## 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 11:19:05 -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/t1259086806kmr1inhf1apyira.htm/, Retrieved Wed, 07 Aug 2024 21:58:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59203, Retrieved Wed, 07 Aug 2024 21:58:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsWorkshop 8 - methode 1 link 1
Estimated Impact184
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]
-    D          [(Partial) Autocorrelation Function] [Workshop 8] [2009-11-24 18:19:05] [100339cefec36dfa6f2b82a1c918e250] [Current]
-    D            [(Partial) Autocorrelation Function] [Workshop 8: Metho...] [2009-11-26 15:48:49] [1433a524809eda02c3198b3ae6eebb69]
-    D              [(Partial) Autocorrelation Function] [Workshop 8: Metho...] [2009-11-26 16:45:29] [6f6b63f0ca778484da1b5c31f09bf8b6]
-   P                 [(Partial) Autocorrelation Function] [Workshop 8: Metho...] [2009-11-26 16:52:54] [6f6b63f0ca778484da1b5c31f09bf8b6]
-   P                 [(Partial) Autocorrelation Function] [Method1: d= 1, D=...] [2009-12-11 12:34:39] [1433a524809eda02c3198b3ae6eebb69]
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Dataseries X:
162
161
149
139
135
130
127
122
117
112
113
149
157
157
147
137
132
125
123
117
114
111
112
144
150
149
134
123
116
117
111
105
102
95
93
124
130
124
115
106
105
105
101
95
93
84
87
116
120
117
109
105
107
109
109
108
107
99
103
131
137

 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=59203&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=59203&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59203&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 0.796105 6.2178 0 2 0.500674 3.9104 0.000117 3 0.286952 2.2412 0.014333 4 0.1748 1.3652 0.088597 5 0.1334 1.0419 0.150788 6 0.113772 0.8886 0.188859 7 0.088843 0.6939 0.245194 8 0.087421 0.6828 0.248665 9 0.176664 1.3798 0.086344 10 0.368142 2.8753 0.002776 11 0.595163 4.6484 9e-06 12 0.663557 5.1825 1e-06 13 0.47189 3.6856 0.000243 14 0.213191 1.6651 0.050513 15 0.02868 0.224 0.411754 16 -0.070506 -0.5507 0.291936 17 -0.112669 -0.88 0.191163 18 -0.136698 -1.0676 0.144943 19 -0.173361 -1.354 0.090367 20 -0.182034 -1.4217 0.080098 21 -0.116442 -0.9094 0.183348 22 0.031185 0.2436 0.404194 23 0.205358 1.6039 0.056951 24 0.246175 1.9227 0.029596 25 0.091455 0.7143 0.238887 26 -0.102592 -0.8013 0.213042 27 -0.21802 -1.7028 0.046849 28 -0.273109 -2.133 0.018476 29 -0.290408 -2.2682 0.013436 30 -0.314784 -2.4585 0.008402 31 -0.337141 -2.6332 0.005352 32 -0.339018 -2.6478 0.005149 33 -0.280966 -2.1944 0.016012 34 -0.155232 -1.2124 0.115017 35 -0.0104 -0.0812 0.467764 36 0.018022 0.1408 0.444262

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.796105 & 6.2178 & 0 \tabularnewline
2 & 0.500674 & 3.9104 & 0.000117 \tabularnewline
3 & 0.286952 & 2.2412 & 0.014333 \tabularnewline
4 & 0.1748 & 1.3652 & 0.088597 \tabularnewline
5 & 0.1334 & 1.0419 & 0.150788 \tabularnewline
