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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 computationFri, 04 Dec 2009 14:19:32 -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/04/t1259961610m61nghh6tjj8wj4.htm/, Retrieved Sat, 27 Apr 2024 19:17:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64158, Retrieved Sat, 27 Apr 2024 19:17:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact72

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 12:16:10] [b98453cac15ba1066b407e146608df68]
-   PD        [(Partial) Autocorrelation Function] [ws8 methode 1 link 3] [2009-11-27 11:51:56] [517ac0676608e46c618c738721d88e41]
-   P             [(Partial) Autocorrelation Function] [] [2009-12-04 21:19:32] [0545e25c765ce26b196961216dc11e13] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3.75
3.75
3.55
3.5
3.5
3.1
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3.21
3.25
3.25
3.45
3.5
3.5
3.64
3.75
3.93
4
4.17
4.25
4.39
4.5
4.5
4.65
4.75
4.75
4.9
5
5
5
5
5
5
5
5
5
5
5
5
5.18
5.25
5.25
4.49
3.92
3.25

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=64158&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=64158&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64158&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
10.5443634.58699e-06
20.3342672.81660.00314
30.0709510.59780.275924
40.0162310.13680.445803
50.0187080.15760.437595
60.0854780.72030.236867
70.0834380.70310.242158
80.0769990.64880.259279
90.067910.57220.28449
100.0649160.5470.29305
110.0413060.3480.364417
120.070110.59080.278279
130.0554040.46680.321022
140.0198160.1670.433933
150.0136950.11540.454229
16-0.043834-0.36930.356483
17-0.065059-0.54820.292638
18-0.057615-0.48550.314418
19-0.056028-0.47210.319151
20-0.06199-0.52230.30153
21-0.072777-0.61320.270841
22-0.071614-0.60340.274072
23-0.088812-0.74830.228363
24-0.120623-1.01640.156447
25-0.086512-0.7290.234212
26-0.145134-1.22290.112702
27-0.115745-0.97530.166365
28-0.129865-1.09430.13877
29-0.083024-0.69960.24324
30-0.111073-0.93590.176245
31-0.081572-0.68730.247055
32-0.08552-0.72060.236759
33-0.154683-1.30340.098328
34-0.111467-0.93920.175396
35-0.091131-0.76790.22255
36-0.133695-1.12650.131866

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.544363 & 4.5869 & 9e-06 \tabularnewline
2 & 0.334267 & 2.8166 & 0.00314 \tabularnewline
3 & 0.070951 & 0.5978 & 0.275924 \tabularnewline
4 & 0.016231 & 0.1368 & 0.445803 \tabularnewline
5 & 0.018708 & 0.1576 & 0.437595 \tabularnewline
6 & 0.085478 & 0.7203 & 0.236867 \tabularnewline
7 & 0.083438 & 0.7031 & 0.242158 \tabularnewline
8 & 0.076999 & 0.6488 & 0.259279 \tabularnewline
9 & 0.06791 & 0.5722 & 0.28449 \tabularnewline
10 & 0.064916 & 0.547 & 0.29305 \tabularnewline
11 & 0.041306 & 0.348 & 0.364417 \tabularnewline
