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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationWed, 02 Dec 2009 12:11:03 -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/Dec/02/t1259781225deuxdsdt3vgt2q3.htm/, Retrieved Sat, 27 Apr 2024 16:52:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62534, Retrieved Sat, 27 Apr 2024 16:52:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118

Tree of Dependent Computations

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 12:19:56] [b98453cac15ba1066b407e146608df68]
- R  D        [(Partial) Autocorrelation Function] [ACF Link 2] [2009-11-25 18:57:31] [1f74ef2f756548f1f3a7b6136ea56d7f]
-    D            [(Partial) Autocorrelation Function] [ACF d=1 D=0] [2009-12-02 19:11:03] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
111.5
108.1
124.5
106.3
111.1
121.3
116.5
117.4
123.6
98.4
107.2
118.9
111.9
115.2
124.4
104.6
117
126.2
117.5
122.2
124.1
105.8
107.5
125.6
112.1
120.1
130.6
109.8
122.1
129.5
132.1
133.3
128.4
114.7
114.1
136.9
123.4
134
137
127.8
140.1
140.4
157.8
151.8
141.1
138.8
141.1
139.5
150.7
144.4
146
143.6
143.1
156.4
164.8
145.1
153.4
133.2
131.4
145.9

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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=62534&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=62534&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62534&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.390671-3.00080.001971
2-0.200669-1.54140.064287
30.3317422.54820.006727
4-0.390005-2.99570.002
5-0.068009-0.52240.301678
60.4998783.83960.000152
7-0.216718-1.66460.050643
8-0.178-1.36720.088368
90.1996031.53320.065289
10-0.244205-1.87580.032818
11-0.041266-0.3170.376193
120.4847913.72380.00022
13-0.191708-1.47250.073096
14-0.083281-0.63970.262424
150.070910.54470.294016
16-0.148517-1.14080.129286
17-0.068376-0.52520.300704
180.2764642.12360.018955
19-0.013554-0.10410.458718
20-0.251601-1.93260.029046
210.1474011.13220.131063
22-0.140995-1.0830.141606
23-0.01471-0.1130.455212
240.2745652.1090.019601
25-0.03665-0.28150.389651
26-0.097022-0.74520.229543
27-0.032199-0.24730.402759
280.0124590.09570.462042
29-0.07431-0.57080.285155
300.1514861.16360.124639
310.0219170.16830.433444
32-0.163345-1.25470.107272
330.0356730.2740.392517
34-0.009553-0.07340.470877
35-0.013723-0.10540.458206
360.0933150.71680.238173

