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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 09:39:41 -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/t1259944847anugib9ff9bqw3j.htm/, Retrieved Sat, 27 Apr 2024 17:02:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63880, Retrieved Sat, 27 Apr 2024 17:02:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact103

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [] [2009-11-27 14:47:30] [b98453cac15ba1066b407e146608df68]
-    D    [(Partial) Autocorrelation Function] [Stap 4 Workshop 5] [2009-12-04 12:46:55] [76ab39dc7a55316678260825bd5ad46c]
-    D        [(Partial) Autocorrelation Function] [stap 4] [2009-12-04 16:39:41] [986e3c28a4248c495afaef9fd432264f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
91.98
91.72
90.27
91.89
92.07
92.92
93.34
93.60
92.41
93.60
93.77
93.60
93.60
93.51
92.66
94.20
94.37
94.45
94.62
94.37
93.43
94.79
94.88
94.79
94.62
94.71
93.77
95.73
95.99
95.82
95.47
95.82
94.71
96.33
96.50
96.16
96.33
96.33
95.05
96.84
96.92
97.44
97.78
97.69
96.67
98.29
98.20
98.71
98.54
98.20
96.92
99.06
99.65
99.82
99.99
100.33
99.31
101.10
101.10
100.93
100.85
100.93
99.60
101.88
101.81
102.38
102.74
102.82
101.72
103.47
102.98
102.68
102.90
103.03
101.29
103.69
103.68
104.20
104.08
104.16
103.05
104.66
104.46
104.95
105.85
106.23
104.86
107.44
108.23
108.45
109.39
110.15
109.13
110.28
110.17
109.99
109.26
109.11
107.06
109.53
108.92
109.24
109.12
109.00
107.23
109.49
109.04
109.02

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=63880&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=63880&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63880&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
1-0.432834-4.47739e-06
20.0427510.44220.329612
3-0.017168-0.17760.42969
40.0303160.31360.377219
5-0.425619-4.40261.3e-05
60.798028.25480
7-0.427778-4.4251.2e-05
80.0063430.06560.473903
9-0.024471-0.25310.400326
100.0091920.09510.462212
11-0.352232-3.64350.000208
120.7492447.75020
13-0.409192-4.23272.4e-05
140.0008490.00880.496507
15-0.003145-0.03250.487053
16-0.007637-0.0790.468591
17-0.378585-3.91617.9e-05
180.7089267.33320
19-0.383275-3.96466.7e-05
20-0.00049-0.00510.497983
21-0.014709-0.15220.439676
220.0429720.44450.328789
23-0.350992-3.63070.000218
240.6969597.20940
25-0.338901-3.50560.000333
260.026940.27870.390517
27-0.021633-0.22380.411682
280.012070.12490.450437
29-0.328693-3.40.000474
300.6247726.46270
31-0.3378-3.49420.000346
320.019480.20150.420344
33-0.004669-0.04830.480786
340.0039230.04060.483855
35-0.287283-2.97170.001829
360.6013996.22090

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.432834 & -4.4773 & 9e-06 \tabularnewline
2 & 0.042751 & 0.4422 & 0.329612 \tabularnewline
3 & -0.017168 & -0.1776 & 0.42969 \tabularnewline
4 & 0.030316 & 0.3136 & 0.377219 \tabularnewline
