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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 computationThu, 17 Dec 2009 07:42:17 -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/17/t1261061021fmnzjbmxfek0ukw.htm/, Retrieved Tue, 30 Apr 2024 00:21:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68916, Retrieved Tue, 30 Apr 2024 00:21:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact89

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]
-   PD        [(Partial) Autocorrelation Function] [ACF] [2009-11-25 16:33:06] [3b0db66ac8145b1be856a517e2900332]
-   P             [(Partial) Autocorrelation Function] [ACF (1)] [2009-12-17 14:42:17] [2ecea65fec1cd5f6b1ab182881aa2a91] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
21
19
25
21
23
23
19
18
19
19
22
23
20
14
14
14
15
11
17
16
20
24
23
20
21
19
23
23
23
23
27
26
17
24
26
24
27
27
26
24
23
23
24
17
21
19
22
22
18
16
14
12
14
16
8
3
0
5
1
1
3

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=68916&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=68916&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68916&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
10.8363696.53230
20.7126545.5660
30.6025594.70617e-06
40.5148324.0218.1e-05
50.3979273.10790.00143
60.3087792.41160.009453
70.2311331.80520.037989
80.1931641.50870.068274
90.1259420.98360.16459
100.058440.45640.324851
11-0.003393-0.02650.489474
12-0.080428-0.62820.266121
13-0.130265-1.01740.156491
14-0.161563-1.26180.105903
15-0.150257-1.17350.12257
16-0.159962-1.24930.108156
17-0.209368-1.63520.053577
18-0.24569-1.91890.02984
19-0.255343-1.99430.025298
20-0.291548-2.27710.013151
21-0.328615-2.56660.006371
22-0.306401-2.39310.009901
23-0.271266-2.11870.0191
24-0.23357-1.82420.036507
25-0.211356-1.65070.051966
26-0.161437-1.26090.10608
27-0.165712-1.29430.100229
28-0.16494-1.28820.101266
29-0.185029-1.44510.076771
30-0.153799-1.20120.117156
31-0.086012-0.67180.252132
32-0.072535-0.56650.286562
33-0.056764-0.44330.329544
34-0.028654-0.22380.411832
350.0039960.03120.487603
360.0208960.16320.43545

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.836369 & 6.5323 & 0 \tabularnewline
2 & 0.712654 & 5.566 & 0 \tabularnewline
3 & 0.602559 & 4.7061 & 7e-06 \tabularnewline
4 & 0.514832 & 4.021 & 8.1e-05 \tabularnewline
5 & 0.397927 & 3.1079 & 0.00143 \tabularnewline
6 & 0.308779 & 2.4116 & 0.009453 \tabularnewline
7 & 0.231133 & 1.8052 & 0.037989 \tabularnewline
8 & 0.193164 & 1.5087 & 0.068274 \tabularnewline
9 & 0.125942 & 0.9836 & 0.16459 \tabularnewline
10 & 0.05844 & 0.4564 & 0.324851 \tabularnewline
11 & -0.003393 & -0.0265 & 0.489474 \tabularnewline
12 & -0.080428 & -0.6282 & 0.266121 \tabularnewline
13 & -0.130265 & -1.0174 & 0.156491 \tabularnewline
