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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 computationSat, 12 Dec 2009 09:20:04 -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/12/t12606348749ldk9z43b0hchrf.htm/, Retrieved Sun, 28 Apr 2024 19:18:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67043, Retrieved Sun, 28 Apr 2024 19:18:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact232

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       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
-   PD        [Univariate Data Series] [Totaal Werkzoeken...] [2009-11-24 16:54:07] [ee7c2e7343f5b1451e62c5c16ec521f1]
-   P           [Univariate Data Series] [Totaal Werkzoeken...] [2009-11-24 17:23:40] [ee7c2e7343f5b1451e62c5c16ec521f1]
- RMPD            [(Partial) Autocorrelation Function] [] [2009-11-26 08:57:08] [5edbdb7a459c4059b6c3b063ba86821c]
-    D                [(Partial) Autocorrelation Function] [] [2009-12-12 16:20:04] [24029b2c7217429de6ff94b5379eb52c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
80.2
74.8
77.8
73
72
75.8
72.6
71.9
74.8
72.9
72.9
79.9
74
76
69.6
77.3
75.2
75.8
77.6
76.7
77
77.9
76.7
71.9
73.4
72.5
73.7
69.5
74.7
72.5
72.1
70.7
71.4
69.5
73.5
72.4
74.5
72.2
73
73.3
71.3
73.6
71.3
71.2
81.4
76.1
71.1
75.7
70
68.5
56.7
57.9
58.8
59.3
61.3
62.9
61.4
64.5
63.8
61.6
64.7

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=67043&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=67043&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67043&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
10.7594525.93150
20.7018155.48130
30.5961494.65619e-06
40.4953813.8690.000134
50.3968683.09960.001465
60.3073272.40030.009724
70.2382551.86080.033795
80.2171621.69610.047483
90.1473051.15050.127216
100.1047350.8180.208269
110.0310010.24210.404747
12-0.067723-0.52890.299386
13-1e-05-1e-040.499968
14-0.068253-0.53310.29796
15-0.021352-0.16680.434053
160.0039890.03120.487624
170.056670.44260.329807
180.0518120.40470.34357
190.0770380.60170.274807
200.0470040.36710.357404
210.0404670.31610.37652
220.0094130.07350.470817
230.0564160.44060.330522
240.0295720.2310.409059
250.028670.22390.411785
260.0463560.36210.359281
270.005430.04240.483155
28-0.024784-0.19360.423578
29-0.069016-0.5390.295913
30-0.146474-1.1440.128547
31-0.173783-1.35730.089845
32-0.178075-1.39080.084668
33-0.176942-1.3820.086011
34-0.183454-1.43280.078507
35-0.22826-1.78280.0398
36-0.158893-1.2410.109679

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.759452 & 5.9315 & 0 \tabularnewline
2 & 0.701815 & 5.4813 & 0 \tabularnewline
3 & 0.596149 & 4.6561 & 9e-06 \tabularnewline
4 & 0.495381 & 3.869 & 0.000134 \tabularnewline
5 & 0.396868 & 3.0996 & 0.001465 \tabularnewline
6 & 0.307327 & 2.4003 & 0.009724 \tabularnewline
7 & 0.238255 & 1.8608 & 0.033795 \tabularnewline
