## 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 09:42:45 -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/Nov/24/t12590810321dcnlt5kaerso15.htm/, Retrieved Wed, 11 Sep 2024 07:42:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59158, Retrieved Wed, 11 Sep 2024 07:42:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact254
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] [SHWWS8methode1a] [2009-11-24 16:42:45] [db49399df1e4a3dbe31268849cebfd7f] [Current]
-   P             [(Partial) Autocorrelation Function] [SHWWS9] [2009-12-01 19:06:31] [a66d3a79ef9e5308cd94a469bc5ca464]
-    D            [(Partial) Autocorrelation Function] [PAPER] [2009-12-13 09:34:23] [a66d3a79ef9e5308cd94a469bc5ca464]
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Dataseries X:
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=59158&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=59158&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59158&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 0.77807 6.0269 0 2 0.480086 3.7187 0.000221 3 0.268207 2.0775 0.02102 4 0.154658 1.198 0.117819 5 0.120124 0.9305 0.177927 6 0.105185 0.8148 0.209216 7 0.088793 0.6878 0.247118 8 0.098169 0.7604 0.224994 9 0.206498 1.5995 0.057478 10 0.413637 3.204 0.001086 11 0.584965 4.5311 1.4e-05 12 0.641523 4.9692 3e-06 13 0.431549 3.3428 0.000716 14 0.16997 1.3166 0.096493 15 -0.009478 -0.0734 0.47086 16 -0.106195 -0.8226 0.207001 17 -0.136721 -1.059 0.146915 18 -0.157948 -1.2235 0.11297 19 -0.184574 -1.4297 0.078995 20 -0.187027 -1.4487 0.076313 21 -0.108521 -0.8406 0.201955 22 0.050875 0.3941 0.34746 23 0.172986 1.3399 0.092658 24 0.203698 1.5778 0.05993 25 0.035969 0.2786 0.390748 26 -0.1446 -1.1201 0.133574 27 -0.246467 -1.9091 0.030516 28 -0.290821 -2.2527 0.013974 29 -0.311022 -2.4092 0.009537 30 -0.324202 -2.5113 0.00737 31 -0.335182 -2.5963 0.005916 32 -0.330237 -2.558 0.006535 33 -0.25141 -1.9474 0.028085 34 -0.109512 -0.8483 0.199827 35 -0.017223 -0.1334 0.447159 36 -0.00018 -0.0014 0.499447

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.77807 & 6.0269 & 0 \tabularnewline
2 & 0.480086 & 3.7187 & 0.000221 \tabularnewline
3 & 0.268207 & 2.0775 & 0.02102 \tabularnewline
4 & 0.154658 & 1.198 & 0.117819 \tabularnewline
5 & 0.120124 & 0.9305 & 0.177927 \tabularnewline
6 & 0.105185 & 0.8148 & 0.209216 \tabularnewline
7 & 0.088793 & 0.6878 & 0.247118 \tabularnewline
8 & 0.098169 & 0.7604 & 0.224994 \tabularnewline
9 & 0.206498 & 1.5995 & 0.057478 \tabularnewline
10 & 0.413637 & 3.204 & 0.001086 \tabularnewline
11 & 0.584965 & 4.5311 & 1.4e-05 \tabularnewline
12 & 0.641523 & 4.9692 & 3e-06 \tabularnewline
13 & 0.431549 & 3.3428 & 0.000716 \tabularnewline
14 & 0.16997 & 1.3166 & 0.096493 \tabularnewline
15 & -0.009478 & -0.0734 & 0.47086 \tabularnewline
