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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, 27 Nov 2009 05:52:23 -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/Nov/27/t1259326404lgfmtv2miq8r9uw.htm/, Retrieved Mon, 29 Apr 2024 22:51:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60677, Retrieved Mon, 29 Apr 2024 22:51:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114

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] [Workshop 8] [2009-11-27 12:40:33] [dc3c82a565f0b2cd85906905748a1f2c]
-   P             [(Partial) Autocorrelation Function] [Workshop 8] [2009-11-27 12:52:23] [0bdf648420800d03e6dbfbd39fe2311c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
62
64
62
64
64
69
69
65
56
58
53
62
55
60
59
58
53
57
57
53
54
53
57
57
55
49
50
49
54
58
58
52
56
52
59
53
52
53
51
50
56
52
46
48
46
48
48
49
53
48
51
48
50
55
52
53
52
55
53
53
56
54
52
55
54
59
56
56
51
53
52
51
46
49
46
55
57
53
52
53
50
54
53
50
51
52
47
51
49
53
52
45
53
51
48
48
48
48
40
43
40
39
39
36
41
39
40
39
46
40
37
37
44
41
40
36
38
43
42
45
46

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60677&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]0 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=60677&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60677&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.434241-4.51288e-06
20.1409931.46520.072879
3-0.105073-1.0920.138642
4-0.057694-0.59960.275023
5-0.017662-0.18360.427354
60.0710450.73830.230959
7-0.089133-0.92630.178179
80.100391.04330.149573
9-0.04816-0.50050.308873
100.0948270.98550.163299
110.0714750.74280.229612
12-0.270403-2.81010.002941
130.019360.20120.420463
140.0092440.09610.461823
15-0.089104-0.9260.178257
160.1292071.34280.091082
170.0027790.02890.488507
18-0.073596-0.76480.22302
190.0784950.81570.20822
20-0.048751-0.50660.306722
21-0.001113-0.01160.495395
22-0.089375-0.92880.17753
230.1212331.25990.105212
24-0.132725-1.37930.085322
250.0394180.40960.34144
260.0842070.87510.19173
270.0148510.15430.438816
280.0645740.67110.251803
29-0.030421-0.31610.376252
30-0.017284-0.17960.428893
310.0108220.11250.455332
32-0.047438-0.4930.31151
330.120371.25090.106833
34-0.082788-0.86040.19575
350.0048170.05010.480084
360.0336310.34950.363696

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.434241 & -4.5128 & 8e-06 \tabularnewline
2 & 0.140993 & 1.4652 & 0.072879 \tabularnewline
3 & -0.105073 & -1.092 & 0.138642 \tabularnewline
4 & -0.057694 & -0.5996 & 0.275023 \tabularnewline
5 & -0.017662 & -0.1836 & 0.427354 \tabularnewline
6 & 0.071045 & 0.7383 & 0.230959 \tabularnewline
7 & -0.089133 & -0.9263 & 0.178179 \tabularnewline
8 & 0.10039 & 1.0433 & 0.149573 \tabularnewline
9 & -0.04816 & -0.5005 & 0.308873 \tabularnewline
10 & 0.094827 & 0.9855 & 0.163299 \tabularnewline
