 & 3.8e-05 \tabularnewline
2 & -0.591457 & -4.0977 & 8e-05 \tabularnewline
3 & 0.073045 & 0.5061 & 0.307562 \tabularnewline
4 & 0.173487 & 1.202 & 0.11764 \tabularnewline
5 & 0.041209 & 0.2855 & 0.388243 \tabularnewline
6 & 0.028295 & 0.196 & 0.422706 \tabularnewline
7 & -0.148304 & -1.0275 & 0.154673 \tabularnewline
8 & -0.056163 & -0.3891 & 0.349457 \tabularnewline
9 & -0.109857 & -0.7611 & 0.225157 \tabularnewline
10 & -0.154453 & -1.0701 & 0.144968 \tabularnewline
11 & 0.120242 & 0.8331 & 0.204469 \tabularnewline
12 & 0.078353 & 0.5428 & 0.294873 \tabularnewline
13 & -0.00299 & -0.0207 & 0.491778 \tabularnewline
14 & -0.155323 & -1.0761 & 0.143628 \tabularnewline
15 & 0.100148 & 0.6938 & 0.245562 \tabularnewline
16 & -0.073828 & -0.5115 & 0.305675 \tabularnewline
17 & -0.073587 & -0.5098 & 0.306255 \tabularnewline
18 & 0.072782 & 0.5042 & 0.308197 \tabularnewline
19 & 0.011984 & 0.083 & 0.467087 \tabularnewline
20 & -0.020889 & -0.1447 & 0.442767 \tabularnewline
21 & 0.148156 & 1.0265 & 0.154911 \tabularnewline
22 & -0.260099 & -1.802 & 0.038912 \tabularnewline
23 & 0.064976 & 0.4502 & 0.327308 \tabularnewline
24 & -0.008812 & -0.0611 & 0.475786 \tabularnewline
25 & 0.029366 & 0.2035 & 0.419819 \tabularnewline
26 & -0.024155 & -0.1673 & 0.4339 \tabularnewline
27 & 0.101917 & 0.7061 & 0.24177 \tabularnewline
28 & -0.092648 & -0.6419 & 0.262001 \tabularnewline
29 & -0.088628 & -0.614 & 0.271047 \tabularnewline
30 & 0.080206 & 0.5557 & 0.290504 \tabularnewline
31 & -0.003887 & -0.0269 & 0.489314 \tabularnewline
32 & -0.061863 & -0.4286 & 0.335066 \tabularnewline
33 & -0.034708 & -0.2405 & 0.405497 \tabularnewline
34 & -0.07086 & -0.4909 & 0.312855 \tabularnewline
35 & -0.086905 & -0.6021 & 0.274972 \tabularnewline
36 & -0.1199 & -0.8307 & 0.205131 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59252&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]-0.625046[/C][C]-4.3304[/C][C]3.8e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.591457[/C][C]-4.0977[/C][C]8e-05[/C][/ROW]
[ROW][C]3[/C][C]0.073045[/C][C]0.5061[/C][C]0.307562[/C][/ROW]
[ROW][C]4[/C][C]0.173487[/C][C]1.202[/C][C]0.11764[/C][/ROW]
[ROW][C]5[/C][C]0.041209[/C][C]0.2855[/C][C]0.388243[/C][/ROW]
[ROW][C]6[/C][C]0.028295[/C][C]0.196[/C][C]0.422706[/C][/ROW]
[ROW][C]7[/C][C]-0.148304[/C][C]-1.0275[/C][C]0.154673[/C][/ROW]
[ROW][C]8[/C][C]-0.056163[/C][C]-0.3891[/C][C]0.349457[/C][/ROW]
[ROW][C]9[/C][C]-0.109857[/C][C]-0.7611[/C][C]0.225157[/C][/ROW]
[ROW][C]10[/C][C]-0.154453[/C][C]-1.0701[/C][C]0.144968[/C][/ROW]
[ROW][C]11[/C][C]0.120242[/C][C]0.8331[/C][C]0.204469[/C][/ROW]
[ROW][C]12[/C][C]0.078353[/C][C]0.5428[/C][C]0.294873[/C][/ROW]
[ROW][C]13[/C][C]-0.00299[/C][C]-0.0207[/C][C]0.491778[/C][/ROW]
