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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationFri, 27 Nov 2009 07:56:22 -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/t1259333833xo3zztf30wsbefm.htm/, Retrieved Mon, 29 Apr 2024 20:10:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60862, Retrieved Mon, 29 Apr 2024 20:10:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact121

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 12:19:56] [b98453cac15ba1066b407e146608df68]
-   PD          [(Partial) Autocorrelation Function] [] [2009-11-27 14:56:22] [f90b018c65398c2fee7b197f24b65ddd] [Current]
-   P             [(Partial) Autocorrelation Function] [] [2009-11-27 15:09:59] [d4e4be187a92369b428eb3a5c1616639]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
902.2
891.9
874
930.9
944.2
935.9
937.1
885.1
892.4
987.3
946.3
799.6
875.4
846.2
880.6
885.7
868.9
882.5
789.6
773.3
804.3
817.8
836.7
721.8
760.8
841.4
1045.6
949.2
850.1
957.4
851.8
913.9
888
973.8
927.6
833
879.5
797.3
834.5
735.1
835
892.8
697.2
821.1
732.7
797.6
866.3
826.3
778.6
779.2
951
692.3
841.4
857.3
760.7
841.2
810.3
1007.4
931.3
931.2

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=60862&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=60862&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60862&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
1-0.469556-3.60670.00032
2-0.009733-0.07480.470329
30.0361070.27730.391244
4-0.118855-0.91290.182494
50.2625482.01670.024144
6-0.342568-2.63130.005418
70.3967543.04750.001725
8-0.318647-2.44760.008689
90.1438591.1050.136822
10-0.04938-0.37930.352916
11-0.163461-1.25560.107112
120.3754752.88410.002736
13-0.354757-2.72490.004225
140.2502411.92210.029711
15-0.253119-1.94420.02832
160.0512050.39330.347752
170.2289061.75830.041945
18-0.302417-2.32290.011826
190.1927231.48030.072052
20-0.121258-0.93140.177721
210.1940721.49070.070685
22-0.232428-1.78530.039675
230.0152860.11740.453464
240.2444941.8780.032663
25-0.23797-1.82790.036312
260.1605071.23290.111256
27-0.13851-1.06390.145851
280.1129610.86770.194545
29-0.057024-0.4380.331491
30-0.091394-0.7020.242716
310.1962671.50760.068502
32-0.057817-0.44410.329298
330.0397670.30550.380547
34-0.096193-0.73890.231457
350.0238220.1830.42772
360.0083190.06390.474634

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.469556 & -3.6067 & 0.00032 \tabularnewline
2 & -0.009733 & -0.0748 & 0.470329 \tabularnewline
3 & 0.036107 & 0.2773 & 0.391244 \tabularnewline
4 & -0.118855 & -0.9129 & 0.182494 \tabularnewline
5 & 0.262548 & 2.0167 & 0.024144 \tabularnewline
6 & -0.342568 & -2.6313 & 0.005418 \tabularnewline
7 & 0.396754 & 3.0475 & 0.001725 \tabularnewline
8 & -0.318647 & -2.4476 & 0.008689 \tabularnewline
9 & 0.143859 & 1.105 & 0.136822 \tabularnewline