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.390671 & -3.0008 & 0.001971 \tabularnewline
2 & -0.200669 & -1.5414 & 0.064287 \tabularnewline
3 & 0.331742 & 2.5482 & 0.006727 \tabularnewline
4 & -0.390005 & -2.9957 & 0.002 \tabularnewline
5 & -0.068009 & -0.5224 & 0.301678 \tabularnewline
6 & 0.499878 & 3.8396 & 0.000152 \tabularnewline
7 & -0.216718 & -1.6646 & 0.050643 \tabularnewline
8 & -0.178 & -1.3672 & 0.088368 \tabularnewline
9 & 0.199603 & 1.5332 & 0.065289 \tabularnewline
10 & -0.244205 & -1.8758 & 0.032818 \tabularnewline
11 & -0.041266 & -0.317 & 0.376193 \tabularnewline
12 & 0.484791 & 3.7238 & 0.00022 \tabularnewline
13 & -0.191708 & -1.4725 & 0.073096 \tabularnewline
14 & -0.083281 & -0.6397 & 0.262424 \tabularnewline
15 & 0.07091 & 0.5447 & 0.294016 \tabularnewline
16 & -0.148517 & -1.1408 & 0.129286 \tabularnewline
17 & -0.068376 & -0.5252 & 0.300704 \tabularnewline
18 & 0.276464 & 2.1236 & 0.018955 \tabularnewline
19 & -0.013554 & -0.1041 & 0.458718 \tabularnewline
20 & -0.251601 & -1.9326 & 0.029046 \tabularnewline
21 & 0.147401 & 1.1322 & 0.131063 \tabularnewline
22 & -0.140995 & -1.083 & 0.141606 \tabularnewline
23 & -0.01471 & -0.113 & 0.455212 \tabularnewline
24 & 0.274565 & 2.109 & 0.019601 \tabularnewline
25 & -0.03665 & -0.2815 & 0.389651 \tabularnewline
26 & -0.097022 & -0.7452 & 0.229543 \tabularnewline
27 & -0.032199 & -0.2473 & 0.402759 \tabularnewline
28 & 0.012459 & 0.0957 & 0.462042 \tabularnewline
29 & -0.07431 & -0.5708 & 0.285155 \tabularnewline
30 & 0.151486 & 1.1636 & 0.124639 \tabularnewline
31 & 0.021917 & 0.1683 & 0.433444 \tabularnewline
32 & -0.163345 & -1.2547 & 0.107272 \tabularnewline
33 & 0.035673 & 0.274 & 0.392517 \tabularnewline
34 & -0.009553 & -0.0734 & 0.470877 \tabularnewline
35 & -0.013723 & -0.1054 & 0.458206 \tabularnewline
36 & 0.093315 & 0.7168 & 0.238173 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62534&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]-0.390671[/C][C]-3.0008[/C][C]0.001971[/C][/ROW]
[ROW][C]2[/C][C]-0.200669[/C][C]-1.5414[/C][C]0.064287[/C][/ROW]
[ROW][C]3[/C][C]0.331742[/C][C]2.5482[/C][C]0.006727[/C][/ROW]
[ROW][C]4[/C][C]-0.390005[/C][C]-2.9957[/C][C]0.002[/C][/ROW]
[ROW][C]5[/C][C]-0.068009[/C][C]-0.5224[/C][C]0.301678[/C][/ROW]
[ROW][C]6[/C][C]0.499878[/C][C]3.8396[/C][C]0.000152[/C][/ROW]
[ROW][C]7[/C][C]-0.216718[/C][C]-1.6646[/C][C]0.050643[/C][/ROW]
[ROW][C]8[/C][C]-0.178[/C][C]-1.3672[/C][C]0.088368[/C][/ROW]
[ROW][C]9[/C][C]0.199603[/C][C]1.5332[/C][C]0.065289[/C][/ROW]
[ROW][C]10[/C][C]-0.244205[/C][C]-1.8758[/C][C]0.032818[/C][/ROW]
[ROW][C]11[/C][C]-0.041266[/C][C]-0.317[/C][C]0.376193[/C][/ROW]
