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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 computationThu, 10 Dec 2009 05:45:23 -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/10/t1260449187ly4gwwslnrnj4xv.htm/, Retrieved Tue, 16 Apr 2024 18:27:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65319, Retrieved Tue, 16 Apr 2024 18:27:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134

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] [W8] [2009-11-25 18:19:32] [315ba876df544ad397193b5931d5f354]
-   P             [(Partial) Autocorrelation Function] [] [2009-12-10 12:45:23] [950726a732ba3ca782ecb1a5307d0f6f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
13132.1
17665.9
16913
17318.8
16224.2
15469.6
16557.5
19414.8
17335
16525.2
18160.4
15553.8
15262.2
18581
17564.1
18948.6
17187.8
17564.8
17668.4
20811.7
17257.8
18984.2
20532.6
17082.3
16894.9
20274.9
20078.6
19900.9
17012.2
19642.9
19024
21691
18835.9
19873.4
21468.2
19406.8
18385.3
20739.3
22268.3
21569
17514.8
21124.7
21251
21393
22145.2
20310.5
23466.9
21264.6
18388.1
22635.4
22014.3
18422.7
16120.2
16037.7
16410.7
17749.8
16349.8
15662.3
17782.3
16398.9

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65319&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]2 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=65319&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65319&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.4862183.76620.00019
20.3646362.82450.00321
30.4395433.40470.000593
40.4477393.46820.000488
50.3740162.89710.002625
60.2644782.04860.02244
70.1648131.27660.103325
80.2189371.69590.047546
90.0789560.61160.27156
10-0.048899-0.37880.353099
110.0773580.59920.275644
120.281392.17960.01661
13-0.043218-0.33480.369483
14-0.113921-0.88240.190534
15-0.065713-0.5090.306306
160.036980.28640.387763
17-0.043997-0.34080.367224
18-0.085444-0.66180.255302
19-0.090487-0.70090.243034
20-0.067273-0.52110.302108
21-0.184823-1.43160.078719
22-0.203931-1.57960.059723
23-0.117491-0.91010.183211
240.0065130.05050.479965
25-0.180138-1.39530.084028
26-0.278475-2.15710.017509
27-0.189835-1.47050.073332
28-0.093614-0.72510.235596
29-0.188863-1.46290.074353
30-0.19114-1.48060.071978
31-0.176665-1.36840.088138
32-0.211468-1.6380.053325
33-0.248927-1.92820.029284
34-0.239592-1.85590.034192
35-0.194668-1.50790.068415
36-0.103096-0.79860.213842

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.486218 & 3.7662 & 0.00019 \tabularnewline
2 & 0.364636 & 2.8245 & 0.00321 \tabularnewline
3 & 0.439543 & 3.4047 & 0.000593 \tabularnewline
4 & 0.447739 & 3.4682 & 0.000488 \tabularnewline
5 & 0.374016 & 2.8971 & 0.002625 \tabularnewline
6 & 0.264478 & 2.0486 & 0.02244 \tabularnewline
7 & 0.164813 & 1.2766 & 0.103325 \tabularnewline
8 & 0.218937 & 1.6959 & 0.047546 \tabularnewline
9 & 0.078956 & 0.6116 & 0.27156 \tabularnewline