6 & 0.113772 & 0.8886 & 0.188859 \tabularnewline
7 & 0.088843 & 0.6939 & 0.245194 \tabularnewline
8 & 0.087421 & 0.6828 & 0.248665 \tabularnewline
9 & 0.176664 & 1.3798 & 0.086344 \tabularnewline
10 & 0.368142 & 2.8753 & 0.002776 \tabularnewline
11 & 0.595163 & 4.6484 & 9e-06 \tabularnewline
12 & 0.663557 & 5.1825 & 1e-06 \tabularnewline
13 & 0.47189 & 3.6856 & 0.000243 \tabularnewline
14 & 0.213191 & 1.6651 & 0.050513 \tabularnewline
15 & 0.02868 & 0.224 & 0.411754 \tabularnewline
16 & -0.070506 & -0.5507 & 0.291936 \tabularnewline
17 & -0.112669 & -0.88 & 0.191163 \tabularnewline
18 & -0.136698 & -1.0676 & 0.144943 \tabularnewline
19 & -0.173361 & -1.354 & 0.090367 \tabularnewline
20 & -0.182034 & -1.4217 & 0.080098 \tabularnewline
21 & -0.116442 & -0.9094 & 0.183348 \tabularnewline
22 & 0.031185 & 0.2436 & 0.404194 \tabularnewline
23 & 0.205358 & 1.6039 & 0.056951 \tabularnewline
24 & 0.246175 & 1.9227 & 0.029596 \tabularnewline
25 & 0.091455 & 0.7143 & 0.238887 \tabularnewline
26 & -0.102592 & -0.8013 & 0.213042 \tabularnewline
27 & -0.21802 & -1.7028 & 0.046849 \tabularnewline
28 & -0.273109 & -2.133 & 0.018476 \tabularnewline
29 & -0.290408 & -2.2682 & 0.013436 \tabularnewline
30 & -0.314784 & -2.4585 & 0.008402 \tabularnewline
31 & -0.337141 & -2.6332 & 0.005352 \tabularnewline
32 & -0.339018 & -2.6478 & 0.005149 \tabularnewline
33 & -0.280966 & -2.1944 & 0.016012 \tabularnewline
34 & -0.155232 & -1.2124 & 0.115017 \tabularnewline
35 & -0.0104 & -0.0812 & 0.467764 \tabularnewline
36 & 0.018022 & 0.1408 & 0.444262 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59203&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]0.796105[/C][C]6.2178[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.500674[/C][C]3.9104[/C][C]0.000117[/C][/ROW]
[ROW][C]3[/C][C]0.286952[/C][C]2.2412[/C][C]0.014333[/C][/ROW]
[ROW][C]4[/C][C]0.1748[/C][C]1.3652[/C][C]0.088597[/C][/ROW]
[ROW][C]5[/C][C]0.1334[/C][C]1.0419[/C][C]0.150788[/C][/ROW]
[ROW][C]6[/C][C]0.113772[/C][C]0.8886[/C][C]0.188859[/C][/ROW]
[ROW][C]7[/C][C]0.088843[/C][C]0.6939[/C][C]0.245194[/C][/ROW]
[ROW][C]8[/C][C]0.087421[/C][C]0.6828[/C][C]0.248665[/C][/ROW]
[ROW][C]9[/C][C]0.176664[/C][C]1.3798[/C][C]0.086344[/C][/ROW]
[ROW][C]10[/C][C]0.368142[/C][C]2.8753[/C][C]0.002776[/C][/ROW]
[ROW][C]11[/C][C]0.595163[/C][C]4.6484[/C][C]9e-06[/C][/ROW]
[ROW][C]12[/C][C]0.663557[/C][C]5.1825[/C][C]1e-06[/C][/ROW]
[ROW][C]13[/C][C]0.47189[/C][C]3.6856[/C][C]0.000243[/C][/ROW]
[ROW][C]14[/C][C]0.213191[/C][C]1.6651[/C][C]0.050513[/C][/ROW]
[ROW][C]15[/C][C]0.02868[/C][C]0.224[/C][C]0.411754[/C][/ROW]
[ROW][C]16[/C][C]-0.070506[/C][C]-0.5507[/C][C]0.291936[/C][/ROW]
[ROW][C]17[/C][C]-0.112669[/C][C]-0.88[/C][C]0.191163[/C][/ROW]
[ROW][C]18[/C][C]-0.136698[/C][C]-1.0676[/C][C]0.144943[/C][/ROW]
[ROW][C]19[/C][C]-0.173361[/C][C]-1.354[/C][C]0.090367[/C][/ROW]
[ROW][C]20[/C][C]-0.182034[/C][C]-1.4217[/C][C]0.080098[/C][/ROW]
