## 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 11:40:40 -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/t1259088180a10jy2oagl39aur.htm/, Retrieved Wed, 07 Aug 2024 21:34:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59219, Retrieved Wed, 07 Aug 2024 21:34:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsWS8- methode 1 link 3
Estimated Impact207
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] [Workshop 8] [2009-11-24 18:40:40] [100339cefec36dfa6f2b82a1c918e250] [Current]
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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 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=59219&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=59219&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59219&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 0.014909 0.1033 0.459081 2 0.260666 1.8059 0.0386 3 0.030835 0.2136 0.41587 4 0.098962 0.6856 0.248124 5 -0.142922 -0.9902 0.163522 6 -0.004316 -0.0299 0.488136 7 0.084342 0.5843 0.280864 8 -0.002383 -0.0165 0.493447 9 0.196387 1.3606 0.089997 10 -0.016692 -0.1156 0.454207 11 0.403528 2.7957 0.003712 12 -0.164607 -1.1404 0.129883 13 0.022723 0.1574 0.437783 14 -0.000366 -0.0025 0.498994 15 0.050192 0.3477 0.364779 16 -0.158291 -1.0967 0.139128 17 0.059682 0.4135 0.340544 18 -0.089964 -0.6233 0.268022 19 -0.149519 -1.0359 0.15272 20 -0.008972 -0.0622 0.475348 21 -0.166586 -1.1541 0.127078 22 0.052409 0.3631 0.359062 23 -0.170476 -1.1811 0.121693 24 -0.036874 -0.2555 0.399725 25 -0.043007 -0.298 0.383509 26 0.013577 0.0941 0.462725 27 -0.157214 -1.0892 0.14075 28 -0.101549 -0.7036 0.242555 29 -0.098285 -0.6809 0.249592 30 -0.103907 -0.7199 0.237542 31 -0.003503 -0.0243 0.49037 32 -0.060095 -0.4164 0.339504 33 0.001085 0.0075 0.497016 34 -0.041513 -0.2876 0.38744 35 -0.020476 -0.1419 0.443892 36 -0.019459 -0.1348 0.446662

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.014909 & 0.1033 & 0.459081 \tabularnewline
2 & 0.260666 & 1.8059 & 0.0386 \tabularnewline
3 & 0.030835 & 0.2136 & 0.41587 \tabularnewline
4 & 0.098962 & 0.6856 & 0.248124 \tabularnewline
5 & -0.142922 & -0.9902 & 0.163522 \tabularnewline
6 & -0.004316 & -0.0299 & 0.488136 \tabularnewline
7 & 0.084342 & 0.5843 & 0.280864 \tabularnewline
8 & -0.002383 & -0.0165 & 0.493447 \tabularnewline
9 & 0.196387 & 1.3606 & 0.089997 \tabularnewline
10 & -0.016692 & -0.1156 & 0.454207 \tabularnewline
11 & 0.403528 & 2.7957 & 0.003712 \tabularnewline
12 & -0.164607 & -1.1404 & 0.129883 \tabularnewline
13 & 0.022723 & 0.1574 & 0.437783 \tabularnewline
14 & -0.000366 & -0.0025 & 0.498994 \tabularnewline
15 & 0.050192 & 0.3477 & 0.364779 \tabularnewline
16 & -0.158291 & -1.0967 & 0.139128 \tabularnewline
17 & 0.059682 & 0.4135 & 0.340544 \tabularnewline