16 & -0.106195 & -0.8226 & 0.207001 \tabularnewline
17 & -0.136721 & -1.059 & 0.146915 \tabularnewline
18 & -0.157948 & -1.2235 & 0.11297 \tabularnewline
19 & -0.184574 & -1.4297 & 0.078995 \tabularnewline
20 & -0.187027 & -1.4487 & 0.076313 \tabularnewline
21 & -0.108521 & -0.8406 & 0.201955 \tabularnewline
22 & 0.050875 & 0.3941 & 0.34746 \tabularnewline
23 & 0.172986 & 1.3399 & 0.092658 \tabularnewline
24 & 0.203698 & 1.5778 & 0.05993 \tabularnewline
25 & 0.035969 & 0.2786 & 0.390748 \tabularnewline
26 & -0.1446 & -1.1201 & 0.133574 \tabularnewline
27 & -0.246467 & -1.9091 & 0.030516 \tabularnewline
28 & -0.290821 & -2.2527 & 0.013974 \tabularnewline
29 & -0.311022 & -2.4092 & 0.009537 \tabularnewline
30 & -0.324202 & -2.5113 & 0.00737 \tabularnewline
31 & -0.335182 & -2.5963 & 0.005916 \tabularnewline
32 & -0.330237 & -2.558 & 0.006535 \tabularnewline
33 & -0.25141 & -1.9474 & 0.028085 \tabularnewline
34 & -0.109512 & -0.8483 & 0.199827 \tabularnewline
35 & -0.017223 & -0.1334 & 0.447159 \tabularnewline
36 & -0.00018 & -0.0014 & 0.499447 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59158&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]0.77807[/C][C]6.0269[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.480086[/C][C]3.7187[/C][C]0.000221[/C][/ROW]
[ROW][C]3[/C][C]0.268207[/C][C]2.0775[/C][C]0.02102[/C][/ROW]
[ROW][C]4[/C][C]0.154658[/C][C]1.198[/C][C]0.117819[/C][/ROW]
[ROW][C]5[/C][C]0.120124[/C][C]0.9305[/C][C]0.177927[/C][/ROW]
[ROW][C]6[/C][C]0.105185[/C][C]0.8148[/C][C]0.209216[/C][/ROW]
[ROW][C]7[/C][C]0.088793[/C][C]0.6878[/C][C]0.247118[/C][/ROW]
[ROW][C]8[/C][C]0.098169[/C][C]0.7604[/C][C]0.224994[/C][/ROW]
[ROW][C]9[/C][C]0.206498[/C][C]1.5995[/C][C]0.057478[/C][/ROW]
[ROW][C]10[/C][C]0.413637[/C][C]3.204[/C][C]0.001086[/C][/ROW]
[ROW][C]11[/C][C]0.584965[/C][C]4.5311[/C][C]1.4e-05[/C][/ROW]
[ROW][C]12[/C][C]0.641523[/C][C]4.9692[/C][C]3e-06[/C][/ROW]
[ROW][C]13[/C][C]0.431549[/C][C]3.3428[/C][C]0.000716[/C][/ROW]
[ROW][C]14[/C][C]0.16997[/C][C]1.3166[/C][C]0.096493[/C][/ROW]
[ROW][C]15[/C][C]-0.009478[/C][C]-0.0734[/C][C]0.47086[/C][/ROW]
[ROW][C]16[/C][C]-0.106195[/C][C]-0.8226[/C][C]0.207001[/C][/ROW]
[ROW][C]17[/C][C]-0.136721[/C][C]-1.059[/C][C]0.146915[/C][/ROW]
[ROW][C]18[/C][C]-0.157948[/C][C]-1.2235[/C][C]0.11297[/C][/ROW]
[ROW][C]19[/C][C]-0.184574[/C][C]-1.4297[/C][C]0.078995[/C][/ROW]
[ROW][C]20[/C][C]-0.187027[/C][C]-1.4487[/C][C]0.076313[/C][/ROW]
[ROW][C]21[/C][C]-0.108521[/C][C]-0.8406[/C][C]0.201955[/C][/ROW]
[ROW][C]22[/C][C]0.050875[/C][C]0.3941[/C][C]0.34746[/C][/ROW]
[ROW][C]23[/C][C]0.172986[/C][C]1.3399[/C][C]0.092658[/C][/ROW]
[ROW][C]24[/C][C]0.203698[/C][C]1.5778[/C][C]0.05993[/C][/ROW]
[ROW][C]25[/C][C]0.035969[/C][C]0.2786[/C][C]0.390748[/C][/ROW]
[ROW][C]26[/C][C]-0.1446[/C][C]-1.1201[/C][C]0.133574[/C][/ROW]
