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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, 17 Dec 2009 05:03:11 -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/17/t1261051441m4czgsjfvjmbbk2.htm/, Retrieved Tue, 30 Apr 2024 02:40:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68776, Retrieved Tue, 30 Apr 2024 02:40:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95

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 12:26:39] [b98453cac15ba1066b407e146608df68]
- R  D        [(Partial) Autocorrelation Function] [ACF Werkloosheid ...] [2009-11-26 11:26:37] [075a06058fde559dd021d126a2b15a40]
-   P             [(Partial) Autocorrelation Function] [ACF Werkloosheid ...] [2009-12-17 12:03:11] [154177ed6b2613a730375f7d341441cf] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
136
133
126
120
114
116
153
162
161
149
139
135
130
127
122
117
112
113
149
157
157
147
137
132
125
123
117
114
111
112
144
150
149
134
123
116
117
111
105
102
95
93
124
130
124
115
106
105
105
101
95
93
84
87
116
120
117
109
105
107
109

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=68776&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=68776&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68776&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
1-0.123588-0.85620.198058
2-0.004258-0.02950.488295
30.0278160.19270.423998
40.085930.59530.277206
5-0.055581-0.38510.350941
60.1800431.24740.109155
70.0997990.69140.246314
8-0.037785-0.26180.397304
90.0108530.07520.470187
10-0.141869-0.98290.165294
110.4386553.03910.001917
12-0.184559-1.27870.103582
13-0.076284-0.52850.299789
14-0.025062-0.17360.431441
150.07190.49810.31033
16-0.167071-1.15750.126398
170.1348290.93410.177458
18-0.0651-0.4510.327001
19-0.189274-1.31130.097992
20-0.032268-0.22360.412026
21-0.08782-0.60840.272884
220.0968350.67090.252753
23-0.138858-0.9620.170427
24-0.04204-0.29130.386053
25-0.108958-0.75490.227004
26-0.031364-0.21730.41445
27-0.065231-0.45190.326677
28-0.012939-0.08960.464472
29-0.043332-0.30020.382655
30-0.052602-0.36440.358565
310.0515660.35730.361233
320.0058290.04040.483977
330.0364460.25250.400865
34-0.056403-0.39080.348846
35-0.005872-0.04070.483859
36-0.050114-0.34720.36498

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.123588 & -0.8562 & 0.198058 \tabularnewline
2 & -0.004258 & -0.0295 & 0.488295 \tabularnewline
3 & 0.027816 & 0.1927 & 0.423998 \tabularnewline
4 & 0.08593 & 0.5953 & 0.277206 \tabularnewline
5 & -0.055581 & -0.3851 & 0.350941 \tabularnewline
6 & 0.180043 & 1.2474 & 0.109155 \tabularnewline
7 & 0.099799 & 0.6914 & 0.246314 \tabularnewline
8 & -0.037785 & -0.2618 & 0.397304 \tabularnewline
9 & 0.010853 & 0.0752 & 0.470187 \tabularnewline
10 & -0.141869 & -0.9829 & 0.165294 \tabularnewline
11 & 0.438655 & 3.0391 & 0.001917 \tabularnewline
