Free Statistics

of Irreproducible Research!

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, 19 Dec 2009 15:19:48 -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/19/t1261261567xoptlke1tlt3jeg.htm/, Retrieved Fri, 03 May 2024 16:35:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69759, Retrieved Fri, 03 May 2024 16:35:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116
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]
-   PD          [(Partial) Autocorrelation Function] [] [2009-12-19 22:19:48] [c88a5f1b97e332c6387d668c465455af] [Current]
Feedback Forum

Post a new message
Dataseries X:
19915
19843
19761
20858
21968
23061
22661
22269
21857
21568
21274
20987
19683
19381
19071
20772
22485
24181
23479
22782
22067
21489
20903
20330
19736
19483
19242
20334
21423
22523
21986
21462
20908
20575
20237
19904
19610
19251
18941
20450
21946
23409
22741
22069
21539
21189
20960
20704
19697
19598
19456
20316
21083
22158
21469
20892
20578
20233
19947
20049




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=69759&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=69759&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69759&T=0

As an alternative you can also use a 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
1-0.165884-1.12510.133196
2-0.138582-0.93990.176087
3-0.22467-1.52380.067204
4-0.011645-0.0790.468697
50.0037080.02520.490021
60.0465890.3160.376722
7-0.025492-0.17290.431747
8-0.085655-0.58090.282058
90.2562131.73770.044475
100.11060.75010.2285
11-0.040127-0.27220.393362
12-0.358989-2.43480.009419
13-0.064116-0.43490.332849
140.0383690.26020.397924
150.2193481.48770.071828
160.0219130.14860.441251
17-0.020367-0.13810.445368
18-0.166665-1.13040.132088
190.1049070.71150.240179
200.0620.42050.338037
21-0.076609-0.51960.302922
22-0.148375-1.00630.15976
230.1275820.86530.195682
240.0313140.21240.416373
250.1556741.05580.148279
260.0206670.14020.444568
27-0.209511-1.4210.081034
28-0.074247-0.50360.308484
290.067680.4590.324188
300.1501931.01870.156847
31-0.095068-0.64480.261136
320.0059260.04020.484057
33-0.010526-0.07140.471698
340.0724910.49170.312649
350.0010940.00740.497056
36-0.136036-0.92260.180504