11 & 0.071475 & 0.7428 & 0.229612 \tabularnewline
12 & -0.270403 & -2.8101 & 0.002941 \tabularnewline
13 & 0.01936 & 0.2012 & 0.420463 \tabularnewline
14 & 0.009244 & 0.0961 & 0.461823 \tabularnewline
15 & -0.089104 & -0.926 & 0.178257 \tabularnewline
16 & 0.129207 & 1.3428 & 0.091082 \tabularnewline
17 & 0.002779 & 0.0289 & 0.488507 \tabularnewline
18 & -0.073596 & -0.7648 & 0.22302 \tabularnewline
19 & 0.078495 & 0.8157 & 0.20822 \tabularnewline
20 & -0.048751 & -0.5066 & 0.306722 \tabularnewline
21 & -0.001113 & -0.0116 & 0.495395 \tabularnewline
22 & -0.089375 & -0.9288 & 0.17753 \tabularnewline
23 & 0.121233 & 1.2599 & 0.105212 \tabularnewline
24 & -0.132725 & -1.3793 & 0.085322 \tabularnewline
25 & 0.039418 & 0.4096 & 0.34144 \tabularnewline
26 & 0.084207 & 0.8751 & 0.19173 \tabularnewline
27 & 0.014851 & 0.1543 & 0.438816 \tabularnewline
28 & 0.064574 & 0.6711 & 0.251803 \tabularnewline
29 & -0.030421 & -0.3161 & 0.376252 \tabularnewline
30 & -0.017284 & -0.1796 & 0.428893 \tabularnewline
31 & 0.010822 & 0.1125 & 0.455332 \tabularnewline
32 & -0.047438 & -0.493 & 0.31151 \tabularnewline
33 & 0.12037 & 1.2509 & 0.106833 \tabularnewline
34 & -0.082788 & -0.8604 & 0.19575 \tabularnewline
35 & 0.004817 & 0.0501 & 0.480084 \tabularnewline
36 & 0.033631 & 0.3495 & 0.363696 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60677&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]-0.434241[/C][C]-4.5128[/C][C]8e-06[/C][/ROW]
[ROW][C]2[/C][C]0.140993[/C][C]1.4652[/C][C]0.072879[/C][/ROW]
[ROW][C]3[/C][C]-0.105073[/C][C]-1.092[/C][C]0.138642[/C][/ROW]
[ROW][C]4[/C][C]-0.057694[/C][C]-0.5996[/C][C]0.275023[/C][/ROW]
[ROW][C]5[/C][C]-0.017662[/C][C]-0.1836[/C][C]0.427354[/C][/ROW]
[ROW][C]6[/C][C]0.071045[/C][C]0.7383[/C][C]0.230959[/C][/ROW]
[ROW][C]7[/C][C]-0.089133[/C][C]-0.9263[/C][C]0.178179[/C][/ROW]
[ROW][C]8[/C][C]0.10039[/C][C]1.0433[/C][C]0.149573[/C][/ROW]
[ROW][C]9[/C][C]-0.04816[/C][C]-0.5005[/C][C]0.308873[/C][/ROW]
[ROW][C]10[/C][C]0.094827[/C][C]0.9855[/C][C]0.163299[/C][/ROW]
[ROW][C]11[/C][C]0.071475[/C][C]0.7428[/C][C]0.229612[/C][/ROW]
[ROW][C]12[/C][C]-0.270403[/C][C]-2.8101[/C][C]0.002941[/C][/ROW]
[ROW][C]13[/C][C]0.01936[/C][C]0.2012[/C][C]0.420463[/C][/ROW]
[ROW][C]14[/C][C]0.009244[/C][C]0.0961[/C][C]0.461823[/C][/ROW]
[ROW][C]15[/C][C]-0.089104[/C][C]-0.926[/C][C]0.178257[/C][/ROW]
[ROW][C]16[/C][C]0.129207[/C][C]1.3428[/C][C]0.091082[/C][/ROW]
[ROW][C]17[/C][C]0.002779[/C][C]0.0289[/C][C]0.488507[/C][/ROW]
[ROW][C]18[/C][C]-0.073596[/C][C]-0.7648[/C][C]0.22302[/C][/ROW]
[ROW][C]19[/C][C]0.078495[/C][C]0.8157[/C][C]0.20822[/C][/ROW]
[ROW][C]20[/C][C]-0.048751[/C][C]-0.5066[/C][C]0.306722[/C][/ROW]
[ROW][C]21[/C][C]-0.001113[/C][C]-0.0116[/C][C]0.495395[/C][/ROW]
[ROW][C]22[/C][C]-0.089375[/C][C]-0.9288[/C][C]0.17753[/C][/ROW]