12 & -0.184559 & -1.2787 & 0.103582 \tabularnewline
13 & -0.076284 & -0.5285 & 0.299789 \tabularnewline
14 & -0.025062 & -0.1736 & 0.431441 \tabularnewline
15 & 0.0719 & 0.4981 & 0.31033 \tabularnewline
16 & -0.167071 & -1.1575 & 0.126398 \tabularnewline
17 & 0.134829 & 0.9341 & 0.177458 \tabularnewline
18 & -0.0651 & -0.451 & 0.327001 \tabularnewline
19 & -0.189274 & -1.3113 & 0.097992 \tabularnewline
20 & -0.032268 & -0.2236 & 0.412026 \tabularnewline
21 & -0.08782 & -0.6084 & 0.272884 \tabularnewline
22 & 0.096835 & 0.6709 & 0.252753 \tabularnewline
23 & -0.138858 & -0.962 & 0.170427 \tabularnewline
24 & -0.04204 & -0.2913 & 0.386053 \tabularnewline
25 & -0.108958 & -0.7549 & 0.227004 \tabularnewline
26 & -0.031364 & -0.2173 & 0.41445 \tabularnewline
27 & -0.065231 & -0.4519 & 0.326677 \tabularnewline
28 & -0.012939 & -0.0896 & 0.464472 \tabularnewline
29 & -0.043332 & -0.3002 & 0.382655 \tabularnewline
30 & -0.052602 & -0.3644 & 0.358565 \tabularnewline
31 & 0.051566 & 0.3573 & 0.361233 \tabularnewline
32 & 0.005829 & 0.0404 & 0.483977 \tabularnewline
33 & 0.036446 & 0.2525 & 0.400865 \tabularnewline
34 & -0.056403 & -0.3908 & 0.348846 \tabularnewline
35 & -0.005872 & -0.0407 & 0.483859 \tabularnewline
36 & -0.050114 & -0.3472 & 0.36498 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68776&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]-0.123588[/C][C]-0.8562[/C][C]0.198058[/C][/ROW]
[ROW][C]2[/C][C]-0.004258[/C][C]-0.0295[/C][C]0.488295[/C][/ROW]
[ROW][C]3[/C][C]0.027816[/C][C]0.1927[/C][C]0.423998[/C][/ROW]
[ROW][C]4[/C][C]0.08593[/C][C]0.5953[/C][C]0.277206[/C][/ROW]
[ROW][C]5[/C][C]-0.055581[/C][C]-0.3851[/C][C]0.350941[/C][/ROW]
[ROW][C]6[/C][C]0.180043[/C][C]1.2474[/C][C]0.109155[/C][/ROW]
[ROW][C]7[/C][C]0.099799[/C][C]0.6914[/C][C]0.246314[/C][/ROW]
[ROW][C]8[/C][C]-0.037785[/C][C]-0.2618[/C][C]0.397304[/C][/ROW]
[ROW][C]9[/C][C]0.010853[/C][C]0.0752[/C][C]0.470187[/C][/ROW]
[ROW][C]10[/C][C]-0.141869[/C][C]-0.9829[/C][C]0.165294[/C][/ROW]
[ROW][C]11[/C][C]0.438655[/C][C]3.0391[/C][C]0.001917[/C][/ROW]
[ROW][C]12[/C][C]-0.184559[/C][C]-1.2787[/C][C]0.103582[/C][/ROW]
[ROW][C]13[/C][C]-0.076284[/C][C]-0.5285[/C][C]0.299789[/C][/ROW]
[ROW][C]14[/C][C]-0.025062[/C][C]-0.1736[/C][C]0.431441[/C][/ROW]
[ROW][C]15[/C][C]0.0719[/C][C]0.4981[/C][C]0.31033[/C][/ROW]
[ROW][C]16[/C][C]-0.167071[/C][C]-1.1575[/C][C]0.126398[/C][/ROW]
[ROW][C]17[/C][C]0.134829[/C][C]0.9341[/C][C]0.177458[/C][/ROW]
[ROW][C]18[/C][C]-0.0651[/C][C]-0.451[/C][C]0.327001[/C][/ROW]
[ROW][C]19[/C][C]-0.189274[/C][C]-1.3113[/C][C]0.097992[/C][/ROW]
[ROW][C]20[/C][C]-0.032268[/C][C]-0.2236[/C][C]0.412026[/C][/ROW]
[ROW][C]21[/C][C]-0.08782[/C][C]-0.6084[/C][C]0.272884[/C][/ROW]
[ROW][C]22[/C][C]0.096835[/C][C]0.6709[/C][C]0.252753[/C][/ROW]
[ROW][C]23[/C][C]-0.138858[/C][C]-0.962[/C][C]0.170427[/C][/ROW]