[ROW][C]21[/C][C]-0.116442[/C][C]-0.9094[/C][C]0.183348[/C][/ROW]
[ROW][C]22[/C][C]0.031185[/C][C]0.2436[/C][C]0.404194[/C][/ROW]
[ROW][C]23[/C][C]0.205358[/C][C]1.6039[/C][C]0.056951[/C][/ROW]
[ROW][C]24[/C][C]0.246175[/C][C]1.9227[/C][C]0.029596[/C][/ROW]
[ROW][C]25[/C][C]0.091455[/C][C]0.7143[/C][C]0.238887[/C][/ROW]
[ROW][C]26[/C][C]-0.102592[/C][C]-0.8013[/C][C]0.213042[/C][/ROW]
[ROW][C]27[/C][C]-0.21802[/C][C]-1.7028[/C][C]0.046849[/C][/ROW]
[ROW][C]28[/C][C]-0.273109[/C][C]-2.133[/C][C]0.018476[/C][/ROW]
[ROW][C]29[/C][C]-0.290408[/C][C]-2.2682[/C][C]0.013436[/C][/ROW]
[ROW][C]30[/C][C]-0.314784[/C][C]-2.4585[/C][C]0.008402[/C][/ROW]
[ROW][C]31[/C][C]-0.337141[/C][C]-2.6332[/C][C]0.005352[/C][/ROW]
[ROW][C]32[/C][C]-0.339018[/C][C]-2.6478[/C][C]0.005149[/C][/ROW]
[ROW][C]33[/C][C]-0.280966[/C][C]-2.1944[/C][C]0.016012[/C][/ROW]
[ROW][C]34[/C][C]-0.155232[/C][C]-1.2124[/C][C]0.115017[/C][/ROW]
[ROW][C]35[/C][C]-0.0104[/C][C]-0.0812[/C][C]0.467764[/C][/ROW]
[ROW][C]36[/C][C]0.018022[/C][C]0.1408[/C][C]0.444262[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59203&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59203&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 0.796105 6.2178 0 2 0.500674 3.9104 0.000117 3 0.286952 2.2412 0.014333 4 0.1748 1.3652 0.088597 5 0.1334 1.0419 0.150788 6 0.113772 0.8886 0.188859 7 0.088843 0.6939 0.245194 8 0.087421 0.6828 0.248665 9 0.176664 1.3798 0.086344 10 0.368142 2.8753 0.002776 11 0.595163 4.6484 9e-06 12 0.663557 5.1825 1e-06 13 0.47189 3.6856 0.000243 14 0.213191 1.6651 0.050513 15 0.02868 0.224 0.411754 16 -0.070506 -0.5507 0.291936 17 -0.112669 -0.88 0.191163 18 -0.136698 -1.0676 0.144943 19 -0.173361 -1.354 0.090367 20 -0.182034 -1.4217 0.080098 21 -0.116442 -0.9094 0.183348 22 0.031185 0.2436 0.404194 23 0.205358 1.6039 0.056951 24 0.246175 1.9227 0.029596 25 0.091455 0.7143 0.238887 26 -0.102592 -0.8013 0.213042 27 -0.21802 -1.7028 0.046849 28 -0.273109 -2.133 0.018476 29 -0.290408 -2.2682 0.013436 30 -0.314784 -2.4585 0.008402 31 -0.337141 -2.6332 0.005352 32 -0.339018 -2.6478 0.005149 33 -0.280966 -2.1944 0.016012 34 -0.155232 -1.2124 0.115017 35 -0.0104 -0.0812 0.467764 36 0.018022 0.1408 0.444262

 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.796105 6.2178 0 2 -0.363471 -2.8388 0.003071 3 0.10335 0.8072 0.211347 4 0.026759 0.209 0.417574 5 0.039506 0.3085 0.379358 6 -0.009805 -0.0766 0.469603 7 -0.011712 -0.0915 0.463707 8 0.086167 0.673 0.251749 9 0.254442 1.9873 0.025695 10 0.321393 2.5102 0.007368 11 0.341255 2.6653 0.004915 12 -0.091496 -0.7146 0.23879 13 -0.425352 -3.3221 0.000757 14 -0.129465 -1.0112 0.157968 15 -0.086574 -0.6762 0.250746 16 -0.082544 -0.6447 0.260774 17 -0.038257 -0.2988 0.383055 18 -0.012746 -0.0996 0.460513 19 -0.064199 -0.5014 0.308944 20 -0.072282 -0.5645 0.287229 21 -0.174215 -1.3607 0.089314 22 -0.14352 -1.1209 0.133355 23 0.056725 0.443 0.329653 24 0.069147 0.5401 0.295562 25 -0.041591 -0.3248 0.373209 26 0.037504 0.2929 0.385289 27 0.077439 0.6048 0.273773 28 -0.033413 -0.261 0.3975 29 -0.024692 -0.1928 0.42386 30 -0.099941 -0.7806 0.219039 31 0.072419 0.5656 0.286867 32 0.006892 0.0538 0.478625 33 -0.006526 -0.051 0.479759 34 -0.063816 -0.4984 0.30999 35 0.00776 0.0606 0.475933 36 -0.043982 -0.3435 0.366198

