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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 computationMon, 28 Dec 2009 11:59:43 -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/28/t1262026855jq0c7wiyr6qouj0.htm/, Retrieved Sat, 04 May 2024 21:10:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71034, Retrieved Sat, 04 May 2024 21:10:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100

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]
-    D          [(Partial) Autocorrelation Function] [tijdreeksanalyse D] [2009-12-28 18:59:43] [f47dffd5f5a8c03c3681db4cc9472742] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
110.75
110.64
110.46
110.66
110.48
110.5
110.96
111.17
111.07
111.75
111.45
111.24
111.09
111.29
111.15
110.88
111.22
110.62
110.2
109.49
109.32
108.71
107.85
107.44
106.93
106.19
105.71
105.67
105.7
105.28
105.34
105.58
105.23
105.46
104.92
104.68
104.58
104.32
104.36
104.38
104.25
103.93
103.95
103.6
103.23
103.31
102.82
102.76
102.68
102.37
102.54
102.65
102.63
102.22
102.04
101.85
101.88
101.33
100.8

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71034&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]5 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=71034&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71034&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 time5 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9341056.40390
20.8358345.73020
30.7096624.86527e-06
40.5604093.8420.000182
50.3686522.52740.007458
60.1909521.30910.098433
70.0267850.18360.427546
8-0.128461-0.88070.191485
9-0.273366-1.87410.03357
10-0.373577-2.56110.006852
11-0.445499-3.05420.001855
12-0.504884-3.46130.000577
13-0.519704-3.56290.000427
14-0.494625-3.3910.00071
15-0.45262-3.1030.001619
16-0.404738-2.77470.003951
17-0.330911-2.26860.013963
18-0.259858-1.78150.040647
19-0.197529-1.35420.091075
20-0.148719-1.01960.156578
21-0.093127-0.63840.263141
22-0.055133-0.3780.353577
23-0.029671-0.20340.419844
24-0.006543-0.04490.482205
250.0074910.05140.47963
260.0032270.02210.491223
27-0.008151-0.05590.477837
28-0.015151-0.10390.458857
29-0.017508-0.120.452486
30-0.020256-0.13890.445075
31-0.016352-0.11210.455609
320.0017550.0120.495226
330.0177560.12170.451816
340.0355730.24390.404194
350.0522690.35830.360848
360.0644470.44180.33032

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.934105 & 6.4039 & 0 \tabularnewline
2 & 0.835834 & 5.7302 & 0 \tabularnewline
3 & 0.709662 & 4.8652 & 7e-06 \tabularnewline
4 & 0.560409 & 3.842 & 0.000182 \tabularnewline
5 & 0.368652 & 2.5274 & 0.007458 \tabularnewline
6 & 0.190952 & 1.3091 & 0.098433 \tabularnewline
7 & 0.026785 & 0.1836 & 0.427546 \tabularnewline
8 & -0.128461 & -0.8807 & 0.191485 \tabularnewline
9 & -0.273366 & -1.8741 & 0.03357 \tabularnewline
10 & -0.373577 & -2.5611 & 0.006852 \tabularnewline