5 & -0.425619 & -4.4026 & 1.3e-05 \tabularnewline
6 & 0.79802 & 8.2548 & 0 \tabularnewline
7 & -0.427778 & -4.425 & 1.2e-05 \tabularnewline
8 & 0.006343 & 0.0656 & 0.473903 \tabularnewline
9 & -0.024471 & -0.2531 & 0.400326 \tabularnewline
10 & 0.009192 & 0.0951 & 0.462212 \tabularnewline
11 & -0.352232 & -3.6435 & 0.000208 \tabularnewline
12 & 0.749244 & 7.7502 & 0 \tabularnewline
13 & -0.409192 & -4.2327 & 2.4e-05 \tabularnewline
14 & 0.000849 & 0.0088 & 0.496507 \tabularnewline
15 & -0.003145 & -0.0325 & 0.487053 \tabularnewline
16 & -0.007637 & -0.079 & 0.468591 \tabularnewline
17 & -0.378585 & -3.9161 & 7.9e-05 \tabularnewline
18 & 0.708926 & 7.3332 & 0 \tabularnewline
19 & -0.383275 & -3.9646 & 6.7e-05 \tabularnewline
20 & -0.00049 & -0.0051 & 0.497983 \tabularnewline
21 & -0.014709 & -0.1522 & 0.439676 \tabularnewline
22 & 0.042972 & 0.4445 & 0.328789 \tabularnewline
23 & -0.350992 & -3.6307 & 0.000218 \tabularnewline
24 & 0.696959 & 7.2094 & 0 \tabularnewline
25 & -0.338901 & -3.5056 & 0.000333 \tabularnewline
26 & 0.02694 & 0.2787 & 0.390517 \tabularnewline
27 & -0.021633 & -0.2238 & 0.411682 \tabularnewline
28 & 0.01207 & 0.1249 & 0.450437 \tabularnewline
29 & -0.328693 & -3.4 & 0.000474 \tabularnewline
30 & 0.624772 & 6.4627 & 0 \tabularnewline
31 & -0.3378 & -3.4942 & 0.000346 \tabularnewline
32 & 0.01948 & 0.2015 & 0.420344 \tabularnewline
33 & -0.004669 & -0.0483 & 0.480786 \tabularnewline
34 & 0.003923 & 0.0406 & 0.483855 \tabularnewline
35 & -0.287283 & -2.9717 & 0.001829 \tabularnewline
36 & 0.601399 & 6.2209 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63880&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]-0.432834[/C][C]-4.4773[/C][C]9e-06[/C][/ROW]
[ROW][C]2[/C][C]0.042751[/C][C]0.4422[/C][C]0.329612[/C][/ROW]
[ROW][C]3[/C][C]-0.017168[/C][C]-0.1776[/C][C]0.42969[/C][/ROW]
[ROW][C]4[/C][C]0.030316[/C][C]0.3136[/C][C]0.377219[/C][/ROW]
[ROW][C]5[/C][C]-0.425619[/C][C]-4.4026[/C][C]1.3e-05[/C][/ROW]
[ROW][C]6[/C][C]0.79802[/C][C]8.2548[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]-0.427778[/C][C]-4.425[/C][C]1.2e-05[/C][/ROW]
[ROW][C]8[/C][C]0.006343[/C][C]0.0656[/C][C]0.473903[/C][/ROW]
[ROW][C]9[/C][C]-0.024471[/C][C]-0.2531[/C][C]0.400326[/C][/ROW]
[ROW][C]10[/C][C]0.009192[/C][C]0.0951[/C][C]0.462212[/C][/ROW]
[ROW][C]11[/C][C]-0.352232[/C][C]-3.6435[/C][C]0.000208[/C][/ROW]
[ROW][C]12[/C][C]0.749244[/C][C]7.7502[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.409192[/C][C]-4.2327[/C][C]2.4e-05[/C][/ROW]
[ROW][C]14[/C][C]0.000849[/C][C]0.0088[/C][C]0.496507[/C][/ROW]
[ROW][C]15[/C][C]-0.003145[/C][C]-0.0325[/C][C]0.487053[/C][/ROW]
[ROW][C]16[/C][C]-0.007637[/C][C]-0.079[/C][C]0.468591[/C][/ROW]
[ROW][C]17[/C][C]-0.378585[/C][C]-3.9161[/C][C]7.9e-05[/C][/ROW]
[ROW][C]18[/C][C]0.708926[/C][C]7.3332[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]-0.383275[/C][C]-3.9646[/C][C]6.7e-05[/C][/ROW]