10 & -0.048899 & -0.3788 & 0.353099 \tabularnewline
11 & 0.077358 & 0.5992 & 0.275644 \tabularnewline
12 & 0.28139 & 2.1796 & 0.01661 \tabularnewline
13 & -0.043218 & -0.3348 & 0.369483 \tabularnewline
14 & -0.113921 & -0.8824 & 0.190534 \tabularnewline
15 & -0.065713 & -0.509 & 0.306306 \tabularnewline
16 & 0.03698 & 0.2864 & 0.387763 \tabularnewline
17 & -0.043997 & -0.3408 & 0.367224 \tabularnewline
18 & -0.085444 & -0.6618 & 0.255302 \tabularnewline
19 & -0.090487 & -0.7009 & 0.243034 \tabularnewline
20 & -0.067273 & -0.5211 & 0.302108 \tabularnewline
21 & -0.184823 & -1.4316 & 0.078719 \tabularnewline
22 & -0.203931 & -1.5796 & 0.059723 \tabularnewline
23 & -0.117491 & -0.9101 & 0.183211 \tabularnewline
24 & 0.006513 & 0.0505 & 0.479965 \tabularnewline
25 & -0.180138 & -1.3953 & 0.084028 \tabularnewline
26 & -0.278475 & -2.1571 & 0.017509 \tabularnewline
27 & -0.189835 & -1.4705 & 0.073332 \tabularnewline
28 & -0.093614 & -0.7251 & 0.235596 \tabularnewline
29 & -0.188863 & -1.4629 & 0.074353 \tabularnewline
30 & -0.19114 & -1.4806 & 0.071978 \tabularnewline
31 & -0.176665 & -1.3684 & 0.088138 \tabularnewline
32 & -0.211468 & -1.638 & 0.053325 \tabularnewline
33 & -0.248927 & -1.9282 & 0.029284 \tabularnewline
34 & -0.239592 & -1.8559 & 0.034192 \tabularnewline
35 & -0.194668 & -1.5079 & 0.068415 \tabularnewline
36 & -0.103096 & -0.7986 & 0.213842 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65319&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]0.486218[/C][C]3.7662[/C][C]0.00019[/C][/ROW]
[ROW][C]2[/C][C]0.364636[/C][C]2.8245[/C][C]0.00321[/C][/ROW]
[ROW][C]3[/C][C]0.439543[/C][C]3.4047[/C][C]0.000593[/C][/ROW]
[ROW][C]4[/C][C]0.447739[/C][C]3.4682[/C][C]0.000488[/C][/ROW]
[ROW][C]5[/C][C]0.374016[/C][C]2.8971[/C][C]0.002625[/C][/ROW]
[ROW][C]6[/C][C]0.264478[/C][C]2.0486[/C][C]0.02244[/C][/ROW]
[ROW][C]7[/C][C]0.164813[/C][C]1.2766[/C][C]0.103325[/C][/ROW]
[ROW][C]8[/C][C]0.218937[/C][C]1.6959[/C][C]0.047546[/C][/ROW]
[ROW][C]9[/C][C]0.078956[/C][C]0.6116[/C][C]0.27156[/C][/ROW]
[ROW][C]10[/C][C]-0.048899[/C][C]-0.3788[/C][C]0.353099[/C][/ROW]
[ROW][C]11[/C][C]0.077358[/C][C]0.5992[/C][C]0.275644[/C][/ROW]
[ROW][C]12[/C][C]0.28139[/C][C]2.1796[/C][C]0.01661[/C][/ROW]
[ROW][C]13[/C][C]-0.043218[/C][C]-0.3348[/C][C]0.369483[/C][/ROW]
[ROW][C]14[/C][C]-0.113921[/C][C]-0.8824[/C][C]0.190534[/C][/ROW]
[ROW][C]15[/C][C]-0.065713[/C][C]-0.509[/C][C]0.306306[/C][/ROW]
[ROW][C]16[/C][C]0.03698[/C][C]0.2864[/C][C]0.387763[/C][/ROW]
[ROW][C]17[/C][C]-0.043997[/C][C]-0.3408[/C][C]0.367224[/C][/ROW]
[ROW][C]18[/C][C]-0.085444[/C][C]-0.6618[/C][C]0.255302[/C][/ROW]
[ROW][C]19[/C][C]-0.090487[/C][C]-0.7009[/C][C]0.243034[/C][/ROW]
[ROW][C]20[/C][C]-0.067273[/C][C]-0.5211[/C][C]0.302108[/C][/ROW]
[ROW][C]21[/C][C]-0.184823[/C][C]-1.4316[/C][C]0.078719[/C][/ROW]