11 & -0.445499 & -3.0542 & 0.001855 \tabularnewline
12 & -0.504884 & -3.4613 & 0.000577 \tabularnewline
13 & -0.519704 & -3.5629 & 0.000427 \tabularnewline
14 & -0.494625 & -3.391 & 0.00071 \tabularnewline
15 & -0.45262 & -3.103 & 0.001619 \tabularnewline
16 & -0.404738 & -2.7747 & 0.003951 \tabularnewline
17 & -0.330911 & -2.2686 & 0.013963 \tabularnewline
18 & -0.259858 & -1.7815 & 0.040647 \tabularnewline
19 & -0.197529 & -1.3542 & 0.091075 \tabularnewline
20 & -0.148719 & -1.0196 & 0.156578 \tabularnewline
21 & -0.093127 & -0.6384 & 0.263141 \tabularnewline
22 & -0.055133 & -0.378 & 0.353577 \tabularnewline
23 & -0.029671 & -0.2034 & 0.419844 \tabularnewline
24 & -0.006543 & -0.0449 & 0.482205 \tabularnewline
25 & 0.007491 & 0.0514 & 0.47963 \tabularnewline
26 & 0.003227 & 0.0221 & 0.491223 \tabularnewline
27 & -0.008151 & -0.0559 & 0.477837 \tabularnewline
28 & -0.015151 & -0.1039 & 0.458857 \tabularnewline
29 & -0.017508 & -0.12 & 0.452486 \tabularnewline
30 & -0.020256 & -0.1389 & 0.445075 \tabularnewline
31 & -0.016352 & -0.1121 & 0.455609 \tabularnewline
32 & 0.001755 & 0.012 & 0.495226 \tabularnewline
33 & 0.017756 & 0.1217 & 0.451816 \tabularnewline
34 & 0.035573 & 0.2439 & 0.404194 \tabularnewline
35 & 0.052269 & 0.3583 & 0.360848 \tabularnewline
36 & 0.064447 & 0.4418 & 0.33032 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71034&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]0.934105[/C][C]6.4039[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.835834[/C][C]5.7302[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.709662[/C][C]4.8652[/C][C]7e-06[/C][/ROW]
[ROW][C]4[/C][C]0.560409[/C][C]3.842[/C][C]0.000182[/C][/ROW]
[ROW][C]5[/C][C]0.368652[/C][C]2.5274[/C][C]0.007458[/C][/ROW]
[ROW][C]6[/C][C]0.190952[/C][C]1.3091[/C][C]0.098433[/C][/ROW]
[ROW][C]7[/C][C]0.026785[/C][C]0.1836[/C][C]0.427546[/C][/ROW]
[ROW][C]8[/C][C]-0.128461[/C][C]-0.8807[/C][C]0.191485[/C][/ROW]
[ROW][C]9[/C][C]-0.273366[/C][C]-1.8741[/C][C]0.03357[/C][/ROW]
[ROW][C]10[/C][C]-0.373577[/C][C]-2.5611[/C][C]0.006852[/C][/ROW]
[ROW][C]11[/C][C]-0.445499[/C][C]-3.0542[/C][C]0.001855[/C][/ROW]
[ROW][C]12[/C][C]-0.504884[/C][C]-3.4613[/C][C]0.000577[/C][/ROW]
[ROW][C]13[/C][C]-0.519704[/C][C]-3.5629[/C][C]0.000427[/C][/ROW]
[ROW][C]14[/C][C]-0.494625[/C][C]-3.391[/C][C]0.00071[/C][/ROW]
[ROW][C]15[/C][C]-0.45262[/C][C]-3.103[/C][C]0.001619[/C][/ROW]
[ROW][C]16[/C][C]-0.404738[/C][C]-2.7747[/C][C]0.003951[/C][/ROW]
[ROW][C]17[/C][C]-0.330911[/C][C]-2.2686[/C][C]0.013963[/C][/ROW]
[ROW][C]18[/C][C]-0.259858[/C][C]-1.7815[/C][C]0.040647[/C][/ROW]
[ROW][C]19[/C][C]-0.197529[/C][C]-1.3542[/C][C]0.091075[/C][/ROW]
[ROW][C]20[/C][C]-0.148719[/C][C]-1.0196[/C][C]0.156578[/C][/ROW]
[ROW][C]21[/C][C]-0.093127[/C][C]-0.6384[/C][C]0.263141[/C][/ROW]
[ROW][C]22[/C][C]-0.055133[/C][C]-0.378[/C][C]0.353577[/C][/ROW]
