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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 computationSun, 20 Dec 2009 00:31:47 -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/20/t126129439612zp2np9jz3thck.htm/, Retrieved Sat, 27 Apr 2024 08:31:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69790, Retrieved Sat, 27 Apr 2024 08:31:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144

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]
-    D        [(Partial) Autocorrelation Function] [] [2009-11-23 15:17:11] [5d885a68c2332cc44f6191ec94766bfa]
-    D            [(Partial) Autocorrelation Function] [] [2009-12-20 07:31:47] [2b679e8ec54382eeb0ec0b6bb527570a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101.09
102.71
102.11
101.68
101.7
101.53
101.76
101.15
100.92
100.73
100.55
102.15
100.79
99.93
100.03
100.25
99.6
100.16
100.49
99.72
100.14
98.48
100.38
101.45
98.42
98.6
100.06
98.62
100.84
100.02
97.95
98.32
98.27
97.22
99.28
100.38
99.02
100.32
99.81
100.6
101.19
100.47
101.77
102.32
102.39
101.16
100.63
101.48
101.44
100.09
100.7
100.78
99.81
98.45
98.49
97.48
97.91
96.94
98.53
96.82
95.76

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69790&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]2 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=69790&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69790&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.6807415.31681e-06
20.5328624.16185e-05
30.548734.28573.3e-05
40.3727042.91090.002513
50.3142082.4540.008498
60.2329041.8190.036908
70.0625720.48870.313402
8-0.011675-0.09120.463823
9-0.107613-0.84050.201959
10-0.22884-1.78730.039428
11-0.207723-1.62240.054941
12-0.272914-2.13150.018541
13-0.344781-2.69280.004567
14-0.28747-2.24520.014195
15-0.303174-2.36790.010538
16-0.282649-2.20760.015523
17-0.209615-1.63710.053374
18-0.223893-1.74870.04269
19-0.158662-1.23920.110011
20-0.125608-0.9810.165227
21-0.055618-0.43440.332769
22-0.003561-0.02780.48895
23-0.012765-0.09970.460457
240.0374380.29240.385487
250.0279990.21870.413815
260.0513750.40120.344819
270.0733350.57280.284455
280.0581660.45430.325616
290.0213430.16670.434082
300.0078320.06120.475712
31-0.026315-0.20550.418922
320.0303440.2370.406727
330.1211210.9460.173943
340.1006230.78590.217486
350.1434251.12020.133513
360.1557561.21650.114241

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.680741 & 5.3168 & 1e-06 \tabularnewline
2 & 0.532862 & 4.1618 & 5e-05 \tabularnewline
3 & 0.54873 & 4.2857 & 3.3e-05 \tabularnewline
4 & 0.372704 & 2.9109 & 0.002513 \tabularnewline
5 & 0.314208 & 2.454 & 0.008498 \tabularnewline
6 & 0.232904 & 1.819 & 0.036908 \tabularnewline
7 & 0.062572 & 0.4887 & 0.313402 \tabularnewline
8 & -0.011675 & -0.0912 & 0.463823 \tabularnewline
9 & -0.107613 & -0.8405 & 0.201959 \tabularnewline