[ROW][C]22[/C][C]-0.203931[/C][C]-1.5796[/C][C]0.059723[/C][/ROW]
[ROW][C]23[/C][C]-0.117491[/C][C]-0.9101[/C][C]0.183211[/C][/ROW]
[ROW][C]24[/C][C]0.006513[/C][C]0.0505[/C][C]0.479965[/C][/ROW]
[ROW][C]25[/C][C]-0.180138[/C][C]-1.3953[/C][C]0.084028[/C][/ROW]
[ROW][C]26[/C][C]-0.278475[/C][C]-2.1571[/C][C]0.017509[/C][/ROW]
[ROW][C]27[/C][C]-0.189835[/C][C]-1.4705[/C][C]0.073332[/C][/ROW]
[ROW][C]28[/C][C]-0.093614[/C][C]-0.7251[/C][C]0.235596[/C][/ROW]
[ROW][C]29[/C][C]-0.188863[/C][C]-1.4629[/C][C]0.074353[/C][/ROW]
[ROW][C]30[/C][C]-0.19114[/C][C]-1.4806[/C][C]0.071978[/C][/ROW]
[ROW][C]31[/C][C]-0.176665[/C][C]-1.3684[/C][C]0.088138[/C][/ROW]
[ROW][C]32[/C][C]-0.211468[/C][C]-1.638[/C][C]0.053325[/C][/ROW]
[ROW][C]33[/C][C]-0.248927[/C][C]-1.9282[/C][C]0.029284[/C][/ROW]
[ROW][C]34[/C][C]-0.239592[/C][C]-1.8559[/C][C]0.034192[/C][/ROW]
[ROW][C]35[/C][C]-0.194668[/C][C]-1.5079[/C][C]0.068415[/C][/ROW]
[ROW][C]36[/C][C]-0.103096[/C][C]-0.7986[/C][C]0.213842[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65319&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65319&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
10.4862183.76620.00019
20.3646362.82450.00321
30.4395433.40470.000593
40.4477393.46820.000488
50.3740162.89710.002625
60.2644782.04860.02244
70.1648131.27660.103325
80.2189371.69590.047546
90.0789560.61160.27156
10-0.048899-0.37880.353099
110.0773580.59920.275644
120.281392.17960.01661
13-0.043218-0.33480.369483
14-0.113921-0.88240.190534
15-0.065713-0.5090.306306
160.036980.28640.387763
17-0.043997-0.34080.367224
18-0.085444-0.66180.255302
19-0.090487-0.70090.243034
20-0.067273-0.52110.302108
21-0.184823-1.43160.078719
22-0.203931-1.57960.059723
23-0.117491-0.91010.183211
240.0065130.05050.479965
25-0.180138-1.39530.084028
26-0.278475-2.15710.017509
27-0.189835-1.47050.073332
28-0.093614-0.72510.235596
29-0.188863-1.46290.074353
30-0.19114-1.48060.071978
31-0.176665-1.36840.088138
32-0.211468-1.6380.053325
33-0.248927-1.92820.029284
34-0.239592-1.85590.034192
35-0.194668-1.50790.068415
36-0.103096-0.79860.213842






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4862183.76620.00019
20.1679281.30080.099157
30.28352.1960.015985
40.1957541.51630.067346
50.071840.55650.28998
6-0.070869-0.54890.292539
7-0.161525-1.25120.107865
80.0187370.14510.442546
9-0.18414-1.42630.079476
10-0.170533-1.32090.095768
110.1478391.14520.128345
120.4485113.47410.000479
13-0.228902-1.77310.040646
14-0.163611-1.26730.104968
15-0.152052-1.17780.121765
160.0221580.17160.432152
17-0.138339-1.07160.144102
180.127690.98910.163298
190.1481911.14790.127787
20-0.078567-0.60860.27255
21-0.159135-1.23270.111257
22-0.001942-0.0150.494023
23-0.101141-0.78340.218226
24-0.033909-0.26270.396858
250.1069170.82820.205426
26-0.018126-0.14040.444407
27-0.056296-0.43610.332176
28-0.05504-0.42630.335694