[ROW][C]23[/C][C]-0.029671[/C][C]-0.2034[/C][C]0.419844[/C][/ROW]
[ROW][C]24[/C][C]-0.006543[/C][C]-0.0449[/C][C]0.482205[/C][/ROW]
[ROW][C]25[/C][C]0.007491[/C][C]0.0514[/C][C]0.47963[/C][/ROW]
[ROW][C]26[/C][C]0.003227[/C][C]0.0221[/C][C]0.491223[/C][/ROW]
[ROW][C]27[/C][C]-0.008151[/C][C]-0.0559[/C][C]0.477837[/C][/ROW]
[ROW][C]28[/C][C]-0.015151[/C][C]-0.1039[/C][C]0.458857[/C][/ROW]
[ROW][C]29[/C][C]-0.017508[/C][C]-0.12[/C][C]0.452486[/C][/ROW]
[ROW][C]30[/C][C]-0.020256[/C][C]-0.1389[/C][C]0.445075[/C][/ROW]
[ROW][C]31[/C][C]-0.016352[/C][C]-0.1121[/C][C]0.455609[/C][/ROW]
[ROW][C]32[/C][C]0.001755[/C][C]0.012[/C][C]0.495226[/C][/ROW]
[ROW][C]33[/C][C]0.017756[/C][C]0.1217[/C][C]0.451816[/C][/ROW]
[ROW][C]34[/C][C]0.035573[/C][C]0.2439[/C][C]0.404194[/C][/ROW]
[ROW][C]35[/C][C]0.052269[/C][C]0.3583[/C][C]0.360848[/C][/ROW]
[ROW][C]36[/C][C]0.064447[/C][C]0.4418[/C][C]0.33032[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71034&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71034&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
10.9341056.40390
20.8358345.73020
30.7096624.86527e-06
40.5604093.8420.000182
50.3686522.52740.007458
60.1909521.30910.098433
70.0267850.18360.427546
8-0.128461-0.88070.191485
9-0.273366-1.87410.03357
10-0.373577-2.56110.006852
11-0.445499-3.05420.001855
12-0.504884-3.46130.000577
13-0.519704-3.56290.000427
14-0.494625-3.3910.00071
15-0.45262-3.1030.001619
16-0.404738-2.77470.003951
17-0.330911-2.26860.013963
18-0.259858-1.78150.040647
19-0.197529-1.35420.091075
20-0.148719-1.01960.156578
21-0.093127-0.63840.263141
22-0.055133-0.3780.353577
23-0.029671-0.20340.419844
24-0.006543-0.04490.482205
250.0074910.05140.47963
260.0032270.02210.491223
27-0.008151-0.05590.477837
28-0.015151-0.10390.458857
29-0.017508-0.120.452486
30-0.020256-0.13890.445075
31-0.016352-0.11210.455609
320.0017550.0120.495226
330.0177560.12170.451816
340.0355730.24390.404194
350.0522690.35830.360848
360.0644470.44180.33032






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9341056.40390
2-0.288102-1.97510.027072
3-0.230295-1.57880.060542
4-0.199399-1.3670.089062
5-0.414871-2.84420.003286
60.1118460.76680.223523
70.0168450.11550.454277
8-0.102746-0.70440.242333
9-0.058232-0.39920.345771
100.0699920.47980.316783
11-0.057087-0.39140.348647
12-0.165685-1.13590.130884
130.2135551.46410.074917
14-0.009488-0.0650.474205
15-0.081083-0.55590.290467
16-0.038863-0.26640.395535
17-0.032959-0.2260.411108
18-0.194405-1.33280.094516
19-0.009628-0.0660.473827
20-0.057716-0.39570.347066
21-0.033291-0.22820.410229
220.0079230.05430.478457
23-0.000675-0.00460.498165
24-0.013061-0.08950.464517
25-0.155562-1.06650.145827
26-0.020571-0.1410.444224
27-0.063861-0.43780.331765
28-0.031192-0.21380.415797
290.1449090.99340.162789
30-0.024617-0.16880.433353
31-0.059732-0.40950.342017