[ROW][C]24[/C][C]-0.04204[/C][C]-0.2913[/C][C]0.386053[/C][/ROW]
[ROW][C]25[/C][C]-0.108958[/C][C]-0.7549[/C][C]0.227004[/C][/ROW]
[ROW][C]26[/C][C]-0.031364[/C][C]-0.2173[/C][C]0.41445[/C][/ROW]
[ROW][C]27[/C][C]-0.065231[/C][C]-0.4519[/C][C]0.326677[/C][/ROW]
[ROW][C]28[/C][C]-0.012939[/C][C]-0.0896[/C][C]0.464472[/C][/ROW]
[ROW][C]29[/C][C]-0.043332[/C][C]-0.3002[/C][C]0.382655[/C][/ROW]
[ROW][C]30[/C][C]-0.052602[/C][C]-0.3644[/C][C]0.358565[/C][/ROW]
[ROW][C]31[/C][C]0.051566[/C][C]0.3573[/C][C]0.361233[/C][/ROW]
[ROW][C]32[/C][C]0.005829[/C][C]0.0404[/C][C]0.483977[/C][/ROW]
[ROW][C]33[/C][C]0.036446[/C][C]0.2525[/C][C]0.400865[/C][/ROW]
[ROW][C]34[/C][C]-0.056403[/C][C]-0.3908[/C][C]0.348846[/C][/ROW]
[ROW][C]35[/C][C]-0.005872[/C][C]-0.0407[/C][C]0.483859[/C][/ROW]
[ROW][C]36[/C][C]-0.050114[/C][C]-0.3472[/C][C]0.36498[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68776&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68776&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
1-0.123588-0.85620.198058
2-0.004258-0.02950.488295
30.0278160.19270.423998
40.085930.59530.277206
5-0.055581-0.38510.350941
60.1800431.24740.109155
70.0997990.69140.246314
8-0.037785-0.26180.397304
90.0108530.07520.470187
10-0.141869-0.98290.165294
110.4386553.03910.001917
12-0.184559-1.27870.103582
13-0.076284-0.52850.299789
14-0.025062-0.17360.431441
150.07190.49810.31033
16-0.167071-1.15750.126398
170.1348290.93410.177458
18-0.0651-0.4510.327001
19-0.189274-1.31130.097992
20-0.032268-0.22360.412026
21-0.08782-0.60840.272884
220.0968350.67090.252753
23-0.138858-0.9620.170427
24-0.04204-0.29130.386053
25-0.108958-0.75490.227004
26-0.031364-0.21730.41445
27-0.065231-0.45190.326677
28-0.012939-0.08960.464472
29-0.043332-0.30020.382655
30-0.052602-0.36440.358565
310.0515660.35730.361233
320.0058290.04040.483977
330.0364460.25250.400865
34-0.056403-0.39080.348846
35-0.005872-0.04070.483859
36-0.050114-0.34720.36498






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.123588-0.85620.198058
2-0.019835-0.13740.445637
30.0252230.17480.431005
40.0939990.65120.258997
5-0.033225-0.23020.409462
60.1740951.20620.116833
70.1438940.99690.161899
8-0.00671-0.04650.481558
90.0054660.03790.484975
10-0.193569-1.34110.093103
110.4323862.99570.002162
12-0.175866-1.21840.114507
13-0.152667-1.05770.147741
14-0.057559-0.39880.345911
150.0073030.05060.479929
16-0.023377-0.1620.436009
17-0.049727-0.34450.365979
18-0.140977-0.97670.166803
19-0.124339-0.86140.196637
20-0.029936-0.20740.418287
21-0.005112-0.03540.485946
22-0.109367-0.75770.226163
23-0.039738-0.27530.392128
240.0210710.1460.442272
25-0.022673-0.15710.43792
26-0.116538-0.80740.211709
270.0909610.63020.265778
28-0.149568-1.03620.152641
290.0476820.33030.371287
300.0963710.66770.253769
310.0617840.42810.335264
320.0770080.53350.298066
33-0.012348-0.08560.46609
