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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 computationSat, 19 Dec 2009 09:12:58 -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/19/t12612393680wx1rk20oqn7e8d.htm/, Retrieved Sat, 04 May 2024 00:48:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69665, Retrieved Sat, 04 May 2024 00:48:23 +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 12:16:10] [b98453cac15ba1066b407e146608df68]
- R  D        [(Partial) Autocorrelation Function] [ACF d=0,D=0] [2009-11-27 15:55:59] [fa71ec4c741ffec745cb91dcbd756720]
-   PD            [(Partial) Autocorrelation Function] [d=1,D=0] [2009-12-19 16:12:58] [18c0746232b29e9668aa6bedcb8dd698] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.6
15.7
13.2
20.3
12.8
8
0.9
3.6
14.1
21.7
24.5
18.9
13.9
11
5.8
15.5
22.4
31.7
30.3
31.4
20.2
19.7
10.8
13.2
15.1
15.6
15.5
12.7
10.9
10
9.1
10.3
16.9
22
27.6
28.9
31
32.9
38.1
28.8
29
21.8
28.8
25.6
28.2
20.2
17.9
16.3
13.2
8.1
4.5
-0.1
0
2.3
2.8
2.9
0.1
3.5
8.6
13.8

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=69665&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=69665&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69665&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
10.1684831.29410.100329
20.2481861.90640.030739
3-0.444058-3.41090.000587
4-0.168099-1.29120.100837
5-0.228368-1.75410.042301
60.1143520.87840.191657
70.0957270.73530.232536
80.224851.72710.044691
90.0767310.58940.278929
10-0.055495-0.42630.335733
11-0.258438-1.98510.025894
12-0.282461-2.16960.017038
13-0.259991-1.9970.025221
14-0.078997-0.60680.273161
150.046360.35610.361519
160.1286890.98850.163477
170.0796290.61160.271563
18-0.031325-0.24060.405346
190.0062310.04790.480993
20-0.088165-0.67720.25046
210.1122270.8620.19608
22-0.098118-0.75370.227026
230.1354631.04050.151174
24-0.039335-0.30210.381804
250.2051931.57610.060173
260.0331020.25430.400089
270.1218520.9360.176554
28-0.025975-0.19950.421272
290.0547080.42020.337925
30-0.089463-0.68720.247331
31-0.086599-0.66520.254265
32-0.11943-0.91740.181345
33-0.034673-0.26630.395459
340.0373980.28730.387459
350.0815010.6260.266858
36-0.071301-0.54770.29299

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.168483 & 1.2941 & 0.100329 \tabularnewline
2 & 0.248186 & 1.9064 & 0.030739 \tabularnewline
3 & -0.444058 & -3.4109 & 0.000587 \tabularnewline
4 & -0.168099 & -1.2912 & 0.100837 \tabularnewline
5 & -0.228368 & -1.7541 & 0.042301 \tabularnewline
6 & 0.114352 & 0.8784 & 0.191657 \tabularnewline
7 & 0.095727 & 0.7353 & 0.232536 \tabularnewline
8 & 0.22485 & 1.7271 & 0.044691 \tabularnewline
9 & 0.076731 & 0.5894 & 0.278929 \tabularnewline
10 & -0.055495 & -0.4263 & 0.335733 \tabularnewline
11 & -0.258438 & -1.9851 & 0.025894 \tabularnewline
