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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 computationWed, 29 Dec 2010 13:00:26 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/29/t12936274911h4t5jyivrbub46.htm/, Retrieved Fri, 03 May 2024 12:58:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116778, Retrieved Fri, 03 May 2024 12:58:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact159

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] [] [2009-11-24 09:55:25] [fef2f8976fa1eef1b54e2cee317fe737]
-    D          [(Partial) Autocorrelation Function] [] [2009-12-18 11:14:21] [fef2f8976fa1eef1b54e2cee317fe737]
- R               [(Partial) Autocorrelation Function] [Paper: ACF] [2010-12-22 20:09:28] [29e492448d11757ae0fad5ef6e7f8e86]
-   PD                [(Partial) Autocorrelation Function] [] [2010-12-29 13:00:26] [e180d4cd19004beeddc12e67012247dc] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
09.166456
07.970589
07.104091
06.621064
07.529215
08.170938
08.157450
07.378962
07.921496
08.156740
08.856365
08.817177
08.734347
09.345927
08.992970
10.785120
08.886867
08.818847
08.823744
09.165298
08.652657
08.173054
07.563416
07.595809
08.381467
07.216432
06.540178
06.238914
05.487288
05.759462
05.993215
07.474726
07.348907
07.303379
07.119314
06.993780
06.958153
07.595706
08.088153
07.555753
07.315433
07.893427
08.858794
08.839367
08.014733
07.873465
08.930377
10.500550
12.611440
11.417870
11.872490
11.060820
12.043310
09.776299
09.557194
09.202590
10.224020
09.350807
08.300913
08.365779
08.133595
07.660470
08.074839
07.848597
07.998220
07.396895
07.900419
08.100500
07.899453
07.599783
08.100929
09.002175
10.298900
10.101520
10.699150
09.698140
09.800951
10.900470
10.697850
09.297252
10.397440
10.900720
12.901270
13.099060
11.698280
11.099870
11.301570
10.702110
10.099310
09.591119

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time13 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 13 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116778&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]13 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116778&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116778&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 time13 seconds
R Server'George Udny Yule' @ 72.249.76.132






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8615617.60910
20.712876.29590
30.5817685.1381e-06
40.5251954.63847e-06
50.4241333.74580.000171
60.2708932.39250.009571
70.1251271.10510.136259
80.026190.23130.408842
9-0.057642-0.50910.306066
10-0.189164-1.67060.0494
11-0.356736-3.15060.001155
12-0.521175-4.60298e-06
13-0.548401-4.84333e-06
14-0.539855-4.76794e-06
15-0.51952-4.58838e-06
16-0.523217-4.62097e-06
17-0.51693-4.56549e-06
18-0.495251-4.37391.9e-05
19-0.476149-4.20523.4e-05
20-0.460714-4.06895.6e-05
21-0.426026-3.76260.000162
22-0.352395-3.11230.001297
23-0.243762-2.15280.017211
24-0.112634-0.99480.161465
25-0.02015-0.1780.429607
260.0441880.39030.348704
270.0952130.84090.201487
280.1544191.36380.088278
290.2161561.9090.029967
300.2745232.42450.008821
310.3427583.02720.001672
320.4069813.59440.000284
330.4583114.04776e-05
340.4488923.96458.1e-05
350.4223073.72970.000181
360.3503333.09410.00137