14 & -0.161563 & -1.2618 & 0.105903 \tabularnewline
15 & -0.150257 & -1.1735 & 0.12257 \tabularnewline
16 & -0.159962 & -1.2493 & 0.108156 \tabularnewline
17 & -0.209368 & -1.6352 & 0.053577 \tabularnewline
18 & -0.24569 & -1.9189 & 0.02984 \tabularnewline
19 & -0.255343 & -1.9943 & 0.025298 \tabularnewline
20 & -0.291548 & -2.2771 & 0.013151 \tabularnewline
21 & -0.328615 & -2.5666 & 0.006371 \tabularnewline
22 & -0.306401 & -2.3931 & 0.009901 \tabularnewline
23 & -0.271266 & -2.1187 & 0.0191 \tabularnewline
24 & -0.23357 & -1.8242 & 0.036507 \tabularnewline
25 & -0.211356 & -1.6507 & 0.051966 \tabularnewline
26 & -0.161437 & -1.2609 & 0.10608 \tabularnewline
27 & -0.165712 & -1.2943 & 0.100229 \tabularnewline
28 & -0.16494 & -1.2882 & 0.101266 \tabularnewline
29 & -0.185029 & -1.4451 & 0.076771 \tabularnewline
30 & -0.153799 & -1.2012 & 0.117156 \tabularnewline
31 & -0.086012 & -0.6718 & 0.252132 \tabularnewline
32 & -0.072535 & -0.5665 & 0.286562 \tabularnewline
33 & -0.056764 & -0.4433 & 0.329544 \tabularnewline
34 & -0.028654 & -0.2238 & 0.411832 \tabularnewline
35 & 0.003996 & 0.0312 & 0.487603 \tabularnewline
36 & 0.020896 & 0.1632 & 0.43545 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68916&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]0.836369[/C][C]6.5323[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.712654[/C][C]5.566[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.602559[/C][C]4.7061[/C][C]7e-06[/C][/ROW]
[ROW][C]4[/C][C]0.514832[/C][C]4.021[/C][C]8.1e-05[/C][/ROW]
[ROW][C]5[/C][C]0.397927[/C][C]3.1079[/C][C]0.00143[/C][/ROW]
[ROW][C]6[/C][C]0.308779[/C][C]2.4116[/C][C]0.009453[/C][/ROW]
[ROW][C]7[/C][C]0.231133[/C][C]1.8052[/C][C]0.037989[/C][/ROW]
[ROW][C]8[/C][C]0.193164[/C][C]1.5087[/C][C]0.068274[/C][/ROW]
[ROW][C]9[/C][C]0.125942[/C][C]0.9836[/C][C]0.16459[/C][/ROW]
[ROW][C]10[/C][C]0.05844[/C][C]0.4564[/C][C]0.324851[/C][/ROW]
[ROW][C]11[/C][C]-0.003393[/C][C]-0.0265[/C][C]0.489474[/C][/ROW]
[ROW][C]12[/C][C]-0.080428[/C][C]-0.6282[/C][C]0.266121[/C][/ROW]
[ROW][C]13[/C][C]-0.130265[/C][C]-1.0174[/C][C]0.156491[/C][/ROW]
[ROW][C]14[/C][C]-0.161563[/C][C]-1.2618[/C][C]0.105903[/C][/ROW]
[ROW][C]15[/C][C]-0.150257[/C][C]-1.1735[/C][C]0.12257[/C][/ROW]
[ROW][C]16[/C][C]-0.159962[/C][C]-1.2493[/C][C]0.108156[/C][/ROW]
[ROW][C]17[/C][C]-0.209368[/C][C]-1.6352[/C][C]0.053577[/C][/ROW]
[ROW][C]18[/C][C]-0.24569[/C][C]-1.9189[/C][C]0.02984[/C][/ROW]
[ROW][C]19[/C][C]-0.255343[/C][C]-1.9943[/C][C]0.025298[/C][/ROW]
[ROW][C]20[/C][C]-0.291548[/C][C]-2.2771[/C][C]0.013151[/C][/ROW]
[ROW][C]21[/C][C]-0.328615[/C][C]-2.5666[/C][C]0.006371[/C][/ROW]
[ROW][C]22[/C][C]-0.306401[/C][C]-2.3931[/C][C]0.009901[/C][/ROW]
[ROW][C]23[/C][C]-0.271266[/C][C]-2.1187[/C][C]0.0191[/C][/ROW]
