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 computationThu, 26 Nov 2009 12:06:43 -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/26/t1259262446wjoexhrnv61qhu4.htm/, Retrieved Sun, 28 Apr 2024 22:16:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60294, Retrieved Sun, 28 Apr 2024 22:16:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact96
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]
-    D          [(Partial) Autocorrelation Function] [] [2009-11-26 19:06:43] [aa8eb70c35ea8a87edcd21d6427e653e] [Current]
Feedback Forum

Post a new message
Dataseries X:
10872
10625
10407
10463
10556
10646
10702
11353
11346
11451
11964
12574
13031
13812
14544
14931
14886
16005
17064
15168
16050
15839
15137
14954
15648
15305
15579
16348
15928
16171
15937
15713
15594
15683
16438
17032
17696
17745
19394
20148
20108
18584
18441
18391
19178
18079
18483
19644
19195
19650
20830
23595
22937
21814
21928
21777
21383
21467
22052
22680




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=60294&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=60294&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60294&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
10.7997285.54071e-06
20.6854144.74879e-06
30.5844374.04919.3e-05
40.4372483.02930.001969
50.1930331.33740.093702
60.0479710.33240.370534
7-0.062502-0.4330.333466
8-0.253242-1.75450.042863
9-0.345242-2.39190.010363
10-0.410119-2.84140.003287
11-0.413071-2.86180.003111
12-0.471899-3.26940.000999
13-0.379252-2.62750.005757
14-0.349996-2.42480.009564
15-0.297021-2.05780.02253
16-0.195723-1.3560.090721
17-0.100013-0.69290.245853
18-0.023918-0.16570.43454
190.0172050.11920.452808
200.0887330.61480.270808
210.0420260.29120.386091
220.0530080.36730.357523
230.038210.26470.396178
24-0.001158-0.0080.496817
25-0.056564-0.39190.348438
26-0.053465-0.37040.356351
27-0.091849-0.63630.263786
28-0.143843-0.99660.161984
29-0.108694-0.75310.227548
30-0.092195-0.63870.263013
31-0.080934-0.56070.288795
32-0.094842-0.65710.257133
33-0.019113-0.13240.447602
340.0099940.06920.472544
350.0210890.14610.442225
360.0635880.44060.330757

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.799728 & 5.5407 & 1e-06 \tabularnewline
2 & 0.685414 & 4.7487 & 9e-06 \tabularnewline
3 & 0.584437 & 4.0491 & 9.3e-05 \tabularnewline
4 & 0.437248 & 3.0293 & 0.001969 \tabularnewline
5 & 0.193033 & 1.3374 & 0.093702 \tabularnewline
6 & 0.047971 & 0.3324 & 0.370534 \tabularnewline
7 & -0.062502 & -0.433 & 0.333466 \tabularnewline
8 & -0.253242 & -1.7545 & 0.042863 \tabularnewline
9 & -0.345242 & -2.3919 & 0.010363 \tabularnewline
10 & -0.410119 & -2.8414 & 0.003287 \tabularnewline
11 & -0.413071 & -2.8618 & 0.003111 \tabularnewline
12 & -0.471899 & -3.2694 & 0.000999 \tabularnewline
13 & -0.379252 & -2.6275 & 0.005757 \tabularnewline