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.861561 & 7.6091 & 0 \tabularnewline
2 & 0.71287 & 6.2959 & 0 \tabularnewline
3 & 0.581768 & 5.138 & 1e-06 \tabularnewline
4 & 0.525195 & 4.6384 & 7e-06 \tabularnewline
5 & 0.424133 & 3.7458 & 0.000171 \tabularnewline
6 & 0.270893 & 2.3925 & 0.009571 \tabularnewline
7 & 0.125127 & 1.1051 & 0.136259 \tabularnewline
8 & 0.02619 & 0.2313 & 0.408842 \tabularnewline
9 & -0.057642 & -0.5091 & 0.306066 \tabularnewline
10 & -0.189164 & -1.6706 & 0.0494 \tabularnewline
11 & -0.356736 & -3.1506 & 0.001155 \tabularnewline
12 & -0.521175 & -4.6029 & 8e-06 \tabularnewline
13 & -0.548401 & -4.8433 & 3e-06 \tabularnewline
14 & -0.539855 & -4.7679 & 4e-06 \tabularnewline
15 & -0.51952 & -4.5883 & 8e-06 \tabularnewline
16 & -0.523217 & -4.6209 & 7e-06 \tabularnewline
17 & -0.51693 & -4.5654 & 9e-06 \tabularnewline
18 & -0.495251 & -4.3739 & 1.9e-05 \tabularnewline
19 & -0.476149 & -4.2052 & 3.4e-05 \tabularnewline
20 & -0.460714 & -4.0689 & 5.6e-05 \tabularnewline
21 & -0.426026 & -3.7626 & 0.000162 \tabularnewline
22 & -0.352395 & -3.1123 & 0.001297 \tabularnewline
23 & -0.243762 & -2.1528 & 0.017211 \tabularnewline
24 & -0.112634 & -0.9948 & 0.161465 \tabularnewline
25 & -0.02015 & -0.178 & 0.429607 \tabularnewline
26 & 0.044188 & 0.3903 & 0.348704 \tabularnewline
27 & 0.095213 & 0.8409 & 0.201487 \tabularnewline
28 & 0.154419 & 1.3638 & 0.088278 \tabularnewline
29 & 0.216156 & 1.909 & 0.029967 \tabularnewline
30 & 0.274523 & 2.4245 & 0.008821 \tabularnewline
31 & 0.342758 & 3.0272 & 0.001672 \tabularnewline
32 & 0.406981 & 3.5944 & 0.000284 \tabularnewline
33 & 0.458311 & 4.0477 & 6e-05 \tabularnewline
34 & 0.448892 & 3.9645 & 8.1e-05 \tabularnewline
35 & 0.422307 & 3.7297 & 0.000181 \tabularnewline
36 & 0.350333 & 3.0941 & 0.00137 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116778&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]0.861561[/C][C]7.6091[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.71287[/C][C]6.2959[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.581768[/C][C]5.138[/C][C]1e-06[/C][/ROW]
[ROW][C]4[/C][C]0.525195[/C][C]4.6384[/C][C]7e-06[/C][/ROW]
[ROW][C]5[/C][C]0.424133[/C][C]3.7458[/C][C]0.000171[/C][/ROW]
[ROW][C]6[/C][C]0.270893[/C][C]2.3925[/C][C]0.009571[/C][/ROW]
[ROW][C]7[/C][C]0.125127[/C][C]1.1051[/C][C]0.136259[/C][/ROW]
[ROW][C]8[/C][C]0.02619[/C][C]0.2313[/C][C]0.408842[/C][/ROW]
[ROW][C]9[/C][C]-0.057642[/C][C]-0.5091[/C][C]0.306066[/C][/ROW]
[ROW][C]10[/C][C]-0.189164[/C][C]-1.6706[/C][C]0.0494[/C][/ROW]
[ROW][C]11[/C][C]-0.356736[/C][C]-3.1506[/C][C]0.001155[/C][/ROW]