[ROW][C]23[/C][C]0.121233[/C][C]1.2599[/C][C]0.105212[/C][/ROW]
[ROW][C]24[/C][C]-0.132725[/C][C]-1.3793[/C][C]0.085322[/C][/ROW]
[ROW][C]25[/C][C]0.039418[/C][C]0.4096[/C][C]0.34144[/C][/ROW]
[ROW][C]26[/C][C]0.084207[/C][C]0.8751[/C][C]0.19173[/C][/ROW]
[ROW][C]27[/C][C]0.014851[/C][C]0.1543[/C][C]0.438816[/C][/ROW]
[ROW][C]28[/C][C]0.064574[/C][C]0.6711[/C][C]0.251803[/C][/ROW]
[ROW][C]29[/C][C]-0.030421[/C][C]-0.3161[/C][C]0.376252[/C][/ROW]
[ROW][C]30[/C][C]-0.017284[/C][C]-0.1796[/C][C]0.428893[/C][/ROW]
[ROW][C]31[/C][C]0.010822[/C][C]0.1125[/C][C]0.455332[/C][/ROW]
[ROW][C]32[/C][C]-0.047438[/C][C]-0.493[/C][C]0.31151[/C][/ROW]
[ROW][C]33[/C][C]0.12037[/C][C]1.2509[/C][C]0.106833[/C][/ROW]
[ROW][C]34[/C][C]-0.082788[/C][C]-0.8604[/C][C]0.19575[/C][/ROW]
[ROW][C]35[/C][C]0.004817[/C][C]0.0501[/C][C]0.480084[/C][/ROW]
[ROW][C]36[/C][C]0.033631[/C][C]0.3495[/C][C]0.363696[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60677&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60677&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
1-0.434241-4.51288e-06
20.1409931.46520.072879
3-0.105073-1.0920.138642
4-0.057694-0.59960.275023
5-0.017662-0.18360.427354
60.0710450.73830.230959
7-0.089133-0.92630.178179
80.100391.04330.149573
9-0.04816-0.50050.308873
100.0948270.98550.163299
110.0714750.74280.229612
12-0.270403-2.81010.002941
130.019360.20120.420463
140.0092440.09610.461823
15-0.089104-0.9260.178257
160.1292071.34280.091082
170.0027790.02890.488507
18-0.073596-0.76480.22302
190.0784950.81570.20822
20-0.048751-0.50660.306722
21-0.001113-0.01160.495395
22-0.089375-0.92880.17753
230.1212331.25990.105212
24-0.132725-1.37930.085322
250.0394180.40960.34144
260.0842070.87510.19173
270.0148510.15430.438816
280.0645740.67110.251803
29-0.030421-0.31610.376252
30-0.017284-0.17960.428893
310.0108220.11250.455332
32-0.047438-0.4930.31151
330.120371.25090.106833
34-0.082788-0.86040.19575
350.0048170.05010.480084
360.0336310.34950.363696






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.434241-4.51288e-06
2-0.058627-0.60930.271812
3-0.081268-0.84460.200111
4-0.159657-1.65920.049988
5-0.13326-1.38490.084472
60.0134540.13980.444534
7-0.085053-0.88390.189359
80.0024980.0260.489669
90.0003070.00320.498732
100.0942980.980.164645
110.1980332.0580.020998
12-0.205236-2.13290.0176
13-0.229979-2.390.00929
14-0.041126-0.42740.334971
15-0.147175-1.52950.064533
16-0.091017-0.94590.173163
170.000260.00270.498924
18-0.092557-0.96190.169129
19-0.044418-0.46160.322647
20-0.012752-0.13250.44741
21-0.045934-0.47740.317037
22-0.124897-1.2980.098533
230.1512641.5720.059439
24-0.136825-1.42190.078964
25-0.258326-2.68460.004203
260.0504530.52430.300566
27-0.001604-0.01670.493366
280.07540.78360.2175
290.1080491.12290.13199
30-0.014261-0.14820.441229