[ROW][C]27[/C][C]-0.246467[/C][C]-1.9091[/C][C]0.030516[/C][/ROW]
[ROW][C]28[/C][C]-0.290821[/C][C]-2.2527[/C][C]0.013974[/C][/ROW]
[ROW][C]29[/C][C]-0.311022[/C][C]-2.4092[/C][C]0.009537[/C][/ROW]
[ROW][C]30[/C][C]-0.324202[/C][C]-2.5113[/C][C]0.00737[/C][/ROW]
[ROW][C]31[/C][C]-0.335182[/C][C]-2.5963[/C][C]0.005916[/C][/ROW]
[ROW][C]32[/C][C]-0.330237[/C][C]-2.558[/C][C]0.006535[/C][/ROW]
[ROW][C]33[/C][C]-0.25141[/C][C]-1.9474[/C][C]0.028085[/C][/ROW]
[ROW][C]34[/C][C]-0.109512[/C][C]-0.8483[/C][C]0.199827[/C][/ROW]
[ROW][C]35[/C][C]-0.017223[/C][C]-0.1334[/C][C]0.447159[/C][/ROW]
[ROW][C]36[/C][C]-0.00018[/C][C]-0.0014[/C][C]0.499447[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59158&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59158&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 0.77807 6.0269 0 2 0.480086 3.7187 0.000221 3 0.268207 2.0775 0.02102 4 0.154658 1.198 0.117819 5 0.120124 0.9305 0.177927 6 0.105185 0.8148 0.209216 7 0.088793 0.6878 0.247118 8 0.098169 0.7604 0.224994 9 0.206498 1.5995 0.057478 10 0.413637 3.204 0.001086 11 0.584965 4.5311 1.4e-05 12 0.641523 4.9692 3e-06 13 0.431549 3.3428 0.000716 14 0.16997 1.3166 0.096493 15 -0.009478 -0.0734 0.47086 16 -0.106195 -0.8226 0.207001 17 -0.136721 -1.059 0.146915 18 -0.157948 -1.2235 0.11297 19 -0.184574 -1.4297 0.078995 20 -0.187027 -1.4487 0.076313 21 -0.108521 -0.8406 0.201955 22 0.050875 0.3941 0.34746 23 0.172986 1.3399 0.092658 24 0.203698 1.5778 0.05993 25 0.035969 0.2786 0.390748 26 -0.1446 -1.1201 0.133574 27 -0.246467 -1.9091 0.030516 28 -0.290821 -2.2527 0.013974 29 -0.311022 -2.4092 0.009537 30 -0.324202 -2.5113 0.00737 31 -0.335182 -2.5963 0.005916 32 -0.330237 -2.558 0.006535 33 -0.25141 -1.9474 0.028085 34 -0.109512 -0.8483 0.199827 35 -0.017223 -0.1334 0.447159 36 -0.00018 -0.0014 0.499447

 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.77807 6.0269 0 2 -0.317548 -2.4597 0.008402 3 0.065173 0.5048 0.307764 4 0.022564 0.1748 0.430921 5 0.061876 0.4793 0.316738 6 -0.019723 -0.1528 0.439546 7 0.009441 0.0731 0.470972 8 0.082286 0.6374 0.26315 9 0.276686 2.1432 0.018081 10 0.332357 2.5744 0.006263 11 0.164447 1.2738 0.103823 12 0.126617 0.9808 0.165321 13 -0.478228 -3.7043 0.000232 14 -0.056326 -0.4363 0.332093 15 -0.163035 -1.2629 0.105762 16 -0.094941 -0.7354 0.232476 17 -0.045502 -0.3525 0.362866 18 -0.068552 -0.531 0.298688 19 -0.101931 -0.7896 0.216448 20 -0.174252 -1.3497 0.091084 21 -0.145798 -1.1293 0.131624 22 -0.111617 -0.8646 0.195356 23 0.044494 0.3446 0.365783 24 0.098937 0.7664 0.223233 25 -0.081968 -0.6349 0.263946 26 0.171981 1.3322 0.093923 27 0.006546 0.0507 0.479865 28 0.060483 0.4685 0.320561 29 -0.056669 -0.439 0.331135 30 0.086187 0.6676 0.253475 31 0.052684 0.4081 0.342331 32 0.001416 0.011 0.495644 33 0.035514 0.2751 0.392096 34 -0.085126 -0.6594 0.256087 35 -0.02587 -0.2004 0.420928 36 -0.108637 -0.8415 0.201705