14 & -0.349996 & -2.4248 & 0.009564 \tabularnewline
15 & -0.297021 & -2.0578 & 0.02253 \tabularnewline
16 & -0.195723 & -1.356 & 0.090721 \tabularnewline
17 & -0.100013 & -0.6929 & 0.245853 \tabularnewline
18 & -0.023918 & -0.1657 & 0.43454 \tabularnewline
19 & 0.017205 & 0.1192 & 0.452808 \tabularnewline
20 & 0.088733 & 0.6148 & 0.270808 \tabularnewline
21 & 0.042026 & 0.2912 & 0.386091 \tabularnewline
22 & 0.053008 & 0.3673 & 0.357523 \tabularnewline
23 & 0.03821 & 0.2647 & 0.396178 \tabularnewline
24 & -0.001158 & -0.008 & 0.496817 \tabularnewline
25 & -0.056564 & -0.3919 & 0.348438 \tabularnewline
26 & -0.053465 & -0.3704 & 0.356351 \tabularnewline
27 & -0.091849 & -0.6363 & 0.263786 \tabularnewline
28 & -0.143843 & -0.9966 & 0.161984 \tabularnewline
29 & -0.108694 & -0.7531 & 0.227548 \tabularnewline
30 & -0.092195 & -0.6387 & 0.263013 \tabularnewline
31 & -0.080934 & -0.5607 & 0.288795 \tabularnewline
32 & -0.094842 & -0.6571 & 0.257133 \tabularnewline
33 & -0.019113 & -0.1324 & 0.447602 \tabularnewline
34 & 0.009994 & 0.0692 & 0.472544 \tabularnewline
35 & 0.021089 & 0.1461 & 0.442225 \tabularnewline
36 & 0.063588 & 0.4406 & 0.330757 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60294&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]0.799728[/C][C]5.5407[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.685414[/C][C]4.7487[/C][C]9e-06[/C][/ROW]
[ROW][C]3[/C][C]0.584437[/C][C]4.0491[/C][C]9.3e-05[/C][/ROW]
[ROW][C]4[/C][C]0.437248[/C][C]3.0293[/C][C]0.001969[/C][/ROW]
[ROW][C]5[/C][C]0.193033[/C][C]1.3374[/C][C]0.093702[/C][/ROW]
[ROW][C]6[/C][C]0.047971[/C][C]0.3324[/C][C]0.370534[/C][/ROW]
[ROW][C]7[/C][C]-0.062502[/C][C]-0.433[/C][C]0.333466[/C][/ROW]
[ROW][C]8[/C][C]-0.253242[/C][C]-1.7545[/C][C]0.042863[/C][/ROW]
[ROW][C]9[/C][C]-0.345242[/C][C]-2.3919[/C][C]0.010363[/C][/ROW]
[ROW][C]10[/C][C]-0.410119[/C][C]-2.8414[/C][C]0.003287[/C][/ROW]
[ROW][C]11[/C][C]-0.413071[/C][C]-2.8618[/C][C]0.003111[/C][/ROW]
[ROW][C]12[/C][C]-0.471899[/C][C]-3.2694[/C][C]0.000999[/C][/ROW]
[ROW][C]13[/C][C]-0.379252[/C][C]-2.6275[/C][C]0.005757[/C][/ROW]
[ROW][C]14[/C][C]-0.349996[/C][C]-2.4248[/C][C]0.009564[/C][/ROW]
[ROW][C]15[/C][C]-0.297021[/C][C]-2.0578[/C][C]0.02253[/C][/ROW]
[ROW][C]16[/C][C]-0.195723[/C][C]-1.356[/C][C]0.090721[/C][/ROW]
[ROW][C]17[/C][C]-0.100013[/C][C]-0.6929[/C][C]0.245853[/C][/ROW]
[ROW][C]18[/C][C]-0.023918[/C][C]-0.1657[/C][C]0.43454[/C][/ROW]
[ROW][C]19[/C][C]0.017205[/C][C]0.1192[/C][C]0.452808[/C][/ROW]
[ROW][C]20[/C][C]0.088733[/C][C]0.6148[/C][C]0.270808[/C][/ROW]
[ROW][C]21[/C][C]0.042026[/C][C]0.2912[/C][C]0.386091[/C][/ROW]
[ROW][C]22[/C][C]0.053008[/C][C]0.3673[/C][C]0.357523[/C][/ROW]
[ROW][C]23[/C][C]0.03821[/C][C]0.2647[/C][C]0.396178[/C][/ROW]