[ROW][C]24[/C][C]-0.23357[/C][C]-1.8242[/C][C]0.036507[/C][/ROW]
[ROW][C]25[/C][C]-0.211356[/C][C]-1.6507[/C][C]0.051966[/C][/ROW]
[ROW][C]26[/C][C]-0.161437[/C][C]-1.2609[/C][C]0.10608[/C][/ROW]
[ROW][C]27[/C][C]-0.165712[/C][C]-1.2943[/C][C]0.100229[/C][/ROW]
[ROW][C]28[/C][C]-0.16494[/C][C]-1.2882[/C][C]0.101266[/C][/ROW]
[ROW][C]29[/C][C]-0.185029[/C][C]-1.4451[/C][C]0.076771[/C][/ROW]
[ROW][C]30[/C][C]-0.153799[/C][C]-1.2012[/C][C]0.117156[/C][/ROW]
[ROW][C]31[/C][C]-0.086012[/C][C]-0.6718[/C][C]0.252132[/C][/ROW]
[ROW][C]32[/C][C]-0.072535[/C][C]-0.5665[/C][C]0.286562[/C][/ROW]
[ROW][C]33[/C][C]-0.056764[/C][C]-0.4433[/C][C]0.329544[/C][/ROW]
[ROW][C]34[/C][C]-0.028654[/C][C]-0.2238[/C][C]0.411832[/C][/ROW]
[ROW][C]35[/C][C]0.003996[/C][C]0.0312[/C][C]0.487603[/C][/ROW]
[ROW][C]36[/C][C]0.020896[/C][C]0.1632[/C][C]0.43545[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68916&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68916&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
10.8363696.53230
20.7126545.5660
30.6025594.70617e-06
40.5148324.0218.1e-05
50.3979273.10790.00143
60.3087792.41160.009453
70.2311331.80520.037989
80.1931641.50870.068274
90.1259420.98360.16459
100.058440.45640.324851
11-0.003393-0.02650.489474
12-0.080428-0.62820.266121
13-0.130265-1.01740.156491
14-0.161563-1.26180.105903
15-0.150257-1.17350.12257
16-0.159962-1.24930.108156
17-0.209368-1.63520.053577
18-0.24569-1.91890.02984
19-0.255343-1.99430.025298
20-0.291548-2.27710.013151
21-0.328615-2.56660.006371
22-0.306401-2.39310.009901
23-0.271266-2.11870.0191
24-0.23357-1.82420.036507
25-0.211356-1.65070.051966
26-0.161437-1.26090.10608
27-0.165712-1.29430.100229
28-0.16494-1.28820.101266
29-0.185029-1.44510.076771
30-0.153799-1.20120.117156
31-0.086012-0.67180.252132
32-0.072535-0.56650.286562
33-0.056764-0.44330.329544
34-0.028654-0.22380.411832
350.0039960.03120.487603
360.0208960.16320.43545






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8363696.53230
20.0437330.34160.366927
3-0.013314-0.1040.458762
40.0164720.12860.44903
5-0.137987-1.07770.142703
60.0003540.00280.498902
7-0.017001-0.13280.447402
80.07330.57250.284547
9-0.09631-0.75220.227411
10-0.073708-0.57570.283474
11-0.042758-0.33390.369782
12-0.139241-1.08750.140545
130.0295330.23070.409175
140.0128560.10040.460176
150.1126190.87960.191269
16-0.063924-0.49930.309694
17-0.197073-1.53920.064465
18-0.046261-0.36130.359558
19-0.008399-0.06560.473955
20-0.072756-0.56820.285979
21-0.043857-0.34250.366564
220.1441471.12580.132325
230.0020670.01610.493586
24-0.024188-0.18890.425393
25-0.029966-0.2340.407867
260.0559690.43710.331778
27-0.159251-1.24380.109168
28-0.007142-0.05580.477849
29-0.057763-0.45110.326742
300.0610190.47660.317685
310.1692441.32180.095579
32-0.173621-1.3560.090045