340.033870.23470.407737
35-0.024866-0.17230.431971
36-0.033646-0.23310.408334

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.123588 & -0.8562 & 0.198058 \tabularnewline
2 & -0.019835 & -0.1374 & 0.445637 \tabularnewline
3 & 0.025223 & 0.1748 & 0.431005 \tabularnewline
4 & 0.093999 & 0.6512 & 0.258997 \tabularnewline
5 & -0.033225 & -0.2302 & 0.409462 \tabularnewline
6 & 0.174095 & 1.2062 & 0.116833 \tabularnewline
7 & 0.143894 & 0.9969 & 0.161899 \tabularnewline
8 & -0.00671 & -0.0465 & 0.481558 \tabularnewline
9 & 0.005466 & 0.0379 & 0.484975 \tabularnewline
10 & -0.193569 & -1.3411 & 0.093103 \tabularnewline
11 & 0.432386 & 2.9957 & 0.002162 \tabularnewline
12 & -0.175866 & -1.2184 & 0.114507 \tabularnewline
13 & -0.152667 & -1.0577 & 0.147741 \tabularnewline
14 & -0.057559 & -0.3988 & 0.345911 \tabularnewline
15 & 0.007303 & 0.0506 & 0.479929 \tabularnewline
16 & -0.023377 & -0.162 & 0.436009 \tabularnewline
17 & -0.049727 & -0.3445 & 0.365979 \tabularnewline
18 & -0.140977 & -0.9767 & 0.166803 \tabularnewline
19 & -0.124339 & -0.8614 & 0.196637 \tabularnewline
20 & -0.029936 & -0.2074 & 0.418287 \tabularnewline
21 & -0.005112 & -0.0354 & 0.485946 \tabularnewline
22 & -0.109367 & -0.7577 & 0.226163 \tabularnewline
23 & -0.039738 & -0.2753 & 0.392128 \tabularnewline
24 & 0.021071 & 0.146 & 0.442272 \tabularnewline
25 & -0.022673 & -0.1571 & 0.43792 \tabularnewline
26 & -0.116538 & -0.8074 & 0.211709 \tabularnewline
27 & 0.090961 & 0.6302 & 0.265778 \tabularnewline
28 & -0.149568 & -1.0362 & 0.152641 \tabularnewline
29 & 0.047682 & 0.3303 & 0.371287 \tabularnewline
30 & 0.096371 & 0.6677 & 0.253769 \tabularnewline
31 & 0.061784 & 0.4281 & 0.335264 \tabularnewline
32 & 0.077008 & 0.5335 & 0.298066 \tabularnewline
33 & -0.012348 & -0.0856 & 0.46609 \tabularnewline
34 & 0.03387 & 0.2347 & 0.407737 \tabularnewline
35 & -0.024866 & -0.1723 & 0.431971 \tabularnewline
36 & -0.033646 & -0.2331 & 0.408334 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68776&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]-0.123588[/C][C]-0.8562[/C][C]0.198058[/C][/ROW]
[ROW][C]2[/C][C]-0.019835[/C][C]-0.1374[/C][C]0.445637[/C][/ROW]
[ROW][C]3[/C][C]0.025223[/C][C]0.1748[/C][C]0.431005[/C][/ROW]
[ROW][C]4[/C][C]0.093999[/C][C]0.6512[/C][C]0.258997[/C][/ROW]
[ROW][C]5[/C][C]-0.033225[/C][C]-0.2302[/C][C]0.409462[/C][/ROW]
[ROW][C]6[/C][C]0.174095[/C][C]1.2062[/C][C]0.116833[/C][/ROW]
[ROW][C]7[/C][C]0.143894[/C][C]0.9969[/C][C]0.161899[/C][/ROW]
[ROW][C]8[/C][C]-0.00671[/C][C]-0.0465[/C][C]0.481558[/C][/ROW]
[ROW][C]9[/C][C]0.005466[/C][C]0.0379[/C][C]0.484975[/C][/ROW]
[ROW][C]10[/C][C]-0.193569[/C][C]-1.3411[/C][C]0.093103[/C][/ROW]
[ROW][C]11[/C][C]0.432386[/C][C]2.9957[/C][C]0.002162[/C][/ROW]
[ROW][C]12[/C][C]-0.175866[/C][C]-1.2184[/C][C]0.114507[/C][/ROW]