310.047950.49830.309637
320.0592510.61580.269677
330.0860080.89380.186704
34-0.056054-0.58250.280714
350.0714260.74230.229763
36-0.037665-0.39140.348128

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.434241 & -4.5128 & 8e-06 \tabularnewline
2 & -0.058627 & -0.6093 & 0.271812 \tabularnewline
3 & -0.081268 & -0.8446 & 0.200111 \tabularnewline
4 & -0.159657 & -1.6592 & 0.049988 \tabularnewline
5 & -0.13326 & -1.3849 & 0.084472 \tabularnewline
6 & 0.013454 & 0.1398 & 0.444534 \tabularnewline
7 & -0.085053 & -0.8839 & 0.189359 \tabularnewline
8 & 0.002498 & 0.026 & 0.489669 \tabularnewline
9 & 0.000307 & 0.0032 & 0.498732 \tabularnewline
10 & 0.094298 & 0.98 & 0.164645 \tabularnewline
11 & 0.198033 & 2.058 & 0.020998 \tabularnewline
12 & -0.205236 & -2.1329 & 0.0176 \tabularnewline
13 & -0.229979 & -2.39 & 0.00929 \tabularnewline
14 & -0.041126 & -0.4274 & 0.334971 \tabularnewline
15 & -0.147175 & -1.5295 & 0.064533 \tabularnewline
16 & -0.091017 & -0.9459 & 0.173163 \tabularnewline
17 & 0.00026 & 0.0027 & 0.498924 \tabularnewline
18 & -0.092557 & -0.9619 & 0.169129 \tabularnewline
19 & -0.044418 & -0.4616 & 0.322647 \tabularnewline
20 & -0.012752 & -0.1325 & 0.44741 \tabularnewline
21 & -0.045934 & -0.4774 & 0.317037 \tabularnewline
22 & -0.124897 & -1.298 & 0.098533 \tabularnewline
23 & 0.151264 & 1.572 & 0.059439 \tabularnewline
24 & -0.136825 & -1.4219 & 0.078964 \tabularnewline
25 & -0.258326 & -2.6846 & 0.004203 \tabularnewline
26 & 0.050453 & 0.5243 & 0.300566 \tabularnewline
27 & -0.001604 & -0.0167 & 0.493366 \tabularnewline
28 & 0.0754 & 0.7836 & 0.2175 \tabularnewline
29 & 0.108049 & 1.1229 & 0.13199 \tabularnewline
30 & -0.014261 & -0.1482 & 0.441229 \tabularnewline
31 & 0.04795 & 0.4983 & 0.309637 \tabularnewline
32 & 0.059251 & 0.6158 & 0.269677 \tabularnewline
33 & 0.086008 & 0.8938 & 0.186704 \tabularnewline
34 & -0.056054 & -0.5825 & 0.280714 \tabularnewline
35 & 0.071426 & 0.7423 & 0.229763 \tabularnewline
36 & -0.037665 & -0.3914 & 0.348128 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60677&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]-0.434241[/C][C]-4.5128[/C][C]8e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.058627[/C][C]-0.6093[/C][C]0.271812[/C][/ROW]
[ROW][C]3[/C][C]-0.081268[/C][C]-0.8446[/C][C]0.200111[/C][/ROW]
[ROW][C]4[/C][C]-0.159657[/C][C]-1.6592[/C][C]0.049988[/C][/ROW]
[ROW][C]5[/C][C]-0.13326[/C][C]-1.3849[/C][C]0.084472[/C][/ROW]
[ROW][C]6[/C][C]0.013454[/C][C]0.1398[/C][C]0.444534[/C][/ROW]
[ROW][C]7[/C][C]-0.085053[/C][C]-0.8839[/C][C]0.189359[/C][/ROW]
[ROW][C]8[/C][C]0.002498[/C][C]0.026[/C][C]0.489669[/C][/ROW]
[ROW][C]9[/C][C]0.000307[/C][C]0.0032[/C][C]0.498732[/C][/ROW]
[ROW][C]10[/C][C]0.094298[/C][C]0.98[/C][C]0.164645[/C][/ROW]
[ROW][C]11[/C][C]0.198033[/C][C]2.058[/C][C]0.020998[/C][/ROW]
