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Description of Statistical Computation

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 computationSun, 06 Dec 2009 07:42:19 -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/06/t126011058315rtbc2uduzd52w.htm/, Retrieved Mon, 06 May 2024 00:03:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64417, Retrieved Mon, 06 May 2024 00:03:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130

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 12:26:39] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [workshop 8] [2009-11-27 08:53:19] [f1a50df816abcbb519e7637ff6b72fa0]
-   PD          [(Partial) Autocorrelation Function] [workshop 9 - ] [2009-12-04 09:23:46] [f1a50df816abcbb519e7637ff6b72fa0]
-    D              [(Partial) Autocorrelation Function] [WS9] [2009-12-06 14:42:19] [48076ccf082563ab8a2c81e57fdb5364] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10414,9
12476,8
12384,6
12266,7
12919,9
11497,3
12142
13919,4
12656,8
12034,1
13199,7
10881,3
11301,2
13643,9
12517
13981,1
14275,7
13435
13565,7
16216,3
12970
14079,9
14235
12213,4
12581
14130,4
14210,8
14378,5
13142,8
13714,7
13621,9
15379,8
13306,3
14391,2
14909,9
14025,4
12951,2
14344,3
16093,4
15413,6
14705,7
15972,8
16241,4
16626,4
17136,2
15622,9
18003,9
16136,1
14423,7
16789,4
16782,2
14133,8
12607
12004,5
12175,4
13268
12299,3
11800,6
13873,3
12269,6

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=64417&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=64417&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64417&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
1-0.330662-2.53990.006872
2-0.268057-2.0590.021959
30.3170822.43560.008955
4-0.099045-0.76080.224908
5-0.109677-0.84240.201472
60.271242.08340.020777
7-0.248284-1.90710.03069
80.0319620.24550.403459
90.2441411.87530.032853
10-0.379244-2.9130.002524
11-0.085137-0.65390.257844
120.4977713.82340.00016
13-0.204128-1.56790.061122
14-0.170971-1.31330.097091
150.1224510.94060.175381
160.0079820.06130.47566
17-0.049639-0.38130.35218
180.0530080.40720.342681
19-0.018313-0.14070.444307
200.0065910.05060.479897
21-0.004653-0.03570.485806
22-0.085263-0.65490.257534
23-0.076098-0.58450.280548
240.1717831.31950.096052
250.1450741.11430.134827
26-0.29991-2.30370.012392
270.1018450.78230.218588
280.0939350.72150.236717
29-0.118385-0.90930.183437
300.0369580.28390.388749
310.1587681.21950.113751
32-0.161443-1.24010.10993
330.0306960.23580.407209
340.068170.52360.30125
35-0.217979-1.67430.04968
360.1654761.2710.10435