10 & -0.22884 & -1.7873 & 0.039428 \tabularnewline
11 & -0.207723 & -1.6224 & 0.054941 \tabularnewline
12 & -0.272914 & -2.1315 & 0.018541 \tabularnewline
13 & -0.344781 & -2.6928 & 0.004567 \tabularnewline
14 & -0.28747 & -2.2452 & 0.014195 \tabularnewline
15 & -0.303174 & -2.3679 & 0.010538 \tabularnewline
16 & -0.282649 & -2.2076 & 0.015523 \tabularnewline
17 & -0.209615 & -1.6371 & 0.053374 \tabularnewline
18 & -0.223893 & -1.7487 & 0.04269 \tabularnewline
19 & -0.158662 & -1.2392 & 0.110011 \tabularnewline
20 & -0.125608 & -0.981 & 0.165227 \tabularnewline
21 & -0.055618 & -0.4344 & 0.332769 \tabularnewline
22 & -0.003561 & -0.0278 & 0.48895 \tabularnewline
23 & -0.012765 & -0.0997 & 0.460457 \tabularnewline
24 & 0.037438 & 0.2924 & 0.385487 \tabularnewline
25 & 0.027999 & 0.2187 & 0.413815 \tabularnewline
26 & 0.051375 & 0.4012 & 0.344819 \tabularnewline
27 & 0.073335 & 0.5728 & 0.284455 \tabularnewline
28 & 0.058166 & 0.4543 & 0.325616 \tabularnewline
29 & 0.021343 & 0.1667 & 0.434082 \tabularnewline
30 & 0.007832 & 0.0612 & 0.475712 \tabularnewline
31 & -0.026315 & -0.2055 & 0.418922 \tabularnewline
32 & 0.030344 & 0.237 & 0.406727 \tabularnewline
33 & 0.121121 & 0.946 & 0.173943 \tabularnewline
34 & 0.100623 & 0.7859 & 0.217486 \tabularnewline
35 & 0.143425 & 1.1202 & 0.133513 \tabularnewline
36 & 0.155756 & 1.2165 & 0.114241 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69790&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]0.680741[/C][C]5.3168[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.532862[/C][C]4.1618[/C][C]5e-05[/C][/ROW]
[ROW][C]3[/C][C]0.54873[/C][C]4.2857[/C][C]3.3e-05[/C][/ROW]
[ROW][C]4[/C][C]0.372704[/C][C]2.9109[/C][C]0.002513[/C][/ROW]
[ROW][C]5[/C][C]0.314208[/C][C]2.454[/C][C]0.008498[/C][/ROW]
[ROW][C]6[/C][C]0.232904[/C][C]1.819[/C][C]0.036908[/C][/ROW]
[ROW][C]7[/C][C]0.062572[/C][C]0.4887[/C][C]0.313402[/C][/ROW]
[ROW][C]8[/C][C]-0.011675[/C][C]-0.0912[/C][C]0.463823[/C][/ROW]
[ROW][C]9[/C][C]-0.107613[/C][C]-0.8405[/C][C]0.201959[/C][/ROW]
[ROW][C]10[/C][C]-0.22884[/C][C]-1.7873[/C][C]0.039428[/C][/ROW]
[ROW][C]11[/C][C]-0.207723[/C][C]-1.6224[/C][C]0.054941[/C][/ROW]
[ROW][C]12[/C][C]-0.272914[/C][C]-2.1315[/C][C]0.018541[/C][/ROW]
[ROW][C]13[/C][C]-0.344781[/C][C]-2.6928[/C][C]0.004567[/C][/ROW]
[ROW][C]14[/C][C]-0.28747[/C][C]-2.2452[/C][C]0.014195[/C][/ROW]
[ROW][C]15[/C][C]-0.303174[/C][C]-2.3679[/C][C]0.010538[/C][/ROW]
[ROW][C]16[/C][C]-0.282649[/C][C]-2.2076[/C][C]0.015523[/C][/ROW]
[ROW][C]17[/C][C]-0.209615[/C][C]-1.6371[/C][C]0.053374[/C][/ROW]
[ROW][C]18[/C][C]-0.223893[/C][C]-1.7487[/C][C]0.04269[/C][/ROW]
[ROW][C]19[/C][C]-0.158662[/C][C]-1.2392[/C][C]0.110011[/C][/ROW]
[ROW][C]20[/C][C]-0.125608[/C][C]-0.981[/C][C]0.165227[/C][/ROW]
[ROW][C]21[/C][C]-0.055618[/C][C]-0.4344[/C][C]0.332769[/C][/ROW]