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.165884 & -1.1251 & 0.133196 \tabularnewline
2 & -0.138582 & -0.9399 & 0.176087 \tabularnewline
3 & -0.22467 & -1.5238 & 0.067204 \tabularnewline
4 & -0.011645 & -0.079 & 0.468697 \tabularnewline
5 & 0.003708 & 0.0252 & 0.490021 \tabularnewline
6 & 0.046589 & 0.316 & 0.376722 \tabularnewline
7 & -0.025492 & -0.1729 & 0.431747 \tabularnewline
8 & -0.085655 & -0.5809 & 0.282058 \tabularnewline
9 & 0.256213 & 1.7377 & 0.044475 \tabularnewline
10 & 0.1106 & 0.7501 & 0.2285 \tabularnewline
11 & -0.040127 & -0.2722 & 0.393362 \tabularnewline
12 & -0.358989 & -2.4348 & 0.009419 \tabularnewline
13 & -0.064116 & -0.4349 & 0.332849 \tabularnewline
14 & 0.038369 & 0.2602 & 0.397924 \tabularnewline
15 & 0.219348 & 1.4877 & 0.071828 \tabularnewline
16 & 0.021913 & 0.1486 & 0.441251 \tabularnewline
17 & -0.020367 & -0.1381 & 0.445368 \tabularnewline
18 & -0.166665 & -1.1304 & 0.132088 \tabularnewline
19 & 0.104907 & 0.7115 & 0.240179 \tabularnewline
20 & 0.062 & 0.4205 & 0.338037 \tabularnewline
21 & -0.076609 & -0.5196 & 0.302922 \tabularnewline
22 & -0.148375 & -1.0063 & 0.15976 \tabularnewline
23 & 0.127582 & 0.8653 & 0.195682 \tabularnewline
24 & 0.031314 & 0.2124 & 0.416373 \tabularnewline
25 & 0.155674 & 1.0558 & 0.148279 \tabularnewline
26 & 0.020667 & 0.1402 & 0.444568 \tabularnewline
27 & -0.209511 & -1.421 & 0.081034 \tabularnewline
28 & -0.074247 & -0.5036 & 0.308484 \tabularnewline
29 & 0.06768 & 0.459 & 0.324188 \tabularnewline
30 & 0.150193 & 1.0187 & 0.156847 \tabularnewline
31 & -0.095068 & -0.6448 & 0.261136 \tabularnewline
32 & 0.005926 & 0.0402 & 0.484057 \tabularnewline
33 & -0.010526 & -0.0714 & 0.471698 \tabularnewline
34 & 0.072491 & 0.4917 & 0.312649 \tabularnewline
35 & 0.001094 & 0.0074 & 0.497056 \tabularnewline
36 & -0.136036 & -0.9226 & 0.180504 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69759&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]-0.165884[/C][C]-1.1251[/C][C]0.133196[/C][/ROW]
[ROW][C]2[/C][C]-0.138582[/C][C]-0.9399[/C][C]0.176087[/C][/ROW]
[ROW][C]3[/C][C]-0.22467[/C][C]-1.5238[/C][C]0.067204[/C][/ROW]
[ROW][C]4[/C][C]-0.011645[/C][C]-0.079[/C][C]0.468697[/C][/ROW]
[ROW][C]5[/C][C]0.003708[/C][C]0.0252[/C][C]0.490021[/C][/ROW]
[ROW][C]6[/C][C]0.046589[/C][C]0.316[/C][C]0.376722[/C][/ROW]
[ROW][C]7[/C][C]-0.025492[/C][C]-0.1729[/C][C]0.431747[/C][/ROW]
[ROW][C]8[/C][C]-0.085655[/C][C]-0.5809[/C][C]0.282058[/C][/ROW]
[ROW][C]9[/C][C]0.256213[/C][C]1.7377[/C][C]0.044475[/C][/ROW]
[ROW][C]10[/C][C]0.1106[/C][C]0.7501[/C][C]0.2285[/C][/ROW]
[ROW][C]11[/C][C]-0.040127[/C][C]-0.2722[/C][C]0.393362[/C][/ROW]