10 & -0.04938 & -0.3793 & 0.352916 \tabularnewline
11 & -0.163461 & -1.2556 & 0.107112 \tabularnewline
12 & 0.375475 & 2.8841 & 0.002736 \tabularnewline
13 & -0.354757 & -2.7249 & 0.004225 \tabularnewline
14 & 0.250241 & 1.9221 & 0.029711 \tabularnewline
15 & -0.253119 & -1.9442 & 0.02832 \tabularnewline
16 & 0.051205 & 0.3933 & 0.347752 \tabularnewline
17 & 0.228906 & 1.7583 & 0.041945 \tabularnewline
18 & -0.302417 & -2.3229 & 0.011826 \tabularnewline
19 & 0.192723 & 1.4803 & 0.072052 \tabularnewline
20 & -0.121258 & -0.9314 & 0.177721 \tabularnewline
21 & 0.194072 & 1.4907 & 0.070685 \tabularnewline
22 & -0.232428 & -1.7853 & 0.039675 \tabularnewline
23 & 0.015286 & 0.1174 & 0.453464 \tabularnewline
24 & 0.244494 & 1.878 & 0.032663 \tabularnewline
25 & -0.23797 & -1.8279 & 0.036312 \tabularnewline
26 & 0.160507 & 1.2329 & 0.111256 \tabularnewline
27 & -0.13851 & -1.0639 & 0.145851 \tabularnewline
28 & 0.112961 & 0.8677 & 0.194545 \tabularnewline
29 & -0.057024 & -0.438 & 0.331491 \tabularnewline
30 & -0.091394 & -0.702 & 0.242716 \tabularnewline
31 & 0.196267 & 1.5076 & 0.068502 \tabularnewline
32 & -0.057817 & -0.4441 & 0.329298 \tabularnewline
33 & 0.039767 & 0.3055 & 0.380547 \tabularnewline
34 & -0.096193 & -0.7389 & 0.231457 \tabularnewline
35 & 0.023822 & 0.183 & 0.42772 \tabularnewline
36 & 0.008319 & 0.0639 & 0.474634 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60862&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]-0.469556[/C][C]-3.6067[/C][C]0.00032[/C][/ROW]
[ROW][C]2[/C][C]-0.009733[/C][C]-0.0748[/C][C]0.470329[/C][/ROW]
[ROW][C]3[/C][C]0.036107[/C][C]0.2773[/C][C]0.391244[/C][/ROW]
[ROW][C]4[/C][C]-0.118855[/C][C]-0.9129[/C][C]0.182494[/C][/ROW]
[ROW][C]5[/C][C]0.262548[/C][C]2.0167[/C][C]0.024144[/C][/ROW]
[ROW][C]6[/C][C]-0.342568[/C][C]-2.6313[/C][C]0.005418[/C][/ROW]
[ROW][C]7[/C][C]0.396754[/C][C]3.0475[/C][C]0.001725[/C][/ROW]
[ROW][C]8[/C][C]-0.318647[/C][C]-2.4476[/C][C]0.008689[/C][/ROW]
[ROW][C]9[/C][C]0.143859[/C][C]1.105[/C][C]0.136822[/C][/ROW]
[ROW][C]10[/C][C]-0.04938[/C][C]-0.3793[/C][C]0.352916[/C][/ROW]
[ROW][C]11[/C][C]-0.163461[/C][C]-1.2556[/C][C]0.107112[/C][/ROW]
[ROW][C]12[/C][C]0.375475[/C][C]2.8841[/C][C]0.002736[/C][/ROW]
[ROW][C]13[/C][C]-0.354757[/C][C]-2.7249[/C][C]0.004225[/C][/ROW]
[ROW][C]14[/C][C]0.250241[/C][C]1.9221[/C][C]0.029711[/C][/ROW]
[ROW][C]15[/C][C]-0.253119[/C][C]-1.9442[/C][C]0.02832[/C][/ROW]
[ROW][C]16[/C][C]0.051205[/C][C]0.3933[/C][C]0.347752[/C][/ROW]
[ROW][C]17[/C][C]0.228906[/C][C]1.7583[/C][C]0.041945[/C][/ROW]
[ROW][C]18[/C][C]-0.302417[/C][C]-2.3229[/C][C]0.011826[/C][/ROW]
[ROW][C]19[/C][C]0.192723[/C][C]1.4803[/C][C]0.072052[/C][/ROW]
[ROW][C]20[/C][C]-0.121258[/C][C]-0.9314[/C][C]0.177721[/C][/ROW]
[ROW][C]21[/C][C]0.194072[/C][C]1.4907[/C][C]0.070685[/C][/ROW]