[ROW][C]12[/C][C]0.484791[/C][C]3.7238[/C][C]0.00022[/C][/ROW]
[ROW][C]13[/C][C]-0.191708[/C][C]-1.4725[/C][C]0.073096[/C][/ROW]
[ROW][C]14[/C][C]-0.083281[/C][C]-0.6397[/C][C]0.262424[/C][/ROW]
[ROW][C]15[/C][C]0.07091[/C][C]0.5447[/C][C]0.294016[/C][/ROW]
[ROW][C]16[/C][C]-0.148517[/C][C]-1.1408[/C][C]0.129286[/C][/ROW]
[ROW][C]17[/C][C]-0.068376[/C][C]-0.5252[/C][C]0.300704[/C][/ROW]
[ROW][C]18[/C][C]0.276464[/C][C]2.1236[/C][C]0.018955[/C][/ROW]
[ROW][C]19[/C][C]-0.013554[/C][C]-0.1041[/C][C]0.458718[/C][/ROW]
[ROW][C]20[/C][C]-0.251601[/C][C]-1.9326[/C][C]0.029046[/C][/ROW]
[ROW][C]21[/C][C]0.147401[/C][C]1.1322[/C][C]0.131063[/C][/ROW]
[ROW][C]22[/C][C]-0.140995[/C][C]-1.083[/C][C]0.141606[/C][/ROW]
[ROW][C]23[/C][C]-0.01471[/C][C]-0.113[/C][C]0.455212[/C][/ROW]
[ROW][C]24[/C][C]0.274565[/C][C]2.109[/C][C]0.019601[/C][/ROW]
[ROW][C]25[/C][C]-0.03665[/C][C]-0.2815[/C][C]0.389651[/C][/ROW]
[ROW][C]26[/C][C]-0.097022[/C][C]-0.7452[/C][C]0.229543[/C][/ROW]
[ROW][C]27[/C][C]-0.032199[/C][C]-0.2473[/C][C]0.402759[/C][/ROW]
[ROW][C]28[/C][C]0.012459[/C][C]0.0957[/C][C]0.462042[/C][/ROW]
[ROW][C]29[/C][C]-0.07431[/C][C]-0.5708[/C][C]0.285155[/C][/ROW]
[ROW][C]30[/C][C]0.151486[/C][C]1.1636[/C][C]0.124639[/C][/ROW]
[ROW][C]31[/C][C]0.021917[/C][C]0.1683[/C][C]0.433444[/C][/ROW]
[ROW][C]32[/C][C]-0.163345[/C][C]-1.2547[/C][C]0.107272[/C][/ROW]
[ROW][C]33[/C][C]0.035673[/C][C]0.274[/C][C]0.392517[/C][/ROW]
[ROW][C]34[/C][C]-0.009553[/C][C]-0.0734[/C][C]0.470877[/C][/ROW]
[ROW][C]35[/C][C]-0.013723[/C][C]-0.1054[/C][C]0.458206[/C][/ROW]
[ROW][C]36[/C][C]0.093315[/C][C]0.7168[/C][C]0.238173[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62534&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62534&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.390671-3.00080.001971
2-0.200669-1.54140.064287
30.3317422.54820.006727
4-0.390005-2.99570.002
5-0.068009-0.52240.301678
60.4998783.83960.000152
7-0.216718-1.66460.050643
8-0.178-1.36720.088368
90.1996031.53320.065289
10-0.244205-1.87580.032818
11-0.041266-0.3170.376193
120.4847913.72380.00022
13-0.191708-1.47250.073096
14-0.083281-0.63970.262424
150.070910.54470.294016
16-0.148517-1.14080.129286
17-0.068376-0.52520.300704
180.2764642.12360.018955
19-0.013554-0.10410.458718
20-0.251601-1.93260.029046
210.1474011.13220.131063
22-0.140995-1.0830.141606
23-0.01471-0.1130.455212
240.2745652.1090.019601
25-0.03665-0.28150.389651
26-0.097022-0.74520.229543
27-0.032199-0.24730.402759
280.0124590.09570.462042
29-0.07431-0.57080.285155
300.1514861.16360.124639
310.0219170.16830.433444
32-0.163345-1.25470.107272
330.0356730.2740.392517
34-0.009553-0.07340.470877
35-0.013723-0.10540.458206
360.0933150.71680.238173






