Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Module--
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 29 Nov 2011 07:10:59 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/29/t1322568671012ok9nidgqloh6.htm/, Retrieved Thu, 25 Apr 2024 19:51:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=148228, Retrieved Thu, 25 Apr 2024 19:51:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact88
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] [Ws8.2ACF2] [2009-11-25 19:27:24] [e0fc65a5811681d807296d590d5b45de]
-               [(Partial) Autocorrelation Function] [Workshop 8 ACF1] [2010-11-29 17:53:26] [814f53995537cd15c528d8efbf1cf544]
- RM                [(Partial) Autocorrelation Function] [] [2011-11-29 12:10:59] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
58608
46865
51378
46235
47206
45382
41227
33795
31295
42625
33625
21538
56421
53152
53536
52408
41454
38271
35306
26414
31917
38030
27534
18387
50556
43901
48572
43899
37532
40357
35489
29027
34485
42598
30306
26451
47460
50104
61465
53726
39477
43895
31481
29896
33842
39120
33702
25094
51442
45594
52518
48564
41745
49585
32747
33379
35645
37034
35681
20972




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'AstonUniversity' @ aston.wessa.net

\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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148228&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148228&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148228&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'AstonUniversity' @ aston.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.4792093.32010.000862
20.3510992.43250.009387
30.1745821.20950.116189
40.0724760.50210.308938
50.1557771.07930.142934
60.11910.82520.206684
70.0491160.34030.367562
80.0525040.36380.358818
90.0460470.3190.375547
10-0.185884-1.28780.101988
11-0.334713-2.3190.01235
12-0.435596-3.01790.002033
13-0.362122-2.50890.007771
14-0.203192-1.40780.082824
15-0.090338-0.62590.267179
16-0.209836-1.45380.076257
17-0.069847-0.48390.315323
18-0.047865-0.33160.37081
19-0.103752-0.71880.237869
20-0.045735-0.31690.376362
21-0.153186-1.06130.146931
22-0.054213-0.37560.354436
230.1162610.80550.212258
240.1574391.09080.140409
250.1395820.96710.169182
260.096350.66750.253814
27-0.041642-0.28850.387102
28-0.010271-0.07120.471783
29-0.064939-0.44990.327399
30-0.070301-0.48710.314216
31-0.014658-0.10160.459768
320.0409510.28370.388923
330.0985990.68310.248909
34-0.006323-0.04380.48262
35-0.041724-0.28910.386885
36-0.136338-0.94460.174802

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.479209 & 3.3201 & 0.000862 \tabularnewline
2 & 0.351099 & 2.4325 & 0.009387 \tabularnewline
3 & 0.174582 & 1.2095 & 0.116189 \tabularnewline
4 & 0.072476 & 0.5021 & 0.308938 \tabularnewline
5 & 0.155777 & 1.0793 & 0.142934 \tabularnewline
6 & 0.1191 & 0.8252 & 0.206684 \tabularnewline