18 & -0.089964 & -0.6233 & 0.268022 \tabularnewline
19 & -0.149519 & -1.0359 & 0.15272 \tabularnewline
20 & -0.008972 & -0.0622 & 0.475348 \tabularnewline
21 & -0.166586 & -1.1541 & 0.127078 \tabularnewline
22 & 0.052409 & 0.3631 & 0.359062 \tabularnewline
23 & -0.170476 & -1.1811 & 0.121693 \tabularnewline
24 & -0.036874 & -0.2555 & 0.399725 \tabularnewline
25 & -0.043007 & -0.298 & 0.383509 \tabularnewline
26 & 0.013577 & 0.0941 & 0.462725 \tabularnewline
27 & -0.157214 & -1.0892 & 0.14075 \tabularnewline
28 & -0.101549 & -0.7036 & 0.242555 \tabularnewline
29 & -0.098285 & -0.6809 & 0.249592 \tabularnewline
30 & -0.103907 & -0.7199 & 0.237542 \tabularnewline
31 & -0.003503 & -0.0243 & 0.49037 \tabularnewline
32 & -0.060095 & -0.4164 & 0.339504 \tabularnewline
33 & 0.001085 & 0.0075 & 0.497016 \tabularnewline
34 & -0.041513 & -0.2876 & 0.38744 \tabularnewline
35 & -0.020476 & -0.1419 & 0.443892 \tabularnewline
36 & -0.019459 & -0.1348 & 0.446662 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59219&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]0.014909[/C][C]0.1033[/C][C]0.459081[/C][/ROW]
[ROW][C]2[/C][C]0.260666[/C][C]1.8059[/C][C]0.0386[/C][/ROW]
[ROW][C]3[/C][C]0.030835[/C][C]0.2136[/C][C]0.41587[/C][/ROW]
[ROW][C]4[/C][C]0.098962[/C][C]0.6856[/C][C]0.248124[/C][/ROW]
[ROW][C]5[/C][C]-0.142922[/C][C]-0.9902[/C][C]0.163522[/C][/ROW]
[ROW][C]6[/C][C]-0.004316[/C][C]-0.0299[/C][C]0.488136[/C][/ROW]
[ROW][C]7[/C][C]0.084342[/C][C]0.5843[/C][C]0.280864[/C][/ROW]
[ROW][C]8[/C][C]-0.002383[/C][C]-0.0165[/C][C]0.493447[/C][/ROW]
[ROW][C]9[/C][C]0.196387[/C][C]1.3606[/C][C]0.089997[/C][/ROW]
[ROW][C]10[/C][C]-0.016692[/C][C]-0.1156[/C][C]0.454207[/C][/ROW]
[ROW][C]11[/C][C]0.403528[/C][C]2.7957[/C][C]0.003712[/C][/ROW]
[ROW][C]12[/C][C]-0.164607[/C][C]-1.1404[/C][C]0.129883[/C][/ROW]
[ROW][C]13[/C][C]0.022723[/C][C]0.1574[/C][C]0.437783[/C][/ROW]
[ROW][C]14[/C][C]-0.000366[/C][C]-0.0025[/C][C]0.498994[/C][/ROW]
[ROW][C]15[/C][C]0.050192[/C][C]0.3477[/C][C]0.364779[/C][/ROW]
[ROW][C]16[/C][C]-0.158291[/C][C]-1.0967[/C][C]0.139128[/C][/ROW]
[ROW][C]17[/C][C]0.059682[/C][C]0.4135[/C][C]0.340544[/C][/ROW]
[ROW][C]18[/C][C]-0.089964[/C][C]-0.6233[/C][C]0.268022[/C][/ROW]
[ROW][C]19[/C][C]-0.149519[/C][C]-1.0359[/C][C]0.15272[/C][/ROW]
[ROW][C]20[/C][C]-0.008972[/C][C]-0.0622[/C][C]0.475348[/C][/ROW]
[ROW][C]21[/C][C]-0.166586[/C][C]-1.1541[/C][C]0.127078[/C][/ROW]
[ROW][C]22[/C][C]0.052409[/C][C]0.3631[/C][C]0.359062[/C][/ROW]
[ROW][C]23[/C][C]-0.170476[/C][C]-1.1811[/C][C]0.121693[/C][/ROW]
[ROW][C]24[/C][C]-0.036874[/C][C]-0.2555[/C][C]0.399725[/C][/ROW]
[ROW][C]25[/C][C]-0.043007[/C][C]-0.298[/C][C]0.383509[/C][/ROW]
[ROW][C]26[/C][C]0.013577[/C][C]0.0941[/C][C]0.462725[/C][/ROW]
[ROW][C]27[/C][C]-0.157214[/C][C]-1.0892[/C][C]0.14075[/C][/ROW]
