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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 computationWed, 02 Dec 2009 12:34:54 -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/t1259782679haraw15umnu8jzt.htm/, Retrieved Sat, 27 Apr 2024 23:11:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62547, Retrieved Sat, 27 Apr 2024 23:11:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact131

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       [Standard Deviation-Mean Plot] [Identifying Integ...] [2009-11-22 12:50:05] [b98453cac15ba1066b407e146608df68]
- R PD        [Standard Deviation-Mean Plot] [SMP] [2009-11-25 20:48:16] [1f74ef2f756548f1f3a7b6136ea56d7f]
- RMPD            [(Partial) Autocorrelation Function] [SMP] [2009-12-02 19:34:54] [026d431dc78a3ce53a040b5408fc0322] [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=62547&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=62547&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62547&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
1-0.582351-3.99240.000114
2-0.074623-0.51160.305668
30.4424963.03360.001964
4-0.373511-2.56070.00686
50.1066790.73140.234097
60.1460251.00110.160954
7-0.247533-1.6970.048155
80.1746211.19710.118628
9-0.002726-0.01870.492585
10-0.153653-1.05340.148774
110.1947281.3350.094156
12-0.102912-0.70550.241982
13-0.119511-0.81930.208368
140.1990571.36470.089428
15-0.089502-0.61360.27122
16-0.054336-0.37250.355593
170.0698210.47870.317197
18-0.00367-0.02520.490017
19-0.068572-0.47010.320227
200.0802810.55040.292334
21-0.012225-0.08380.466781
22-0.112391-0.77050.222426
230.1814971.24430.109783
24-0.128467-0.88070.191475
250.0177960.1220.451708
260.0505510.34660.365234
27-0.008456-0.0580.477008
28-0.101408-0.69520.245171
290.0985640.67570.251265
300.0241860.16580.43451
31-0.105399-0.72260.23676
320.0682330.46780.321052
330.0386640.26510.39606
34-0.110035-0.75440.227197
350.1171390.80310.21299
36-0.077739-0.5330.298289

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.582351 & -3.9924 & 0.000114 \tabularnewline
2 & -0.074623 & -0.5116 & 0.305668 \tabularnewline
3 & 0.442496 & 3.0336 & 0.001964 \tabularnewline
4 & -0.373511 & -2.5607 & 0.00686 \tabularnewline
5 & 0.106679 & 0.7314 & 0.234097 \tabularnewline
6 & 0.146025 & 1.0011 & 0.160954 \tabularnewline
7 & -0.247533 & -1.697 & 0.048155 \tabularnewline
8 & 0.174621 & 1.1971 & 0.118628 \tabularnewline
9 & -0.002726 & -0.0187 & 0.492585 \tabularnewline
10 & -0.153653 & -1.0534 & 0.148774 \tabularnewline
11 & 0.194728 & 1.335 & 0.094156 \tabularnewline
12 & -0.102912 & -0.7055 & 0.241982 \tabularnewline
13 & -0.119511 & -0.8193 & 0.208368 \tabularnewline
14 & 0.199057 & 1.3647 & 0.089428 \tabularnewline
15 & -0.089502 & -0.6136 & 0.27122 \tabularnewline