[ROW][C]12[/C][C]-0.521175[/C][C]-4.6029[/C][C]8e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.548401[/C][C]-4.8433[/C][C]3e-06[/C][/ROW]
[ROW][C]14[/C][C]-0.539855[/C][C]-4.7679[/C][C]4e-06[/C][/ROW]
[ROW][C]15[/C][C]-0.51952[/C][C]-4.5883[/C][C]8e-06[/C][/ROW]
[ROW][C]16[/C][C]-0.523217[/C][C]-4.6209[/C][C]7e-06[/C][/ROW]
[ROW][C]17[/C][C]-0.51693[/C][C]-4.5654[/C][C]9e-06[/C][/ROW]
[ROW][C]18[/C][C]-0.495251[/C][C]-4.3739[/C][C]1.9e-05[/C][/ROW]
[ROW][C]19[/C][C]-0.476149[/C][C]-4.2052[/C][C]3.4e-05[/C][/ROW]
[ROW][C]20[/C][C]-0.460714[/C][C]-4.0689[/C][C]5.6e-05[/C][/ROW]
[ROW][C]21[/C][C]-0.426026[/C][C]-3.7626[/C][C]0.000162[/C][/ROW]
[ROW][C]22[/C][C]-0.352395[/C][C]-3.1123[/C][C]0.001297[/C][/ROW]
[ROW][C]23[/C][C]-0.243762[/C][C]-2.1528[/C][C]0.017211[/C][/ROW]
[ROW][C]24[/C][C]-0.112634[/C][C]-0.9948[/C][C]0.161465[/C][/ROW]
[ROW][C]25[/C][C]-0.02015[/C][C]-0.178[/C][C]0.429607[/C][/ROW]
[ROW][C]26[/C][C]0.044188[/C][C]0.3903[/C][C]0.348704[/C][/ROW]
[ROW][C]27[/C][C]0.095213[/C][C]0.8409[/C][C]0.201487[/C][/ROW]
[ROW][C]28[/C][C]0.154419[/C][C]1.3638[/C][C]0.088278[/C][/ROW]
[ROW][C]29[/C][C]0.216156[/C][C]1.909[/C][C]0.029967[/C][/ROW]
[ROW][C]30[/C][C]0.274523[/C][C]2.4245[/C][C]0.008821[/C][/ROW]
[ROW][C]31[/C][C]0.342758[/C][C]3.0272[/C][C]0.001672[/C][/ROW]
[ROW][C]32[/C][C]0.406981[/C][C]3.5944[/C][C]0.000284[/C][/ROW]
[ROW][C]33[/C][C]0.458311[/C][C]4.0477[/C][C]6e-05[/C][/ROW]
[ROW][C]34[/C][C]0.448892[/C][C]3.9645[/C][C]8.1e-05[/C][/ROW]
[ROW][C]35[/C][C]0.422307[/C][C]3.7297[/C][C]0.000181[/C][/ROW]
[ROW][C]36[/C][C]0.350333[/C][C]3.0941[/C][C]0.00137[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116778&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116778&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
10.8615617.60910
20.712876.29590
30.5817685.1381e-06
40.5251954.63847e-06
50.4241333.74580.000171
60.2708932.39250.009571
70.1251271.10510.136259
80.026190.23130.408842
9-0.057642-0.50910.306066
10-0.189164-1.67060.0494
11-0.356736-3.15060.001155
12-0.521175-4.60298e-06
13-0.548401-4.84333e-06
14-0.539855-4.76794e-06
15-0.51952-4.58838e-06
16-0.523217-4.62097e-06
17-0.51693-4.56549e-06
18-0.495251-4.37391.9e-05
19-0.476149-4.20523.4e-05
20-0.460714-4.06895.6e-05
21-0.426026-3.76260.000162
22-0.352395-3.11230.001297
23-0.243762-2.15280.017211
24-0.112634-0.99480.161465
25-0.02015-0.1780.429607
260.0441880.39030.348704
270.0952130.84090.201487
280.1544191.36380.088278
290.2161561.9090.029967
300.2745232.42450.008821
310.3427583.02720.001672
320.4069813.59440.000284
330.4583114.04776e-05
340.4488923.96458.1e-05
350.4223073.72970.000181
360.3503333.09410.00137