320.0081530.05590.477831
33-0.082583-0.56620.286988
34-0.057536-0.39440.347517
35-0.045026-0.30870.379465
36-0.062612-0.42920.334853

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.934105 & 6.4039 & 0 \tabularnewline
2 & -0.288102 & -1.9751 & 0.027072 \tabularnewline
3 & -0.230295 & -1.5788 & 0.060542 \tabularnewline
4 & -0.199399 & -1.367 & 0.089062 \tabularnewline
5 & -0.414871 & -2.8442 & 0.003286 \tabularnewline
6 & 0.111846 & 0.7668 & 0.223523 \tabularnewline
7 & 0.016845 & 0.1155 & 0.454277 \tabularnewline
8 & -0.102746 & -0.7044 & 0.242333 \tabularnewline
9 & -0.058232 & -0.3992 & 0.345771 \tabularnewline
10 & 0.069992 & 0.4798 & 0.316783 \tabularnewline
11 & -0.057087 & -0.3914 & 0.348647 \tabularnewline
12 & -0.165685 & -1.1359 & 0.130884 \tabularnewline
13 & 0.213555 & 1.4641 & 0.074917 \tabularnewline
14 & -0.009488 & -0.065 & 0.474205 \tabularnewline
15 & -0.081083 & -0.5559 & 0.290467 \tabularnewline
16 & -0.038863 & -0.2664 & 0.395535 \tabularnewline
17 & -0.032959 & -0.226 & 0.411108 \tabularnewline
18 & -0.194405 & -1.3328 & 0.094516 \tabularnewline
19 & -0.009628 & -0.066 & 0.473827 \tabularnewline
20 & -0.057716 & -0.3957 & 0.347066 \tabularnewline
21 & -0.033291 & -0.2282 & 0.410229 \tabularnewline
22 & 0.007923 & 0.0543 & 0.478457 \tabularnewline
23 & -0.000675 & -0.0046 & 0.498165 \tabularnewline
24 & -0.013061 & -0.0895 & 0.464517 \tabularnewline
25 & -0.155562 & -1.0665 & 0.145827 \tabularnewline
26 & -0.020571 & -0.141 & 0.444224 \tabularnewline
27 & -0.063861 & -0.4378 & 0.331765 \tabularnewline
28 & -0.031192 & -0.2138 & 0.415797 \tabularnewline
29 & 0.144909 & 0.9934 & 0.162789 \tabularnewline
30 & -0.024617 & -0.1688 & 0.433353 \tabularnewline
31 & -0.059732 & -0.4095 & 0.342017 \tabularnewline
32 & 0.008153 & 0.0559 & 0.477831 \tabularnewline
33 & -0.082583 & -0.5662 & 0.286988 \tabularnewline
34 & -0.057536 & -0.3944 & 0.347517 \tabularnewline
35 & -0.045026 & -0.3087 & 0.379465 \tabularnewline
36 & -0.062612 & -0.4292 & 0.334853 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71034&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]0.934105[/C][C]6.4039[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.288102[/C][C]-1.9751[/C][C]0.027072[/C][/ROW]
[ROW][C]3[/C][C]-0.230295[/C][C]-1.5788[/C][C]0.060542[/C][/ROW]
[ROW][C]4[/C][C]-0.199399[/C][C]-1.367[/C][C]0.089062[/C][/ROW]
[ROW][C]5[/C][C]-0.414871[/C][C]-2.8442[/C][C]0.003286[/C][/ROW]
[ROW][C]6[/C][C]0.111846[/C][C]0.7668[/C][C]0.223523[/C][/ROW]
[ROW][C]7[/C][C]0.016845[/C][C]0.1155[/C][C]0.454277[/C][/ROW]
[ROW][C]8[/C][C]-0.102746[/C][C]-0.7044[/C][C]0.242333[/C][/ROW]
[ROW][C]9[/C][C]-0.058232[/C][C]-0.3992[/C][C]0.345771[/C][/ROW]
[ROW][C]10[/C][C]0.069992[/C][C]0.4798[/C][C]0.316783[/C][/ROW]
[ROW][C]11[/C][C]-0.057087[/C][C]-0.3914[/C][C]0.348647[/C][/ROW]