8 & 0.217162 & 1.6961 & 0.047483 \tabularnewline
9 & 0.147305 & 1.1505 & 0.127216 \tabularnewline
10 & 0.104735 & 0.818 & 0.208269 \tabularnewline
11 & 0.031001 & 0.2421 & 0.404747 \tabularnewline
12 & -0.067723 & -0.5289 & 0.299386 \tabularnewline
13 & -1e-05 & -1e-04 & 0.499968 \tabularnewline
14 & -0.068253 & -0.5331 & 0.29796 \tabularnewline
15 & -0.021352 & -0.1668 & 0.434053 \tabularnewline
16 & 0.003989 & 0.0312 & 0.487624 \tabularnewline
17 & 0.05667 & 0.4426 & 0.329807 \tabularnewline
18 & 0.051812 & 0.4047 & 0.34357 \tabularnewline
19 & 0.077038 & 0.6017 & 0.274807 \tabularnewline
20 & 0.047004 & 0.3671 & 0.357404 \tabularnewline
21 & 0.040467 & 0.3161 & 0.37652 \tabularnewline
22 & 0.009413 & 0.0735 & 0.470817 \tabularnewline
23 & 0.056416 & 0.4406 & 0.330522 \tabularnewline
24 & 0.029572 & 0.231 & 0.409059 \tabularnewline
25 & 0.02867 & 0.2239 & 0.411785 \tabularnewline
26 & 0.046356 & 0.3621 & 0.359281 \tabularnewline
27 & 0.00543 & 0.0424 & 0.483155 \tabularnewline
28 & -0.024784 & -0.1936 & 0.423578 \tabularnewline
29 & -0.069016 & -0.539 & 0.295913 \tabularnewline
30 & -0.146474 & -1.144 & 0.128547 \tabularnewline
31 & -0.173783 & -1.3573 & 0.089845 \tabularnewline
32 & -0.178075 & -1.3908 & 0.084668 \tabularnewline
33 & -0.176942 & -1.382 & 0.086011 \tabularnewline
34 & -0.183454 & -1.4328 & 0.078507 \tabularnewline
35 & -0.22826 & -1.7828 & 0.0398 \tabularnewline
36 & -0.158893 & -1.241 & 0.109679 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67043&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]0.759452[/C][C]5.9315[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.701815[/C][C]5.4813[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.596149[/C][C]4.6561[/C][C]9e-06[/C][/ROW]
[ROW][C]4[/C][C]0.495381[/C][C]3.869[/C][C]0.000134[/C][/ROW]
[ROW][C]5[/C][C]0.396868[/C][C]3.0996[/C][C]0.001465[/C][/ROW]
[ROW][C]6[/C][C]0.307327[/C][C]2.4003[/C][C]0.009724[/C][/ROW]
[ROW][C]7[/C][C]0.238255[/C][C]1.8608[/C][C]0.033795[/C][/ROW]
[ROW][C]8[/C][C]0.217162[/C][C]1.6961[/C][C]0.047483[/C][/ROW]
[ROW][C]9[/C][C]0.147305[/C][C]1.1505[/C][C]0.127216[/C][/ROW]
[ROW][C]10[/C][C]0.104735[/C][C]0.818[/C][C]0.208269[/C][/ROW]
[ROW][C]11[/C][C]0.031001[/C][C]0.2421[/C][C]0.404747[/C][/ROW]
[ROW][C]12[/C][C]-0.067723[/C][C]-0.5289[/C][C]0.299386[/C][/ROW]
[ROW][C]13[/C][C]-1e-05[/C][C]-1e-04[/C][C]0.499968[/C][/ROW]
[ROW][C]14[/C][C]-0.068253[/C][C]-0.5331[/C][C]0.29796[/C][/ROW]
[ROW][C]15[/C][C]-0.021352[/C][C]-0.1668[/C][C]0.434053[/C][/ROW]
[ROW][C]16[/C][C]0.003989[/C][C]0.0312[/C][C]0.487624[/C][/ROW]
[ROW][C]17[/C][C]0.05667[/C][C]0.4426[/C][C]0.329807[/C][/ROW]
[ROW][C]18[/C][C]0.051812[/C][C]0.4047[/C][C]0.34357[/C][/ROW]
[ROW][C]19[/C][C]0.077038[/C][C]0.6017[/C][C]0.274807[/C][/ROW]
[ROW][C]20[/C][C]0.047004[/C][C]0.3671[/C][C]0.357404[/C][/ROW]