[ROW][C]24[/C][C]-0.001158[/C][C]-0.008[/C][C]0.496817[/C][/ROW]
[ROW][C]25[/C][C]-0.056564[/C][C]-0.3919[/C][C]0.348438[/C][/ROW]
[ROW][C]26[/C][C]-0.053465[/C][C]-0.3704[/C][C]0.356351[/C][/ROW]
[ROW][C]27[/C][C]-0.091849[/C][C]-0.6363[/C][C]0.263786[/C][/ROW]
[ROW][C]28[/C][C]-0.143843[/C][C]-0.9966[/C][C]0.161984[/C][/ROW]
[ROW][C]29[/C][C]-0.108694[/C][C]-0.7531[/C][C]0.227548[/C][/ROW]
[ROW][C]30[/C][C]-0.092195[/C][C]-0.6387[/C][C]0.263013[/C][/ROW]
[ROW][C]31[/C][C]-0.080934[/C][C]-0.5607[/C][C]0.288795[/C][/ROW]
[ROW][C]32[/C][C]-0.094842[/C][C]-0.6571[/C][C]0.257133[/C][/ROW]
[ROW][C]33[/C][C]-0.019113[/C][C]-0.1324[/C][C]0.447602[/C][/ROW]
[ROW][C]34[/C][C]0.009994[/C][C]0.0692[/C][C]0.472544[/C][/ROW]
[ROW][C]35[/C][C]0.021089[/C][C]0.1461[/C][C]0.442225[/C][/ROW]
[ROW][C]36[/C][C]0.063588[/C][C]0.4406[/C][C]0.330757[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60294&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60294&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
10.7997285.54071e-06
20.6854144.74879e-06
30.5844374.04919.3e-05
40.4372483.02930.001969
50.1930331.33740.093702
60.0479710.33240.370534
7-0.062502-0.4330.333466
8-0.253242-1.75450.042863
9-0.345242-2.39190.010363
10-0.410119-2.84140.003287
11-0.413071-2.86180.003111
12-0.471899-3.26940.000999
13-0.379252-2.62750.005757
14-0.349996-2.42480.009564
15-0.297021-2.05780.02253
16-0.195723-1.3560.090721
17-0.100013-0.69290.245853
18-0.023918-0.16570.43454
190.0172050.11920.452808
200.0887330.61480.270808
210.0420260.29120.386091
220.0530080.36730.357523
230.038210.26470.396178
24-0.001158-0.0080.496817
25-0.056564-0.39190.348438
26-0.053465-0.37040.356351
27-0.091849-0.63630.263786
28-0.143843-0.99660.161984
29-0.108694-0.75310.227548
30-0.092195-0.63870.263013
31-0.080934-0.56070.288795
32-0.094842-0.65710.257133
33-0.019113-0.13240.447602
340.0099940.06920.472544
350.0210890.14610.442225
360.0635880.44060.330757







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7997285.54071e-06
20.1272050.88130.191273
30.0120950.08380.466784
4-0.171663-1.18930.120083
5-0.426258-2.95320.002429
6-0.054222-0.37570.354412
70.049760.34480.365894
8-0.23532-1.63030.054787
90.0745230.51630.304005
10-0.106516-0.7380.232065
110.1085990.75240.227744
12-0.116661-0.80830.211467
130.1640441.13650.130688
14-0.166227-1.15170.127584
15-0.017366-0.12030.452368
160.1120110.7760.220768
17-0.077305-0.53560.297359
180.0513640.35590.361752
19-0.096571-0.66910.25333
20-0.128489-0.89020.1889
21-0.196313-1.36010.090077
220.0062560.04330.482804
230.0469640.32540.373157
24-0.149734-1.03740.152377
250.1017680.70510.242087
26-0.006301-0.04370.482679
27-0.131526-0.91120.183362
280.0666530.46180.32316
29-0.013094-0.09070.464047
300.012370.08570.466031
31-0.034503-0.2390.406046
32-0.129803-0.89930.18649