[ROW][C]28[/C][C]-0.101549[/C][C]-0.7036[/C][C]0.242555[/C][/ROW]
[ROW][C]29[/C][C]-0.098285[/C][C]-0.6809[/C][C]0.249592[/C][/ROW]
[ROW][C]30[/C][C]-0.103907[/C][C]-0.7199[/C][C]0.237542[/C][/ROW]
[ROW][C]31[/C][C]-0.003503[/C][C]-0.0243[/C][C]0.49037[/C][/ROW]
[ROW][C]32[/C][C]-0.060095[/C][C]-0.4164[/C][C]0.339504[/C][/ROW]
[ROW][C]33[/C][C]0.001085[/C][C]0.0075[/C][C]0.497016[/C][/ROW]
[ROW][C]34[/C][C]-0.041513[/C][C]-0.2876[/C][C]0.38744[/C][/ROW]
[ROW][C]35[/C][C]-0.020476[/C][C]-0.1419[/C][C]0.443892[/C][/ROW]
[ROW][C]36[/C][C]-0.019459[/C][C]-0.1348[/C][C]0.446662[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59219&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59219&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 0.014909 0.1033 0.459081 2 0.260666 1.8059 0.0386 3 0.030835 0.2136 0.41587 4 0.098962 0.6856 0.248124 5 -0.142922 -0.9902 0.163522 6 -0.004316 -0.0299 0.488136 7 0.084342 0.5843 0.280864 8 -0.002383 -0.0165 0.493447 9 0.196387 1.3606 0.089997 10 -0.016692 -0.1156 0.454207 11 0.403528 2.7957 0.003712 12 -0.164607 -1.1404 0.129883 13 0.022723 0.1574 0.437783 14 -0.000366 -0.0025 0.498994 15 0.050192 0.3477 0.364779 16 -0.158291 -1.0967 0.139128 17 0.059682 0.4135 0.340544 18 -0.089964 -0.6233 0.268022 19 -0.149519 -1.0359 0.15272 20 -0.008972 -0.0622 0.475348 21 -0.166586 -1.1541 0.127078 22 0.052409 0.3631 0.359062 23 -0.170476 -1.1811 0.121693 24 -0.036874 -0.2555 0.399725 25 -0.043007 -0.298 0.383509 26 0.013577 0.0941 0.462725 27 -0.157214 -1.0892 0.14075 28 -0.101549 -0.7036 0.242555 29 -0.098285 -0.6809 0.249592 30 -0.103907 -0.7199 0.237542 31 -0.003503 -0.0243 0.49037 32 -0.060095 -0.4164 0.339504 33 0.001085 0.0075 0.497016 34 -0.041513 -0.2876 0.38744 35 -0.020476 -0.1419 0.443892 36 -0.019459 -0.1348 0.446662

 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.014909 0.1033 0.459081 2 0.260501 1.8048 0.03869 3 0.025836 0.179 0.429347 4 0.032872 0.2277 0.410405 5 -0.170064 -1.1782 0.122255 6 -0.04058 -0.2811 0.389904 7 0.174709 1.2104 0.116022 8 0.021445 0.1486 0.441255 9 0.176004 1.2194 0.114326 10 -0.071023 -0.4921 0.312461 11 0.332428 2.3031 0.012824 12 -0.194418 -1.347 0.092158 13 -0.185509 -1.2852 0.102437 14 0.133685 0.9262 0.179489 15 0.054676 0.3788 0.35325 16 -0.078533 -0.5441 0.294448 17 -0.005489 -0.038 0.484911 18 -0.225341 -1.5612 0.062522 19 -0.118391 -0.8202 0.208069 20 -0.01413 -0.0979 0.461212 21 -0.10275 -0.7119 0.239995 22 0.008754 0.0607 0.475944 23 -0.021201 -0.1469 0.441918 24 -0.083135 -0.576 0.283661 25 -0.019409 -0.1345 0.446798 26 -0.023401 -0.1621 0.435943 27 0.022029 0.1526 0.439667 28 -0.178469 -1.2365 0.11115 29 0.029156 0.202 0.420386 30 0.147387 1.0211 0.156157 31 -0.032895 -0.2279 0.410346 32 0.045456 0.3149 0.377092 33 -0.067657 -0.4687 0.320689 34 -0.011496 -0.0796 0.468425 35 0.083619 0.5793 0.282539 36 -0.027641 -0.1915 0.424469