[ROW][C]12[/C][C]-0.358989[/C][C]-2.4348[/C][C]0.009419[/C][/ROW]
[ROW][C]13[/C][C]-0.064116[/C][C]-0.4349[/C][C]0.332849[/C][/ROW]
[ROW][C]14[/C][C]0.038369[/C][C]0.2602[/C][C]0.397924[/C][/ROW]
[ROW][C]15[/C][C]0.219348[/C][C]1.4877[/C][C]0.071828[/C][/ROW]
[ROW][C]16[/C][C]0.021913[/C][C]0.1486[/C][C]0.441251[/C][/ROW]
[ROW][C]17[/C][C]-0.020367[/C][C]-0.1381[/C][C]0.445368[/C][/ROW]
[ROW][C]18[/C][C]-0.166665[/C][C]-1.1304[/C][C]0.132088[/C][/ROW]
[ROW][C]19[/C][C]0.104907[/C][C]0.7115[/C][C]0.240179[/C][/ROW]
[ROW][C]20[/C][C]0.062[/C][C]0.4205[/C][C]0.338037[/C][/ROW]
[ROW][C]21[/C][C]-0.076609[/C][C]-0.5196[/C][C]0.302922[/C][/ROW]
[ROW][C]22[/C][C]-0.148375[/C][C]-1.0063[/C][C]0.15976[/C][/ROW]
[ROW][C]23[/C][C]0.127582[/C][C]0.8653[/C][C]0.195682[/C][/ROW]
[ROW][C]24[/C][C]0.031314[/C][C]0.2124[/C][C]0.416373[/C][/ROW]
[ROW][C]25[/C][C]0.155674[/C][C]1.0558[/C][C]0.148279[/C][/ROW]
[ROW][C]26[/C][C]0.020667[/C][C]0.1402[/C][C]0.444568[/C][/ROW]
[ROW][C]27[/C][C]-0.209511[/C][C]-1.421[/C][C]0.081034[/C][/ROW]
[ROW][C]28[/C][C]-0.074247[/C][C]-0.5036[/C][C]0.308484[/C][/ROW]
[ROW][C]29[/C][C]0.06768[/C][C]0.459[/C][C]0.324188[/C][/ROW]
[ROW][C]30[/C][C]0.150193[/C][C]1.0187[/C][C]0.156847[/C][/ROW]
[ROW][C]31[/C][C]-0.095068[/C][C]-0.6448[/C][C]0.261136[/C][/ROW]
[ROW][C]32[/C][C]0.005926[/C][C]0.0402[/C][C]0.484057[/C][/ROW]
[ROW][C]33[/C][C]-0.010526[/C][C]-0.0714[/C][C]0.471698[/C][/ROW]
[ROW][C]34[/C][C]0.072491[/C][C]0.4917[/C][C]0.312649[/C][/ROW]
[ROW][C]35[/C][C]0.001094[/C][C]0.0074[/C][C]0.497056[/C][/ROW]
[ROW][C]36[/C][C]-0.136036[/C][C]-0.9226[/C][C]0.180504[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69759&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69759&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.165884-1.12510.133196
2-0.138582-0.93990.176087
3-0.22467-1.52380.067204
4-0.011645-0.0790.468697
50.0037080.02520.490021
60.0465890.3160.376722
7-0.025492-0.17290.431747
8-0.085655-0.58090.282058
90.2562131.73770.044475
100.11060.75010.2285
11-0.040127-0.27220.393362
12-0.358989-2.43480.009419
13-0.064116-0.43490.332849
140.0383690.26020.397924
150.2193481.48770.071828
160.0219130.14860.441251
17-0.020367-0.13810.445368
18-0.166665-1.13040.132088
190.1049070.71150.240179
200.0620.42050.338037
21-0.076609-0.51960.302922
22-0.148375-1.00630.15976
230.1275820.86530.195682
240.0313140.21240.416373
250.1556741.05580.148279
260.0206670.14020.444568
27-0.209511-1.4210.081034
28-0.074247-0.50360.308484
290.067680.4590.324188
300.1501931.01870.156847
31-0.095068-0.64480.261136
320.0059260.04020.484057
33-0.010526-0.07140.471698
340.0724910.49170.312649
350.0010940.00740.497056
36-0.136036-0.92260.180504