29-0.054279-0.42040.337831
30-0.114052-0.88340.190261
31-0.00134-0.01040.495878
32-0.061686-0.47780.317258
330.0319290.24730.402751
340.0070090.05430.478443
35-0.040942-0.31710.376121
36-0.086945-0.67350.251615

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.486218 & 3.7662 & 0.00019 \tabularnewline
2 & 0.167928 & 1.3008 & 0.099157 \tabularnewline
3 & 0.2835 & 2.196 & 0.015985 \tabularnewline
4 & 0.195754 & 1.5163 & 0.067346 \tabularnewline
5 & 0.07184 & 0.5565 & 0.28998 \tabularnewline
6 & -0.070869 & -0.5489 & 0.292539 \tabularnewline
7 & -0.161525 & -1.2512 & 0.107865 \tabularnewline
8 & 0.018737 & 0.1451 & 0.442546 \tabularnewline
9 & -0.18414 & -1.4263 & 0.079476 \tabularnewline
10 & -0.170533 & -1.3209 & 0.095768 \tabularnewline
11 & 0.147839 & 1.1452 & 0.128345 \tabularnewline
12 & 0.448511 & 3.4741 & 0.000479 \tabularnewline
13 & -0.228902 & -1.7731 & 0.040646 \tabularnewline
14 & -0.163611 & -1.2673 & 0.104968 \tabularnewline
15 & -0.152052 & -1.1778 & 0.121765 \tabularnewline
16 & 0.022158 & 0.1716 & 0.432152 \tabularnewline
17 & -0.138339 & -1.0716 & 0.144102 \tabularnewline
18 & 0.12769 & 0.9891 & 0.163298 \tabularnewline
19 & 0.148191 & 1.1479 & 0.127787 \tabularnewline
20 & -0.078567 & -0.6086 & 0.27255 \tabularnewline
21 & -0.159135 & -1.2327 & 0.111257 \tabularnewline
22 & -0.001942 & -0.015 & 0.494023 \tabularnewline
23 & -0.101141 & -0.7834 & 0.218226 \tabularnewline
24 & -0.033909 & -0.2627 & 0.396858 \tabularnewline
25 & 0.106917 & 0.8282 & 0.205426 \tabularnewline
26 & -0.018126 & -0.1404 & 0.444407 \tabularnewline
27 & -0.056296 & -0.4361 & 0.332176 \tabularnewline
28 & -0.05504 & -0.4263 & 0.335694 \tabularnewline
29 & -0.054279 & -0.4204 & 0.337831 \tabularnewline
30 & -0.114052 & -0.8834 & 0.190261 \tabularnewline
31 & -0.00134 & -0.0104 & 0.495878 \tabularnewline
32 & -0.061686 & -0.4778 & 0.317258 \tabularnewline
33 & 0.031929 & 0.2473 & 0.402751 \tabularnewline
34 & 0.007009 & 0.0543 & 0.478443 \tabularnewline
35 & -0.040942 & -0.3171 & 0.376121 \tabularnewline
36 & -0.086945 & -0.6735 & 0.251615 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65319&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]0.486218[/C][C]3.7662[/C][C]0.00019[/C][/ROW]
[ROW][C]2[/C][C]0.167928[/C][C]1.3008[/C][C]0.099157[/C][/ROW]
[ROW][C]3[/C][C]0.2835[/C][C]2.196[/C][C]0.015985[/C][/ROW]
[ROW][C]4[/C][C]0.195754[/C][C]1.5163[/C][C]0.067346[/C][/ROW]
[ROW][C]5[/C][C]0.07184[/C][C]0.5565[/C][C]0.28998[/C][/ROW]
[ROW][C]6[/C][C]-0.070869[/C][C]-0.5489[/C][C]0.292539[/C][/ROW]
[ROW][C]7[/C][C]-0.161525[/C][C]-1.2512[/C][C]0.107865[/C][/ROW]
[ROW][C]8[/C][C]0.018737[/C][C]0.1451[/C][C]0.442546[/C][/ROW]
[ROW][C]9[/C][C]-0.18414[/C][C]-1.4263[/C][C]0.079476[/C][/ROW]
[ROW][C]10[/C][C]-0.170533[/C][C]-1.3209[/C][C]0.095768[/C][/ROW]
[ROW][C]11[/C][C]0.147839[/C][C]1.1452[/C][C]0.128345[/C][/ROW]