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8615617.60910
2-0.114145-1.00810.158262
3-0.016416-0.1450.442548
40.2049851.81040.037044
5-0.247089-2.18220.016051
6-0.250069-2.20860.015071
70.0065340.05770.477065
8-0.02788-0.24620.403075
9-0.132694-1.17190.122397
10-0.229171-2.0240.023198
11-0.231401-2.04370.022181
12-0.273607-2.41640.009005
130.2787192.46160.00802
140.0079070.06980.472251
150.0047480.04190.48333
160.1256811.110.135207
17-0.178553-1.57690.059428
18-0.260882-2.3040.011941
19-0.114207-1.00860.158131
20-0.083261-0.73530.232167
21-0.021812-0.19260.42387
220.0601330.53110.298436
230.001060.00940.496276
24-0.000658-0.00580.497688
250.0335470.29630.383902
26-0.097995-0.86550.194719
270.0074410.06570.473884
280.08710.76920.222035
29-0.039056-0.34490.365538
30-0.026505-0.23410.407766
310.0559540.49420.311288
32-0.082202-0.7260.235009
330.0118770.10490.458363
34-0.122161-1.07890.141979
350.0414020.36570.357806
36-0.066578-0.5880.279116

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.861561 & 7.6091 & 0 \tabularnewline
2 & -0.114145 & -1.0081 & 0.158262 \tabularnewline
3 & -0.016416 & -0.145 & 0.442548 \tabularnewline
4 & 0.204985 & 1.8104 & 0.037044 \tabularnewline
5 & -0.247089 & -2.1822 & 0.016051 \tabularnewline
6 & -0.250069 & -2.2086 & 0.015071 \tabularnewline
7 & 0.006534 & 0.0577 & 0.477065 \tabularnewline
8 & -0.02788 & -0.2462 & 0.403075 \tabularnewline
9 & -0.132694 & -1.1719 & 0.122397 \tabularnewline
10 & -0.229171 & -2.024 & 0.023198 \tabularnewline
11 & -0.231401 & -2.0437 & 0.022181 \tabularnewline
12 & -0.273607 & -2.4164 & 0.009005 \tabularnewline
13 & 0.278719 & 2.4616 & 0.00802 \tabularnewline
14 & 0.007907 & 0.0698 & 0.472251 \tabularnewline
15 & 0.004748 & 0.0419 & 0.48333 \tabularnewline
16 & 0.125681 & 1.11 & 0.135207 \tabularnewline
17 & -0.178553 & -1.5769 & 0.059428 \tabularnewline
18 & -0.260882 & -2.304 & 0.011941 \tabularnewline
19 & -0.114207 & -1.0086 & 0.158131 \tabularnewline
20 & -0.083261 & -0.7353 & 0.232167 \tabularnewline
21 & -0.021812 & -0.1926 & 0.42387 \tabularnewline
22 & 0.060133 & 0.5311 & 0.298436 \tabularnewline
23 & 0.00106 & 0.0094 & 0.496276 \tabularnewline
24 & -0.000658 & -0.0058 & 0.497688 \tabularnewline
25 & 0.033547 & 0.2963 & 0.383902 \tabularnewline
26 & -0.097995 & -0.8655 & 0.194719 \tabularnewline
27 & 0.007441 & 0.0657 & 0.473884 \tabularnewline
28 & 0.0871 & 0.7692 & 0.222035 \tabularnewline
29 & -0.039056 & -0.3449 & 0.365538 \tabularnewline
30 & -0.026505 & -0.2341 & 0.407766 \tabularnewline
31 & 0.055954 & 0.4942 & 0.311288 \tabularnewline
32 & -0.082202 & -0.726 & 0.235009 \tabularnewline
33 & 0.011877 & 0.1049 & 0.458363 \tabularnewline
34 & -0.122161 & -1.0789 & 0.141979 \tabularnewline
35 & 0.041402 & 0.3657 & 0.357806 \tabularnewline
36 & -0.066578 & -0.588 & 0.279116 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116778&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]0.861561[/C][C]7.6091[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.114145[/C][C]-1.0081[/C][C]0.158262[/C][/ROW]
[ROW][C]3[/C][C]-0.016416[/C][C]-0.145[/C][C]0.442548[/C][/ROW]
[ROW][C]4[/C][C]0.204985[/C][C]1.8104[/C][C]0.037044[/C][/ROW]
[ROW][C]5[/C][C]-0.247089[/C][C]-2.1822[/C][C]0.016051[/C][/ROW]
[ROW][C]6[/C][C]-0.250069[/C][C]-2.2086[/C][C]0.015071[/C][/ROW]