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.77807 & 6.0269 & 0 \tabularnewline
2 & -0.317548 & -2.4597 & 0.008402 \tabularnewline
3 & 0.065173 & 0.5048 & 0.307764 \tabularnewline
4 & 0.022564 & 0.1748 & 0.430921 \tabularnewline
5 & 0.061876 & 0.4793 & 0.316738 \tabularnewline
6 & -0.019723 & -0.1528 & 0.439546 \tabularnewline
7 & 0.009441 & 0.0731 & 0.470972 \tabularnewline
8 & 0.082286 & 0.6374 & 0.26315 \tabularnewline
9 & 0.276686 & 2.1432 & 0.018081 \tabularnewline
10 & 0.332357 & 2.5744 & 0.006263 \tabularnewline
11 & 0.164447 & 1.2738 & 0.103823 \tabularnewline
12 & 0.126617 & 0.9808 & 0.165321 \tabularnewline
13 & -0.478228 & -3.7043 & 0.000232 \tabularnewline
14 & -0.056326 & -0.4363 & 0.332093 \tabularnewline
15 & -0.163035 & -1.2629 & 0.105762 \tabularnewline
16 & -0.094941 & -0.7354 & 0.232476 \tabularnewline
17 & -0.045502 & -0.3525 & 0.362866 \tabularnewline
18 & -0.068552 & -0.531 & 0.298688 \tabularnewline
19 & -0.101931 & -0.7896 & 0.216448 \tabularnewline
20 & -0.174252 & -1.3497 & 0.091084 \tabularnewline
21 & -0.145798 & -1.1293 & 0.131624 \tabularnewline
22 & -0.111617 & -0.8646 & 0.195356 \tabularnewline
23 & 0.044494 & 0.3446 & 0.365783 \tabularnewline
24 & 0.098937 & 0.7664 & 0.223233 \tabularnewline
25 & -0.081968 & -0.6349 & 0.263946 \tabularnewline
26 & 0.171981 & 1.3322 & 0.093923 \tabularnewline
27 & 0.006546 & 0.0507 & 0.479865 \tabularnewline
28 & 0.060483 & 0.4685 & 0.320561 \tabularnewline
29 & -0.056669 & -0.439 & 0.331135 \tabularnewline
30 & 0.086187 & 0.6676 & 0.253475 \tabularnewline
31 & 0.052684 & 0.4081 & 0.342331 \tabularnewline
32 & 0.001416 & 0.011 & 0.495644 \tabularnewline
33 & 0.035514 & 0.2751 & 0.392096 \tabularnewline
34 & -0.085126 & -0.6594 & 0.256087 \tabularnewline
35 & -0.02587 & -0.2004 & 0.420928 \tabularnewline
36 & -0.108637 & -0.8415 & 0.201705 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59158&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]0.77807[/C][C]6.0269[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.317548[/C][C]-2.4597[/C][C]0.008402[/C][/ROW]
[ROW][C]3[/C][C]0.065173[/C][C]0.5048[/C][C]0.307764[/C][/ROW]
[ROW][C]4[/C][C]0.022564[/C][C]0.1748[/C][C]0.430921[/C][/ROW]
[ROW][C]5[/C][C]0.061876[/C][C]0.4793[/C][C]0.316738[/C][/ROW]
[ROW][C]6[/C][C]-0.019723[/C][C]-0.1528[/C][C]0.439546[/C][/ROW]
[ROW][C]7[/C][C]0.009441[/C][C]0.0731[/C][C]0.470972[/C][/ROW]
[ROW][C]8[/C][C]0.082286[/C][C]0.6374[/C][C]0.26315[/C][/ROW]
[ROW][C]9[/C][C]0.276686[/C][C]2.1432[/C][C]0.018081[/C][/ROW]
[ROW][C]10[/C][C]0.332357[/C][C]2.5744[/C][C]0.006263[/C][/ROW]
[ROW][C]11[/C][C]0.164447[/C][C]1.2738[/C][C]0.103823[/C][/ROW]
[ROW][C]12[/C][C]0.126617[/C][C]0.9808[/C][C]0.165321[/C][/ROW]
[ROW][C]13[/C][C]-0.478228[/C][C]-3.7043[/C][C]0.000232[/C][/ROW]