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.014909 & 0.1033 & 0.459081 \tabularnewline
2 & 0.260501 & 1.8048 & 0.03869 \tabularnewline
3 & 0.025836 & 0.179 & 0.429347 \tabularnewline
4 & 0.032872 & 0.2277 & 0.410405 \tabularnewline
5 & -0.170064 & -1.1782 & 0.122255 \tabularnewline
6 & -0.04058 & -0.2811 & 0.389904 \tabularnewline
7 & 0.174709 & 1.2104 & 0.116022 \tabularnewline
8 & 0.021445 & 0.1486 & 0.441255 \tabularnewline
9 & 0.176004 & 1.2194 & 0.114326 \tabularnewline
10 & -0.071023 & -0.4921 & 0.312461 \tabularnewline
11 & 0.332428 & 2.3031 & 0.012824 \tabularnewline
12 & -0.194418 & -1.347 & 0.092158 \tabularnewline
13 & -0.185509 & -1.2852 & 0.102437 \tabularnewline
14 & 0.133685 & 0.9262 & 0.179489 \tabularnewline
15 & 0.054676 & 0.3788 & 0.35325 \tabularnewline
16 & -0.078533 & -0.5441 & 0.294448 \tabularnewline
17 & -0.005489 & -0.038 & 0.484911 \tabularnewline
18 & -0.225341 & -1.5612 & 0.062522 \tabularnewline
19 & -0.118391 & -0.8202 & 0.208069 \tabularnewline
20 & -0.01413 & -0.0979 & 0.461212 \tabularnewline
21 & -0.10275 & -0.7119 & 0.239995 \tabularnewline
22 & 0.008754 & 0.0607 & 0.475944 \tabularnewline
23 & -0.021201 & -0.1469 & 0.441918 \tabularnewline
24 & -0.083135 & -0.576 & 0.283661 \tabularnewline
25 & -0.019409 & -0.1345 & 0.446798 \tabularnewline
26 & -0.023401 & -0.1621 & 0.435943 \tabularnewline
27 & 0.022029 & 0.1526 & 0.439667 \tabularnewline
28 & -0.178469 & -1.2365 & 0.11115 \tabularnewline
29 & 0.029156 & 0.202 & 0.420386 \tabularnewline
30 & 0.147387 & 1.0211 & 0.156157 \tabularnewline
31 & -0.032895 & -0.2279 & 0.410346 \tabularnewline
32 & 0.045456 & 0.3149 & 0.377092 \tabularnewline
33 & -0.067657 & -0.4687 & 0.320689 \tabularnewline
34 & -0.011496 & -0.0796 & 0.468425 \tabularnewline
35 & 0.083619 & 0.5793 & 0.282539 \tabularnewline
36 & -0.027641 & -0.1915 & 0.424469 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59219&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]0.014909[/C][C]0.1033[/C][C]0.459081[/C][/ROW]
[ROW][C]2[/C][C]0.260501[/C][C]1.8048[/C][C]0.03869[/C][/ROW]
[ROW][C]3[/C][C]0.025836[/C][C]0.179[/C][C]0.429347[/C][/ROW]
[ROW][C]4[/C][C]0.032872[/C][C]0.2277[/C][C]0.410405[/C][/ROW]
[ROW][C]5[/C][C]-0.170064[/C][C]-1.1782[/C][C]0.122255[/C][/ROW]
[ROW][C]6[/C][C]-0.04058[/C][C]-0.2811[/C][C]0.389904[/C][/ROW]
[ROW][C]7[/C][C]0.174709[/C][C]1.2104[/C][C]0.116022[/C][/ROW]
[ROW][C]8[/C][C]0.021445[/C][C]0.1486[/C][C]0.441255[/C][/ROW]
[ROW][C]9[/C][C]0.176004[/C][C]1.2194[/C][C]0.114326[/C][/ROW]
[ROW][C]10[/C][C]-0.071023[/C][C]-0.4921[/C][C]0.312461[/C][/ROW]
[ROW][C]11[/C][C]0.332428[/C][C]2.3031[/C][C]0.012824[/C][/ROW]
[ROW][C]12[/C][C]-0.194418[/C][C]-1.347[/C][C]0.092158[/C][/ROW]