7 & 0.049116 & 0.3403 & 0.367562 \tabularnewline
8 & 0.052504 & 0.3638 & 0.358818 \tabularnewline
9 & 0.046047 & 0.319 & 0.375547 \tabularnewline
10 & -0.185884 & -1.2878 & 0.101988 \tabularnewline
11 & -0.334713 & -2.319 & 0.01235 \tabularnewline
12 & -0.435596 & -3.0179 & 0.002033 \tabularnewline
13 & -0.362122 & -2.5089 & 0.007771 \tabularnewline
14 & -0.203192 & -1.4078 & 0.082824 \tabularnewline
15 & -0.090338 & -0.6259 & 0.267179 \tabularnewline
16 & -0.209836 & -1.4538 & 0.076257 \tabularnewline
17 & -0.069847 & -0.4839 & 0.315323 \tabularnewline
18 & -0.047865 & -0.3316 & 0.37081 \tabularnewline
19 & -0.103752 & -0.7188 & 0.237869 \tabularnewline
20 & -0.045735 & -0.3169 & 0.376362 \tabularnewline
21 & -0.153186 & -1.0613 & 0.146931 \tabularnewline
22 & -0.054213 & -0.3756 & 0.354436 \tabularnewline
23 & 0.116261 & 0.8055 & 0.212258 \tabularnewline
24 & 0.157439 & 1.0908 & 0.140409 \tabularnewline
25 & 0.139582 & 0.9671 & 0.169182 \tabularnewline
26 & 0.09635 & 0.6675 & 0.253814 \tabularnewline
27 & -0.041642 & -0.2885 & 0.387102 \tabularnewline
28 & -0.010271 & -0.0712 & 0.471783 \tabularnewline
29 & -0.064939 & -0.4499 & 0.327399 \tabularnewline
30 & -0.070301 & -0.4871 & 0.314216 \tabularnewline
31 & -0.014658 & -0.1016 & 0.459768 \tabularnewline
32 & 0.040951 & 0.2837 & 0.388923 \tabularnewline
33 & 0.098599 & 0.6831 & 0.248909 \tabularnewline
34 & -0.006323 & -0.0438 & 0.48262 \tabularnewline
35 & -0.041724 & -0.2891 & 0.386885 \tabularnewline
36 & -0.136338 & -0.9446 & 0.174802 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148228&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]0.479209[/C][C]3.3201[/C][C]0.000862[/C][/ROW]
[ROW][C]2[/C][C]0.351099[/C][C]2.4325[/C][C]0.009387[/C][/ROW]
[ROW][C]3[/C][C]0.174582[/C][C]1.2095[/C][C]0.116189[/C][/ROW]
[ROW][C]4[/C][C]0.072476[/C][C]0.5021[/C][C]0.308938[/C][/ROW]
[ROW][C]5[/C][C]0.155777[/C][C]1.0793[/C][C]0.142934[/C][/ROW]
[ROW][C]6[/C][C]0.1191[/C][C]0.8252[/C][C]0.206684[/C][/ROW]
[ROW][C]7[/C][C]0.049116[/C][C]0.3403[/C][C]0.367562[/C][/ROW]
[ROW][C]8[/C][C]0.052504[/C][C]0.3638[/C][C]0.358818[/C][/ROW]
[ROW][C]9[/C][C]0.046047[/C][C]0.319[/C][C]0.375547[/C][/ROW]
[ROW][C]10[/C][C]-0.185884[/C][C]-1.2878[/C][C]0.101988[/C][/ROW]
[ROW][C]11[/C][C]-0.334713[/C][C]-2.319[/C][C]0.01235[/C][/ROW]
[ROW][C]12[/C][C]-0.435596[/C][C]-3.0179[/C][C]0.002033[/C][/ROW]
[ROW][C]13[/C][C]-0.362122[/C][C]-2.5089[/C][C]0.007771[/C][/ROW]
[ROW][C]14[/C][C]-0.203192[/C][C]-1.4078[/C][C]0.082824[/C][/ROW]
[ROW][C]15[/C][C]-0.090338[/C][C]-0.6259[/C][C]0.267179[/C][/ROW]
[ROW][C]16[/C][C]-0.209836[/C][C]-1.4538[/C][C]0.076257[/C][/ROW]
[ROW][C]17[/C][C]-0.069847[/C][C]-0.4839[/C][C]0.315323[/C][/ROW]
[ROW][C]18[/C][C]-0.047865[/C][C]-0.3316[/C][C]0.37081[/C][/ROW]
[ROW][C]19[/C][C]-0.103752[/C][C]-0.7188[/C][C]0.237869[/C][/ROW]