[ROW][C]14[/C][C]-0.056326[/C][C]-0.4363[/C][C]0.332093[/C][/ROW]
[ROW][C]15[/C][C]-0.163035[/C][C]-1.2629[/C][C]0.105762[/C][/ROW]
[ROW][C]16[/C][C]-0.094941[/C][C]-0.7354[/C][C]0.232476[/C][/ROW]
[ROW][C]17[/C][C]-0.045502[/C][C]-0.3525[/C][C]0.362866[/C][/ROW]
[ROW][C]18[/C][C]-0.068552[/C][C]-0.531[/C][C]0.298688[/C][/ROW]
[ROW][C]19[/C][C]-0.101931[/C][C]-0.7896[/C][C]0.216448[/C][/ROW]
[ROW][C]20[/C][C]-0.174252[/C][C]-1.3497[/C][C]0.091084[/C][/ROW]
[ROW][C]21[/C][C]-0.145798[/C][C]-1.1293[/C][C]0.131624[/C][/ROW]
[ROW][C]22[/C][C]-0.111617[/C][C]-0.8646[/C][C]0.195356[/C][/ROW]
[ROW][C]23[/C][C]0.044494[/C][C]0.3446[/C][C]0.365783[/C][/ROW]
[ROW][C]24[/C][C]0.098937[/C][C]0.7664[/C][C]0.223233[/C][/ROW]
[ROW][C]25[/C][C]-0.081968[/C][C]-0.6349[/C][C]0.263946[/C][/ROW]
[ROW][C]26[/C][C]0.171981[/C][C]1.3322[/C][C]0.093923[/C][/ROW]
[ROW][C]27[/C][C]0.006546[/C][C]0.0507[/C][C]0.479865[/C][/ROW]
[ROW][C]28[/C][C]0.060483[/C][C]0.4685[/C][C]0.320561[/C][/ROW]
[ROW][C]29[/C][C]-0.056669[/C][C]-0.439[/C][C]0.331135[/C][/ROW]
[ROW][C]30[/C][C]0.086187[/C][C]0.6676[/C][C]0.253475[/C][/ROW]
[ROW][C]31[/C][C]0.052684[/C][C]0.4081[/C][C]0.342331[/C][/ROW]
[ROW][C]32[/C][C]0.001416[/C][C]0.011[/C][C]0.495644[/C][/ROW]
[ROW][C]33[/C][C]0.035514[/C][C]0.2751[/C][C]0.392096[/C][/ROW]
[ROW][C]34[/C][C]-0.085126[/C][C]-0.6594[/C][C]0.256087[/C][/ROW]
[ROW][C]35[/C][C]-0.02587[/C][C]-0.2004[/C][C]0.420928[/C][/ROW]
[ROW][C]36[/C][C]-0.108637[/C][C]-0.8415[/C][C]0.201705[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59158&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59158&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 0.77807 6.0269 0 2 -0.317548 -2.4597 0.008402 3 0.065173 0.5048 0.307764 4 0.022564 0.1748 0.430921 5 0.061876 0.4793 0.316738 6 -0.019723 -0.1528 0.439546 7 0.009441 0.0731 0.470972 8 0.082286 0.6374 0.26315 9 0.276686 2.1432 0.018081 10 0.332357 2.5744 0.006263 11 0.164447 1.2738 0.103823 12 0.126617 0.9808 0.165321 13 -0.478228 -3.7043 0.000232 14 -0.056326 -0.4363 0.332093 15 -0.163035 -1.2629 0.105762 16 -0.094941 -0.7354 0.232476 17 -0.045502 -0.3525 0.362866 18 -0.068552 -0.531 0.298688 19 -0.101931 -0.7896 0.216448 20 -0.174252 -1.3497 0.091084 21 -0.145798 -1.1293 0.131624 22 -0.111617 -0.8646 0.195356 23 0.044494 0.3446 0.365783 24 0.098937 0.7664 0.223233 25 -0.081968 -0.6349 0.263946 26 0.171981 1.3322 0.093923 27 0.006546 0.0507 0.479865 28 0.060483 0.4685 0.320561 29 -0.056669 -0.439 0.331135 30 0.086187 0.6676 0.253475 31 0.052684 0.4081 0.342331 32 0.001416 0.011 0.495644 33 0.035514 0.2751 0.392096 34 -0.085126 -0.6594 0.256087 35 -0.02587 -0.2004 0.420928 36 -0.108637 -0.8415 0.201705

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; 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]*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')