[ROW][C]22[/C][C]-0.003561[/C][C]-0.0278[/C][C]0.48895[/C][/ROW]
[ROW][C]23[/C][C]-0.012765[/C][C]-0.0997[/C][C]0.460457[/C][/ROW]
[ROW][C]24[/C][C]0.037438[/C][C]0.2924[/C][C]0.385487[/C][/ROW]
[ROW][C]25[/C][C]0.027999[/C][C]0.2187[/C][C]0.413815[/C][/ROW]
[ROW][C]26[/C][C]0.051375[/C][C]0.4012[/C][C]0.344819[/C][/ROW]
[ROW][C]27[/C][C]0.073335[/C][C]0.5728[/C][C]0.284455[/C][/ROW]
[ROW][C]28[/C][C]0.058166[/C][C]0.4543[/C][C]0.325616[/C][/ROW]
[ROW][C]29[/C][C]0.021343[/C][C]0.1667[/C][C]0.434082[/C][/ROW]
[ROW][C]30[/C][C]0.007832[/C][C]0.0612[/C][C]0.475712[/C][/ROW]
[ROW][C]31[/C][C]-0.026315[/C][C]-0.2055[/C][C]0.418922[/C][/ROW]
[ROW][C]32[/C][C]0.030344[/C][C]0.237[/C][C]0.406727[/C][/ROW]
[ROW][C]33[/C][C]0.121121[/C][C]0.946[/C][C]0.173943[/C][/ROW]
[ROW][C]34[/C][C]0.100623[/C][C]0.7859[/C][C]0.217486[/C][/ROW]
[ROW][C]35[/C][C]0.143425[/C][C]1.1202[/C][C]0.133513[/C][/ROW]
[ROW][C]36[/C][C]0.155756[/C][C]1.2165[/C][C]0.114241[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69790&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69790&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
10.6807415.31681e-06
20.5328624.16185e-05
30.548734.28573.3e-05
40.3727042.91090.002513
50.3142082.4540.008498
60.2329041.8190.036908
70.0625720.48870.313402
8-0.011675-0.09120.463823
9-0.107613-0.84050.201959
10-0.22884-1.78730.039428
11-0.207723-1.62240.054941
12-0.272914-2.13150.018541
13-0.344781-2.69280.004567
14-0.28747-2.24520.014195
15-0.303174-2.36790.010538
16-0.282649-2.20760.015523
17-0.209615-1.63710.053374
18-0.223893-1.74870.04269
19-0.158662-1.23920.110011
20-0.125608-0.9810.165227
21-0.055618-0.43440.332769
22-0.003561-0.02780.48895
23-0.012765-0.09970.460457
240.0374380.29240.385487
250.0279990.21870.413815
260.0513750.40120.344819
270.0733350.57280.284455
280.0581660.45430.325616
290.0213430.16670.434082
300.0078320.06120.475712
31-0.026315-0.20550.418922
320.0303440.2370.406727
330.1211210.9460.173943
340.1006230.78590.217486
350.1434251.12020.133513
360.1557561.21650.114241






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.6807415.31681e-06
20.1294331.01090.158027
30.2745052.14390.018016
4-0.20938-1.63530.053568
50.0885840.69190.245824
6-0.160852-1.25630.106899
7-0.139121-1.08660.14075
8-0.103144-0.80560.211807
9-0.113931-0.88980.188527
10-0.115426-0.90150.185432
110.0970730.75820.225635
12-0.105825-0.82650.205865
13-0.021244-0.16590.434384
140.0267550.2090.417586
15-0.014198-0.11090.456034
160.030130.23530.407373
170.0002310.00180.499282
18-0.062542-0.48850.313484
190.0455770.3560.361546
20-0.118573-0.92610.179026
210.1835191.43330.078435
22-0.133806-1.04510.150059
230.0038540.03010.488042
24-0.003173-0.02480.490154
25-0.111329-0.86950.193989
260.084140.65720.256776
27-0.066479-0.51920.302743
280.0094330.07370.470756