[ROW][C]13[/C][C]-0.152667[/C][C]-1.0577[/C][C]0.147741[/C][/ROW]
[ROW][C]14[/C][C]-0.057559[/C][C]-0.3988[/C][C]0.345911[/C][/ROW]
[ROW][C]15[/C][C]0.007303[/C][C]0.0506[/C][C]0.479929[/C][/ROW]
[ROW][C]16[/C][C]-0.023377[/C][C]-0.162[/C][C]0.436009[/C][/ROW]
[ROW][C]17[/C][C]-0.049727[/C][C]-0.3445[/C][C]0.365979[/C][/ROW]
[ROW][C]18[/C][C]-0.140977[/C][C]-0.9767[/C][C]0.166803[/C][/ROW]
[ROW][C]19[/C][C]-0.124339[/C][C]-0.8614[/C][C]0.196637[/C][/ROW]
[ROW][C]20[/C][C]-0.029936[/C][C]-0.2074[/C][C]0.418287[/C][/ROW]
[ROW][C]21[/C][C]-0.005112[/C][C]-0.0354[/C][C]0.485946[/C][/ROW]
[ROW][C]22[/C][C]-0.109367[/C][C]-0.7577[/C][C]0.226163[/C][/ROW]
[ROW][C]23[/C][C]-0.039738[/C][C]-0.2753[/C][C]0.392128[/C][/ROW]
[ROW][C]24[/C][C]0.021071[/C][C]0.146[/C][C]0.442272[/C][/ROW]
[ROW][C]25[/C][C]-0.022673[/C][C]-0.1571[/C][C]0.43792[/C][/ROW]
[ROW][C]26[/C][C]-0.116538[/C][C]-0.8074[/C][C]0.211709[/C][/ROW]
[ROW][C]27[/C][C]0.090961[/C][C]0.6302[/C][C]0.265778[/C][/ROW]
[ROW][C]28[/C][C]-0.149568[/C][C]-1.0362[/C][C]0.152641[/C][/ROW]
[ROW][C]29[/C][C]0.047682[/C][C]0.3303[/C][C]0.371287[/C][/ROW]
[ROW][C]30[/C][C]0.096371[/C][C]0.6677[/C][C]0.253769[/C][/ROW]
[ROW][C]31[/C][C]0.061784[/C][C]0.4281[/C][C]0.335264[/C][/ROW]
[ROW][C]32[/C][C]0.077008[/C][C]0.5335[/C][C]0.298066[/C][/ROW]
[ROW][C]33[/C][C]-0.012348[/C][C]-0.0856[/C][C]0.46609[/C][/ROW]
[ROW][C]34[/C][C]0.03387[/C][C]0.2347[/C][C]0.407737[/C][/ROW]
[ROW][C]35[/C][C]-0.024866[/C][C]-0.1723[/C][C]0.431971[/C][/ROW]
[ROW][C]36[/C][C]-0.033646[/C][C]-0.2331[/C][C]0.408334[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68776&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68776&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
1-0.123588-0.85620.198058
2-0.019835-0.13740.445637
30.0252230.17480.431005
40.0939990.65120.258997
5-0.033225-0.23020.409462
60.1740951.20620.116833
70.1438940.99690.161899
8-0.00671-0.04650.481558
90.0054660.03790.484975
10-0.193569-1.34110.093103
110.4323862.99570.002162
12-0.175866-1.21840.114507
13-0.152667-1.05770.147741
14-0.057559-0.39880.345911
150.0073030.05060.479929
16-0.023377-0.1620.436009
17-0.049727-0.34450.365979
18-0.140977-0.97670.166803
19-0.124339-0.86140.196637
20-0.029936-0.20740.418287
21-0.005112-0.03540.485946
22-0.109367-0.75770.226163
23-0.039738-0.27530.392128
240.0210710.1460.442272
25-0.022673-0.15710.43792
26-0.116538-0.80740.211709
270.0909610.63020.265778
28-0.149568-1.03620.152641
290.0476820.33030.371287
300.0963710.66770.253769
310.0617840.42810.335264
320.0770080.53350.298066
33-0.012348-0.08560.46609
340.033870.23470.407737
35-0.024866-0.17230.431971
36-0.033646-0.23310.408334


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = -0.4 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = -0.4 ; par3 = 1 ; 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')