[ROW][C]21[/C][C]0.040467[/C][C]0.3161[/C][C]0.37652[/C][/ROW]
[ROW][C]22[/C][C]0.009413[/C][C]0.0735[/C][C]0.470817[/C][/ROW]
[ROW][C]23[/C][C]0.056416[/C][C]0.4406[/C][C]0.330522[/C][/ROW]
[ROW][C]24[/C][C]0.029572[/C][C]0.231[/C][C]0.409059[/C][/ROW]
[ROW][C]25[/C][C]0.02867[/C][C]0.2239[/C][C]0.411785[/C][/ROW]
[ROW][C]26[/C][C]0.046356[/C][C]0.3621[/C][C]0.359281[/C][/ROW]
[ROW][C]27[/C][C]0.00543[/C][C]0.0424[/C][C]0.483155[/C][/ROW]
[ROW][C]28[/C][C]-0.024784[/C][C]-0.1936[/C][C]0.423578[/C][/ROW]
[ROW][C]29[/C][C]-0.069016[/C][C]-0.539[/C][C]0.295913[/C][/ROW]
[ROW][C]30[/C][C]-0.146474[/C][C]-1.144[/C][C]0.128547[/C][/ROW]
[ROW][C]31[/C][C]-0.173783[/C][C]-1.3573[/C][C]0.089845[/C][/ROW]
[ROW][C]32[/C][C]-0.178075[/C][C]-1.3908[/C][C]0.084668[/C][/ROW]
[ROW][C]33[/C][C]-0.176942[/C][C]-1.382[/C][C]0.086011[/C][/ROW]
[ROW][C]34[/C][C]-0.183454[/C][C]-1.4328[/C][C]0.078507[/C][/ROW]
[ROW][C]35[/C][C]-0.22826[/C][C]-1.7828[/C][C]0.0398[/C][/ROW]
[ROW][C]36[/C][C]-0.158893[/C][C]-1.241[/C][C]0.109679[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67043&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67043&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
10.7594525.93150
20.7018155.48130
30.5961494.65619e-06
40.4953813.8690.000134
50.3968683.09960.001465
60.3073272.40030.009724
70.2382551.86080.033795
80.2171621.69610.047483
90.1473051.15050.127216
100.1047350.8180.208269
110.0310010.24210.404747
12-0.067723-0.52890.299386
13-1e-05-1e-040.499968
14-0.068253-0.53310.29796
15-0.021352-0.16680.434053
160.0039890.03120.487624
170.056670.44260.329807
180.0518120.40470.34357
190.0770380.60170.274807
200.0470040.36710.357404
210.0404670.31610.37652
220.0094130.07350.470817
230.0564160.44060.330522
240.0295720.2310.409059
250.028670.22390.411785
260.0463560.36210.359281
270.005430.04240.483155
28-0.024784-0.19360.423578
29-0.069016-0.5390.295913
30-0.146474-1.1440.128547
31-0.173783-1.35730.089845
32-0.178075-1.39080.084668
33-0.176942-1.3820.086011
34-0.183454-1.43280.078507
35-0.22826-1.78280.0398
36-0.158893-1.2410.109679






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7594525.93150
20.2954562.30760.012215
3-0.009719-0.07590.469871
4-0.074912-0.58510.280324
5-0.068964-0.53860.296053
6-0.04587-0.35830.360695
7-0.000778-0.00610.497585
80.1050.82010.207683
9-0.063907-0.49910.309742
10-0.054365-0.42460.33631
11-0.11456-0.89470.187221
12-0.182414-1.42470.07967
130.3118822.43590.008896
14-0.050293-0.39280.347919
150.1148990.89740.18652
160.0502850.39270.347942
170.0501630.39180.348291
18-0.122894-0.95980.170463
190.0229370.17910.429209
20-0.037173-0.29030.386274
21-0.067071-0.52380.301143
220.0118260.09240.463355
230.1211960.94660.173797
24-0.100959-0.78850.216725
250.0376330.29390.384906
26-0.046697-0.36470.358292
27-0.054978-0.42940.334576
28-0.053951-0.42140.337483