330.0156950.12260.451421
34-0.049433-0.38610.350388
350.0293550.22930.409712
360.0807460.63060.265314

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.836369 & 6.5323 & 0 \tabularnewline
2 & 0.043733 & 0.3416 & 0.366927 \tabularnewline
3 & -0.013314 & -0.104 & 0.458762 \tabularnewline
4 & 0.016472 & 0.1286 & 0.44903 \tabularnewline
5 & -0.137987 & -1.0777 & 0.142703 \tabularnewline
6 & 0.000354 & 0.0028 & 0.498902 \tabularnewline
7 & -0.017001 & -0.1328 & 0.447402 \tabularnewline
8 & 0.0733 & 0.5725 & 0.284547 \tabularnewline
9 & -0.09631 & -0.7522 & 0.227411 \tabularnewline
10 & -0.073708 & -0.5757 & 0.283474 \tabularnewline
11 & -0.042758 & -0.3339 & 0.369782 \tabularnewline
12 & -0.139241 & -1.0875 & 0.140545 \tabularnewline
13 & 0.029533 & 0.2307 & 0.409175 \tabularnewline
14 & 0.012856 & 0.1004 & 0.460176 \tabularnewline
15 & 0.112619 & 0.8796 & 0.191269 \tabularnewline
16 & -0.063924 & -0.4993 & 0.309694 \tabularnewline
17 & -0.197073 & -1.5392 & 0.064465 \tabularnewline
18 & -0.046261 & -0.3613 & 0.359558 \tabularnewline
19 & -0.008399 & -0.0656 & 0.473955 \tabularnewline
20 & -0.072756 & -0.5682 & 0.285979 \tabularnewline
21 & -0.043857 & -0.3425 & 0.366564 \tabularnewline
22 & 0.144147 & 1.1258 & 0.132325 \tabularnewline
23 & 0.002067 & 0.0161 & 0.493586 \tabularnewline
24 & -0.024188 & -0.1889 & 0.425393 \tabularnewline
25 & -0.029966 & -0.234 & 0.407867 \tabularnewline
26 & 0.055969 & 0.4371 & 0.331778 \tabularnewline
27 & -0.159251 & -1.2438 & 0.109168 \tabularnewline
28 & -0.007142 & -0.0558 & 0.477849 \tabularnewline
29 & -0.057763 & -0.4511 & 0.326742 \tabularnewline
30 & 0.061019 & 0.4766 & 0.317685 \tabularnewline
31 & 0.169244 & 1.3218 & 0.095579 \tabularnewline
32 & -0.173621 & -1.356 & 0.090045 \tabularnewline
33 & 0.015695 & 0.1226 & 0.451421 \tabularnewline
34 & -0.049433 & -0.3861 & 0.350388 \tabularnewline
35 & 0.029355 & 0.2293 & 0.409712 \tabularnewline
36 & 0.080746 & 0.6306 & 0.265314 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68916&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]0.836369[/C][C]6.5323[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.043733[/C][C]0.3416[/C][C]0.366927[/C][/ROW]
[ROW][C]3[/C][C]-0.013314[/C][C]-0.104[/C][C]0.458762[/C][/ROW]
[ROW][C]4[/C][C]0.016472[/C][C]0.1286[/C][C]0.44903[/C][/ROW]
[ROW][C]5[/C][C]-0.137987[/C][C]-1.0777[/C][C]0.142703[/C][/ROW]
[ROW][C]6[/C][C]0.000354[/C][C]0.0028[/C][C]0.498902[/C][/ROW]
[ROW][C]7[/C][C]-0.017001[/C][C]-0.1328[/C][C]0.447402[/C][/ROW]
[ROW][C]8[/C][C]0.0733[/C][C]0.5725[/C][C]0.284547[/C][/ROW]
[ROW][C]9[/C][C]-0.09631[/C][C]-0.7522[/C][C]0.227411[/C][/ROW]
[ROW][C]10[/C][C]-0.073708[/C][C]-0.5757[/C][C]0.283474[/C][/ROW]
[ROW][C]11[/C][C]-0.042758[/C][C]-0.3339[/C][C]0.369782[/C][/ROW]