[ROW][C]22[/C][C]-0.232428[/C][C]-1.7853[/C][C]0.039675[/C][/ROW]
[ROW][C]23[/C][C]0.015286[/C][C]0.1174[/C][C]0.453464[/C][/ROW]
[ROW][C]24[/C][C]0.244494[/C][C]1.878[/C][C]0.032663[/C][/ROW]
[ROW][C]25[/C][C]-0.23797[/C][C]-1.8279[/C][C]0.036312[/C][/ROW]
[ROW][C]26[/C][C]0.160507[/C][C]1.2329[/C][C]0.111256[/C][/ROW]
[ROW][C]27[/C][C]-0.13851[/C][C]-1.0639[/C][C]0.145851[/C][/ROW]
[ROW][C]28[/C][C]0.112961[/C][C]0.8677[/C][C]0.194545[/C][/ROW]
[ROW][C]29[/C][C]-0.057024[/C][C]-0.438[/C][C]0.331491[/C][/ROW]
[ROW][C]30[/C][C]-0.091394[/C][C]-0.702[/C][C]0.242716[/C][/ROW]
[ROW][C]31[/C][C]0.196267[/C][C]1.5076[/C][C]0.068502[/C][/ROW]
[ROW][C]32[/C][C]-0.057817[/C][C]-0.4441[/C][C]0.329298[/C][/ROW]
[ROW][C]33[/C][C]0.039767[/C][C]0.3055[/C][C]0.380547[/C][/ROW]
[ROW][C]34[/C][C]-0.096193[/C][C]-0.7389[/C][C]0.231457[/C][/ROW]
[ROW][C]35[/C][C]0.023822[/C][C]0.183[/C][C]0.42772[/C][/ROW]
[ROW][C]36[/C][C]0.008319[/C][C]0.0639[/C][C]0.474634[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60862&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60862&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
1-0.469556-3.60670.00032
2-0.009733-0.07480.470329
30.0361070.27730.391244
4-0.118855-0.91290.182494
50.2625482.01670.024144
6-0.342568-2.63130.005418
70.3967543.04750.001725
8-0.318647-2.44760.008689
90.1438591.1050.136822
10-0.04938-0.37930.352916
11-0.163461-1.25560.107112
120.3754752.88410.002736
13-0.354757-2.72490.004225
140.2502411.92210.029711
15-0.253119-1.94420.02832
160.0512050.39330.347752
170.2289061.75830.041945
18-0.302417-2.32290.011826
190.1927231.48030.072052
20-0.121258-0.93140.177721
210.1940721.49070.070685
22-0.232428-1.78530.039675
230.0152860.11740.453464
240.2444941.8780.032663
25-0.23797-1.82790.036312
260.1605071.23290.111256
27-0.13851-1.06390.145851
280.1129610.86770.194545
29-0.057024-0.4380.331491
30-0.091394-0.7020.242716
310.1962671.50760.068502
32-0.057817-0.44410.329298
330.0397670.30550.380547
34-0.096193-0.73890.231457
350.0238220.1830.42772
360.0083190.06390.474634






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.469556-3.60670.00032
2-0.295332-2.26850.013487
3-0.152472-1.17120.123121
4-0.24553-1.88590.032114
50.121840.93590.176577
6-0.244313-1.87660.03276
70.2726052.09390.020287
8-0.163059-1.25250.107669
90.1578931.21280.11502
10-0.206416-1.58550.059098
11-0.091588-0.70350.242255
120.0312260.23990.405638
13-0.024946-0.19160.424352
140.0060040.04610.481688
15-0.148809-1.1430.128822
16-0.187458-1.43990.077592
170.1249130.95950.170617
18-0.130291-1.00080.160509
19-0.130397-1.00160.160314
200.0396420.30450.38091
210.0656390.50420.308006
22-0.113284-0.87010.193873
23-0.071392-0.54840.292751
24-0.008382-0.06440.474442
250.0586290.45030.32706
26-0.084319-0.64770.259855
270.08070.61990.268865
28-0.015687-0.12050.452251