12 & -0.282461 & -2.1696 & 0.017038 \tabularnewline
13 & -0.259991 & -1.997 & 0.025221 \tabularnewline
14 & -0.078997 & -0.6068 & 0.273161 \tabularnewline
15 & 0.04636 & 0.3561 & 0.361519 \tabularnewline
16 & 0.128689 & 0.9885 & 0.163477 \tabularnewline
17 & 0.079629 & 0.6116 & 0.271563 \tabularnewline
18 & -0.031325 & -0.2406 & 0.405346 \tabularnewline
19 & 0.006231 & 0.0479 & 0.480993 \tabularnewline
20 & -0.088165 & -0.6772 & 0.25046 \tabularnewline
21 & 0.112227 & 0.862 & 0.19608 \tabularnewline
22 & -0.098118 & -0.7537 & 0.227026 \tabularnewline
23 & 0.135463 & 1.0405 & 0.151174 \tabularnewline
24 & -0.039335 & -0.3021 & 0.381804 \tabularnewline
25 & 0.205193 & 1.5761 & 0.060173 \tabularnewline
26 & 0.033102 & 0.2543 & 0.400089 \tabularnewline
27 & 0.121852 & 0.936 & 0.176554 \tabularnewline
28 & -0.025975 & -0.1995 & 0.421272 \tabularnewline
29 & 0.054708 & 0.4202 & 0.337925 \tabularnewline
30 & -0.089463 & -0.6872 & 0.247331 \tabularnewline
31 & -0.086599 & -0.6652 & 0.254265 \tabularnewline
32 & -0.11943 & -0.9174 & 0.181345 \tabularnewline
33 & -0.034673 & -0.2663 & 0.395459 \tabularnewline
34 & 0.037398 & 0.2873 & 0.387459 \tabularnewline
35 & 0.081501 & 0.626 & 0.266858 \tabularnewline
36 & -0.071301 & -0.5477 & 0.29299 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69665&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]0.168483[/C][C]1.2941[/C][C]0.100329[/C][/ROW]
[ROW][C]2[/C][C]0.248186[/C][C]1.9064[/C][C]0.030739[/C][/ROW]
[ROW][C]3[/C][C]-0.444058[/C][C]-3.4109[/C][C]0.000587[/C][/ROW]
[ROW][C]4[/C][C]-0.168099[/C][C]-1.2912[/C][C]0.100837[/C][/ROW]
[ROW][C]5[/C][C]-0.228368[/C][C]-1.7541[/C][C]0.042301[/C][/ROW]
[ROW][C]6[/C][C]0.114352[/C][C]0.8784[/C][C]0.191657[/C][/ROW]
[ROW][C]7[/C][C]0.095727[/C][C]0.7353[/C][C]0.232536[/C][/ROW]
[ROW][C]8[/C][C]0.22485[/C][C]1.7271[/C][C]0.044691[/C][/ROW]
[ROW][C]9[/C][C]0.076731[/C][C]0.5894[/C][C]0.278929[/C][/ROW]
[ROW][C]10[/C][C]-0.055495[/C][C]-0.4263[/C][C]0.335733[/C][/ROW]
[ROW][C]11[/C][C]-0.258438[/C][C]-1.9851[/C][C]0.025894[/C][/ROW]
[ROW][C]12[/C][C]-0.282461[/C][C]-2.1696[/C][C]0.017038[/C][/ROW]
[ROW][C]13[/C][C]-0.259991[/C][C]-1.997[/C][C]0.025221[/C][/ROW]
[ROW][C]14[/C][C]-0.078997[/C][C]-0.6068[/C][C]0.273161[/C][/ROW]
[ROW][C]15[/C][C]0.04636[/C][C]0.3561[/C][C]0.361519[/C][/ROW]
[ROW][C]16[/C][C]0.128689[/C][C]0.9885[/C][C]0.163477[/C][/ROW]
[ROW][C]17[/C][C]0.079629[/C][C]0.6116[/C][C]0.271563[/C][/ROW]
[ROW][C]18[/C][C]-0.031325[/C][C]-0.2406[/C][C]0.405346[/C][/ROW]
[ROW][C]19[/C][C]0.006231[/C][C]0.0479[/C][C]0.480993[/C][/ROW]
[ROW][C]20[/C][C]-0.088165[/C][C]-0.6772[/C][C]0.25046[/C][/ROW]
[ROW][C]21[/C][C]0.112227[/C][C]0.862[/C][C]0.19608[/C][/ROW]
[ROW][C]22[/C][C]-0.098118[/C][C]-0.7537[/C][C]0.227026[/C][/ROW]