[ROW][C]12[/C][C]-0.205236[/C][C]-2.1329[/C][C]0.0176[/C][/ROW]
[ROW][C]13[/C][C]-0.229979[/C][C]-2.39[/C][C]0.00929[/C][/ROW]
[ROW][C]14[/C][C]-0.041126[/C][C]-0.4274[/C][C]0.334971[/C][/ROW]
[ROW][C]15[/C][C]-0.147175[/C][C]-1.5295[/C][C]0.064533[/C][/ROW]
[ROW][C]16[/C][C]-0.091017[/C][C]-0.9459[/C][C]0.173163[/C][/ROW]
[ROW][C]17[/C][C]0.00026[/C][C]0.0027[/C][C]0.498924[/C][/ROW]
[ROW][C]18[/C][C]-0.092557[/C][C]-0.9619[/C][C]0.169129[/C][/ROW]
[ROW][C]19[/C][C]-0.044418[/C][C]-0.4616[/C][C]0.322647[/C][/ROW]
[ROW][C]20[/C][C]-0.012752[/C][C]-0.1325[/C][C]0.44741[/C][/ROW]
[ROW][C]21[/C][C]-0.045934[/C][C]-0.4774[/C][C]0.317037[/C][/ROW]
[ROW][C]22[/C][C]-0.124897[/C][C]-1.298[/C][C]0.098533[/C][/ROW]
[ROW][C]23[/C][C]0.151264[/C][C]1.572[/C][C]0.059439[/C][/ROW]
[ROW][C]24[/C][C]-0.136825[/C][C]-1.4219[/C][C]0.078964[/C][/ROW]
[ROW][C]25[/C][C]-0.258326[/C][C]-2.6846[/C][C]0.004203[/C][/ROW]
[ROW][C]26[/C][C]0.050453[/C][C]0.5243[/C][C]0.300566[/C][/ROW]
[ROW][C]27[/C][C]-0.001604[/C][C]-0.0167[/C][C]0.493366[/C][/ROW]
[ROW][C]28[/C][C]0.0754[/C][C]0.7836[/C][C]0.2175[/C][/ROW]
[ROW][C]29[/C][C]0.108049[/C][C]1.1229[/C][C]0.13199[/C][/ROW]
[ROW][C]30[/C][C]-0.014261[/C][C]-0.1482[/C][C]0.441229[/C][/ROW]
[ROW][C]31[/C][C]0.04795[/C][C]0.4983[/C][C]0.309637[/C][/ROW]
[ROW][C]32[/C][C]0.059251[/C][C]0.6158[/C][C]0.269677[/C][/ROW]
[ROW][C]33[/C][C]0.086008[/C][C]0.8938[/C][C]0.186704[/C][/ROW]
[ROW][C]34[/C][C]-0.056054[/C][C]-0.5825[/C][C]0.280714[/C][/ROW]
[ROW][C]35[/C][C]0.071426[/C][C]0.7423[/C][C]0.229763[/C][/ROW]
[ROW][C]36[/C][C]-0.037665[/C][C]-0.3914[/C][C]0.348128[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60677&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60677&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
1-0.434241-4.51288e-06
2-0.058627-0.60930.271812
3-0.081268-0.84460.200111
4-0.159657-1.65920.049988
5-0.13326-1.38490.084472
60.0134540.13980.444534
7-0.085053-0.88390.189359
80.0024980.0260.489669
90.0003070.00320.498732
100.0942980.980.164645
110.1980332.0580.020998
12-0.205236-2.13290.0176
13-0.229979-2.390.00929
14-0.041126-0.42740.334971
15-0.147175-1.52950.064533
16-0.091017-0.94590.173163
170.000260.00270.498924
18-0.092557-0.96190.169129
19-0.044418-0.46160.322647
20-0.012752-0.13250.44741
21-0.045934-0.47740.317037
22-0.124897-1.2980.098533
230.1512641.5720.059439
24-0.136825-1.42190.078964
25-0.258326-2.68460.004203
260.0504530.52430.300566
27-0.001604-0.01670.493366
280.07540.78360.2175
290.1080491.12290.13199
30-0.014261-0.14820.441229
310.047950.49830.309637
320.0592510.61580.269677
330.0860080.89380.186704
34-0.056054-0.58250.280714
350.0714260.74230.229763
36-0.037665-0.39140.348128


Figures (Output of Computation)

Input Parameters & R Code

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