290.017880.13960.444699
30-0.213093-1.66430.05059
310.0797920.62320.267739
320.0324530.25350.40038
330.0192790.15060.440406
34-0.080302-0.62720.266442
35-0.06995-0.54630.293416
360.069460.54250.294726

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.759452 & 5.9315 & 0 \tabularnewline
2 & 0.295456 & 2.3076 & 0.012215 \tabularnewline
3 & -0.009719 & -0.0759 & 0.469871 \tabularnewline
4 & -0.074912 & -0.5851 & 0.280324 \tabularnewline
5 & -0.068964 & -0.5386 & 0.296053 \tabularnewline
6 & -0.04587 & -0.3583 & 0.360695 \tabularnewline
7 & -0.000778 & -0.0061 & 0.497585 \tabularnewline
8 & 0.105 & 0.8201 & 0.207683 \tabularnewline
9 & -0.063907 & -0.4991 & 0.309742 \tabularnewline
10 & -0.054365 & -0.4246 & 0.33631 \tabularnewline
11 & -0.11456 & -0.8947 & 0.187221 \tabularnewline
12 & -0.182414 & -1.4247 & 0.07967 \tabularnewline
13 & 0.311882 & 2.4359 & 0.008896 \tabularnewline
14 & -0.050293 & -0.3928 & 0.347919 \tabularnewline
15 & 0.114899 & 0.8974 & 0.18652 \tabularnewline
16 & 0.050285 & 0.3927 & 0.347942 \tabularnewline
17 & 0.050163 & 0.3918 & 0.348291 \tabularnewline
18 & -0.122894 & -0.9598 & 0.170463 \tabularnewline
19 & 0.022937 & 0.1791 & 0.429209 \tabularnewline
20 & -0.037173 & -0.2903 & 0.386274 \tabularnewline
21 & -0.067071 & -0.5238 & 0.301143 \tabularnewline
22 & 0.011826 & 0.0924 & 0.463355 \tabularnewline
23 & 0.121196 & 0.9466 & 0.173797 \tabularnewline
24 & -0.100959 & -0.7885 & 0.216725 \tabularnewline
25 & 0.037633 & 0.2939 & 0.384906 \tabularnewline
26 & -0.046697 & -0.3647 & 0.358292 \tabularnewline
27 & -0.054978 & -0.4294 & 0.334576 \tabularnewline
28 & -0.053951 & -0.4214 & 0.337483 \tabularnewline
29 & 0.01788 & 0.1396 & 0.444699 \tabularnewline
30 & -0.213093 & -1.6643 & 0.05059 \tabularnewline
31 & 0.079792 & 0.6232 & 0.267739 \tabularnewline
32 & 0.032453 & 0.2535 & 0.40038 \tabularnewline
33 & 0.019279 & 0.1506 & 0.440406 \tabularnewline
34 & -0.080302 & -0.6272 & 0.266442 \tabularnewline
35 & -0.06995 & -0.5463 & 0.293416 \tabularnewline
36 & 0.06946 & 0.5425 & 0.294726 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67043&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]0.759452[/C][C]5.9315[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.295456[/C][C]2.3076[/C][C]0.012215[/C][/ROW]
[ROW][C]3[/C][C]-0.009719[/C][C]-0.0759[/C][C]0.469871[/C][/ROW]
[ROW][C]4[/C][C]-0.074912[/C][C]-0.5851[/C][C]0.280324[/C][/ROW]
[ROW][C]5[/C][C]-0.068964[/C][C]-0.5386[/C][C]0.296053[/C][/ROW]
[ROW][C]6[/C][C]-0.04587[/C][C]-0.3583[/C][C]0.360695[/C][/ROW]
[ROW][C]7[/C][C]-0.000778[/C][C]-0.0061[/C][C]0.497585[/C][/ROW]
[ROW][C]8[/C][C]0.105[/C][C]0.8201[/C][C]0.207683[/C][/ROW]
[ROW][C]9[/C][C]-0.063907[/C][C]-0.4991[/C][C]0.309742[/C][/ROW]
[ROW][C]10[/C][C]-0.054365[/C][C]-0.4246[/C][C]0.33631[/C][/ROW]
[ROW][C]11[/C][C]-0.11456[/C][C]-0.8947[/C][C]0.187221[/C][/ROW]