29-0.085333-0.65550.257361
30-0.137486-1.0560.147625
310.0183660.14110.444146
320.1983521.52360.066479
330.0102860.0790.468646
340.0736190.56550.286947
350.039290.30180.381937
36-0.031055-0.23850.406145

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.469556 & -3.6067 & 0.00032 \tabularnewline
2 & -0.295332 & -2.2685 & 0.013487 \tabularnewline
3 & -0.152472 & -1.1712 & 0.123121 \tabularnewline
4 & -0.24553 & -1.8859 & 0.032114 \tabularnewline
5 & 0.12184 & 0.9359 & 0.176577 \tabularnewline
6 & -0.244313 & -1.8766 & 0.03276 \tabularnewline
7 & 0.272605 & 2.0939 & 0.020287 \tabularnewline
8 & -0.163059 & -1.2525 & 0.107669 \tabularnewline
9 & 0.157893 & 1.2128 & 0.11502 \tabularnewline
10 & -0.206416 & -1.5855 & 0.059098 \tabularnewline
11 & -0.091588 & -0.7035 & 0.242255 \tabularnewline
12 & 0.031226 & 0.2399 & 0.405638 \tabularnewline
13 & -0.024946 & -0.1916 & 0.424352 \tabularnewline
14 & 0.006004 & 0.0461 & 0.481688 \tabularnewline
15 & -0.148809 & -1.143 & 0.128822 \tabularnewline
16 & -0.187458 & -1.4399 & 0.077592 \tabularnewline
17 & 0.124913 & 0.9595 & 0.170617 \tabularnewline
18 & -0.130291 & -1.0008 & 0.160509 \tabularnewline
19 & -0.130397 & -1.0016 & 0.160314 \tabularnewline
20 & 0.039642 & 0.3045 & 0.38091 \tabularnewline
21 & 0.065639 & 0.5042 & 0.308006 \tabularnewline
22 & -0.113284 & -0.8701 & 0.193873 \tabularnewline
23 & -0.071392 & -0.5484 & 0.292751 \tabularnewline
24 & -0.008382 & -0.0644 & 0.474442 \tabularnewline
25 & 0.058629 & 0.4503 & 0.32706 \tabularnewline
26 & -0.084319 & -0.6477 & 0.259855 \tabularnewline
27 & 0.0807 & 0.6199 & 0.268865 \tabularnewline
28 & -0.015687 & -0.1205 & 0.452251 \tabularnewline
29 & -0.085333 & -0.6555 & 0.257361 \tabularnewline
30 & -0.137486 & -1.056 & 0.147625 \tabularnewline
31 & 0.018366 & 0.1411 & 0.444146 \tabularnewline
32 & 0.198352 & 1.5236 & 0.066479 \tabularnewline
33 & 0.010286 & 0.079 & 0.468646 \tabularnewline
34 & 0.073619 & 0.5655 & 0.286947 \tabularnewline
35 & 0.03929 & 0.3018 & 0.381937 \tabularnewline
36 & -0.031055 & -0.2385 & 0.406145 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60862&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]-0.469556[/C][C]-3.6067[/C][C]0.00032[/C][/ROW]
[ROW][C]2[/C][C]-0.295332[/C][C]-2.2685[/C][C]0.013487[/C][/ROW]
[ROW][C]3[/C][C]-0.152472[/C][C]-1.1712[/C][C]0.123121[/C][/ROW]
[ROW][C]4[/C][C]-0.24553[/C][C]-1.8859[/C][C]0.032114[/C][/ROW]
[ROW][C]5[/C][C]0.12184[/C][C]0.9359[/C][C]0.176577[/C][/ROW]
[ROW][C]6[/C][C]-0.244313[/C][C]-1.8766[/C][C]0.03276[/C][/ROW]
[ROW][C]7[/C][C]0.272605[/C][C]2.0939[/C][C]0.020287[/C][/ROW]
[ROW][C]8[/C][C]-0.163059[/C][C]-1.2525[/C][C]0.107669[/C][/ROW]
[ROW][C]9[/C][C]0.157893[/C][C]1.2128[/C][C]0.11502[/C][/ROW]
[ROW][C]10[/C][C]-0.206416[/C][C]-1.5855[/C][C]0.059098[/C][/ROW]