[ROW][C]12[/C][C]-0.165685[/C][C]-1.1359[/C][C]0.130884[/C][/ROW]
[ROW][C]13[/C][C]0.213555[/C][C]1.4641[/C][C]0.074917[/C][/ROW]
[ROW][C]14[/C][C]-0.009488[/C][C]-0.065[/C][C]0.474205[/C][/ROW]
[ROW][C]15[/C][C]-0.081083[/C][C]-0.5559[/C][C]0.290467[/C][/ROW]
[ROW][C]16[/C][C]-0.038863[/C][C]-0.2664[/C][C]0.395535[/C][/ROW]
[ROW][C]17[/C][C]-0.032959[/C][C]-0.226[/C][C]0.411108[/C][/ROW]
[ROW][C]18[/C][C]-0.194405[/C][C]-1.3328[/C][C]0.094516[/C][/ROW]
[ROW][C]19[/C][C]-0.009628[/C][C]-0.066[/C][C]0.473827[/C][/ROW]
[ROW][C]20[/C][C]-0.057716[/C][C]-0.3957[/C][C]0.347066[/C][/ROW]
[ROW][C]21[/C][C]-0.033291[/C][C]-0.2282[/C][C]0.410229[/C][/ROW]
[ROW][C]22[/C][C]0.007923[/C][C]0.0543[/C][C]0.478457[/C][/ROW]
[ROW][C]23[/C][C]-0.000675[/C][C]-0.0046[/C][C]0.498165[/C][/ROW]
[ROW][C]24[/C][C]-0.013061[/C][C]-0.0895[/C][C]0.464517[/C][/ROW]
[ROW][C]25[/C][C]-0.155562[/C][C]-1.0665[/C][C]0.145827[/C][/ROW]
[ROW][C]26[/C][C]-0.020571[/C][C]-0.141[/C][C]0.444224[/C][/ROW]
[ROW][C]27[/C][C]-0.063861[/C][C]-0.4378[/C][C]0.331765[/C][/ROW]
[ROW][C]28[/C][C]-0.031192[/C][C]-0.2138[/C][C]0.415797[/C][/ROW]
[ROW][C]29[/C][C]0.144909[/C][C]0.9934[/C][C]0.162789[/C][/ROW]
[ROW][C]30[/C][C]-0.024617[/C][C]-0.1688[/C][C]0.433353[/C][/ROW]
[ROW][C]31[/C][C]-0.059732[/C][C]-0.4095[/C][C]0.342017[/C][/ROW]
[ROW][C]32[/C][C]0.008153[/C][C]0.0559[/C][C]0.477831[/C][/ROW]
[ROW][C]33[/C][C]-0.082583[/C][C]-0.5662[/C][C]0.286988[/C][/ROW]
[ROW][C]34[/C][C]-0.057536[/C][C]-0.3944[/C][C]0.347517[/C][/ROW]
[ROW][C]35[/C][C]-0.045026[/C][C]-0.3087[/C][C]0.379465[/C][/ROW]
[ROW][C]36[/C][C]-0.062612[/C][C]-0.4292[/C][C]0.334853[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71034&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71034&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
10.9341056.40390
2-0.288102-1.97510.027072
3-0.230295-1.57880.060542
4-0.199399-1.3670.089062
5-0.414871-2.84420.003286
60.1118460.76680.223523
70.0168450.11550.454277
8-0.102746-0.70440.242333
9-0.058232-0.39920.345771
100.0699920.47980.316783
11-0.057087-0.39140.348647
12-0.165685-1.13590.130884
130.2135551.46410.074917
14-0.009488-0.0650.474205
15-0.081083-0.55590.290467
16-0.038863-0.26640.395535
17-0.032959-0.2260.411108
18-0.194405-1.33280.094516
19-0.009628-0.0660.473827
20-0.057716-0.39570.347066
21-0.033291-0.22820.410229
220.0079230.05430.478457
23-0.000675-0.00460.498165
24-0.013061-0.08950.464517
25-0.155562-1.06650.145827
26-0.020571-0.1410.444224
27-0.063861-0.43780.331765
28-0.031192-0.21380.415797
290.1449090.99340.162789
30-0.024617-0.16880.433353
31-0.059732-0.40950.342017
320.0081530.05590.477831
33-0.082583-0.56620.286988
34-0.057536-0.39440.347517
35-0.045026-0.30870.379465
36-0.062612-0.42920.334853


Figures (Output of Computation)

Input Parameters & R Code

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