29-0.085766-0.66990.252739
30-0.029313-0.22890.409841
31-0.040097-0.31320.377612
320.1918221.49820.069622
330.1390361.08590.140896
340.1042850.81450.209266
350.059470.46450.32198
36-0.042317-0.33050.371076

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.680741 & 5.3168 & 1e-06 \tabularnewline
2 & 0.129433 & 1.0109 & 0.158027 \tabularnewline
3 & 0.274505 & 2.1439 & 0.018016 \tabularnewline
4 & -0.20938 & -1.6353 & 0.053568 \tabularnewline
5 & 0.088584 & 0.6919 & 0.245824 \tabularnewline
6 & -0.160852 & -1.2563 & 0.106899 \tabularnewline
7 & -0.139121 & -1.0866 & 0.14075 \tabularnewline
8 & -0.103144 & -0.8056 & 0.211807 \tabularnewline
9 & -0.113931 & -0.8898 & 0.188527 \tabularnewline
10 & -0.115426 & -0.9015 & 0.185432 \tabularnewline
11 & 0.097073 & 0.7582 & 0.225635 \tabularnewline
12 & -0.105825 & -0.8265 & 0.205865 \tabularnewline
13 & -0.021244 & -0.1659 & 0.434384 \tabularnewline
14 & 0.026755 & 0.209 & 0.417586 \tabularnewline
15 & -0.014198 & -0.1109 & 0.456034 \tabularnewline
16 & 0.03013 & 0.2353 & 0.407373 \tabularnewline
17 & 0.000231 & 0.0018 & 0.499282 \tabularnewline
18 & -0.062542 & -0.4885 & 0.313484 \tabularnewline
19 & 0.045577 & 0.356 & 0.361546 \tabularnewline
20 & -0.118573 & -0.9261 & 0.179026 \tabularnewline
21 & 0.183519 & 1.4333 & 0.078435 \tabularnewline
22 & -0.133806 & -1.0451 & 0.150059 \tabularnewline
23 & 0.003854 & 0.0301 & 0.488042 \tabularnewline
24 & -0.003173 & -0.0248 & 0.490154 \tabularnewline
25 & -0.111329 & -0.8695 & 0.193989 \tabularnewline
26 & 0.08414 & 0.6572 & 0.256776 \tabularnewline
27 & -0.066479 & -0.5192 & 0.302743 \tabularnewline
28 & 0.009433 & 0.0737 & 0.470756 \tabularnewline
29 & -0.085766 & -0.6699 & 0.252739 \tabularnewline
30 & -0.029313 & -0.2289 & 0.409841 \tabularnewline
31 & -0.040097 & -0.3132 & 0.377612 \tabularnewline
32 & 0.191822 & 1.4982 & 0.069622 \tabularnewline
33 & 0.139036 & 1.0859 & 0.140896 \tabularnewline
34 & 0.104285 & 0.8145 & 0.209266 \tabularnewline
35 & 0.05947 & 0.4645 & 0.32198 \tabularnewline
36 & -0.042317 & -0.3305 & 0.371076 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69790&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]0.680741[/C][C]5.3168[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.129433[/C][C]1.0109[/C][C]0.158027[/C][/ROW]
[ROW][C]3[/C][C]0.274505[/C][C]2.1439[/C][C]0.018016[/C][/ROW]
[ROW][C]4[/C][C]-0.20938[/C][C]-1.6353[/C][C]0.053568[/C][/ROW]
[ROW][C]5[/C][C]0.088584[/C][C]0.6919[/C][C]0.245824[/C][/ROW]
[ROW][C]6[/C][C]-0.160852[/C][C]-1.2563[/C][C]0.106899[/C][/ROW]
[ROW][C]7[/C][C]-0.139121[/C][C]-1.0866[/C][C]0.14075[/C][/ROW]
[ROW][C]8[/C][C]-0.103144[/C][C]-0.8056[/C][C]0.211807[/C][/ROW]
[ROW][C]9[/C][C]-0.113931[/C][C]-0.8898[/C][C]0.188527[/C][/ROW]
[ROW][C]10[/C][C]-0.115426[/C][C]-0.9015[/C][C]0.185432[/C][/ROW]