[ROW][C]11[/C][C]-0.091588[/C][C]-0.7035[/C][C]0.242255[/C][/ROW]
[ROW][C]12[/C][C]0.031226[/C][C]0.2399[/C][C]0.405638[/C][/ROW]
[ROW][C]13[/C][C]-0.024946[/C][C]-0.1916[/C][C]0.424352[/C][/ROW]
[ROW][C]14[/C][C]0.006004[/C][C]0.0461[/C][C]0.481688[/C][/ROW]
[ROW][C]15[/C][C]-0.148809[/C][C]-1.143[/C][C]0.128822[/C][/ROW]
[ROW][C]16[/C][C]-0.187458[/C][C]-1.4399[/C][C]0.077592[/C][/ROW]
[ROW][C]17[/C][C]0.124913[/C][C]0.9595[/C][C]0.170617[/C][/ROW]
[ROW][C]18[/C][C]-0.130291[/C][C]-1.0008[/C][C]0.160509[/C][/ROW]
[ROW][C]19[/C][C]-0.130397[/C][C]-1.0016[/C][C]0.160314[/C][/ROW]
[ROW][C]20[/C][C]0.039642[/C][C]0.3045[/C][C]0.38091[/C][/ROW]
[ROW][C]21[/C][C]0.065639[/C][C]0.5042[/C][C]0.308006[/C][/ROW]
[ROW][C]22[/C][C]-0.113284[/C][C]-0.8701[/C][C]0.193873[/C][/ROW]
[ROW][C]23[/C][C]-0.071392[/C][C]-0.5484[/C][C]0.292751[/C][/ROW]
[ROW][C]24[/C][C]-0.008382[/C][C]-0.0644[/C][C]0.474442[/C][/ROW]
[ROW][C]25[/C][C]0.058629[/C][C]0.4503[/C][C]0.32706[/C][/ROW]
[ROW][C]26[/C][C]-0.084319[/C][C]-0.6477[/C][C]0.259855[/C][/ROW]
[ROW][C]27[/C][C]0.0807[/C][C]0.6199[/C][C]0.268865[/C][/ROW]
[ROW][C]28[/C][C]-0.015687[/C][C]-0.1205[/C][C]0.452251[/C][/ROW]
[ROW][C]29[/C][C]-0.085333[/C][C]-0.6555[/C][C]0.257361[/C][/ROW]
[ROW][C]30[/C][C]-0.137486[/C][C]-1.056[/C][C]0.147625[/C][/ROW]
[ROW][C]31[/C][C]0.018366[/C][C]0.1411[/C][C]0.444146[/C][/ROW]
[ROW][C]32[/C][C]0.198352[/C][C]1.5236[/C][C]0.066479[/C][/ROW]
[ROW][C]33[/C][C]0.010286[/C][C]0.079[/C][C]0.468646[/C][/ROW]
[ROW][C]34[/C][C]0.073619[/C][C]0.5655[/C][C]0.286947[/C][/ROW]
[ROW][C]35[/C][C]0.03929[/C][C]0.3018[/C][C]0.381937[/C][/ROW]
[ROW][C]36[/C][C]-0.031055[/C][C]-0.2385[/C][C]0.406145[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60862&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60862&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
1-0.469556-3.60670.00032
2-0.295332-2.26850.013487
3-0.152472-1.17120.123121
4-0.24553-1.88590.032114
50.121840.93590.176577
6-0.244313-1.87660.03276
70.2726052.09390.020287
8-0.163059-1.25250.107669
90.1578931.21280.11502
10-0.206416-1.58550.059098
11-0.091588-0.70350.242255
120.0312260.23990.405638
13-0.024946-0.19160.424352
140.0060040.04610.481688
15-0.148809-1.1430.128822
16-0.187458-1.43990.077592
170.1249130.95950.170617
18-0.130291-1.00080.160509
19-0.130397-1.00160.160314
200.0396420.30450.38091
210.0656390.50420.308006
22-0.113284-0.87010.193873
23-0.071392-0.54840.292751
24-0.008382-0.06440.474442
250.0586290.45030.32706
26-0.084319-0.64770.259855
270.08070.61990.268865
28-0.015687-0.12050.452251
29-0.085333-0.65550.257361
30-0.137486-1.0560.147625
310.0183660.14110.444146
320.1983521.52360.066479
330.0102860.0790.468646
340.0736190.56550.286947
350.039290.30180.381937
36-0.031055-0.23850.406145


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')