16 & -0.054336 & -0.3725 & 0.355593 \tabularnewline
17 & 0.069821 & 0.4787 & 0.317197 \tabularnewline
18 & -0.00367 & -0.0252 & 0.490017 \tabularnewline
19 & -0.068572 & -0.4701 & 0.320227 \tabularnewline
20 & 0.080281 & 0.5504 & 0.292334 \tabularnewline
21 & -0.012225 & -0.0838 & 0.466781 \tabularnewline
22 & -0.112391 & -0.7705 & 0.222426 \tabularnewline
23 & 0.181497 & 1.2443 & 0.109783 \tabularnewline
24 & -0.128467 & -0.8807 & 0.191475 \tabularnewline
25 & 0.017796 & 0.122 & 0.451708 \tabularnewline
26 & 0.050551 & 0.3466 & 0.365234 \tabularnewline
27 & -0.008456 & -0.058 & 0.477008 \tabularnewline
28 & -0.101408 & -0.6952 & 0.245171 \tabularnewline
29 & 0.098564 & 0.6757 & 0.251265 \tabularnewline
30 & 0.024186 & 0.1658 & 0.43451 \tabularnewline
31 & -0.105399 & -0.7226 & 0.23676 \tabularnewline
32 & 0.068233 & 0.4678 & 0.321052 \tabularnewline
33 & 0.038664 & 0.2651 & 0.39606 \tabularnewline
34 & -0.110035 & -0.7544 & 0.227197 \tabularnewline
35 & 0.117139 & 0.8031 & 0.21299 \tabularnewline
36 & -0.077739 & -0.533 & 0.298289 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62547&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]-0.582351[/C][C]-3.9924[/C][C]0.000114[/C][/ROW]
[ROW][C]2[/C][C]-0.074623[/C][C]-0.5116[/C][C]0.305668[/C][/ROW]
[ROW][C]3[/C][C]0.442496[/C][C]3.0336[/C][C]0.001964[/C][/ROW]
[ROW][C]4[/C][C]-0.373511[/C][C]-2.5607[/C][C]0.00686[/C][/ROW]
[ROW][C]5[/C][C]0.106679[/C][C]0.7314[/C][C]0.234097[/C][/ROW]
[ROW][C]6[/C][C]0.146025[/C][C]1.0011[/C][C]0.160954[/C][/ROW]
[ROW][C]7[/C][C]-0.247533[/C][C]-1.697[/C][C]0.048155[/C][/ROW]
[ROW][C]8[/C][C]0.174621[/C][C]1.1971[/C][C]0.118628[/C][/ROW]
[ROW][C]9[/C][C]-0.002726[/C][C]-0.0187[/C][C]0.492585[/C][/ROW]
[ROW][C]10[/C][C]-0.153653[/C][C]-1.0534[/C][C]0.148774[/C][/ROW]
[ROW][C]11[/C][C]0.194728[/C][C]1.335[/C][C]0.094156[/C][/ROW]
[ROW][C]12[/C][C]-0.102912[/C][C]-0.7055[/C][C]0.241982[/C][/ROW]
[ROW][C]13[/C][C]-0.119511[/C][C]-0.8193[/C][C]0.208368[/C][/ROW]
[ROW][C]14[/C][C]0.199057[/C][C]1.3647[/C][C]0.089428[/C][/ROW]
[ROW][C]15[/C][C]-0.089502[/C][C]-0.6136[/C][C]0.27122[/C][/ROW]
[ROW][C]16[/C][C]-0.054336[/C][C]-0.3725[/C][C]0.355593[/C][/ROW]
[ROW][C]17[/C][C]0.069821[/C][C]0.4787[/C][C]0.317197[/C][/ROW]
[ROW][C]18[/C][C]-0.00367[/C][C]-0.0252[/C][C]0.490017[/C][/ROW]
[ROW][C]19[/C][C]-0.068572[/C][C]-0.4701[/C][C]0.320227[/C][/ROW]
[ROW][C]20[/C][C]0.080281[/C][C]0.5504[/C][C]0.292334[/C][/ROW]
[ROW][C]21[/C][C]-0.012225[/C][C]-0.0838[/C][C]0.466781[/C][/ROW]
[ROW][C]22[/C][C]-0.112391[/C][C]-0.7705[/C][C]0.222426[/C][/ROW]
[ROW][C]23[/C][C]0.181497[/C][C]1.2443[/C][C]0.109783[/C][/ROW]
[ROW][C]24[/C][C]-0.128467[/C][C]-0.8807[/C][C]0.191475[/C][/ROW]
[ROW][C]25[/C][C]0.017796[/C][C]0.122[/C][C]0.451708[/C][/ROW]