[ROW][C]20[/C][C]-0.00049[/C][C]-0.0051[/C][C]0.497983[/C][/ROW]
[ROW][C]21[/C][C]-0.014709[/C][C]-0.1522[/C][C]0.439676[/C][/ROW]
[ROW][C]22[/C][C]0.042972[/C][C]0.4445[/C][C]0.328789[/C][/ROW]
[ROW][C]23[/C][C]-0.350992[/C][C]-3.6307[/C][C]0.000218[/C][/ROW]
[ROW][C]24[/C][C]0.696959[/C][C]7.2094[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]-0.338901[/C][C]-3.5056[/C][C]0.000333[/C][/ROW]
[ROW][C]26[/C][C]0.02694[/C][C]0.2787[/C][C]0.390517[/C][/ROW]
[ROW][C]27[/C][C]-0.021633[/C][C]-0.2238[/C][C]0.411682[/C][/ROW]
[ROW][C]28[/C][C]0.01207[/C][C]0.1249[/C][C]0.450437[/C][/ROW]
[ROW][C]29[/C][C]-0.328693[/C][C]-3.4[/C][C]0.000474[/C][/ROW]
[ROW][C]30[/C][C]0.624772[/C][C]6.4627[/C][C]0[/C][/ROW]
[ROW][C]31[/C][C]-0.3378[/C][C]-3.4942[/C][C]0.000346[/C][/ROW]
[ROW][C]32[/C][C]0.01948[/C][C]0.2015[/C][C]0.420344[/C][/ROW]
[ROW][C]33[/C][C]-0.004669[/C][C]-0.0483[/C][C]0.480786[/C][/ROW]
[ROW][C]34[/C][C]0.003923[/C][C]0.0406[/C][C]0.483855[/C][/ROW]
[ROW][C]35[/C][C]-0.287283[/C][C]-2.9717[/C][C]0.001829[/C][/ROW]
[ROW][C]36[/C][C]0.601399[/C][C]6.2209[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63880&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63880&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
1-0.432834-4.47739e-06
20.0427510.44220.329612
3-0.017168-0.17760.42969
40.0303160.31360.377219
5-0.425619-4.40261.3e-05
60.798028.25480
7-0.427778-4.4251.2e-05
80.0063430.06560.473903
9-0.024471-0.25310.400326
100.0091920.09510.462212
11-0.352232-3.64350.000208
120.7492447.75020
13-0.409192-4.23272.4e-05
140.0008490.00880.496507
15-0.003145-0.03250.487053
16-0.007637-0.0790.468591
17-0.378585-3.91617.9e-05
180.7089267.33320
19-0.383275-3.96466.7e-05
20-0.00049-0.00510.497983
21-0.014709-0.15220.439676
220.0429720.44450.328789
23-0.350992-3.63070.000218
240.6969597.20940
25-0.338901-3.50560.000333
260.026940.27870.390517
27-0.021633-0.22380.411682
280.012070.12490.450437
29-0.328693-3.40.000474
300.6247726.46270
31-0.3378-3.49420.000346
320.019480.20150.420344
33-0.004669-0.04830.480786
340.0039230.04060.483855
35-0.287283-2.97170.001829
360.6013996.22090






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.432834-4.47739e-06
2-0.177929-1.84050.034232
3-0.091985-0.95150.171747
4-0.011433-0.11830.453042
5-0.531036-5.49310
60.6397216.61730
7-0.082749-0.8560.196965
8-0.203415-2.10410.018854
9-0.129422-1.33880.091744
10-0.148065-1.53160.064287
110.0264360.27350.392514
120.2570212.65860.004525
13-0.042648-0.44120.329996
14-0.117487-1.21530.113464
15-0.050336-0.52070.301831
16-0.064658-0.66880.252522
17-0.252857-2.61560.005097
180.0210940.21820.413846
190.0409450.42350.336377
20-0.016195-0.16750.433637
21-0.136518-1.41220.080403
220.0188520.1950.42288
23-0.034076-0.35250.362584
240.0687560.71120.239249
250.0946090.97860.164981
260.0519230.53710.296159