[ROW][C]20[/C][C]-0.045735[/C][C]-0.3169[/C][C]0.376362[/C][/ROW]
[ROW][C]21[/C][C]-0.153186[/C][C]-1.0613[/C][C]0.146931[/C][/ROW]
[ROW][C]22[/C][C]-0.054213[/C][C]-0.3756[/C][C]0.354436[/C][/ROW]
[ROW][C]23[/C][C]0.116261[/C][C]0.8055[/C][C]0.212258[/C][/ROW]
[ROW][C]24[/C][C]0.157439[/C][C]1.0908[/C][C]0.140409[/C][/ROW]
[ROW][C]25[/C][C]0.139582[/C][C]0.9671[/C][C]0.169182[/C][/ROW]
[ROW][C]26[/C][C]0.09635[/C][C]0.6675[/C][C]0.253814[/C][/ROW]
[ROW][C]27[/C][C]-0.041642[/C][C]-0.2885[/C][C]0.387102[/C][/ROW]
[ROW][C]28[/C][C]-0.010271[/C][C]-0.0712[/C][C]0.471783[/C][/ROW]
[ROW][C]29[/C][C]-0.064939[/C][C]-0.4499[/C][C]0.327399[/C][/ROW]
[ROW][C]30[/C][C]-0.070301[/C][C]-0.4871[/C][C]0.314216[/C][/ROW]
[ROW][C]31[/C][C]-0.014658[/C][C]-0.1016[/C][C]0.459768[/C][/ROW]
[ROW][C]32[/C][C]0.040951[/C][C]0.2837[/C][C]0.388923[/C][/ROW]
[ROW][C]33[/C][C]0.098599[/C][C]0.6831[/C][C]0.248909[/C][/ROW]
[ROW][C]34[/C][C]-0.006323[/C][C]-0.0438[/C][C]0.48262[/C][/ROW]
[ROW][C]35[/C][C]-0.041724[/C][C]-0.2891[/C][C]0.386885[/C][/ROW]
[ROW][C]36[/C][C]-0.136338[/C][C]-0.9446[/C][C]0.174802[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148228&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148228&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
10.4792093.32010.000862
20.3510992.43250.009387
30.1745821.20950.116189
40.0724760.50210.308938
50.1557771.07930.142934
60.11910.82520.206684
70.0491160.34030.367562
80.0525040.36380.358818
90.0460470.3190.375547
10-0.185884-1.28780.101988
11-0.334713-2.3190.01235
12-0.435596-3.01790.002033
13-0.362122-2.50890.007771
14-0.203192-1.40780.082824
15-0.090338-0.62590.267179
16-0.209836-1.45380.076257
17-0.069847-0.48390.315323
18-0.047865-0.33160.37081
19-0.103752-0.71880.237869
20-0.045735-0.31690.376362
21-0.153186-1.06130.146931
22-0.054213-0.37560.354436
230.1162610.80550.212258
240.1574391.09080.140409
250.1395820.96710.169182
260.096350.66750.253814
27-0.041642-0.28850.387102
28-0.010271-0.07120.471783
29-0.064939-0.44990.327399
30-0.070301-0.48710.314216
31-0.014658-0.10160.459768
320.0409510.28370.388923
330.0985990.68310.248909
34-0.006323-0.04380.48262
35-0.041724-0.28910.386885
36-0.136338-0.94460.174802







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4792093.32010.000862
20.1576641.09230.140071
3-0.056834-0.39380.347752
4-0.047724-0.33060.371177
50.1725981.19580.118826
60.0149780.10380.458891
7-0.097326-0.67430.25168
80.0323270.2240.411867
90.0620730.43010.334541
10-0.337092-2.33540.011874
11-0.308932-2.14030.018718
12-0.144184-0.99890.161418
130.0226320.15680.438029
140.0251790.17440.431124
150.0975360.67570.251222
16-0.1555-1.07730.143358
170.1931671.33830.093551
180.1549081.07320.144267
19-0.111232-0.77060.222349
20-0.033192-0.230.40955
21-0.106042-0.73470.233054
22-0.11362-0.78720.217522
23-0.036029-0.24960.401975
24-0.011386-0.07890.468727
250.0260770.18070.428694