[ROW][C]23[/C][C]0.135463[/C][C]1.0405[/C][C]0.151174[/C][/ROW]
[ROW][C]24[/C][C]-0.039335[/C][C]-0.3021[/C][C]0.381804[/C][/ROW]
[ROW][C]25[/C][C]0.205193[/C][C]1.5761[/C][C]0.060173[/C][/ROW]
[ROW][C]26[/C][C]0.033102[/C][C]0.2543[/C][C]0.400089[/C][/ROW]
[ROW][C]27[/C][C]0.121852[/C][C]0.936[/C][C]0.176554[/C][/ROW]
[ROW][C]28[/C][C]-0.025975[/C][C]-0.1995[/C][C]0.421272[/C][/ROW]
[ROW][C]29[/C][C]0.054708[/C][C]0.4202[/C][C]0.337925[/C][/ROW]
[ROW][C]30[/C][C]-0.089463[/C][C]-0.6872[/C][C]0.247331[/C][/ROW]
[ROW][C]31[/C][C]-0.086599[/C][C]-0.6652[/C][C]0.254265[/C][/ROW]
[ROW][C]32[/C][C]-0.11943[/C][C]-0.9174[/C][C]0.181345[/C][/ROW]
[ROW][C]33[/C][C]-0.034673[/C][C]-0.2663[/C][C]0.395459[/C][/ROW]
[ROW][C]34[/C][C]0.037398[/C][C]0.2873[/C][C]0.387459[/C][/ROW]
[ROW][C]35[/C][C]0.081501[/C][C]0.626[/C][C]0.266858[/C][/ROW]
[ROW][C]36[/C][C]-0.071301[/C][C]-0.5477[/C][C]0.29299[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69665&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69665&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
10.1684831.29410.100329
20.2481861.90640.030739
3-0.444058-3.41090.000587
4-0.168099-1.29120.100837
5-0.228368-1.75410.042301
60.1143520.87840.191657
70.0957270.73530.232536
80.224851.72710.044691
90.0767310.58940.278929
10-0.055495-0.42630.335733
11-0.258438-1.98510.025894
12-0.282461-2.16960.017038
13-0.259991-1.9970.025221
14-0.078997-0.60680.273161
150.046360.35610.361519
160.1286890.98850.163477
170.0796290.61160.271563
18-0.031325-0.24060.405346
190.0062310.04790.480993
20-0.088165-0.67720.25046
210.1122270.8620.19608
22-0.098118-0.75370.227026
230.1354631.04050.151174
24-0.039335-0.30210.381804
250.2051931.57610.060173
260.0331020.25430.400089
270.1218520.9360.176554
28-0.025975-0.19950.421272
290.0547080.42020.337925
30-0.089463-0.68720.247331
31-0.086599-0.66520.254265
32-0.11943-0.91740.181345
33-0.034673-0.26630.395459
340.0373980.28730.387459
350.0815010.6260.266858
36-0.071301-0.54770.29299






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1684831.29410.100329
20.2262211.73760.043746
3-0.558123-4.2873.4e-05
4-0.054055-0.41520.339748
50.1482541.13880.129702
6-0.050439-0.38740.349916
7-0.013258-0.10180.459617
80.1447781.11210.135311
90.044560.34230.366681
10-0.19545-1.50130.069308
11-0.181451-1.39380.08431
12-0.072745-0.55880.289219
13-0.202359-1.55430.062725
14-0.185479-1.42470.079758
15-0.026771-0.20560.418893
16-0.068146-0.52340.301314
17-0.134838-1.03570.152282
18-0.107613-0.82660.2059
190.2069271.58940.058653
20-0.047012-0.36110.359655
210.0420140.32270.374024
22-0.119288-0.91630.181628
230.0119520.09180.463583
24-0.027243-0.20930.417483
25-0.055134-0.42350.336739
260.010750.08260.467236
27-0.039223-0.30130.38213
280.0235520.18090.42853
290.081550.62640.266736
30-0.102262-0.78550.217655