[ROW][C]26[/C][C]0.050551[/C][C]0.3466[/C][C]0.365234[/C][/ROW]
[ROW][C]27[/C][C]-0.008456[/C][C]-0.058[/C][C]0.477008[/C][/ROW]
[ROW][C]28[/C][C]-0.101408[/C][C]-0.6952[/C][C]0.245171[/C][/ROW]
[ROW][C]29[/C][C]0.098564[/C][C]0.6757[/C][C]0.251265[/C][/ROW]
[ROW][C]30[/C][C]0.024186[/C][C]0.1658[/C][C]0.43451[/C][/ROW]
[ROW][C]31[/C][C]-0.105399[/C][C]-0.7226[/C][C]0.23676[/C][/ROW]
[ROW][C]32[/C][C]0.068233[/C][C]0.4678[/C][C]0.321052[/C][/ROW]
[ROW][C]33[/C][C]0.038664[/C][C]0.2651[/C][C]0.39606[/C][/ROW]
[ROW][C]34[/C][C]-0.110035[/C][C]-0.7544[/C][C]0.227197[/C][/ROW]
[ROW][C]35[/C][C]0.117139[/C][C]0.8031[/C][C]0.21299[/C][/ROW]
[ROW][C]36[/C][C]-0.077739[/C][C]-0.533[/C][C]0.298289[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62547&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62547&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
1-0.582351-3.99240.000114
2-0.074623-0.51160.305668
30.4424963.03360.001964
4-0.373511-2.56070.00686
50.1066790.73140.234097
60.1460251.00110.160954
7-0.247533-1.6970.048155
80.1746211.19710.118628
9-0.002726-0.01870.492585
10-0.153653-1.05340.148774
110.1947281.3350.094156
12-0.102912-0.70550.241982
13-0.119511-0.81930.208368
140.1990571.36470.089428
15-0.089502-0.61360.27122
16-0.054336-0.37250.355593
170.0698210.47870.317197
18-0.00367-0.02520.490017
19-0.068572-0.47010.320227
200.0802810.55040.292334
21-0.012225-0.08380.466781
22-0.112391-0.77050.222426
230.1814971.24430.109783
24-0.128467-0.88070.191475
250.0177960.1220.451708
260.0505510.34660.365234
27-0.008456-0.0580.477008
28-0.101408-0.69520.245171
290.0985640.67570.251265
300.0241860.16580.43451
31-0.105399-0.72260.23676
320.0682330.46780.321052
330.0386640.26510.39606
34-0.110035-0.75440.227197
350.1171390.80310.21299
36-0.077739-0.5330.298289






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.582351-3.99240.000114
2-0.62608-4.29224.4e-05
30.0180030.12340.451149
40.0138390.09490.462408
50.0827480.56730.286608
60.100320.68780.247493
7-0.031958-0.21910.413764
8-0.009218-0.06320.47494
90.0145960.10010.460359
10-0.059885-0.41060.341634
110.0206060.14130.444132
120.0080420.05510.478133
13-0.199568-1.36820.088883
14-0.201764-1.38320.086566
15-0.033301-0.22830.410202
160.0850230.58290.281379
17-0.037144-0.25460.400054
180.0169810.11640.45391
19-0.065349-0.4480.328101
20-0.018262-0.12520.450451
210.0678340.4650.322023
22-0.098481-0.67520.251444
230.0195290.13390.447034
24-0.038379-0.26310.396808
250.013880.09520.462298
26-0.132499-0.90840.184159
270.1222190.83790.203166
28-0.077605-0.5320.298603
29-0.164703-1.12910.132284
30-0.030214-0.20710.4184
310.069840.47880.317151
320.0038270.02620.489591
330.075290.51620.304081
34-0.045875-0.31450.377266
350.002450.01680.493336