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.330662 & -2.5399 & 0.006872 \tabularnewline
2 & -0.268057 & -2.059 & 0.021959 \tabularnewline
3 & 0.317082 & 2.4356 & 0.008955 \tabularnewline
4 & -0.099045 & -0.7608 & 0.224908 \tabularnewline
5 & -0.109677 & -0.8424 & 0.201472 \tabularnewline
6 & 0.27124 & 2.0834 & 0.020777 \tabularnewline
7 & -0.248284 & -1.9071 & 0.03069 \tabularnewline
8 & 0.031962 & 0.2455 & 0.403459 \tabularnewline
9 & 0.244141 & 1.8753 & 0.032853 \tabularnewline
10 & -0.379244 & -2.913 & 0.002524 \tabularnewline
11 & -0.085137 & -0.6539 & 0.257844 \tabularnewline
12 & 0.497771 & 3.8234 & 0.00016 \tabularnewline
13 & -0.204128 & -1.5679 & 0.061122 \tabularnewline
14 & -0.170971 & -1.3133 & 0.097091 \tabularnewline
15 & 0.122451 & 0.9406 & 0.175381 \tabularnewline
16 & 0.007982 & 0.0613 & 0.47566 \tabularnewline
17 & -0.049639 & -0.3813 & 0.35218 \tabularnewline
18 & 0.053008 & 0.4072 & 0.342681 \tabularnewline
19 & -0.018313 & -0.1407 & 0.444307 \tabularnewline
20 & 0.006591 & 0.0506 & 0.479897 \tabularnewline
21 & -0.004653 & -0.0357 & 0.485806 \tabularnewline
22 & -0.085263 & -0.6549 & 0.257534 \tabularnewline
23 & -0.076098 & -0.5845 & 0.280548 \tabularnewline
24 & 0.171783 & 1.3195 & 0.096052 \tabularnewline
25 & 0.145074 & 1.1143 & 0.134827 \tabularnewline
26 & -0.29991 & -2.3037 & 0.012392 \tabularnewline
27 & 0.101845 & 0.7823 & 0.218588 \tabularnewline
28 & 0.093935 & 0.7215 & 0.236717 \tabularnewline
29 & -0.118385 & -0.9093 & 0.183437 \tabularnewline
30 & 0.036958 & 0.2839 & 0.388749 \tabularnewline
31 & 0.158768 & 1.2195 & 0.113751 \tabularnewline
32 & -0.161443 & -1.2401 & 0.10993 \tabularnewline
33 & 0.030696 & 0.2358 & 0.407209 \tabularnewline
34 & 0.06817 & 0.5236 & 0.30125 \tabularnewline
35 & -0.217979 & -1.6743 & 0.04968 \tabularnewline
36 & 0.165476 & 1.271 & 0.10435 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64417&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]-0.330662[/C][C]-2.5399[/C][C]0.006872[/C][/ROW]
[ROW][C]2[/C][C]-0.268057[/C][C]-2.059[/C][C]0.021959[/C][/ROW]
[ROW][C]3[/C][C]0.317082[/C][C]2.4356[/C][C]0.008955[/C][/ROW]
[ROW][C]4[/C][C]-0.099045[/C][C]-0.7608[/C][C]0.224908[/C][/ROW]
[ROW][C]5[/C][C]-0.109677[/C][C]-0.8424[/C][C]0.201472[/C][/ROW]
[ROW][C]6[/C][C]0.27124[/C][C]2.0834[/C][C]0.020777[/C][/ROW]
[ROW][C]7[/C][C]-0.248284[/C][C]-1.9071[/C][C]0.03069[/C][/ROW]
[ROW][C]8[/C][C]0.031962[/C][C]0.2455[/C][C]0.403459[/C][/ROW]
[ROW][C]9[/C][C]0.244141[/C][C]1.8753[/C][C]0.032853[/C][/ROW]
[ROW][C]10[/C][C]-0.379244[/C][C]-2.913[/C][C]0.002524[/C][/ROW]
[ROW][C]11[/C][C]-0.085137[/C][C]-0.6539[/C][C]0.257844[/C][/ROW]