27-0.021659-0.2240.411578
28-0.110707-1.14520.127349
290.002460.02540.489872
30-0.094768-0.98030.164577
31-0.056711-0.58660.279347
320.0444030.45930.323471
330.0233130.24110.404951
34-0.059318-0.61360.270395
350.0067460.06980.472251
360.0236630.24480.40355

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.432834 & -4.4773 & 9e-06 \tabularnewline
2 & -0.177929 & -1.8405 & 0.034232 \tabularnewline
3 & -0.091985 & -0.9515 & 0.171747 \tabularnewline
4 & -0.011433 & -0.1183 & 0.453042 \tabularnewline
5 & -0.531036 & -5.4931 & 0 \tabularnewline
6 & 0.639721 & 6.6173 & 0 \tabularnewline
7 & -0.082749 & -0.856 & 0.196965 \tabularnewline
8 & -0.203415 & -2.1041 & 0.018854 \tabularnewline
9 & -0.129422 & -1.3388 & 0.091744 \tabularnewline
10 & -0.148065 & -1.5316 & 0.064287 \tabularnewline
11 & 0.026436 & 0.2735 & 0.392514 \tabularnewline
12 & 0.257021 & 2.6586 & 0.004525 \tabularnewline
13 & -0.042648 & -0.4412 & 0.329996 \tabularnewline
14 & -0.117487 & -1.2153 & 0.113464 \tabularnewline
15 & -0.050336 & -0.5207 & 0.301831 \tabularnewline
16 & -0.064658 & -0.6688 & 0.252522 \tabularnewline
17 & -0.252857 & -2.6156 & 0.005097 \tabularnewline
18 & 0.021094 & 0.2182 & 0.413846 \tabularnewline
19 & 0.040945 & 0.4235 & 0.336377 \tabularnewline
20 & -0.016195 & -0.1675 & 0.433637 \tabularnewline
21 & -0.136518 & -1.4122 & 0.080403 \tabularnewline
22 & 0.018852 & 0.195 & 0.42288 \tabularnewline
23 & -0.034076 & -0.3525 & 0.362584 \tabularnewline
24 & 0.068756 & 0.7112 & 0.239249 \tabularnewline
25 & 0.094609 & 0.9786 & 0.164981 \tabularnewline
26 & 0.051923 & 0.5371 & 0.296159 \tabularnewline
27 & -0.021659 & -0.224 & 0.411578 \tabularnewline
28 & -0.110707 & -1.1452 & 0.127349 \tabularnewline
29 & 0.00246 & 0.0254 & 0.489872 \tabularnewline
30 & -0.094768 & -0.9803 & 0.164577 \tabularnewline
31 & -0.056711 & -0.5866 & 0.279347 \tabularnewline
32 & 0.044403 & 0.4593 & 0.323471 \tabularnewline
33 & 0.023313 & 0.2411 & 0.404951 \tabularnewline
34 & -0.059318 & -0.6136 & 0.270395 \tabularnewline
35 & 0.006746 & 0.0698 & 0.472251 \tabularnewline
36 & 0.023663 & 0.2448 & 0.40355 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63880&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]-0.432834[/C][C]-4.4773[/C][C]9e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.177929[/C][C]-1.8405[/C][C]0.034232[/C][/ROW]
[ROW][C]3[/C][C]-0.091985[/C][C]-0.9515[/C][C]0.171747[/C][/ROW]
[ROW][C]4[/C][C]-0.011433[/C][C]-0.1183[/C][C]0.453042[/C][/ROW]
[ROW][C]5[/C][C]-0.531036[/C][C]-5.4931[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.639721[/C][C]6.6173[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]-0.082749[/C][C]-0.856[/C][C]0.196965[/C][/ROW]
[ROW][C]8[/C][C]-0.203415[/C][C]-2.1041[/C][C]0.018854[/C][/ROW]
[ROW][C]9[/C][C]-0.129422[/C][C]-1.3388[/C][C]0.091744[/C][/ROW]