[ROW][C]14[/C][C]-0.155323[/C][C]-1.0761[/C][C]0.143628[/C][/ROW]
[ROW][C]15[/C][C]0.100148[/C][C]0.6938[/C][C]0.245562[/C][/ROW]
[ROW][C]16[/C][C]-0.073828[/C][C]-0.5115[/C][C]0.305675[/C][/ROW]
[ROW][C]17[/C][C]-0.073587[/C][C]-0.5098[/C][C]0.306255[/C][/ROW]
[ROW][C]18[/C][C]0.072782[/C][C]0.5042[/C][C]0.308197[/C][/ROW]
[ROW][C]19[/C][C]0.011984[/C][C]0.083[/C][C]0.467087[/C][/ROW]
[ROW][C]20[/C][C]-0.020889[/C][C]-0.1447[/C][C]0.442767[/C][/ROW]
[ROW][C]21[/C][C]0.148156[/C][C]1.0265[/C][C]0.154911[/C][/ROW]
[ROW][C]22[/C][C]-0.260099[/C][C]-1.802[/C][C]0.038912[/C][/ROW]
[ROW][C]23[/C][C]0.064976[/C][C]0.4502[/C][C]0.327308[/C][/ROW]
[ROW][C]24[/C][C]-0.008812[/C][C]-0.0611[/C][C]0.475786[/C][/ROW]
[ROW][C]25[/C][C]0.029366[/C][C]0.2035[/C][C]0.419819[/C][/ROW]
[ROW][C]26[/C][C]-0.024155[/C][C]-0.1673[/C][C]0.4339[/C][/ROW]
[ROW][C]27[/C][C]0.101917[/C][C]0.7061[/C][C]0.24177[/C][/ROW]
[ROW][C]28[/C][C]-0.092648[/C][C]-0.6419[/C][C]0.262001[/C][/ROW]
[ROW][C]29[/C][C]-0.088628[/C][C]-0.614[/C][C]0.271047[/C][/ROW]
[ROW][C]30[/C][C]0.080206[/C][C]0.5557[/C][C]0.290504[/C][/ROW]
[ROW][C]31[/C][C]-0.003887[/C][C]-0.0269[/C][C]0.489314[/C][/ROW]
[ROW][C]32[/C][C]-0.061863[/C][C]-0.4286[/C][C]0.335066[/C][/ROW]
[ROW][C]33[/C][C]-0.034708[/C][C]-0.2405[/C][C]0.405497[/C][/ROW]
[ROW][C]34[/C][C]-0.07086[/C][C]-0.4909[/C][C]0.312855[/C][/ROW]
[ROW][C]35[/C][C]-0.086905[/C][C]-0.6021[/C][C]0.274972[/C][/ROW]
[ROW][C]36[/C][C]-0.1199[/C][C]-0.8307[/C][C]0.205131[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59252&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59252&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 -0.625046 -4.3304 3.8e-05 2 -0.591457 -4.0977 8e-05 3 0.073045 0.5061 0.307562 4 0.173487 1.202 0.11764 5 0.041209 0.2855 0.388243 6 0.028295 0.196 0.422706 7 -0.148304 -1.0275 0.154673 8 -0.056163 -0.3891 0.349457 9 -0.109857 -0.7611 0.225157 10 -0.154453 -1.0701 0.144968 11 0.120242 0.8331 0.204469 12 0.078353 0.5428 0.294873 13 -0.00299 -0.0207 0.491778 14 -0.155323 -1.0761 0.143628 15 0.100148 0.6938 0.245562 16 -0.073828 -0.5115 0.305675 17 -0.073587 -0.5098 0.306255 18 0.072782 0.5042 0.308197 19 0.011984 0.083 0.467087 20 -0.020889 -0.1447 0.442767 21 0.148156 1.0265 0.154911 22 -0.260099 -1.802 0.038912 23 0.064976 0.4502 0.327308 24 -0.008812 -0.0611 0.475786 25 0.029366 0.2035 0.419819 26 -0.024155 -0.1673 0.4339 27 0.101917 0.7061 0.24177 28 -0.092648 -0.6419 0.262001 29 -0.088628 -0.614 0.271047 30 0.080206 0.5557 0.290504 31 -0.003887 -0.0269 0.489314 32 -0.061863 -0.4286 0.335066 33 -0.034708 -0.2405 0.405497 34 -0.07086 -0.4909 0.312855 35 -0.086905 -0.6021 0.274972 36 -0.1199 -0.8307 0.205131

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')