12 & 0.07011 & 0.5908 & 0.278279 \tabularnewline
13 & 0.055404 & 0.4668 & 0.321022 \tabularnewline
14 & 0.019816 & 0.167 & 0.433933 \tabularnewline
15 & 0.013695 & 0.1154 & 0.454229 \tabularnewline
16 & -0.043834 & -0.3693 & 0.356483 \tabularnewline
17 & -0.065059 & -0.5482 & 0.292638 \tabularnewline
18 & -0.057615 & -0.4855 & 0.314418 \tabularnewline
19 & -0.056028 & -0.4721 & 0.319151 \tabularnewline
20 & -0.06199 & -0.5223 & 0.30153 \tabularnewline
21 & -0.072777 & -0.6132 & 0.270841 \tabularnewline
22 & -0.071614 & -0.6034 & 0.274072 \tabularnewline
23 & -0.088812 & -0.7483 & 0.228363 \tabularnewline
24 & -0.120623 & -1.0164 & 0.156447 \tabularnewline
25 & -0.086512 & -0.729 & 0.234212 \tabularnewline
26 & -0.145134 & -1.2229 & 0.112702 \tabularnewline
27 & -0.115745 & -0.9753 & 0.166365 \tabularnewline
28 & -0.129865 & -1.0943 & 0.13877 \tabularnewline
29 & -0.083024 & -0.6996 & 0.24324 \tabularnewline
30 & -0.111073 & -0.9359 & 0.176245 \tabularnewline
31 & -0.081572 & -0.6873 & 0.247055 \tabularnewline
32 & -0.08552 & -0.7206 & 0.236759 \tabularnewline
33 & -0.154683 & -1.3034 & 0.098328 \tabularnewline
34 & -0.111467 & -0.9392 & 0.175396 \tabularnewline
35 & -0.091131 & -0.7679 & 0.22255 \tabularnewline
36 & -0.133695 & -1.1265 & 0.131866 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64158&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]0.544363[/C][C]4.5869[/C][C]9e-06[/C][/ROW]
[ROW][C]2[/C][C]0.334267[/C][C]2.8166[/C][C]0.00314[/C][/ROW]
[ROW][C]3[/C][C]0.070951[/C][C]0.5978[/C][C]0.275924[/C][/ROW]
[ROW][C]4[/C][C]0.016231[/C][C]0.1368[/C][C]0.445803[/C][/ROW]
[ROW][C]5[/C][C]0.018708[/C][C]0.1576[/C][C]0.437595[/C][/ROW]
[ROW][C]6[/C][C]0.085478[/C][C]0.7203[/C][C]0.236867[/C][/ROW]
[ROW][C]7[/C][C]0.083438[/C][C]0.7031[/C][C]0.242158[/C][/ROW]
[ROW][C]8[/C][C]0.076999[/C][C]0.6488[/C][C]0.259279[/C][/ROW]
[ROW][C]9[/C][C]0.06791[/C][C]0.5722[/C][C]0.28449[/C][/ROW]
[ROW][C]10[/C][C]0.064916[/C][C]0.547[/C][C]0.29305[/C][/ROW]
[ROW][C]11[/C][C]0.041306[/C][C]0.348[/C][C]0.364417[/C][/ROW]
[ROW][C]12[/C][C]0.07011[/C][C]0.5908[/C][C]0.278279[/C][/ROW]
[ROW][C]13[/C][C]0.055404[/C][C]0.4668[/C][C]0.321022[/C][/ROW]
[ROW][C]14[/C][C]0.019816[/C][C]0.167[/C][C]0.433933[/C][/ROW]
[ROW][C]15[/C][C]0.013695[/C][C]0.1154[/C][C]0.454229[/C][/ROW]
[ROW][C]16[/C][C]-0.043834[/C][C]-0.3693[/C][C]0.356483[/C][/ROW]
[ROW][C]17[/C][C]-0.065059[/C][C]-0.5482[/C][C]0.292638[/C][/ROW]
[ROW][C]18[/C][C]-0.057615[/C][C]-0.4855[/C][C]0.314418[/C][/ROW]
[ROW][C]19[/C][C]-0.056028[/C][C]-0.4721[/C][C]0.319151[/C][/ROW]
[ROW][C]20[/C][C]-0.06199[/C][C]-0.5223[/C][C]0.30153[/C][/ROW]
[ROW][C]21[/C][C]-0.072777[/C][C]-0.6132[/C][C]0.270841[/C][/ROW]
[ROW][C]22[/C][C]-0.071614[/C][C]-0.6034[/C][C]0.274072[/C][/ROW]