[ROW][C]13[/C][C]-0.185509[/C][C]-1.2852[/C][C]0.102437[/C][/ROW]
[ROW][C]14[/C][C]0.133685[/C][C]0.9262[/C][C]0.179489[/C][/ROW]
[ROW][C]15[/C][C]0.054676[/C][C]0.3788[/C][C]0.35325[/C][/ROW]
[ROW][C]16[/C][C]-0.078533[/C][C]-0.5441[/C][C]0.294448[/C][/ROW]
[ROW][C]17[/C][C]-0.005489[/C][C]-0.038[/C][C]0.484911[/C][/ROW]
[ROW][C]18[/C][C]-0.225341[/C][C]-1.5612[/C][C]0.062522[/C][/ROW]
[ROW][C]19[/C][C]-0.118391[/C][C]-0.8202[/C][C]0.208069[/C][/ROW]
[ROW][C]20[/C][C]-0.01413[/C][C]-0.0979[/C][C]0.461212[/C][/ROW]
[ROW][C]21[/C][C]-0.10275[/C][C]-0.7119[/C][C]0.239995[/C][/ROW]
[ROW][C]22[/C][C]0.008754[/C][C]0.0607[/C][C]0.475944[/C][/ROW]
[ROW][C]23[/C][C]-0.021201[/C][C]-0.1469[/C][C]0.441918[/C][/ROW]
[ROW][C]24[/C][C]-0.083135[/C][C]-0.576[/C][C]0.283661[/C][/ROW]
[ROW][C]25[/C][C]-0.019409[/C][C]-0.1345[/C][C]0.446798[/C][/ROW]
[ROW][C]26[/C][C]-0.023401[/C][C]-0.1621[/C][C]0.435943[/C][/ROW]
[ROW][C]27[/C][C]0.022029[/C][C]0.1526[/C][C]0.439667[/C][/ROW]
[ROW][C]28[/C][C]-0.178469[/C][C]-1.2365[/C][C]0.11115[/C][/ROW]
[ROW][C]29[/C][C]0.029156[/C][C]0.202[/C][C]0.420386[/C][/ROW]
[ROW][C]30[/C][C]0.147387[/C][C]1.0211[/C][C]0.156157[/C][/ROW]
[ROW][C]31[/C][C]-0.032895[/C][C]-0.2279[/C][C]0.410346[/C][/ROW]
[ROW][C]32[/C][C]0.045456[/C][C]0.3149[/C][C]0.377092[/C][/ROW]
[ROW][C]33[/C][C]-0.067657[/C][C]-0.4687[/C][C]0.320689[/C][/ROW]
[ROW][C]34[/C][C]-0.011496[/C][C]-0.0796[/C][C]0.468425[/C][/ROW]
[ROW][C]35[/C][C]0.083619[/C][C]0.5793[/C][C]0.282539[/C][/ROW]
[ROW][C]36[/C][C]-0.027641[/C][C]-0.1915[/C][C]0.424469[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59219&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59219&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 0.014909 0.1033 0.459081 2 0.260501 1.8048 0.03869 3 0.025836 0.179 0.429347 4 0.032872 0.2277 0.410405 5 -0.170064 -1.1782 0.122255 6 -0.04058 -0.2811 0.389904 7 0.174709 1.2104 0.116022 8 0.021445 0.1486 0.441255 9 0.176004 1.2194 0.114326 10 -0.071023 -0.4921 0.312461 11 0.332428 2.3031 0.012824 12 -0.194418 -1.347 0.092158 13 -0.185509 -1.2852 0.102437 14 0.133685 0.9262 0.179489 15 0.054676 0.3788 0.35325 16 -0.078533 -0.5441 0.294448 17 -0.005489 -0.038 0.484911 18 -0.225341 -1.5612 0.062522 19 -0.118391 -0.8202 0.208069 20 -0.01413 -0.0979 0.461212 21 -0.10275 -0.7119 0.239995 22 0.008754 0.0607 0.475944 23 -0.021201 -0.1469 0.441918 24 -0.083135 -0.576 0.283661 25 -0.019409 -0.1345 0.446798 26 -0.023401 -0.1621 0.435943 27 0.022029 0.1526 0.439667 28 -0.178469 -1.2365 0.11115 29 0.029156 0.202 0.420386 30 0.147387 1.0211 0.156157 31 -0.032895 -0.2279 0.410346 32 0.045456 0.3149 0.377092 33 -0.067657 -0.4687 0.320689 34 -0.011496 -0.0796 0.468425 35 0.083619 0.5793 0.282539 36 -0.027641 -0.1915 0.424469

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')