36-0.046289-0.31730.376194

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.582351 & -3.9924 & 0.000114 \tabularnewline
2 & -0.62608 & -4.2922 & 4.4e-05 \tabularnewline
3 & 0.018003 & 0.1234 & 0.451149 \tabularnewline
4 & 0.013839 & 0.0949 & 0.462408 \tabularnewline
5 & 0.082748 & 0.5673 & 0.286608 \tabularnewline
6 & 0.10032 & 0.6878 & 0.247493 \tabularnewline
7 & -0.031958 & -0.2191 & 0.413764 \tabularnewline
8 & -0.009218 & -0.0632 & 0.47494 \tabularnewline
9 & 0.014596 & 0.1001 & 0.460359 \tabularnewline
10 & -0.059885 & -0.4106 & 0.341634 \tabularnewline
11 & 0.020606 & 0.1413 & 0.444132 \tabularnewline
12 & 0.008042 & 0.0551 & 0.478133 \tabularnewline
13 & -0.199568 & -1.3682 & 0.088883 \tabularnewline
14 & -0.201764 & -1.3832 & 0.086566 \tabularnewline
15 & -0.033301 & -0.2283 & 0.410202 \tabularnewline
16 & 0.085023 & 0.5829 & 0.281379 \tabularnewline
17 & -0.037144 & -0.2546 & 0.400054 \tabularnewline
18 & 0.016981 & 0.1164 & 0.45391 \tabularnewline
19 & -0.065349 & -0.448 & 0.328101 \tabularnewline
20 & -0.018262 & -0.1252 & 0.450451 \tabularnewline
21 & 0.067834 & 0.465 & 0.322023 \tabularnewline
22 & -0.098481 & -0.6752 & 0.251444 \tabularnewline
23 & 0.019529 & 0.1339 & 0.447034 \tabularnewline
24 & -0.038379 & -0.2631 & 0.396808 \tabularnewline
25 & 0.01388 & 0.0952 & 0.462298 \tabularnewline
26 & -0.132499 & -0.9084 & 0.184159 \tabularnewline
27 & 0.122219 & 0.8379 & 0.203166 \tabularnewline
28 & -0.077605 & -0.532 & 0.298603 \tabularnewline
29 & -0.164703 & -1.1291 & 0.132284 \tabularnewline
30 & -0.030214 & -0.2071 & 0.4184 \tabularnewline
31 & 0.06984 & 0.4788 & 0.317151 \tabularnewline
32 & 0.003827 & 0.0262 & 0.489591 \tabularnewline
33 & 0.07529 & 0.5162 & 0.304081 \tabularnewline
34 & -0.045875 & -0.3145 & 0.377266 \tabularnewline
35 & 0.00245 & 0.0168 & 0.493336 \tabularnewline
36 & -0.046289 & -0.3173 & 0.376194 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62547&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]-0.582351[/C][C]-3.9924[/C][C]0.000114[/C][/ROW]
[ROW][C]2[/C][C]-0.62608[/C][C]-4.2922[/C][C]4.4e-05[/C][/ROW]
[ROW][C]3[/C][C]0.018003[/C][C]0.1234[/C][C]0.451149[/C][/ROW]
[ROW][C]4[/C][C]0.013839[/C][C]0.0949[/C][C]0.462408[/C][/ROW]
[ROW][C]5[/C][C]0.082748[/C][C]0.5673[/C][C]0.286608[/C][/ROW]
[ROW][C]6[/C][C]0.10032[/C][C]0.6878[/C][C]0.247493[/C][/ROW]
[ROW][C]7[/C][C]-0.031958[/C][C]-0.2191[/C][C]0.413764[/C][/ROW]
[ROW][C]8[/C][C]-0.009218[/C][C]-0.0632[/C][C]0.47494[/C][/ROW]
[ROW][C]9[/C][C]0.014596[/C][C]0.1001[/C][C]0.460359[/C][/ROW]
[ROW][C]10[/C][C]-0.059885[/C][C]-0.4106[/C][C]0.341634[/C][/ROW]
[ROW][C]11[/C][C]0.020606[/C][C]0.1413[/C][C]0.444132[/C][/ROW]
[ROW][C]12[/C][C]0.008042[/C][C]0.0551[/C][C]0.478133[/C][/ROW]