[ROW][C]23[/C][C]-0.088812[/C][C]-0.7483[/C][C]0.228363[/C][/ROW]
[ROW][C]24[/C][C]-0.120623[/C][C]-1.0164[/C][C]0.156447[/C][/ROW]
[ROW][C]25[/C][C]-0.086512[/C][C]-0.729[/C][C]0.234212[/C][/ROW]
[ROW][C]26[/C][C]-0.145134[/C][C]-1.2229[/C][C]0.112702[/C][/ROW]
[ROW][C]27[/C][C]-0.115745[/C][C]-0.9753[/C][C]0.166365[/C][/ROW]
[ROW][C]28[/C][C]-0.129865[/C][C]-1.0943[/C][C]0.13877[/C][/ROW]
[ROW][C]29[/C][C]-0.083024[/C][C]-0.6996[/C][C]0.24324[/C][/ROW]
[ROW][C]30[/C][C]-0.111073[/C][C]-0.9359[/C][C]0.176245[/C][/ROW]
[ROW][C]31[/C][C]-0.081572[/C][C]-0.6873[/C][C]0.247055[/C][/ROW]
[ROW][C]32[/C][C]-0.08552[/C][C]-0.7206[/C][C]0.236759[/C][/ROW]
[ROW][C]33[/C][C]-0.154683[/C][C]-1.3034[/C][C]0.098328[/C][/ROW]
[ROW][C]34[/C][C]-0.111467[/C][C]-0.9392[/C][C]0.175396[/C][/ROW]
[ROW][C]35[/C][C]-0.091131[/C][C]-0.7679[/C][C]0.22255[/C][/ROW]
[ROW][C]36[/C][C]-0.133695[/C][C]-1.1265[/C][C]0.131866[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64158&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64158&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
10.5443634.58699e-06
20.3342672.81660.00314
30.0709510.59780.275924
40.0162310.13680.445803
50.0187080.15760.437595
60.0854780.72030.236867
70.0834380.70310.242158
80.0769990.64880.259279
90.067910.57220.28449
100.0649160.5470.29305
110.0413060.3480.364417
120.070110.59080.278279
130.0554040.46680.321022
140.0198160.1670.433933
150.0136950.11540.454229
16-0.043834-0.36930.356483
17-0.065059-0.54820.292638
18-0.057615-0.48550.314418
19-0.056028-0.47210.319151
20-0.06199-0.52230.30153
21-0.072777-0.61320.270841
22-0.071614-0.60340.274072
23-0.088812-0.74830.228363
24-0.120623-1.01640.156447
25-0.086512-0.7290.234212
26-0.145134-1.22290.112702
27-0.115745-0.97530.166365
28-0.129865-1.09430.13877
29-0.083024-0.69960.24324
30-0.111073-0.93590.176245
31-0.081572-0.68730.247055
32-0.08552-0.72060.236759
33-0.154683-1.30340.098328
34-0.111467-0.93920.175396
35-0.091131-0.76790.22255
36-0.133695-1.12650.131866






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5443634.58699e-06
20.0539110.45430.325514
3-0.186067-1.56780.060684
40.0446070.37590.354068
50.0675220.56890.285594
60.0727070.61260.271037
7-0.015186-0.1280.449273
80.0039090.03290.486909
90.043660.36790.357026
100.025750.2170.414424
11-0.019984-0.16840.433379
120.0594250.50070.309056
130.0012520.01050.495807
14-0.051073-0.43040.334121
150.0228910.19290.423799
16-0.067581-0.56950.285424
17-0.036582-0.30820.379399
180.0098040.08260.467197
19-0.034916-0.29420.384729
20-0.040444-0.34080.367134
21-0.035872-0.30230.381666
22-0.009832-0.08280.467102
23-0.039026-0.32880.371623
24-0.082189-0.69250.245429
250.0328130.27650.391487
26-0.105997-0.89320.187397
27-0.010424-0.08780.465126
28-0.029976-0.25260.400662
290.0206990.17440.431018
30-0.07382-0.6220.267962