26-0.03125-0.21650.414754
27-0.166274-1.1520.127518
280.0267830.18560.426785
29-0.027112-0.18780.425897
300.0265410.18390.427441
310.0264170.1830.427774
32-0.07084-0.49080.312905
330.0790620.54780.293199
34-0.071858-0.49780.310432
35-0.037437-0.25940.398229
360.0363450.25180.401133

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.479209 & 3.3201 & 0.000862 \tabularnewline
2 & 0.157664 & 1.0923 & 0.140071 \tabularnewline
3 & -0.056834 & -0.3938 & 0.347752 \tabularnewline
4 & -0.047724 & -0.3306 & 0.371177 \tabularnewline
5 & 0.172598 & 1.1958 & 0.118826 \tabularnewline
6 & 0.014978 & 0.1038 & 0.458891 \tabularnewline
7 & -0.097326 & -0.6743 & 0.25168 \tabularnewline
8 & 0.032327 & 0.224 & 0.411867 \tabularnewline
9 & 0.062073 & 0.4301 & 0.334541 \tabularnewline
10 & -0.337092 & -2.3354 & 0.011874 \tabularnewline
11 & -0.308932 & -2.1403 & 0.018718 \tabularnewline
12 & -0.144184 & -0.9989 & 0.161418 \tabularnewline
13 & 0.022632 & 0.1568 & 0.438029 \tabularnewline
14 & 0.025179 & 0.1744 & 0.431124 \tabularnewline
15 & 0.097536 & 0.6757 & 0.251222 \tabularnewline
16 & -0.1555 & -1.0773 & 0.143358 \tabularnewline
17 & 0.193167 & 1.3383 & 0.093551 \tabularnewline
18 & 0.154908 & 1.0732 & 0.144267 \tabularnewline
19 & -0.111232 & -0.7706 & 0.222349 \tabularnewline
20 & -0.033192 & -0.23 & 0.40955 \tabularnewline
21 & -0.106042 & -0.7347 & 0.233054 \tabularnewline
22 & -0.11362 & -0.7872 & 0.217522 \tabularnewline
23 & -0.036029 & -0.2496 & 0.401975 \tabularnewline
24 & -0.011386 & -0.0789 & 0.468727 \tabularnewline
25 & 0.026077 & 0.1807 & 0.428694 \tabularnewline
26 & -0.03125 & -0.2165 & 0.414754 \tabularnewline
27 & -0.166274 & -1.152 & 0.127518 \tabularnewline
28 & 0.026783 & 0.1856 & 0.426785 \tabularnewline
29 & -0.027112 & -0.1878 & 0.425897 \tabularnewline
30 & 0.026541 & 0.1839 & 0.427441 \tabularnewline
31 & 0.026417 & 0.183 & 0.427774 \tabularnewline
32 & -0.07084 & -0.4908 & 0.312905 \tabularnewline
33 & 0.079062 & 0.5478 & 0.293199 \tabularnewline
34 & -0.071858 & -0.4978 & 0.310432 \tabularnewline
35 & -0.037437 & -0.2594 & 0.398229 \tabularnewline
36 & 0.036345 & 0.2518 & 0.401133 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148228&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]0.479209[/C][C]3.3201[/C][C]0.000862[/C][/ROW]
[ROW][C]2[/C][C]0.157664[/C][C]1.0923[/C][C]0.140071[/C][/ROW]
[ROW][C]3[/C][C]-0.056834[/C][C]-0.3938[/C][C]0.347752[/C][/ROW]
[ROW][C]4[/C][C]-0.047724[/C][C]-0.3306[/C][C]0.371177[/C][/ROW]
[ROW][C]5[/C][C]0.172598[/C][C]1.1958[/C][C]0.118826[/C][/ROW]
[ROW][C]6[/C][C]0.014978[/C][C]0.1038[/C][C]0.458891[/C][/ROW]
[ROW][C]7[/C][C]-0.097326[/C][C]-0.6743[/C][C]0.25168[/C][/ROW]
[ROW][C]8[/C][C]0.032327[/C][C]0.224[/C][C]0.411867[/C][/ROW]
[ROW][C]9[/C][C]0.062073[/C][C]0.4301[/C][C]0.334541[/C][/ROW]
[ROW][C]10[/C][C]-0.337092[/C][C]-2.3354[/C][C]0.011874[/C][/ROW]