[ROW][C]10[/C][C]-0.148065[/C][C]-1.5316[/C][C]0.064287[/C][/ROW]
[ROW][C]11[/C][C]0.026436[/C][C]0.2735[/C][C]0.392514[/C][/ROW]
[ROW][C]12[/C][C]0.257021[/C][C]2.6586[/C][C]0.004525[/C][/ROW]
[ROW][C]13[/C][C]-0.042648[/C][C]-0.4412[/C][C]0.329996[/C][/ROW]
[ROW][C]14[/C][C]-0.117487[/C][C]-1.2153[/C][C]0.113464[/C][/ROW]
[ROW][C]15[/C][C]-0.050336[/C][C]-0.5207[/C][C]0.301831[/C][/ROW]
[ROW][C]16[/C][C]-0.064658[/C][C]-0.6688[/C][C]0.252522[/C][/ROW]
[ROW][C]17[/C][C]-0.252857[/C][C]-2.6156[/C][C]0.005097[/C][/ROW]
[ROW][C]18[/C][C]0.021094[/C][C]0.2182[/C][C]0.413846[/C][/ROW]
[ROW][C]19[/C][C]0.040945[/C][C]0.4235[/C][C]0.336377[/C][/ROW]
[ROW][C]20[/C][C]-0.016195[/C][C]-0.1675[/C][C]0.433637[/C][/ROW]
[ROW][C]21[/C][C]-0.136518[/C][C]-1.4122[/C][C]0.080403[/C][/ROW]
[ROW][C]22[/C][C]0.018852[/C][C]0.195[/C][C]0.42288[/C][/ROW]
[ROW][C]23[/C][C]-0.034076[/C][C]-0.3525[/C][C]0.362584[/C][/ROW]
[ROW][C]24[/C][C]0.068756[/C][C]0.7112[/C][C]0.239249[/C][/ROW]
[ROW][C]25[/C][C]0.094609[/C][C]0.9786[/C][C]0.164981[/C][/ROW]
[ROW][C]26[/C][C]0.051923[/C][C]0.5371[/C][C]0.296159[/C][/ROW]
[ROW][C]27[/C][C]-0.021659[/C][C]-0.224[/C][C]0.411578[/C][/ROW]
[ROW][C]28[/C][C]-0.110707[/C][C]-1.1452[/C][C]0.127349[/C][/ROW]
[ROW][C]29[/C][C]0.00246[/C][C]0.0254[/C][C]0.489872[/C][/ROW]
[ROW][C]30[/C][C]-0.094768[/C][C]-0.9803[/C][C]0.164577[/C][/ROW]
[ROW][C]31[/C][C]-0.056711[/C][C]-0.5866[/C][C]0.279347[/C][/ROW]
[ROW][C]32[/C][C]0.044403[/C][C]0.4593[/C][C]0.323471[/C][/ROW]
[ROW][C]33[/C][C]0.023313[/C][C]0.2411[/C][C]0.404951[/C][/ROW]
[ROW][C]34[/C][C]-0.059318[/C][C]-0.6136[/C][C]0.270395[/C][/ROW]
[ROW][C]35[/C][C]0.006746[/C][C]0.0698[/C][C]0.472251[/C][/ROW]
[ROW][C]36[/C][C]0.023663[/C][C]0.2448[/C][C]0.40355[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63880&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63880&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
1-0.432834-4.47739e-06
2-0.177929-1.84050.034232
3-0.091985-0.95150.171747
4-0.011433-0.11830.453042
5-0.531036-5.49310
60.6397216.61730
7-0.082749-0.8560.196965
8-0.203415-2.10410.018854
9-0.129422-1.33880.091744
10-0.148065-1.53160.064287
110.0264360.27350.392514
120.2570212.65860.004525
13-0.042648-0.44120.329996
14-0.117487-1.21530.113464
15-0.050336-0.52070.301831
16-0.064658-0.66880.252522
17-0.252857-2.61560.005097
180.0210940.21820.413846
190.0409450.42350.336377
20-0.016195-0.16750.433637
21-0.136518-1.41220.080403
220.0188520.1950.42288
23-0.034076-0.35250.362584
240.0687560.71120.239249
250.0946090.97860.164981
260.0519230.53710.296159
27-0.021659-0.2240.411578
28-0.110707-1.14520.127349
290.002460.02540.489872
30-0.094768-0.98030.164577
31-0.056711-0.58660.279347
320.0444030.45930.323471
330.0233130.24110.404951
34-0.059318-0.61360.270395
350.0067460.06980.472251
360.0236630.24480.40355


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')