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.165884-1.12510.133196
2-0.170799-1.15840.126337
3-0.296488-2.01090.02511
4-0.171275-1.16160.125686
5-0.161683-1.09660.139264
6-0.121492-0.8240.207096
7-0.148657-1.00820.159307
8-0.235373-1.59640.058626
90.139250.94440.17494
100.1816071.23170.112157
110.1301130.88250.191055
12-0.199164-1.35080.091685
13-0.15263-1.03520.152996
14-0.138486-0.93930.176253
15-0.009696-0.06580.473925
16-0.06153-0.41730.339193
17-0.019351-0.13120.448077
18-0.233351-1.58270.060175
19-0.096981-0.65780.256987
20-0.059021-0.40030.345394
21-0.008576-0.05820.476935
22-0.092472-0.62720.266822
230.1238410.83990.202647
24-0.12474-0.8460.200958
250.0450360.30540.380701
260.0744690.50510.307959
270.0108990.07390.470697
28-0.040763-0.27650.391713
29-0.011039-0.07490.470321
30-0.001756-0.01190.495275
31-0.03156-0.2140.415727
32-0.044413-0.30120.382301
330.0484180.32840.372055
34-0.020354-0.1380.445403
350.0257160.17440.431152
36-0.180898-1.22690.11305

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.165884 & -1.1251 & 0.133196 \tabularnewline
2 & -0.170799 & -1.1584 & 0.126337 \tabularnewline
3 & -0.296488 & -2.0109 & 0.02511 \tabularnewline
4 & -0.171275 & -1.1616 & 0.125686 \tabularnewline
5 & -0.161683 & -1.0966 & 0.139264 \tabularnewline
6 & -0.121492 & -0.824 & 0.207096 \tabularnewline
7 & -0.148657 & -1.0082 & 0.159307 \tabularnewline
8 & -0.235373 & -1.5964 & 0.058626 \tabularnewline
9 & 0.13925 & 0.9444 & 0.17494 \tabularnewline
10 & 0.181607 & 1.2317 & 0.112157 \tabularnewline
11 & 0.130113 & 0.8825 & 0.191055 \tabularnewline
12 & -0.199164 & -1.3508 & 0.091685 \tabularnewline
13 & -0.15263 & -1.0352 & 0.152996 \tabularnewline
14 & -0.138486 & -0.9393 & 0.176253 \tabularnewline
15 & -0.009696 & -0.0658 & 0.473925 \tabularnewline
16 & -0.06153 & -0.4173 & 0.339193 \tabularnewline
17 & -0.019351 & -0.1312 & 0.448077 \tabularnewline
18 & -0.233351 & -1.5827 & 0.060175 \tabularnewline
19 & -0.096981 & -0.6578 & 0.256987 \tabularnewline
20 & -0.059021 & -0.4003 & 0.345394 \tabularnewline
21 & -0.008576 & -0.0582 & 0.476935 \tabularnewline
22 & -0.092472 & -0.6272 & 0.266822 \tabularnewline
23 & 0.123841 & 0.8399 & 0.202647 \tabularnewline
24 & -0.12474 & -0.846 & 0.200958 \tabularnewline
25 & 0.045036 & 0.3054 & 0.380701 \tabularnewline
26 & 0.074469 & 0.5051 & 0.307959 \tabularnewline
27 & 0.010899 & 0.0739 & 0.470697 \tabularnewline
28 & -0.040763 & -0.2765 & 0.391713 \tabularnewline
29 & -0.011039 & -0.0749 & 0.470321 \tabularnewline
30 & -0.001756 & -0.0119 & 0.495275 \tabularnewline
31 & -0.03156 & -0.214 & 0.415727 \tabularnewline
32 & -0.044413 & -0.3012 & 0.382301 \tabularnewline
33 & 0.048418 & 0.3284 & 0.372055 \tabularnewline
34 & -0.020354 & -0.138 & 0.445403 \tabularnewline
35 & 0.025716 & 0.1744 & 0.431152 \tabularnewline
36 & -0.180898 & -1.2269 & 0.11305 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69759&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]-0.165884[/C][C]-1.1251[/C][C]0.133196[/C][/ROW]
[ROW][C]2[/C][C]-0.170799[/C][C]-1.1584[/C][C]0.126337[/C][/ROW]
[ROW][C]3[/C][C]-0.296488[/C][C]-2.0109[/C][C]0.02511[/C][/ROW]
[ROW][C]4[/C][C]-0.171275[/C][C]-1.1616[/C][C]0.125686[/C][/ROW]
[ROW][C]5[/C][C]-0.161683[/C][C]-1.0966[/C][C]0.139264[/C][/ROW]