[ROW][C]13[/C][C]-0.199568[/C][C]-1.3682[/C][C]0.088883[/C][/ROW]
[ROW][C]14[/C][C]-0.201764[/C][C]-1.3832[/C][C]0.086566[/C][/ROW]
[ROW][C]15[/C][C]-0.033301[/C][C]-0.2283[/C][C]0.410202[/C][/ROW]
[ROW][C]16[/C][C]0.085023[/C][C]0.5829[/C][C]0.281379[/C][/ROW]
[ROW][C]17[/C][C]-0.037144[/C][C]-0.2546[/C][C]0.400054[/C][/ROW]
[ROW][C]18[/C][C]0.016981[/C][C]0.1164[/C][C]0.45391[/C][/ROW]
[ROW][C]19[/C][C]-0.065349[/C][C]-0.448[/C][C]0.328101[/C][/ROW]
[ROW][C]20[/C][C]-0.018262[/C][C]-0.1252[/C][C]0.450451[/C][/ROW]
[ROW][C]21[/C][C]0.067834[/C][C]0.465[/C][C]0.322023[/C][/ROW]
[ROW][C]22[/C][C]-0.098481[/C][C]-0.6752[/C][C]0.251444[/C][/ROW]
[ROW][C]23[/C][C]0.019529[/C][C]0.1339[/C][C]0.447034[/C][/ROW]
[ROW][C]24[/C][C]-0.038379[/C][C]-0.2631[/C][C]0.396808[/C][/ROW]
[ROW][C]25[/C][C]0.01388[/C][C]0.0952[/C][C]0.462298[/C][/ROW]
[ROW][C]26[/C][C]-0.132499[/C][C]-0.9084[/C][C]0.184159[/C][/ROW]
[ROW][C]27[/C][C]0.122219[/C][C]0.8379[/C][C]0.203166[/C][/ROW]
[ROW][C]28[/C][C]-0.077605[/C][C]-0.532[/C][C]0.298603[/C][/ROW]
[ROW][C]29[/C][C]-0.164703[/C][C]-1.1291[/C][C]0.132284[/C][/ROW]
[ROW][C]30[/C][C]-0.030214[/C][C]-0.2071[/C][C]0.4184[/C][/ROW]
[ROW][C]31[/C][C]0.06984[/C][C]0.4788[/C][C]0.317151[/C][/ROW]
[ROW][C]32[/C][C]0.003827[/C][C]0.0262[/C][C]0.489591[/C][/ROW]
[ROW][C]33[/C][C]0.07529[/C][C]0.5162[/C][C]0.304081[/C][/ROW]
[ROW][C]34[/C][C]-0.045875[/C][C]-0.3145[/C][C]0.377266[/C][/ROW]
[ROW][C]35[/C][C]0.00245[/C][C]0.0168[/C][C]0.493336[/C][/ROW]
[ROW][C]36[/C][C]-0.046289[/C][C]-0.3173[/C][C]0.376194[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62547&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62547&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
1-0.582351-3.99240.000114
2-0.62608-4.29224.4e-05
30.0180030.12340.451149
40.0138390.09490.462408
50.0827480.56730.286608
60.100320.68780.247493
7-0.031958-0.21910.413764
8-0.009218-0.06320.47494
90.0145960.10010.460359
10-0.059885-0.41060.341634
110.0206060.14130.444132
120.0080420.05510.478133
13-0.199568-1.36820.088883
14-0.201764-1.38320.086566
15-0.033301-0.22830.410202
160.0850230.58290.281379
17-0.037144-0.25460.400054
180.0169810.11640.45391
19-0.065349-0.4480.328101
20-0.018262-0.12520.450451
210.0678340.4650.322023
22-0.098481-0.67520.251444
230.0195290.13390.447034
24-0.038379-0.26310.396808
250.013880.09520.462298
26-0.132499-0.90840.184159
270.1222190.83790.203166
28-0.077605-0.5320.298603
29-0.164703-1.12910.132284
30-0.030214-0.20710.4184
310.069840.47880.317151
320.0038270.02620.489591
330.075290.51620.304081
34-0.045875-0.31450.377266
350.002450.01680.493336
36-0.046289-0.31730.376194


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 = 0.4 ; par3 = 1 ; par4 = 1 ; 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')