[ROW][C]12[/C][C]0.497771[/C][C]3.8234[/C][C]0.00016[/C][/ROW]
[ROW][C]13[/C][C]-0.204128[/C][C]-1.5679[/C][C]0.061122[/C][/ROW]
[ROW][C]14[/C][C]-0.170971[/C][C]-1.3133[/C][C]0.097091[/C][/ROW]
[ROW][C]15[/C][C]0.122451[/C][C]0.9406[/C][C]0.175381[/C][/ROW]
[ROW][C]16[/C][C]0.007982[/C][C]0.0613[/C][C]0.47566[/C][/ROW]
[ROW][C]17[/C][C]-0.049639[/C][C]-0.3813[/C][C]0.35218[/C][/ROW]
[ROW][C]18[/C][C]0.053008[/C][C]0.4072[/C][C]0.342681[/C][/ROW]
[ROW][C]19[/C][C]-0.018313[/C][C]-0.1407[/C][C]0.444307[/C][/ROW]
[ROW][C]20[/C][C]0.006591[/C][C]0.0506[/C][C]0.479897[/C][/ROW]
[ROW][C]21[/C][C]-0.004653[/C][C]-0.0357[/C][C]0.485806[/C][/ROW]
[ROW][C]22[/C][C]-0.085263[/C][C]-0.6549[/C][C]0.257534[/C][/ROW]
[ROW][C]23[/C][C]-0.076098[/C][C]-0.5845[/C][C]0.280548[/C][/ROW]
[ROW][C]24[/C][C]0.171783[/C][C]1.3195[/C][C]0.096052[/C][/ROW]
[ROW][C]25[/C][C]0.145074[/C][C]1.1143[/C][C]0.134827[/C][/ROW]
[ROW][C]26[/C][C]-0.29991[/C][C]-2.3037[/C][C]0.012392[/C][/ROW]
[ROW][C]27[/C][C]0.101845[/C][C]0.7823[/C][C]0.218588[/C][/ROW]
[ROW][C]28[/C][C]0.093935[/C][C]0.7215[/C][C]0.236717[/C][/ROW]
[ROW][C]29[/C][C]-0.118385[/C][C]-0.9093[/C][C]0.183437[/C][/ROW]
[ROW][C]30[/C][C]0.036958[/C][C]0.2839[/C][C]0.388749[/C][/ROW]
[ROW][C]31[/C][C]0.158768[/C][C]1.2195[/C][C]0.113751[/C][/ROW]
[ROW][C]32[/C][C]-0.161443[/C][C]-1.2401[/C][C]0.10993[/C][/ROW]
[ROW][C]33[/C][C]0.030696[/C][C]0.2358[/C][C]0.407209[/C][/ROW]
[ROW][C]34[/C][C]0.06817[/C][C]0.5236[/C][C]0.30125[/C][/ROW]
[ROW][C]35[/C][C]-0.217979[/C][C]-1.6743[/C][C]0.04968[/C][/ROW]
[ROW][C]36[/C][C]0.165476[/C][C]1.271[/C][C]0.10435[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64417&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64417&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
1-0.330662-2.53990.006872
2-0.268057-2.0590.021959
30.3170822.43560.008955
4-0.099045-0.76080.224908
5-0.109677-0.84240.201472
60.271242.08340.020777
7-0.248284-1.90710.03069
80.0319620.24550.403459
90.2441411.87530.032853
10-0.379244-2.9130.002524
11-0.085137-0.65390.257844
120.4977713.82340.00016
13-0.204128-1.56790.061122
14-0.170971-1.31330.097091
150.1224510.94060.175381
160.0079820.06130.47566
17-0.049639-0.38130.35218
180.0530080.40720.342681
19-0.018313-0.14070.444307
200.0065910.05060.479897
21-0.004653-0.03570.485806
22-0.085263-0.65490.257534
23-0.076098-0.58450.280548
240.1717831.31950.096052
250.1450741.11430.134827
26-0.29991-2.30370.012392
270.1018450.78230.218588
280.0939350.72150.236717
29-0.118385-0.90930.183437
300.0369580.28390.388749
310.1587681.21950.113751
32-0.161443-1.24010.10993
330.0306960.23580.407209
340.068170.52360.30125
35-0.217979-1.67430.04968
360.1654761.2710.10435