31-0.000305-0.00260.49898
320.0032640.02750.489069
33-0.147788-1.24530.108561
340.0575710.48510.314547
350.0109220.0920.463467
36-0.13849-1.16690.12357

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.544363 & 4.5869 & 9e-06 \tabularnewline
2 & 0.053911 & 0.4543 & 0.325514 \tabularnewline
3 & -0.186067 & -1.5678 & 0.060684 \tabularnewline
4 & 0.044607 & 0.3759 & 0.354068 \tabularnewline
5 & 0.067522 & 0.5689 & 0.285594 \tabularnewline
6 & 0.072707 & 0.6126 & 0.271037 \tabularnewline
7 & -0.015186 & -0.128 & 0.449273 \tabularnewline
8 & 0.003909 & 0.0329 & 0.486909 \tabularnewline
9 & 0.04366 & 0.3679 & 0.357026 \tabularnewline
10 & 0.02575 & 0.217 & 0.414424 \tabularnewline
11 & -0.019984 & -0.1684 & 0.433379 \tabularnewline
12 & 0.059425 & 0.5007 & 0.309056 \tabularnewline
13 & 0.001252 & 0.0105 & 0.495807 \tabularnewline
14 & -0.051073 & -0.4304 & 0.334121 \tabularnewline
15 & 0.022891 & 0.1929 & 0.423799 \tabularnewline
16 & -0.067581 & -0.5695 & 0.285424 \tabularnewline
17 & -0.036582 & -0.3082 & 0.379399 \tabularnewline
18 & 0.009804 & 0.0826 & 0.467197 \tabularnewline
19 & -0.034916 & -0.2942 & 0.384729 \tabularnewline
20 & -0.040444 & -0.3408 & 0.367134 \tabularnewline
21 & -0.035872 & -0.3023 & 0.381666 \tabularnewline
22 & -0.009832 & -0.0828 & 0.467102 \tabularnewline
23 & -0.039026 & -0.3288 & 0.371623 \tabularnewline
24 & -0.082189 & -0.6925 & 0.245429 \tabularnewline
25 & 0.032813 & 0.2765 & 0.391487 \tabularnewline
26 & -0.105997 & -0.8932 & 0.187397 \tabularnewline
27 & -0.010424 & -0.0878 & 0.465126 \tabularnewline
28 & -0.029976 & -0.2526 & 0.400662 \tabularnewline
29 & 0.020699 & 0.1744 & 0.431018 \tabularnewline
30 & -0.07382 & -0.622 & 0.267962 \tabularnewline
31 & -0.000305 & -0.0026 & 0.49898 \tabularnewline
32 & 0.003264 & 0.0275 & 0.489069 \tabularnewline
33 & -0.147788 & -1.2453 & 0.108561 \tabularnewline
34 & 0.057571 & 0.4851 & 0.314547 \tabularnewline
35 & 0.010922 & 0.092 & 0.463467 \tabularnewline
36 & -0.13849 & -1.1669 & 0.12357 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64158&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]0.544363[/C][C]4.5869[/C][C]9e-06[/C][/ROW]
[ROW][C]2[/C][C]0.053911[/C][C]0.4543[/C][C]0.325514[/C][/ROW]
[ROW][C]3[/C][C]-0.186067[/C][C]-1.5678[/C][C]0.060684[/C][/ROW]
[ROW][C]4[/C][C]0.044607[/C][C]0.3759[/C][C]0.354068[/C][/ROW]
[ROW][C]5[/C][C]0.067522[/C][C]0.5689[/C][C]0.285594[/C][/ROW]
[ROW][C]6[/C][C]0.072707[/C][C]0.6126[/C][C]0.271037[/C][/ROW]
[ROW][C]7[/C][C]-0.015186[/C][C]-0.128[/C][C]0.449273[/C][/ROW]
[ROW][C]8[/C][C]0.003909[/C][C]0.0329[/C][C]0.486909[/C][/ROW]
[ROW][C]9[/C][C]0.04366[/C][C]0.3679[/C][C]0.357026[/C][/ROW]
[ROW][C]10[/C][C]0.02575[/C][C]0.217[/C][C]0.414424[/C][/ROW]
[ROW][C]11[/C][C]-0.019984[/C][C]-0.1684[/C][C]0.433379[/C][/ROW]