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.796105 & 6.2178 & 0 \tabularnewline
2 & -0.363471 & -2.8388 & 0.003071 \tabularnewline
3 & 0.10335 & 0.8072 & 0.211347 \tabularnewline
4 & 0.026759 & 0.209 & 0.417574 \tabularnewline
5 & 0.039506 & 0.3085 & 0.379358 \tabularnewline
6 & -0.009805 & -0.0766 & 0.469603 \tabularnewline
7 & -0.011712 & -0.0915 & 0.463707 \tabularnewline
8 & 0.086167 & 0.673 & 0.251749 \tabularnewline
9 & 0.254442 & 1.9873 & 0.025695 \tabularnewline
10 & 0.321393 & 2.5102 & 0.007368 \tabularnewline
11 & 0.341255 & 2.6653 & 0.004915 \tabularnewline
12 & -0.091496 & -0.7146 & 0.23879 \tabularnewline
13 & -0.425352 & -3.3221 & 0.000757 \tabularnewline
14 & -0.129465 & -1.0112 & 0.157968 \tabularnewline
15 & -0.086574 & -0.6762 & 0.250746 \tabularnewline
16 & -0.082544 & -0.6447 & 0.260774 \tabularnewline
17 & -0.038257 & -0.2988 & 0.383055 \tabularnewline
18 & -0.012746 & -0.0996 & 0.460513 \tabularnewline
19 & -0.064199 & -0.5014 & 0.308944 \tabularnewline
20 & -0.072282 & -0.5645 & 0.287229 \tabularnewline
21 & -0.174215 & -1.3607 & 0.089314 \tabularnewline
22 & -0.14352 & -1.1209 & 0.133355 \tabularnewline
23 & 0.056725 & 0.443 & 0.329653 \tabularnewline
24 & 0.069147 & 0.5401 & 0.295562 \tabularnewline
25 & -0.041591 & -0.3248 & 0.373209 \tabularnewline
26 & 0.037504 & 0.2929 & 0.385289 \tabularnewline
27 & 0.077439 & 0.6048 & 0.273773 \tabularnewline
28 & -0.033413 & -0.261 & 0.3975 \tabularnewline
29 & -0.024692 & -0.1928 & 0.42386 \tabularnewline
30 & -0.099941 & -0.7806 & 0.219039 \tabularnewline
31 & 0.072419 & 0.5656 & 0.286867 \tabularnewline
32 & 0.006892 & 0.0538 & 0.478625 \tabularnewline
33 & -0.006526 & -0.051 & 0.479759 \tabularnewline
34 & -0.063816 & -0.4984 & 0.30999 \tabularnewline
35 & 0.00776 & 0.0606 & 0.475933 \tabularnewline
36 & -0.043982 & -0.3435 & 0.366198 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59203&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]0.796105[/C][C]6.2178[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.363471[/C][C]-2.8388[/C][C]0.003071[/C][/ROW]
[ROW][C]3[/C][C]0.10335[/C][C]0.8072[/C][C]0.211347[/C][/ROW]
[ROW][C]4[/C][C]0.026759[/C][C]0.209[/C][C]0.417574[/C][/ROW]
[ROW][C]5[/C][C]0.039506[/C][C]0.3085[/C][C]0.379358[/C][/ROW]
[ROW][C]6[/C][C]-0.009805[/C][C]-0.0766[/C][C]0.469603[/C][/ROW]
[ROW][C]7[/C][C]-0.011712[/C][C]-0.0915[/C][C]0.463707[/C][/ROW]
[ROW][C]8[/C][C]0.086167[/C][C]0.673[/C][C]0.251749[/C][/ROW]
[ROW][C]9[/C][C]0.254442[/C][C]1.9873[/C][C]0.025695[/C][/ROW]
[ROW][C]10[/C][C]0.321393[/C][C]2.5102[/C][C]0.007368[/C][/ROW]