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.330662-2.53990.006872
2-0.423723-3.25470.000941
30.069490.53380.297755
4-0.056302-0.43250.333491
5-0.039574-0.3040.381108
60.1941161.4910.07064
7-0.140581-1.07980.142308
80.0489230.37580.354211
90.1277860.98150.165166
10-0.246886-1.89640.031406
11-0.300343-2.3070.012292
120.2109011.620.055287
130.1832021.40720.082307
14-0.00657-0.05050.479962
15-0.19783-1.51960.066982
160.0973930.74810.228688
170.006750.05180.479413
18-0.152271-1.16960.123429
190.1461.12140.133321
200.0313880.24110.405157
21-0.260382-20.025053
22-0.003834-0.02950.488301
230.0743430.5710.285071
24-0.129451-0.99430.162061
250.1625581.24860.108365
260.0333790.25640.399273
270.1116050.85730.197386
28-0.20112-1.54480.063867
290.0612090.47020.319988
300.1060650.81470.209259
31-0.040755-0.3130.377675
32-0.026357-0.20240.420131
330.073710.56620.28671
340.0530030.40710.342696
35-0.162133-1.24540.10896
360.0127320.09780.461212

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.330662 & -2.5399 & 0.006872 \tabularnewline
2 & -0.423723 & -3.2547 & 0.000941 \tabularnewline
3 & 0.06949 & 0.5338 & 0.297755 \tabularnewline
4 & -0.056302 & -0.4325 & 0.333491 \tabularnewline
5 & -0.039574 & -0.304 & 0.381108 \tabularnewline
6 & 0.194116 & 1.491 & 0.07064 \tabularnewline
7 & -0.140581 & -1.0798 & 0.142308 \tabularnewline
8 & 0.048923 & 0.3758 & 0.354211 \tabularnewline
9 & 0.127786 & 0.9815 & 0.165166 \tabularnewline
10 & -0.246886 & -1.8964 & 0.031406 \tabularnewline
11 & -0.300343 & -2.307 & 0.012292 \tabularnewline
12 & 0.210901 & 1.62 & 0.055287 \tabularnewline
13 & 0.183202 & 1.4072 & 0.082307 \tabularnewline
14 & -0.00657 & -0.0505 & 0.479962 \tabularnewline
15 & -0.19783 & -1.5196 & 0.066982 \tabularnewline
16 & 0.097393 & 0.7481 & 0.228688 \tabularnewline
17 & 0.00675 & 0.0518 & 0.479413 \tabularnewline
18 & -0.152271 & -1.1696 & 0.123429 \tabularnewline
19 & 0.146 & 1.1214 & 0.133321 \tabularnewline
20 & 0.031388 & 0.2411 & 0.405157 \tabularnewline
21 & -0.260382 & -2 & 0.025053 \tabularnewline
22 & -0.003834 & -0.0295 & 0.488301 \tabularnewline
23 & 0.074343 & 0.571 & 0.285071 \tabularnewline
24 & -0.129451 & -0.9943 & 0.162061 \tabularnewline
25 & 0.162558 & 1.2486 & 0.108365 \tabularnewline
26 & 0.033379 & 0.2564 & 0.399273 \tabularnewline
27 & 0.111605 & 0.8573 & 0.197386 \tabularnewline
28 & -0.20112 & -1.5448 & 0.063867 \tabularnewline
29 & 0.061209 & 0.4702 & 0.319988 \tabularnewline
30 & 0.106065 & 0.8147 & 0.209259 \tabularnewline
31 & -0.040755 & -0.313 & 0.377675 \tabularnewline
32 & -0.026357 & -0.2024 & 0.420131 \tabularnewline
33 & 0.07371 & 0.5662 & 0.28671 \tabularnewline
34 & 0.053003 & 0.4071 & 0.342696 \tabularnewline
35 & -0.162133 & -1.2454 & 0.10896 \tabularnewline
36 & 0.012732 & 0.0978 & 0.461212 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64417&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]-0.330662[/C][C]-2.5399[/C][C]0.006872[/C][/ROW]
[ROW][C]2[/C][C]-0.423723[/C][C]-3.2547[/C][C]0.000941[/C][/ROW]
[ROW][C]3[/C][C]0.06949[/C][C]0.5338[/C][C]0.297755[/C][/ROW]
[ROW][C]4[/C][C]-0.056302[/C][C]-0.4325[/C][C]0.333491[/C][/ROW]
[ROW][C]5[/C][C]-0.039574[/C][C]-0.304[/C][C]0.381108[/C][/ROW]