[ROW][C]11[/C][C]-0.308932[/C][C]-2.1403[/C][C]0.018718[/C][/ROW]
[ROW][C]12[/C][C]-0.144184[/C][C]-0.9989[/C][C]0.161418[/C][/ROW]
[ROW][C]13[/C][C]0.022632[/C][C]0.1568[/C][C]0.438029[/C][/ROW]
[ROW][C]14[/C][C]0.025179[/C][C]0.1744[/C][C]0.431124[/C][/ROW]
[ROW][C]15[/C][C]0.097536[/C][C]0.6757[/C][C]0.251222[/C][/ROW]
[ROW][C]16[/C][C]-0.1555[/C][C]-1.0773[/C][C]0.143358[/C][/ROW]
[ROW][C]17[/C][C]0.193167[/C][C]1.3383[/C][C]0.093551[/C][/ROW]
[ROW][C]18[/C][C]0.154908[/C][C]1.0732[/C][C]0.144267[/C][/ROW]
[ROW][C]19[/C][C]-0.111232[/C][C]-0.7706[/C][C]0.222349[/C][/ROW]
[ROW][C]20[/C][C]-0.033192[/C][C]-0.23[/C][C]0.40955[/C][/ROW]
[ROW][C]21[/C][C]-0.106042[/C][C]-0.7347[/C][C]0.233054[/C][/ROW]
[ROW][C]22[/C][C]-0.11362[/C][C]-0.7872[/C][C]0.217522[/C][/ROW]
[ROW][C]23[/C][C]-0.036029[/C][C]-0.2496[/C][C]0.401975[/C][/ROW]
[ROW][C]24[/C][C]-0.011386[/C][C]-0.0789[/C][C]0.468727[/C][/ROW]
[ROW][C]25[/C][C]0.026077[/C][C]0.1807[/C][C]0.428694[/C][/ROW]
[ROW][C]26[/C][C]-0.03125[/C][C]-0.2165[/C][C]0.414754[/C][/ROW]
[ROW][C]27[/C][C]-0.166274[/C][C]-1.152[/C][C]0.127518[/C][/ROW]
[ROW][C]28[/C][C]0.026783[/C][C]0.1856[/C][C]0.426785[/C][/ROW]
[ROW][C]29[/C][C]-0.027112[/C][C]-0.1878[/C][C]0.425897[/C][/ROW]
[ROW][C]30[/C][C]0.026541[/C][C]0.1839[/C][C]0.427441[/C][/ROW]
[ROW][C]31[/C][C]0.026417[/C][C]0.183[/C][C]0.427774[/C][/ROW]
[ROW][C]32[/C][C]-0.07084[/C][C]-0.4908[/C][C]0.312905[/C][/ROW]
[ROW][C]33[/C][C]0.079062[/C][C]0.5478[/C][C]0.293199[/C][/ROW]
[ROW][C]34[/C][C]-0.071858[/C][C]-0.4978[/C][C]0.310432[/C][/ROW]
[ROW][C]35[/C][C]-0.037437[/C][C]-0.2594[/C][C]0.398229[/C][/ROW]
[ROW][C]36[/C][C]0.036345[/C][C]0.2518[/C][C]0.401133[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148228&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148228&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
10.4792093.32010.000862
20.1576641.09230.140071
3-0.056834-0.39380.347752
4-0.047724-0.33060.371177
50.1725981.19580.118826
60.0149780.10380.458891
7-0.097326-0.67430.25168
80.0323270.2240.411867
90.0620730.43010.334541
10-0.337092-2.33540.011874
11-0.308932-2.14030.018718
12-0.144184-0.99890.161418
130.0226320.15680.438029
140.0251790.17440.431124
150.0975360.67570.251222
16-0.1555-1.07730.143358
170.1931671.33830.093551
180.1549081.07320.144267
19-0.111232-0.77060.222349
20-0.033192-0.230.40955
21-0.106042-0.73470.233054
22-0.11362-0.78720.217522
23-0.036029-0.24960.401975
24-0.011386-0.07890.468727
250.0260770.18070.428694
26-0.03125-0.21650.414754
27-0.166274-1.1520.127518
280.0267830.18560.426785
29-0.027112-0.18780.425897
300.0265410.18390.427441
310.0264170.1830.427774
32-0.07084-0.49080.312905
330.0790620.54780.293199
34-0.071858-0.49780.310432
35-0.037437-0.25940.398229
360.0363450.25180.401133



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 ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')