[ROW][C]11[/C][C]0.341255[/C][C]2.6653[/C][C]0.004915[/C][/ROW]
[ROW][C]12[/C][C]-0.091496[/C][C]-0.7146[/C][C]0.23879[/C][/ROW]
[ROW][C]13[/C][C]-0.425352[/C][C]-3.3221[/C][C]0.000757[/C][/ROW]
[ROW][C]14[/C][C]-0.129465[/C][C]-1.0112[/C][C]0.157968[/C][/ROW]
[ROW][C]15[/C][C]-0.086574[/C][C]-0.6762[/C][C]0.250746[/C][/ROW]
[ROW][C]16[/C][C]-0.082544[/C][C]-0.6447[/C][C]0.260774[/C][/ROW]
[ROW][C]17[/C][C]-0.038257[/C][C]-0.2988[/C][C]0.383055[/C][/ROW]
[ROW][C]18[/C][C]-0.012746[/C][C]-0.0996[/C][C]0.460513[/C][/ROW]
[ROW][C]19[/C][C]-0.064199[/C][C]-0.5014[/C][C]0.308944[/C][/ROW]
[ROW][C]20[/C][C]-0.072282[/C][C]-0.5645[/C][C]0.287229[/C][/ROW]
[ROW][C]21[/C][C]-0.174215[/C][C]-1.3607[/C][C]0.089314[/C][/ROW]
[ROW][C]22[/C][C]-0.14352[/C][C]-1.1209[/C][C]0.133355[/C][/ROW]
[ROW][C]23[/C][C]0.056725[/C][C]0.443[/C][C]0.329653[/C][/ROW]
[ROW][C]24[/C][C]0.069147[/C][C]0.5401[/C][C]0.295562[/C][/ROW]
[ROW][C]25[/C][C]-0.041591[/C][C]-0.3248[/C][C]0.373209[/C][/ROW]
[ROW][C]26[/C][C]0.037504[/C][C]0.2929[/C][C]0.385289[/C][/ROW]
[ROW][C]27[/C][C]0.077439[/C][C]0.6048[/C][C]0.273773[/C][/ROW]
[ROW][C]28[/C][C]-0.033413[/C][C]-0.261[/C][C]0.3975[/C][/ROW]
[ROW][C]29[/C][C]-0.024692[/C][C]-0.1928[/C][C]0.42386[/C][/ROW]
[ROW][C]30[/C][C]-0.099941[/C][C]-0.7806[/C][C]0.219039[/C][/ROW]
[ROW][C]31[/C][C]0.072419[/C][C]0.5656[/C][C]0.286867[/C][/ROW]
[ROW][C]32[/C][C]0.006892[/C][C]0.0538[/C][C]0.478625[/C][/ROW]
[ROW][C]33[/C][C]-0.006526[/C][C]-0.051[/C][C]0.479759[/C][/ROW]
[ROW][C]34[/C][C]-0.063816[/C][C]-0.4984[/C][C]0.30999[/C][/ROW]
[ROW][C]35[/C][C]0.00776[/C][C]0.0606[/C][C]0.475933[/C][/ROW]
[ROW][C]36[/C][C]-0.043982[/C][C]-0.3435[/C][C]0.366198[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59203&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59203&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 0.796105 6.2178 0 2 -0.363471 -2.8388 0.003071 3 0.10335 0.8072 0.211347 4 0.026759 0.209 0.417574 5 0.039506 0.3085 0.379358 6 -0.009805 -0.0766 0.469603 7 -0.011712 -0.0915 0.463707 8 0.086167 0.673 0.251749 9 0.254442 1.9873 0.025695 10 0.321393 2.5102 0.007368 11 0.341255 2.6653 0.004915 12 -0.091496 -0.7146 0.23879 13 -0.425352 -3.3221 0.000757 14 -0.129465 -1.0112 0.157968 15 -0.086574 -0.6762 0.250746 16 -0.082544 -0.6447 0.260774 17 -0.038257 -0.2988 0.383055 18 -0.012746 -0.0996 0.460513 19 -0.064199 -0.5014 0.308944 20 -0.072282 -0.5645 0.287229 21 -0.174215 -1.3607 0.089314 22 -0.14352 -1.1209 0.133355 23 0.056725 0.443 0.329653 24 0.069147 0.5401 0.295562 25 -0.041591 -0.3248 0.373209 26 0.037504 0.2929 0.385289 27 0.077439 0.6048 0.273773 28 -0.033413 -0.261 0.3975 29 -0.024692 -0.1928 0.42386 30 -0.099941 -0.7806 0.219039 31 0.072419 0.5656 0.286867 32 0.006892 0.0538 0.478625 33 -0.006526 -0.051 0.479759 34 -0.063816 -0.4984 0.30999 35 0.00776 0.0606 0.475933 36 -0.043982 -0.3435 0.366198

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')