[ROW][C]11[/C][C]0.097073[/C][C]0.7582[/C][C]0.225635[/C][/ROW]
[ROW][C]12[/C][C]-0.105825[/C][C]-0.8265[/C][C]0.205865[/C][/ROW]
[ROW][C]13[/C][C]-0.021244[/C][C]-0.1659[/C][C]0.434384[/C][/ROW]
[ROW][C]14[/C][C]0.026755[/C][C]0.209[/C][C]0.417586[/C][/ROW]
[ROW][C]15[/C][C]-0.014198[/C][C]-0.1109[/C][C]0.456034[/C][/ROW]
[ROW][C]16[/C][C]0.03013[/C][C]0.2353[/C][C]0.407373[/C][/ROW]
[ROW][C]17[/C][C]0.000231[/C][C]0.0018[/C][C]0.499282[/C][/ROW]
[ROW][C]18[/C][C]-0.062542[/C][C]-0.4885[/C][C]0.313484[/C][/ROW]
[ROW][C]19[/C][C]0.045577[/C][C]0.356[/C][C]0.361546[/C][/ROW]
[ROW][C]20[/C][C]-0.118573[/C][C]-0.9261[/C][C]0.179026[/C][/ROW]
[ROW][C]21[/C][C]0.183519[/C][C]1.4333[/C][C]0.078435[/C][/ROW]
[ROW][C]22[/C][C]-0.133806[/C][C]-1.0451[/C][C]0.150059[/C][/ROW]
[ROW][C]23[/C][C]0.003854[/C][C]0.0301[/C][C]0.488042[/C][/ROW]
[ROW][C]24[/C][C]-0.003173[/C][C]-0.0248[/C][C]0.490154[/C][/ROW]
[ROW][C]25[/C][C]-0.111329[/C][C]-0.8695[/C][C]0.193989[/C][/ROW]
[ROW][C]26[/C][C]0.08414[/C][C]0.6572[/C][C]0.256776[/C][/ROW]
[ROW][C]27[/C][C]-0.066479[/C][C]-0.5192[/C][C]0.302743[/C][/ROW]
[ROW][C]28[/C][C]0.009433[/C][C]0.0737[/C][C]0.470756[/C][/ROW]
[ROW][C]29[/C][C]-0.085766[/C][C]-0.6699[/C][C]0.252739[/C][/ROW]
[ROW][C]30[/C][C]-0.029313[/C][C]-0.2289[/C][C]0.409841[/C][/ROW]
[ROW][C]31[/C][C]-0.040097[/C][C]-0.3132[/C][C]0.377612[/C][/ROW]
[ROW][C]32[/C][C]0.191822[/C][C]1.4982[/C][C]0.069622[/C][/ROW]
[ROW][C]33[/C][C]0.139036[/C][C]1.0859[/C][C]0.140896[/C][/ROW]
[ROW][C]34[/C][C]0.104285[/C][C]0.8145[/C][C]0.209266[/C][/ROW]
[ROW][C]35[/C][C]0.05947[/C][C]0.4645[/C][C]0.32198[/C][/ROW]
[ROW][C]36[/C][C]-0.042317[/C][C]-0.3305[/C][C]0.371076[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69790&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69790&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
10.6807415.31681e-06
20.1294331.01090.158027
30.2745052.14390.018016
4-0.20938-1.63530.053568
50.0885840.69190.245824
6-0.160852-1.25630.106899
7-0.139121-1.08660.14075
8-0.103144-0.80560.211807
9-0.113931-0.88980.188527
10-0.115426-0.90150.185432
110.0970730.75820.225635
12-0.105825-0.82650.205865
13-0.021244-0.16590.434384
140.0267550.2090.417586
15-0.014198-0.11090.456034
160.030130.23530.407373
170.0002310.00180.499282
18-0.062542-0.48850.313484
190.0455770.3560.361546
20-0.118573-0.92610.179026
210.1835191.43330.078435
22-0.133806-1.04510.150059
230.0038540.03010.488042
24-0.003173-0.02480.490154
25-0.111329-0.86950.193989
260.084140.65720.256776
27-0.066479-0.51920.302743
280.0094330.07370.470756
29-0.085766-0.66990.252739
30-0.029313-0.22890.409841
31-0.040097-0.31320.377612
320.1918221.49820.069622
330.1390361.08590.140896
340.1042850.81450.209266
350.059470.46450.32198
36-0.042317-0.33050.371076


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')