31-0.157551-1.21020.11552
320.0680170.52240.301658
33-0.006452-0.04960.480321
34-0.090081-0.69190.245849
350.0036320.02790.48892
36-0.179336-1.37750.08678

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.168483 & 1.2941 & 0.100329 \tabularnewline
2 & 0.226221 & 1.7376 & 0.043746 \tabularnewline
3 & -0.558123 & -4.287 & 3.4e-05 \tabularnewline
4 & -0.054055 & -0.4152 & 0.339748 \tabularnewline
5 & 0.148254 & 1.1388 & 0.129702 \tabularnewline
6 & -0.050439 & -0.3874 & 0.349916 \tabularnewline
7 & -0.013258 & -0.1018 & 0.459617 \tabularnewline
8 & 0.144778 & 1.1121 & 0.135311 \tabularnewline
9 & 0.04456 & 0.3423 & 0.366681 \tabularnewline
10 & -0.19545 & -1.5013 & 0.069308 \tabularnewline
11 & -0.181451 & -1.3938 & 0.08431 \tabularnewline
12 & -0.072745 & -0.5588 & 0.289219 \tabularnewline
13 & -0.202359 & -1.5543 & 0.062725 \tabularnewline
14 & -0.185479 & -1.4247 & 0.079758 \tabularnewline
15 & -0.026771 & -0.2056 & 0.418893 \tabularnewline
16 & -0.068146 & -0.5234 & 0.301314 \tabularnewline
17 & -0.134838 & -1.0357 & 0.152282 \tabularnewline
18 & -0.107613 & -0.8266 & 0.2059 \tabularnewline
19 & 0.206927 & 1.5894 & 0.058653 \tabularnewline
20 & -0.047012 & -0.3611 & 0.359655 \tabularnewline
21 & 0.042014 & 0.3227 & 0.374024 \tabularnewline
22 & -0.119288 & -0.9163 & 0.181628 \tabularnewline
23 & 0.011952 & 0.0918 & 0.463583 \tabularnewline
24 & -0.027243 & -0.2093 & 0.417483 \tabularnewline
25 & -0.055134 & -0.4235 & 0.336739 \tabularnewline
26 & 0.01075 & 0.0826 & 0.467236 \tabularnewline
27 & -0.039223 & -0.3013 & 0.38213 \tabularnewline
28 & 0.023552 & 0.1809 & 0.42853 \tabularnewline
29 & 0.08155 & 0.6264 & 0.266736 \tabularnewline
30 & -0.102262 & -0.7855 & 0.217655 \tabularnewline
31 & -0.157551 & -1.2102 & 0.11552 \tabularnewline
32 & 0.068017 & 0.5224 & 0.301658 \tabularnewline
33 & -0.006452 & -0.0496 & 0.480321 \tabularnewline
34 & -0.090081 & -0.6919 & 0.245849 \tabularnewline
35 & 0.003632 & 0.0279 & 0.48892 \tabularnewline
36 & -0.179336 & -1.3775 & 0.08678 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69665&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]0.168483[/C][C]1.2941[/C][C]0.100329[/C][/ROW]
[ROW][C]2[/C][C]0.226221[/C][C]1.7376[/C][C]0.043746[/C][/ROW]
[ROW][C]3[/C][C]-0.558123[/C][C]-4.287[/C][C]3.4e-05[/C][/ROW]
[ROW][C]4[/C][C]-0.054055[/C][C]-0.4152[/C][C]0.339748[/C][/ROW]
[ROW][C]5[/C][C]0.148254[/C][C]1.1388[/C][C]0.129702[/C][/ROW]
[ROW][C]6[/C][C]-0.050439[/C][C]-0.3874[/C][C]0.349916[/C][/ROW]
[ROW][C]7[/C][C]-0.013258[/C][C]-0.1018[/C][C]0.459617[/C][/ROW]
[ROW][C]8[/C][C]0.144778[/C][C]1.1121[/C][C]0.135311[/C][/ROW]
[ROW][C]9[/C][C]0.04456[/C][C]0.3423[/C][C]0.366681[/C][/ROW]
[ROW][C]10[/C][C]-0.19545[/C][C]-1.5013[/C][C]0.069308[/C][/ROW]
[ROW][C]11[/C][C]-0.181451[/C][C]-1.3938[/C][C]0.08431[/C][/ROW]