[ROW][C]12[/C][C]-0.182414[/C][C]-1.4247[/C][C]0.07967[/C][/ROW]
[ROW][C]13[/C][C]0.311882[/C][C]2.4359[/C][C]0.008896[/C][/ROW]
[ROW][C]14[/C][C]-0.050293[/C][C]-0.3928[/C][C]0.347919[/C][/ROW]
[ROW][C]15[/C][C]0.114899[/C][C]0.8974[/C][C]0.18652[/C][/ROW]
[ROW][C]16[/C][C]0.050285[/C][C]0.3927[/C][C]0.347942[/C][/ROW]
[ROW][C]17[/C][C]0.050163[/C][C]0.3918[/C][C]0.348291[/C][/ROW]
[ROW][C]18[/C][C]-0.122894[/C][C]-0.9598[/C][C]0.170463[/C][/ROW]
[ROW][C]19[/C][C]0.022937[/C][C]0.1791[/C][C]0.429209[/C][/ROW]
[ROW][C]20[/C][C]-0.037173[/C][C]-0.2903[/C][C]0.386274[/C][/ROW]
[ROW][C]21[/C][C]-0.067071[/C][C]-0.5238[/C][C]0.301143[/C][/ROW]
[ROW][C]22[/C][C]0.011826[/C][C]0.0924[/C][C]0.463355[/C][/ROW]
[ROW][C]23[/C][C]0.121196[/C][C]0.9466[/C][C]0.173797[/C][/ROW]
[ROW][C]24[/C][C]-0.100959[/C][C]-0.7885[/C][C]0.216725[/C][/ROW]
[ROW][C]25[/C][C]0.037633[/C][C]0.2939[/C][C]0.384906[/C][/ROW]
[ROW][C]26[/C][C]-0.046697[/C][C]-0.3647[/C][C]0.358292[/C][/ROW]
[ROW][C]27[/C][C]-0.054978[/C][C]-0.4294[/C][C]0.334576[/C][/ROW]
[ROW][C]28[/C][C]-0.053951[/C][C]-0.4214[/C][C]0.337483[/C][/ROW]
[ROW][C]29[/C][C]0.01788[/C][C]0.1396[/C][C]0.444699[/C][/ROW]
[ROW][C]30[/C][C]-0.213093[/C][C]-1.6643[/C][C]0.05059[/C][/ROW]
[ROW][C]31[/C][C]0.079792[/C][C]0.6232[/C][C]0.267739[/C][/ROW]
[ROW][C]32[/C][C]0.032453[/C][C]0.2535[/C][C]0.40038[/C][/ROW]
[ROW][C]33[/C][C]0.019279[/C][C]0.1506[/C][C]0.440406[/C][/ROW]
[ROW][C]34[/C][C]-0.080302[/C][C]-0.6272[/C][C]0.266442[/C][/ROW]
[ROW][C]35[/C][C]-0.06995[/C][C]-0.5463[/C][C]0.293416[/C][/ROW]
[ROW][C]36[/C][C]0.06946[/C][C]0.5425[/C][C]0.294726[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67043&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67043&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
10.7594525.93150
20.2954562.30760.012215
3-0.009719-0.07590.469871
4-0.074912-0.58510.280324
5-0.068964-0.53860.296053
6-0.04587-0.35830.360695
7-0.000778-0.00610.497585
80.1050.82010.207683
9-0.063907-0.49910.309742
10-0.054365-0.42460.33631
11-0.11456-0.89470.187221
12-0.182414-1.42470.07967
130.3118822.43590.008896
14-0.050293-0.39280.347919
150.1148990.89740.18652
160.0502850.39270.347942
170.0501630.39180.348291
18-0.122894-0.95980.170463
190.0229370.17910.429209
20-0.037173-0.29030.386274
21-0.067071-0.52380.301143
220.0118260.09240.463355
230.1211960.94660.173797
24-0.100959-0.78850.216725
250.0376330.29390.384906
26-0.046697-0.36470.358292
27-0.054978-0.42940.334576
28-0.053951-0.42140.337483
290.017880.13960.444699
30-0.213093-1.66430.05059
310.0797920.62320.267739
320.0324530.25350.40038
330.0192790.15060.440406
34-0.080302-0.62720.266442
35-0.06995-0.54630.293416
360.069460.54250.294726


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 = 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')