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.390671-3.00080.001971
2-0.416925-3.20250.001099
30.0825350.6340.264277
4-0.373986-2.87260.002824
5-0.430939-3.31010.000797
60.128010.98330.164746
70.1777491.36530.088668
8-0.196748-1.51130.068031
9-0.294192-2.25970.013772
10-0.188041-1.44440.076962
11-0.192744-1.48050.072031
120.1414651.08660.140813
130.1400361.07560.143234
140.1903791.46230.074479
15-0.063633-0.48880.313406
160.1436761.10360.137125
17-0.000811-0.00620.497526
18-0.096882-0.74420.229865
190.0489570.3760.354115
20-0.115165-0.88460.189982
21-0.050208-0.38570.350569
22-0.202185-1.5530.062884
23-0.015895-0.12210.45162
24-0.132523-1.01790.156434
25-0.097558-0.74940.228309
260.0098130.07540.470085
27-0.131739-1.01190.157858
280.0260780.20030.420964
290.0313260.24060.405343
300.0346770.26640.395445
31-0.128599-0.98780.163646
32-0.013833-0.10630.457871
330.0525550.40370.343954
340.0783530.60180.274793
35-0.005121-0.03930.484378
36-0.081084-0.62280.267901

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.390671 & -3.0008 & 0.001971 \tabularnewline
2 & -0.416925 & -3.2025 & 0.001099 \tabularnewline
3 & 0.082535 & 0.634 & 0.264277 \tabularnewline
4 & -0.373986 & -2.8726 & 0.002824 \tabularnewline
5 & -0.430939 & -3.3101 & 0.000797 \tabularnewline
6 & 0.12801 & 0.9833 & 0.164746 \tabularnewline
7 & 0.177749 & 1.3653 & 0.088668 \tabularnewline
8 & -0.196748 & -1.5113 & 0.068031 \tabularnewline
9 & -0.294192 & -2.2597 & 0.013772 \tabularnewline
10 & -0.188041 & -1.4444 & 0.076962 \tabularnewline
11 & -0.192744 & -1.4805 & 0.072031 \tabularnewline
12 & 0.141465 & 1.0866 & 0.140813 \tabularnewline
13 & 0.140036 & 1.0756 & 0.143234 \tabularnewline
14 & 0.190379 & 1.4623 & 0.074479 \tabularnewline
15 & -0.063633 & -0.4888 & 0.313406 \tabularnewline
16 & 0.143676 & 1.1036 & 0.137125 \tabularnewline
17 & -0.000811 & -0.0062 & 0.497526 \tabularnewline
18 & -0.096882 & -0.7442 & 0.229865 \tabularnewline
19 & 0.048957 & 0.376 & 0.354115 \tabularnewline
20 & -0.115165 & -0.8846 & 0.189982 \tabularnewline
21 & -0.050208 & -0.3857 & 0.350569 \tabularnewline
22 & -0.202185 & -1.553 & 0.062884 \tabularnewline
23 & -0.015895 & -0.1221 & 0.45162 \tabularnewline
24 & -0.132523 & -1.0179 & 0.156434 \tabularnewline
25 & -0.097558 & -0.7494 & 0.228309 \tabularnewline
26 & 0.009813 & 0.0754 & 0.470085 \tabularnewline
27 & -0.131739 & -1.0119 & 0.157858 \tabularnewline
28 & 0.026078 & 0.2003 & 0.420964 \tabularnewline
29 & 0.031326 & 0.2406 & 0.405343 \tabularnewline
30 & 0.034677 & 0.2664 & 0.395445 \tabularnewline
31 & -0.128599 & -0.9878 & 0.163646 \tabularnewline
32 & -0.013833 & -0.1063 & 0.457871 \tabularnewline
33 & 0.052555 & 0.4037 & 0.343954 \tabularnewline
34 & 0.078353 & 0.6018 & 0.274793 \tabularnewline
35 & -0.005121 & -0.0393 & 0.484378 \tabularnewline
36 & -0.081084 & -0.6228 & 0.267901 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62534&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]-0.390671[/C][C]-3.0008[/C][C]0.001971[/C][/ROW]
[ROW][C]2[/C][C]-0.416925[/C][C]-3.2025[/C][C]0.001099[/C][/ROW]
[ROW][C]3[/C][C]0.082535[/C][C]0.634[/C][C]0.264277[/C][/ROW]
[ROW][C]4[/C][C]-0.373986[/C][C]-2.8726[/C][C]0.002824[/C][/ROW]
[ROW][C]5[/C][C]-0.430939[/C][C]-3.3101[/C][C]0.000797[/C][/ROW]