[ROW][C]6[/C][C]0.194116[/C][C]1.491[/C][C]0.07064[/C][/ROW]
[ROW][C]7[/C][C]-0.140581[/C][C]-1.0798[/C][C]0.142308[/C][/ROW]
[ROW][C]8[/C][C]0.048923[/C][C]0.3758[/C][C]0.354211[/C][/ROW]
[ROW][C]9[/C][C]0.127786[/C][C]0.9815[/C][C]0.165166[/C][/ROW]
[ROW][C]10[/C][C]-0.246886[/C][C]-1.8964[/C][C]0.031406[/C][/ROW]
[ROW][C]11[/C][C]-0.300343[/C][C]-2.307[/C][C]0.012292[/C][/ROW]
[ROW][C]12[/C][C]0.210901[/C][C]1.62[/C][C]0.055287[/C][/ROW]
[ROW][C]13[/C][C]0.183202[/C][C]1.4072[/C][C]0.082307[/C][/ROW]
[ROW][C]14[/C][C]-0.00657[/C][C]-0.0505[/C][C]0.479962[/C][/ROW]
[ROW][C]15[/C][C]-0.19783[/C][C]-1.5196[/C][C]0.066982[/C][/ROW]
[ROW][C]16[/C][C]0.097393[/C][C]0.7481[/C][C]0.228688[/C][/ROW]
[ROW][C]17[/C][C]0.00675[/C][C]0.0518[/C][C]0.479413[/C][/ROW]
[ROW][C]18[/C][C]-0.152271[/C][C]-1.1696[/C][C]0.123429[/C][/ROW]
[ROW][C]19[/C][C]0.146[/C][C]1.1214[/C][C]0.133321[/C][/ROW]
[ROW][C]20[/C][C]0.031388[/C][C]0.2411[/C][C]0.405157[/C][/ROW]
[ROW][C]21[/C][C]-0.260382[/C][C]-2[/C][C]0.025053[/C][/ROW]
[ROW][C]22[/C][C]-0.003834[/C][C]-0.0295[/C][C]0.488301[/C][/ROW]
[ROW][C]23[/C][C]0.074343[/C][C]0.571[/C][C]0.285071[/C][/ROW]
[ROW][C]24[/C][C]-0.129451[/C][C]-0.9943[/C][C]0.162061[/C][/ROW]
[ROW][C]25[/C][C]0.162558[/C][C]1.2486[/C][C]0.108365[/C][/ROW]
[ROW][C]26[/C][C]0.033379[/C][C]0.2564[/C][C]0.399273[/C][/ROW]
[ROW][C]27[/C][C]0.111605[/C][C]0.8573[/C][C]0.197386[/C][/ROW]
[ROW][C]28[/C][C]-0.20112[/C][C]-1.5448[/C][C]0.063867[/C][/ROW]
[ROW][C]29[/C][C]0.061209[/C][C]0.4702[/C][C]0.319988[/C][/ROW]
[ROW][C]30[/C][C]0.106065[/C][C]0.8147[/C][C]0.209259[/C][/ROW]
[ROW][C]31[/C][C]-0.040755[/C][C]-0.313[/C][C]0.377675[/C][/ROW]
[ROW][C]32[/C][C]-0.026357[/C][C]-0.2024[/C][C]0.420131[/C][/ROW]
[ROW][C]33[/C][C]0.07371[/C][C]0.5662[/C][C]0.28671[/C][/ROW]
[ROW][C]34[/C][C]0.053003[/C][C]0.4071[/C][C]0.342696[/C][/ROW]
[ROW][C]35[/C][C]-0.162133[/C][C]-1.2454[/C][C]0.10896[/C][/ROW]
[ROW][C]36[/C][C]0.012732[/C][C]0.0978[/C][C]0.461212[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64417&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64417&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
1-0.330662-2.53990.006872
2-0.423723-3.25470.000941
30.069490.53380.297755
4-0.056302-0.43250.333491
5-0.039574-0.3040.381108
60.1941161.4910.07064
7-0.140581-1.07980.142308
80.0489230.37580.354211
90.1277860.98150.165166
10-0.246886-1.89640.031406
11-0.300343-2.3070.012292
120.2109011.620.055287
130.1832021.40720.082307
14-0.00657-0.05050.479962
15-0.19783-1.51960.066982
160.0973930.74810.228688
170.006750.05180.479413
18-0.152271-1.16960.123429
190.1461.12140.133321
200.0313880.24110.405157
21-0.260382-20.025053
22-0.003834-0.02950.488301
230.0743430.5710.285071
24-0.129451-0.99430.162061
250.1625581.24860.108365
260.0333790.25640.399273
270.1116050.85730.197386
28-0.20112-1.54480.063867
290.0612090.47020.319988
300.1060650.81470.209259
31-0.040755-0.3130.377675
32-0.026357-0.20240.420131
330.073710.56620.28671
340.0530030.40710.342696
35-0.162133-1.24540.10896
360.0127320.09780.461212


Figures (Output of Computation)

Input Parameters & R Code

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