[ROW][C]6[/C][C]-0.121492[/C][C]-0.824[/C][C]0.207096[/C][/ROW]
[ROW][C]7[/C][C]-0.148657[/C][C]-1.0082[/C][C]0.159307[/C][/ROW]
[ROW][C]8[/C][C]-0.235373[/C][C]-1.5964[/C][C]0.058626[/C][/ROW]
[ROW][C]9[/C][C]0.13925[/C][C]0.9444[/C][C]0.17494[/C][/ROW]
[ROW][C]10[/C][C]0.181607[/C][C]1.2317[/C][C]0.112157[/C][/ROW]
[ROW][C]11[/C][C]0.130113[/C][C]0.8825[/C][C]0.191055[/C][/ROW]
[ROW][C]12[/C][C]-0.199164[/C][C]-1.3508[/C][C]0.091685[/C][/ROW]
[ROW][C]13[/C][C]-0.15263[/C][C]-1.0352[/C][C]0.152996[/C][/ROW]
[ROW][C]14[/C][C]-0.138486[/C][C]-0.9393[/C][C]0.176253[/C][/ROW]
[ROW][C]15[/C][C]-0.009696[/C][C]-0.0658[/C][C]0.473925[/C][/ROW]
[ROW][C]16[/C][C]-0.06153[/C][C]-0.4173[/C][C]0.339193[/C][/ROW]
[ROW][C]17[/C][C]-0.019351[/C][C]-0.1312[/C][C]0.448077[/C][/ROW]
[ROW][C]18[/C][C]-0.233351[/C][C]-1.5827[/C][C]0.060175[/C][/ROW]
[ROW][C]19[/C][C]-0.096981[/C][C]-0.6578[/C][C]0.256987[/C][/ROW]
[ROW][C]20[/C][C]-0.059021[/C][C]-0.4003[/C][C]0.345394[/C][/ROW]
[ROW][C]21[/C][C]-0.008576[/C][C]-0.0582[/C][C]0.476935[/C][/ROW]
[ROW][C]22[/C][C]-0.092472[/C][C]-0.6272[/C][C]0.266822[/C][/ROW]
[ROW][C]23[/C][C]0.123841[/C][C]0.8399[/C][C]0.202647[/C][/ROW]
[ROW][C]24[/C][C]-0.12474[/C][C]-0.846[/C][C]0.200958[/C][/ROW]
[ROW][C]25[/C][C]0.045036[/C][C]0.3054[/C][C]0.380701[/C][/ROW]
[ROW][C]26[/C][C]0.074469[/C][C]0.5051[/C][C]0.307959[/C][/ROW]
[ROW][C]27[/C][C]0.010899[/C][C]0.0739[/C][C]0.470697[/C][/ROW]
[ROW][C]28[/C][C]-0.040763[/C][C]-0.2765[/C][C]0.391713[/C][/ROW]
[ROW][C]29[/C][C]-0.011039[/C][C]-0.0749[/C][C]0.470321[/C][/ROW]
[ROW][C]30[/C][C]-0.001756[/C][C]-0.0119[/C][C]0.495275[/C][/ROW]
[ROW][C]31[/C][C]-0.03156[/C][C]-0.214[/C][C]0.415727[/C][/ROW]
[ROW][C]32[/C][C]-0.044413[/C][C]-0.3012[/C][C]0.382301[/C][/ROW]
[ROW][C]33[/C][C]0.048418[/C][C]0.3284[/C][C]0.372055[/C][/ROW]
[ROW][C]34[/C][C]-0.020354[/C][C]-0.138[/C][C]0.445403[/C][/ROW]
[ROW][C]35[/C][C]0.025716[/C][C]0.1744[/C][C]0.431152[/C][/ROW]
[ROW][C]36[/C][C]-0.180898[/C][C]-1.2269[/C][C]0.11305[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69759&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69759&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.165884-1.12510.133196
2-0.170799-1.15840.126337
3-0.296488-2.01090.02511
4-0.171275-1.16160.125686
5-0.161683-1.09660.139264
6-0.121492-0.8240.207096
7-0.148657-1.00820.159307
8-0.235373-1.59640.058626
90.139250.94440.17494
100.1816071.23170.112157
110.1301130.88250.191055
12-0.199164-1.35080.091685
13-0.15263-1.03520.152996
14-0.138486-0.93930.176253
15-0.009696-0.06580.473925
16-0.06153-0.41730.339193
17-0.019351-0.13120.448077
18-0.233351-1.58270.060175
19-0.096981-0.65780.256987
20-0.059021-0.40030.345394
21-0.008576-0.05820.476935
22-0.092472-0.62720.266822
230.1238410.83990.202647
24-0.12474-0.8460.200958
250.0450360.30540.380701
260.0744690.50510.307959
270.0108990.07390.470697
28-0.040763-0.27650.391713
29-0.011039-0.07490.470321
30-0.001756-0.01190.495275
31-0.03156-0.2140.415727
32-0.044413-0.30120.382301
330.0484180.32840.372055
34-0.020354-0.1380.445403
350.0257160.17440.431152
36-0.180898-1.22690.11305



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 2 ; 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')