[ROW][C]12[/C][C]-0.139241[/C][C]-1.0875[/C][C]0.140545[/C][/ROW]
[ROW][C]13[/C][C]0.029533[/C][C]0.2307[/C][C]0.409175[/C][/ROW]
[ROW][C]14[/C][C]0.012856[/C][C]0.1004[/C][C]0.460176[/C][/ROW]
[ROW][C]15[/C][C]0.112619[/C][C]0.8796[/C][C]0.191269[/C][/ROW]
[ROW][C]16[/C][C]-0.063924[/C][C]-0.4993[/C][C]0.309694[/C][/ROW]
[ROW][C]17[/C][C]-0.197073[/C][C]-1.5392[/C][C]0.064465[/C][/ROW]
[ROW][C]18[/C][C]-0.046261[/C][C]-0.3613[/C][C]0.359558[/C][/ROW]
[ROW][C]19[/C][C]-0.008399[/C][C]-0.0656[/C][C]0.473955[/C][/ROW]
[ROW][C]20[/C][C]-0.072756[/C][C]-0.5682[/C][C]0.285979[/C][/ROW]
[ROW][C]21[/C][C]-0.043857[/C][C]-0.3425[/C][C]0.366564[/C][/ROW]
[ROW][C]22[/C][C]0.144147[/C][C]1.1258[/C][C]0.132325[/C][/ROW]
[ROW][C]23[/C][C]0.002067[/C][C]0.0161[/C][C]0.493586[/C][/ROW]
[ROW][C]24[/C][C]-0.024188[/C][C]-0.1889[/C][C]0.425393[/C][/ROW]
[ROW][C]25[/C][C]-0.029966[/C][C]-0.234[/C][C]0.407867[/C][/ROW]
[ROW][C]26[/C][C]0.055969[/C][C]0.4371[/C][C]0.331778[/C][/ROW]
[ROW][C]27[/C][C]-0.159251[/C][C]-1.2438[/C][C]0.109168[/C][/ROW]
[ROW][C]28[/C][C]-0.007142[/C][C]-0.0558[/C][C]0.477849[/C][/ROW]
[ROW][C]29[/C][C]-0.057763[/C][C]-0.4511[/C][C]0.326742[/C][/ROW]
[ROW][C]30[/C][C]0.061019[/C][C]0.4766[/C][C]0.317685[/C][/ROW]
[ROW][C]31[/C][C]0.169244[/C][C]1.3218[/C][C]0.095579[/C][/ROW]
[ROW][C]32[/C][C]-0.173621[/C][C]-1.356[/C][C]0.090045[/C][/ROW]
[ROW][C]33[/C][C]0.015695[/C][C]0.1226[/C][C]0.451421[/C][/ROW]
[ROW][C]34[/C][C]-0.049433[/C][C]-0.3861[/C][C]0.350388[/C][/ROW]
[ROW][C]35[/C][C]0.029355[/C][C]0.2293[/C][C]0.409712[/C][/ROW]
[ROW][C]36[/C][C]0.080746[/C][C]0.6306[/C][C]0.265314[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68916&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68916&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
10.8363696.53230
20.0437330.34160.366927
3-0.013314-0.1040.458762
40.0164720.12860.44903
5-0.137987-1.07770.142703
60.0003540.00280.498902
7-0.017001-0.13280.447402
80.07330.57250.284547
9-0.09631-0.75220.227411
10-0.073708-0.57570.283474
11-0.042758-0.33390.369782
12-0.139241-1.08750.140545
130.0295330.23070.409175
140.0128560.10040.460176
150.1126190.87960.191269
16-0.063924-0.49930.309694
17-0.197073-1.53920.064465
18-0.046261-0.36130.359558
19-0.008399-0.06560.473955
20-0.072756-0.56820.285979
21-0.043857-0.34250.366564
220.1441471.12580.132325
230.0020670.01610.493586
24-0.024188-0.18890.425393
25-0.029966-0.2340.407867
260.0559690.43710.331778
27-0.159251-1.24380.109168
28-0.007142-0.05580.477849
29-0.057763-0.45110.326742
300.0610190.47660.317685
310.1692441.32180.095579
32-0.173621-1.3560.090045
330.0156950.12260.451421
34-0.049433-0.38610.350388
350.0293550.22930.409712
360.0807460.63060.265314


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')