[ROW][C]7[/C][C]0.006534[/C][C]0.0577[/C][C]0.477065[/C][/ROW]
[ROW][C]8[/C][C]-0.02788[/C][C]-0.2462[/C][C]0.403075[/C][/ROW]
[ROW][C]9[/C][C]-0.132694[/C][C]-1.1719[/C][C]0.122397[/C][/ROW]
[ROW][C]10[/C][C]-0.229171[/C][C]-2.024[/C][C]0.023198[/C][/ROW]
[ROW][C]11[/C][C]-0.231401[/C][C]-2.0437[/C][C]0.022181[/C][/ROW]
[ROW][C]12[/C][C]-0.273607[/C][C]-2.4164[/C][C]0.009005[/C][/ROW]
[ROW][C]13[/C][C]0.278719[/C][C]2.4616[/C][C]0.00802[/C][/ROW]
[ROW][C]14[/C][C]0.007907[/C][C]0.0698[/C][C]0.472251[/C][/ROW]
[ROW][C]15[/C][C]0.004748[/C][C]0.0419[/C][C]0.48333[/C][/ROW]
[ROW][C]16[/C][C]0.125681[/C][C]1.11[/C][C]0.135207[/C][/ROW]
[ROW][C]17[/C][C]-0.178553[/C][C]-1.5769[/C][C]0.059428[/C][/ROW]
[ROW][C]18[/C][C]-0.260882[/C][C]-2.304[/C][C]0.011941[/C][/ROW]
[ROW][C]19[/C][C]-0.114207[/C][C]-1.0086[/C][C]0.158131[/C][/ROW]
[ROW][C]20[/C][C]-0.083261[/C][C]-0.7353[/C][C]0.232167[/C][/ROW]
[ROW][C]21[/C][C]-0.021812[/C][C]-0.1926[/C][C]0.42387[/C][/ROW]
[ROW][C]22[/C][C]0.060133[/C][C]0.5311[/C][C]0.298436[/C][/ROW]
[ROW][C]23[/C][C]0.00106[/C][C]0.0094[/C][C]0.496276[/C][/ROW]
[ROW][C]24[/C][C]-0.000658[/C][C]-0.0058[/C][C]0.497688[/C][/ROW]
[ROW][C]25[/C][C]0.033547[/C][C]0.2963[/C][C]0.383902[/C][/ROW]
[ROW][C]26[/C][C]-0.097995[/C][C]-0.8655[/C][C]0.194719[/C][/ROW]
[ROW][C]27[/C][C]0.007441[/C][C]0.0657[/C][C]0.473884[/C][/ROW]
[ROW][C]28[/C][C]0.0871[/C][C]0.7692[/C][C]0.222035[/C][/ROW]
[ROW][C]29[/C][C]-0.039056[/C][C]-0.3449[/C][C]0.365538[/C][/ROW]
[ROW][C]30[/C][C]-0.026505[/C][C]-0.2341[/C][C]0.407766[/C][/ROW]
[ROW][C]31[/C][C]0.055954[/C][C]0.4942[/C][C]0.311288[/C][/ROW]
[ROW][C]32[/C][C]-0.082202[/C][C]-0.726[/C][C]0.235009[/C][/ROW]
[ROW][C]33[/C][C]0.011877[/C][C]0.1049[/C][C]0.458363[/C][/ROW]
[ROW][C]34[/C][C]-0.122161[/C][C]-1.0789[/C][C]0.141979[/C][/ROW]
[ROW][C]35[/C][C]0.041402[/C][C]0.3657[/C][C]0.357806[/C][/ROW]
[ROW][C]36[/C][C]-0.066578[/C][C]-0.588[/C][C]0.279116[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116778&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116778&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
10.8615617.60910
2-0.114145-1.00810.158262
3-0.016416-0.1450.442548
40.2049851.81040.037044
5-0.247089-2.18220.016051
6-0.250069-2.20860.015071
70.0065340.05770.477065
8-0.02788-0.24620.403075
9-0.132694-1.17190.122397
10-0.229171-2.0240.023198
11-0.231401-2.04370.022181
12-0.273607-2.41640.009005
130.2787192.46160.00802
140.0079070.06980.472251
150.0047480.04190.48333
160.1256811.110.135207
17-0.178553-1.57690.059428
18-0.260882-2.3040.011941
19-0.114207-1.00860.158131
20-0.083261-0.73530.232167
21-0.021812-0.19260.42387
220.0601330.53110.298436
230.001060.00940.496276
24-0.000658-0.00580.497688
250.0335470.29630.383902
26-0.097995-0.86550.194719
270.0074410.06570.473884
280.08710.76920.222035
29-0.039056-0.34490.365538
30-0.026505-0.23410.407766
310.0559540.49420.311288
32-0.082202-0.7260.235009
330.0118770.10490.458363
34-0.122161-1.07890.141979
350.0414020.36570.357806
36-0.066578-0.5880.279116


Figures (Output of Computation)

Input Parameters & R Code

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 = ;
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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')