33-0.003515-0.02440.490337
340.0495460.34330.366448
35-0.046524-0.32230.374301
36-0.076189-0.52790.300016

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.799728 & 5.5407 & 1e-06 \tabularnewline
2 & 0.127205 & 0.8813 & 0.191273 \tabularnewline
3 & 0.012095 & 0.0838 & 0.466784 \tabularnewline
4 & -0.171663 & -1.1893 & 0.120083 \tabularnewline
5 & -0.426258 & -2.9532 & 0.002429 \tabularnewline
6 & -0.054222 & -0.3757 & 0.354412 \tabularnewline
7 & 0.04976 & 0.3448 & 0.365894 \tabularnewline
8 & -0.23532 & -1.6303 & 0.054787 \tabularnewline
9 & 0.074523 & 0.5163 & 0.304005 \tabularnewline
10 & -0.106516 & -0.738 & 0.232065 \tabularnewline
11 & 0.108599 & 0.7524 & 0.227744 \tabularnewline
12 & -0.116661 & -0.8083 & 0.211467 \tabularnewline
13 & 0.164044 & 1.1365 & 0.130688 \tabularnewline
14 & -0.166227 & -1.1517 & 0.127584 \tabularnewline
15 & -0.017366 & -0.1203 & 0.452368 \tabularnewline
16 & 0.112011 & 0.776 & 0.220768 \tabularnewline
17 & -0.077305 & -0.5356 & 0.297359 \tabularnewline
18 & 0.051364 & 0.3559 & 0.361752 \tabularnewline
19 & -0.096571 & -0.6691 & 0.25333 \tabularnewline
20 & -0.128489 & -0.8902 & 0.1889 \tabularnewline
21 & -0.196313 & -1.3601 & 0.090077 \tabularnewline
22 & 0.006256 & 0.0433 & 0.482804 \tabularnewline
23 & 0.046964 & 0.3254 & 0.373157 \tabularnewline
24 & -0.149734 & -1.0374 & 0.152377 \tabularnewline
25 & 0.101768 & 0.7051 & 0.242087 \tabularnewline
26 & -0.006301 & -0.0437 & 0.482679 \tabularnewline
27 & -0.131526 & -0.9112 & 0.183362 \tabularnewline
28 & 0.066653 & 0.4618 & 0.32316 \tabularnewline
29 & -0.013094 & -0.0907 & 0.464047 \tabularnewline
30 & 0.01237 & 0.0857 & 0.466031 \tabularnewline
31 & -0.034503 & -0.239 & 0.406046 \tabularnewline
32 & -0.129803 & -0.8993 & 0.18649 \tabularnewline
33 & -0.003515 & -0.0244 & 0.490337 \tabularnewline
34 & 0.049546 & 0.3433 & 0.366448 \tabularnewline
35 & -0.046524 & -0.3223 & 0.374301 \tabularnewline
36 & -0.076189 & -0.5279 & 0.300016 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60294&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]0.799728[/C][C]5.5407[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.127205[/C][C]0.8813[/C][C]0.191273[/C][/ROW]
[ROW][C]3[/C][C]0.012095[/C][C]0.0838[/C][C]0.466784[/C][/ROW]
[ROW][C]4[/C][C]-0.171663[/C][C]-1.1893[/C][C]0.120083[/C][/ROW]
[ROW][C]5[/C][C]-0.426258[/C][C]-2.9532[/C][C]0.002429[/C][/ROW]
[ROW][C]6[/C][C]-0.054222[/C][C]-0.3757[/C][C]0.354412[/C][/ROW]
[ROW][C]7[/C][C]0.04976[/C][C]0.3448[/C][C]0.365894[/C][/ROW]
[ROW][C]8[/C][C]-0.23532[/C][C]-1.6303[/C][C]0.054787[/C][/ROW]
[ROW][C]9[/C][C]0.074523[/C][C]0.5163[/C][C]0.304005[/C][/ROW]
[ROW][C]10[/C][C]-0.106516[/C][C]-0.738[/C][C]0.232065[/C][/ROW]
[ROW][C]11[/C][C]0.108599[/C][C]0.7524[/C][C]0.227744[/C][/ROW]