[ROW][C]12[/C][C]-0.072745[/C][C]-0.5588[/C][C]0.289219[/C][/ROW]
[ROW][C]13[/C][C]-0.202359[/C][C]-1.5543[/C][C]0.062725[/C][/ROW]
[ROW][C]14[/C][C]-0.185479[/C][C]-1.4247[/C][C]0.079758[/C][/ROW]
[ROW][C]15[/C][C]-0.026771[/C][C]-0.2056[/C][C]0.418893[/C][/ROW]
[ROW][C]16[/C][C]-0.068146[/C][C]-0.5234[/C][C]0.301314[/C][/ROW]
[ROW][C]17[/C][C]-0.134838[/C][C]-1.0357[/C][C]0.152282[/C][/ROW]
[ROW][C]18[/C][C]-0.107613[/C][C]-0.8266[/C][C]0.2059[/C][/ROW]
[ROW][C]19[/C][C]0.206927[/C][C]1.5894[/C][C]0.058653[/C][/ROW]
[ROW][C]20[/C][C]-0.047012[/C][C]-0.3611[/C][C]0.359655[/C][/ROW]
[ROW][C]21[/C][C]0.042014[/C][C]0.3227[/C][C]0.374024[/C][/ROW]
[ROW][C]22[/C][C]-0.119288[/C][C]-0.9163[/C][C]0.181628[/C][/ROW]
[ROW][C]23[/C][C]0.011952[/C][C]0.0918[/C][C]0.463583[/C][/ROW]
[ROW][C]24[/C][C]-0.027243[/C][C]-0.2093[/C][C]0.417483[/C][/ROW]
[ROW][C]25[/C][C]-0.055134[/C][C]-0.4235[/C][C]0.336739[/C][/ROW]
[ROW][C]26[/C][C]0.01075[/C][C]0.0826[/C][C]0.467236[/C][/ROW]
[ROW][C]27[/C][C]-0.039223[/C][C]-0.3013[/C][C]0.38213[/C][/ROW]
[ROW][C]28[/C][C]0.023552[/C][C]0.1809[/C][C]0.42853[/C][/ROW]
[ROW][C]29[/C][C]0.08155[/C][C]0.6264[/C][C]0.266736[/C][/ROW]
[ROW][C]30[/C][C]-0.102262[/C][C]-0.7855[/C][C]0.217655[/C][/ROW]
[ROW][C]31[/C][C]-0.157551[/C][C]-1.2102[/C][C]0.11552[/C][/ROW]
[ROW][C]32[/C][C]0.068017[/C][C]0.5224[/C][C]0.301658[/C][/ROW]
[ROW][C]33[/C][C]-0.006452[/C][C]-0.0496[/C][C]0.480321[/C][/ROW]
[ROW][C]34[/C][C]-0.090081[/C][C]-0.6919[/C][C]0.245849[/C][/ROW]
[ROW][C]35[/C][C]0.003632[/C][C]0.0279[/C][C]0.48892[/C][/ROW]
[ROW][C]36[/C][C]-0.179336[/C][C]-1.3775[/C][C]0.08678[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69665&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69665&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
10.1684831.29410.100329
20.2262211.73760.043746
3-0.558123-4.2873.4e-05
4-0.054055-0.41520.339748
50.1482541.13880.129702
6-0.050439-0.38740.349916
7-0.013258-0.10180.459617
80.1447781.11210.135311
90.044560.34230.366681
10-0.19545-1.50130.069308
11-0.181451-1.39380.08431
12-0.072745-0.55880.289219
13-0.202359-1.55430.062725
14-0.185479-1.42470.079758
15-0.026771-0.20560.418893
16-0.068146-0.52340.301314
17-0.134838-1.03570.152282
18-0.107613-0.82660.2059
190.2069271.58940.058653
20-0.047012-0.36110.359655
210.0420140.32270.374024
22-0.119288-0.91630.181628
230.0119520.09180.463583
24-0.027243-0.20930.417483
25-0.055134-0.42350.336739
260.010750.08260.467236
27-0.039223-0.30130.38213
280.0235520.18090.42853
290.081550.62640.266736
30-0.102262-0.78550.217655
31-0.157551-1.21020.11552
320.0680170.52240.301658
33-0.006452-0.04960.480321
34-0.090081-0.69190.245849
350.0036320.02790.48892
36-0.179336-1.37750.08678


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')