[ROW][C]12[/C][C]0.448511[/C][C]3.4741[/C][C]0.000479[/C][/ROW]
[ROW][C]13[/C][C]-0.228902[/C][C]-1.7731[/C][C]0.040646[/C][/ROW]
[ROW][C]14[/C][C]-0.163611[/C][C]-1.2673[/C][C]0.104968[/C][/ROW]
[ROW][C]15[/C][C]-0.152052[/C][C]-1.1778[/C][C]0.121765[/C][/ROW]
[ROW][C]16[/C][C]0.022158[/C][C]0.1716[/C][C]0.432152[/C][/ROW]
[ROW][C]17[/C][C]-0.138339[/C][C]-1.0716[/C][C]0.144102[/C][/ROW]
[ROW][C]18[/C][C]0.12769[/C][C]0.9891[/C][C]0.163298[/C][/ROW]
[ROW][C]19[/C][C]0.148191[/C][C]1.1479[/C][C]0.127787[/C][/ROW]
[ROW][C]20[/C][C]-0.078567[/C][C]-0.6086[/C][C]0.27255[/C][/ROW]
[ROW][C]21[/C][C]-0.159135[/C][C]-1.2327[/C][C]0.111257[/C][/ROW]
[ROW][C]22[/C][C]-0.001942[/C][C]-0.015[/C][C]0.494023[/C][/ROW]
[ROW][C]23[/C][C]-0.101141[/C][C]-0.7834[/C][C]0.218226[/C][/ROW]
[ROW][C]24[/C][C]-0.033909[/C][C]-0.2627[/C][C]0.396858[/C][/ROW]
[ROW][C]25[/C][C]0.106917[/C][C]0.8282[/C][C]0.205426[/C][/ROW]
[ROW][C]26[/C][C]-0.018126[/C][C]-0.1404[/C][C]0.444407[/C][/ROW]
[ROW][C]27[/C][C]-0.056296[/C][C]-0.4361[/C][C]0.332176[/C][/ROW]
[ROW][C]28[/C][C]-0.05504[/C][C]-0.4263[/C][C]0.335694[/C][/ROW]
[ROW][C]29[/C][C]-0.054279[/C][C]-0.4204[/C][C]0.337831[/C][/ROW]
[ROW][C]30[/C][C]-0.114052[/C][C]-0.8834[/C][C]0.190261[/C][/ROW]
[ROW][C]31[/C][C]-0.00134[/C][C]-0.0104[/C][C]0.495878[/C][/ROW]
[ROW][C]32[/C][C]-0.061686[/C][C]-0.4778[/C][C]0.317258[/C][/ROW]
[ROW][C]33[/C][C]0.031929[/C][C]0.2473[/C][C]0.402751[/C][/ROW]
[ROW][C]34[/C][C]0.007009[/C][C]0.0543[/C][C]0.478443[/C][/ROW]
[ROW][C]35[/C][C]-0.040942[/C][C]-0.3171[/C][C]0.376121[/C][/ROW]
[ROW][C]36[/C][C]-0.086945[/C][C]-0.6735[/C][C]0.251615[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65319&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65319&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
10.4862183.76620.00019
20.1679281.30080.099157
30.28352.1960.015985
40.1957541.51630.067346
50.071840.55650.28998
6-0.070869-0.54890.292539
7-0.161525-1.25120.107865
80.0187370.14510.442546
9-0.18414-1.42630.079476
10-0.170533-1.32090.095768
110.1478391.14520.128345
120.4485113.47410.000479
13-0.228902-1.77310.040646
14-0.163611-1.26730.104968
15-0.152052-1.17780.121765
160.0221580.17160.432152
17-0.138339-1.07160.144102
180.127690.98910.163298
190.1481911.14790.127787
20-0.078567-0.60860.27255
21-0.159135-1.23270.111257
22-0.001942-0.0150.494023
23-0.101141-0.78340.218226
24-0.033909-0.26270.396858
250.1069170.82820.205426
26-0.018126-0.14040.444407
27-0.056296-0.43610.332176
28-0.05504-0.42630.335694
29-0.054279-0.42040.337831
30-0.114052-0.88340.190261
31-0.00134-0.01040.495878
32-0.061686-0.47780.317258
330.0319290.24730.402751
340.0070090.05430.478443
35-0.040942-0.31710.376121
36-0.086945-0.67350.251615


Figures (Output of Computation)

Input Parameters & R Code

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