[ROW][C]6[/C][C]0.12801[/C][C]0.9833[/C][C]0.164746[/C][/ROW]
[ROW][C]7[/C][C]0.177749[/C][C]1.3653[/C][C]0.088668[/C][/ROW]
[ROW][C]8[/C][C]-0.196748[/C][C]-1.5113[/C][C]0.068031[/C][/ROW]
[ROW][C]9[/C][C]-0.294192[/C][C]-2.2597[/C][C]0.013772[/C][/ROW]
[ROW][C]10[/C][C]-0.188041[/C][C]-1.4444[/C][C]0.076962[/C][/ROW]
[ROW][C]11[/C][C]-0.192744[/C][C]-1.4805[/C][C]0.072031[/C][/ROW]
[ROW][C]12[/C][C]0.141465[/C][C]1.0866[/C][C]0.140813[/C][/ROW]
[ROW][C]13[/C][C]0.140036[/C][C]1.0756[/C][C]0.143234[/C][/ROW]
[ROW][C]14[/C][C]0.190379[/C][C]1.4623[/C][C]0.074479[/C][/ROW]
[ROW][C]15[/C][C]-0.063633[/C][C]-0.4888[/C][C]0.313406[/C][/ROW]
[ROW][C]16[/C][C]0.143676[/C][C]1.1036[/C][C]0.137125[/C][/ROW]
[ROW][C]17[/C][C]-0.000811[/C][C]-0.0062[/C][C]0.497526[/C][/ROW]
[ROW][C]18[/C][C]-0.096882[/C][C]-0.7442[/C][C]0.229865[/C][/ROW]
[ROW][C]19[/C][C]0.048957[/C][C]0.376[/C][C]0.354115[/C][/ROW]
[ROW][C]20[/C][C]-0.115165[/C][C]-0.8846[/C][C]0.189982[/C][/ROW]
[ROW][C]21[/C][C]-0.050208[/C][C]-0.3857[/C][C]0.350569[/C][/ROW]
[ROW][C]22[/C][C]-0.202185[/C][C]-1.553[/C][C]0.062884[/C][/ROW]
[ROW][C]23[/C][C]-0.015895[/C][C]-0.1221[/C][C]0.45162[/C][/ROW]
[ROW][C]24[/C][C]-0.132523[/C][C]-1.0179[/C][C]0.156434[/C][/ROW]
[ROW][C]25[/C][C]-0.097558[/C][C]-0.7494[/C][C]0.228309[/C][/ROW]
[ROW][C]26[/C][C]0.009813[/C][C]0.0754[/C][C]0.470085[/C][/ROW]
[ROW][C]27[/C][C]-0.131739[/C][C]-1.0119[/C][C]0.157858[/C][/ROW]
[ROW][C]28[/C][C]0.026078[/C][C]0.2003[/C][C]0.420964[/C][/ROW]
[ROW][C]29[/C][C]0.031326[/C][C]0.2406[/C][C]0.405343[/C][/ROW]
[ROW][C]30[/C][C]0.034677[/C][C]0.2664[/C][C]0.395445[/C][/ROW]
[ROW][C]31[/C][C]-0.128599[/C][C]-0.9878[/C][C]0.163646[/C][/ROW]
[ROW][C]32[/C][C]-0.013833[/C][C]-0.1063[/C][C]0.457871[/C][/ROW]
[ROW][C]33[/C][C]0.052555[/C][C]0.4037[/C][C]0.343954[/C][/ROW]
[ROW][C]34[/C][C]0.078353[/C][C]0.6018[/C][C]0.274793[/C][/ROW]
[ROW][C]35[/C][C]-0.005121[/C][C]-0.0393[/C][C]0.484378[/C][/ROW]
[ROW][C]36[/C][C]-0.081084[/C][C]-0.6228[/C][C]0.267901[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62534&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62534&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.390671-3.00080.001971
2-0.416925-3.20250.001099
30.0825350.6340.264277
4-0.373986-2.87260.002824
5-0.430939-3.31010.000797
60.128010.98330.164746
70.1777491.36530.088668
8-0.196748-1.51130.068031
9-0.294192-2.25970.013772
10-0.188041-1.44440.076962
11-0.192744-1.48050.072031
120.1414651.08660.140813
130.1400361.07560.143234
140.1903791.46230.074479
15-0.063633-0.48880.313406
160.1436761.10360.137125
17-0.000811-0.00620.497526
18-0.096882-0.74420.229865
190.0489570.3760.354115
20-0.115165-0.88460.189982
21-0.050208-0.38570.350569
22-0.202185-1.5530.062884
23-0.015895-0.12210.45162
24-0.132523-1.01790.156434
25-0.097558-0.74940.228309
260.0098130.07540.470085
27-0.131739-1.01190.157858
280.0260780.20030.420964
290.0313260.24060.405343
300.0346770.26640.395445
31-0.128599-0.98780.163646
32-0.013833-0.10630.457871
330.0525550.40370.343954
340.0783530.60180.274793
35-0.005121-0.03930.484378
36-0.081084-0.62280.267901


Figures (Output of Computation)

Input Parameters & R Code

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