[ROW][C]12[/C][C]0.059425[/C][C]0.5007[/C][C]0.309056[/C][/ROW]
[ROW][C]13[/C][C]0.001252[/C][C]0.0105[/C][C]0.495807[/C][/ROW]
[ROW][C]14[/C][C]-0.051073[/C][C]-0.4304[/C][C]0.334121[/C][/ROW]
[ROW][C]15[/C][C]0.022891[/C][C]0.1929[/C][C]0.423799[/C][/ROW]
[ROW][C]16[/C][C]-0.067581[/C][C]-0.5695[/C][C]0.285424[/C][/ROW]
[ROW][C]17[/C][C]-0.036582[/C][C]-0.3082[/C][C]0.379399[/C][/ROW]
[ROW][C]18[/C][C]0.009804[/C][C]0.0826[/C][C]0.467197[/C][/ROW]
[ROW][C]19[/C][C]-0.034916[/C][C]-0.2942[/C][C]0.384729[/C][/ROW]
[ROW][C]20[/C][C]-0.040444[/C][C]-0.3408[/C][C]0.367134[/C][/ROW]
[ROW][C]21[/C][C]-0.035872[/C][C]-0.3023[/C][C]0.381666[/C][/ROW]
[ROW][C]22[/C][C]-0.009832[/C][C]-0.0828[/C][C]0.467102[/C][/ROW]
[ROW][C]23[/C][C]-0.039026[/C][C]-0.3288[/C][C]0.371623[/C][/ROW]
[ROW][C]24[/C][C]-0.082189[/C][C]-0.6925[/C][C]0.245429[/C][/ROW]
[ROW][C]25[/C][C]0.032813[/C][C]0.2765[/C][C]0.391487[/C][/ROW]
[ROW][C]26[/C][C]-0.105997[/C][C]-0.8932[/C][C]0.187397[/C][/ROW]
[ROW][C]27[/C][C]-0.010424[/C][C]-0.0878[/C][C]0.465126[/C][/ROW]
[ROW][C]28[/C][C]-0.029976[/C][C]-0.2526[/C][C]0.400662[/C][/ROW]
[ROW][C]29[/C][C]0.020699[/C][C]0.1744[/C][C]0.431018[/C][/ROW]
[ROW][C]30[/C][C]-0.07382[/C][C]-0.622[/C][C]0.267962[/C][/ROW]
[ROW][C]31[/C][C]-0.000305[/C][C]-0.0026[/C][C]0.49898[/C][/ROW]
[ROW][C]32[/C][C]0.003264[/C][C]0.0275[/C][C]0.489069[/C][/ROW]
[ROW][C]33[/C][C]-0.147788[/C][C]-1.2453[/C][C]0.108561[/C][/ROW]
[ROW][C]34[/C][C]0.057571[/C][C]0.4851[/C][C]0.314547[/C][/ROW]
[ROW][C]35[/C][C]0.010922[/C][C]0.092[/C][C]0.463467[/C][/ROW]
[ROW][C]36[/C][C]-0.13849[/C][C]-1.1669[/C][C]0.12357[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64158&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64158&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
10.5443634.58699e-06
20.0539110.45430.325514
3-0.186067-1.56780.060684
40.0446070.37590.354068
50.0675220.56890.285594
60.0727070.61260.271037
7-0.015186-0.1280.449273
80.0039090.03290.486909
90.043660.36790.357026
100.025750.2170.414424
11-0.019984-0.16840.433379
120.0594250.50070.309056
130.0012520.01050.495807
14-0.051073-0.43040.334121
150.0228910.19290.423799
16-0.067581-0.56950.285424
17-0.036582-0.30820.379399
180.0098040.08260.467197
19-0.034916-0.29420.384729
20-0.040444-0.34080.367134
21-0.035872-0.30230.381666
22-0.009832-0.08280.467102
23-0.039026-0.32880.371623
24-0.082189-0.69250.245429
250.0328130.27650.391487
26-0.105997-0.89320.187397
27-0.010424-0.08780.465126
28-0.029976-0.25260.400662
290.0206990.17440.431018
30-0.07382-0.6220.267962
31-0.000305-0.00260.49898
320.0032640.02750.489069
33-0.147788-1.24530.108561
340.0575710.48510.314547
350.0109220.0920.463467
36-0.13849-1.16690.12357


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')