[ROW][C]12[/C][C]-0.116661[/C][C]-0.8083[/C][C]0.211467[/C][/ROW]
[ROW][C]13[/C][C]0.164044[/C][C]1.1365[/C][C]0.130688[/C][/ROW]
[ROW][C]14[/C][C]-0.166227[/C][C]-1.1517[/C][C]0.127584[/C][/ROW]
[ROW][C]15[/C][C]-0.017366[/C][C]-0.1203[/C][C]0.452368[/C][/ROW]
[ROW][C]16[/C][C]0.112011[/C][C]0.776[/C][C]0.220768[/C][/ROW]
[ROW][C]17[/C][C]-0.077305[/C][C]-0.5356[/C][C]0.297359[/C][/ROW]
[ROW][C]18[/C][C]0.051364[/C][C]0.3559[/C][C]0.361752[/C][/ROW]
[ROW][C]19[/C][C]-0.096571[/C][C]-0.6691[/C][C]0.25333[/C][/ROW]
[ROW][C]20[/C][C]-0.128489[/C][C]-0.8902[/C][C]0.1889[/C][/ROW]
[ROW][C]21[/C][C]-0.196313[/C][C]-1.3601[/C][C]0.090077[/C][/ROW]
[ROW][C]22[/C][C]0.006256[/C][C]0.0433[/C][C]0.482804[/C][/ROW]
[ROW][C]23[/C][C]0.046964[/C][C]0.3254[/C][C]0.373157[/C][/ROW]
[ROW][C]24[/C][C]-0.149734[/C][C]-1.0374[/C][C]0.152377[/C][/ROW]
[ROW][C]25[/C][C]0.101768[/C][C]0.7051[/C][C]0.242087[/C][/ROW]
[ROW][C]26[/C][C]-0.006301[/C][C]-0.0437[/C][C]0.482679[/C][/ROW]
[ROW][C]27[/C][C]-0.131526[/C][C]-0.9112[/C][C]0.183362[/C][/ROW]
[ROW][C]28[/C][C]0.066653[/C][C]0.4618[/C][C]0.32316[/C][/ROW]
[ROW][C]29[/C][C]-0.013094[/C][C]-0.0907[/C][C]0.464047[/C][/ROW]
[ROW][C]30[/C][C]0.01237[/C][C]0.0857[/C][C]0.466031[/C][/ROW]
[ROW][C]31[/C][C]-0.034503[/C][C]-0.239[/C][C]0.406046[/C][/ROW]
[ROW][C]32[/C][C]-0.129803[/C][C]-0.8993[/C][C]0.18649[/C][/ROW]
[ROW][C]33[/C][C]-0.003515[/C][C]-0.0244[/C][C]0.490337[/C][/ROW]
[ROW][C]34[/C][C]0.049546[/C][C]0.3433[/C][C]0.366448[/C][/ROW]
[ROW][C]35[/C][C]-0.046524[/C][C]-0.3223[/C][C]0.374301[/C][/ROW]
[ROW][C]36[/C][C]-0.076189[/C][C]-0.5279[/C][C]0.300016[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60294&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60294&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
10.7997285.54071e-06
20.1272050.88130.191273
30.0120950.08380.466784
4-0.171663-1.18930.120083
5-0.426258-2.95320.002429
6-0.054222-0.37570.354412
70.049760.34480.365894
8-0.23532-1.63030.054787
90.0745230.51630.304005
10-0.106516-0.7380.232065
110.1085990.75240.227744
12-0.116661-0.80830.211467
130.1640441.13650.130688
14-0.166227-1.15170.127584
15-0.017366-0.12030.452368
160.1120110.7760.220768
17-0.077305-0.53560.297359
180.0513640.35590.361752
19-0.096571-0.66910.25333
20-0.128489-0.89020.1889
21-0.196313-1.36010.090077
220.0062560.04330.482804
230.0469640.32540.373157
24-0.149734-1.03740.152377
250.1017680.70510.242087
26-0.006301-0.04370.482679
27-0.131526-0.91120.183362
280.0666530.46180.32316
29-0.013094-0.09070.464047
300.012370.08570.466031
31-0.034503-0.2390.406046
32-0.129803-0.89930.18649
33-0.003515-0.02440.490337
340.0495460.34330.366448
35-0.046524-0.32230.374301
36-0.076189-0.52790.300016



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; 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')