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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 12:50:49 +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/t1293626919h1qroh7k13oi2fk.htm/, Retrieved Fri, 03 May 2024 11:44:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116769, Retrieved Fri, 03 May 2024 11:44:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact173
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 12:50:49] [e180d4cd19004beeddc12e67012247dc] [Current]
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Dataseries X:
04.031636
03.702076
03.056167
03.280707
02.984728
03.693712
03.226317
02.190349
02.599515
03.080288
02.929672
02.922548
03.234943
02.983081
03.284389
03.806511
03.784579
02.645654
03.092081
03.204859
03.107225
03.466909
02.984404
03.218072
02.827310
03.182049
02.236319
02.033218
01.644804
01.627971
01.677559
02.330828
02.493615
02.257172
02.655517
02.298655
02.600402
03.045230
02.790583
03.227052
02.967479
02.938817
03.277961
03.423985
03.072646
02.754253
02.910431
03.174369
03.068387
03.089543
02.906654
02.931161
03.025660
02.939551
02.691019
03.198120
03.076390
02.863873
03.013802
03.053364
02.864753
03.057062
02.959365
03.252258
03.602988
03.497704
03.296867
03.602417
03.300100
03.401930
03.502591
03.402348
03.498551
03.199823
02.700064
02.801034
02.898628
02.800854
02.399942
02.402724
02.202331
02.102594
01.798293
01.202484
01.400201
01.200832
01.298083
01.099742
01.001377
00.836174




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116769&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116769&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116769&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 time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.172704-1.51550.066873
2-0.018221-0.15990.436694
3-0.071419-0.62670.266355
40.0289140.25370.400196
50.1030060.90390.184441
60.0017350.01520.493948
70.0045970.04030.483963
8-0.16201-1.42160.079586
90.1215491.06660.144745
10-0.046782-0.41050.341287
110.0999950.87740.191486
12-0.429761-3.77110.000159
130.0650590.57090.284869
14-0.141638-1.24290.108843
15-0.027745-0.24350.404149
160.1053940.92480.178972
17-0.046806-0.41070.341208
180.1010310.88650.189044
19-0.060612-0.53190.298174
200.0294340.25830.398439
21-0.045762-0.40160.344559
220.0564270.49510.310955
230.0602950.52910.299135
240.1113240.97690.165847
25-0.008412-0.07380.470674
26-0.001104-0.00970.496147
270.0886610.7780.219478
280.0537660.47180.319204
29-0.017853-0.15670.437961
30-0.080481-0.70620.241092
310.0120810.1060.457926
320.0253330.22230.412337
330.0627530.55070.291733
340.0472130.41430.339907
35-0.132884-1.16610.123596
36-0.06235-0.54710.292939

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.172704 & -1.5155 & 0.066873 \tabularnewline
2 & -0.018221 & -0.1599 & 0.436694 \tabularnewline
3 & -0.071419 & -0.6267 & 0.266355 \tabularnewline
4 & 0.028914 & 0.2537 & 0.400196 \tabularnewline
5 & 0.103006 & 0.9039 & 0.184441 \tabularnewline
6 & 0.001735 & 0.0152 & 0.493948 \tabularnewline
7 & 0.004597 & 0.0403 & 0.483963 \tabularnewline
8 & -0.16201 & -1.4216 & 0.079586 \tabularnewline
9 & 0.121549 & 1.0666 & 0.144745 \tabularnewline
10 & -0.046782 & -0.4105 & 0.341287 \tabularnewline
11 & 0.099995 & 0.8774 & 0.191486 \tabularnewline
12 & -0.429761 & -3.7711 & 0.000159 \tabularnewline
13 & 0.065059 & 0.5709 & 0.284869 \tabularnewline
14 & -0.141638 & -1.2429 & 0.108843 \tabularnewline
15 & -0.027745 & -0.2435 & 0.404149 \tabularnewline
16 & 0.105394 & 0.9248 & 0.178972 \tabularnewline
17 & -0.046806 & -0.4107 & 0.341208 \tabularnewline
18 & 0.101031 & 0.8865 & 0.189044 \tabularnewline
19 & -0.060612 & -0.5319 & 0.298174 \tabularnewline
20 & 0.029434 & 0.2583 & 0.398439 \tabularnewline
21 & -0.045762 & -0.4016 & 0.344559 \tabularnewline
22 & 0.056427 & 0.4951 & 0.310955 \tabularnewline
23 & 0.060295 & 0.5291 & 0.299135 \tabularnewline
24 & 0.111324 & 0.9769 & 0.165847 \tabularnewline
25 & -0.008412 & -0.0738 & 0.470674 \tabularnewline
26 & -0.001104 & -0.0097 & 0.496147 \tabularnewline
27 & 0.088661 & 0.778 & 0.219478 \tabularnewline
28 & 0.053766 & 0.4718 & 0.319204 \tabularnewline
29 & -0.017853 & -0.1567 & 0.437961 \tabularnewline
30 & -0.080481 & -0.7062 & 0.241092 \tabularnewline
31 & 0.012081 & 0.106 & 0.457926 \tabularnewline
32 & 0.025333 & 0.2223 & 0.412337 \tabularnewline
33 & 0.062753 & 0.5507 & 0.291733 \tabularnewline
34 & 0.047213 & 0.4143 & 0.339907 \tabularnewline
35 & -0.132884 & -1.1661 & 0.123596 \tabularnewline
36 & -0.06235 & -0.5471 & 0.292939 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116769&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]-0.172704[/C][C]-1.5155[/C][C]0.066873[/C][/ROW]
[ROW][C]2[/C][C]-0.018221[/C][C]-0.1599[/C][C]0.436694[/C][/ROW]
[ROW][C]3[/C][C]-0.071419[/C][C]-0.6267[/C][C]0.266355[/C][/ROW]
[ROW][C]4[/C][C]0.028914[/C][C]0.2537[/C][C]0.400196[/C][/ROW]
[ROW][C]5[/C][C]0.103006[/C][C]0.9039[/C][C]0.184441[/C][/ROW]
[ROW][C]6[/C][C]0.001735[/C][C]0.0152[/C][C]0.493948[/C][/ROW]
[ROW][C]7[/C][C]0.004597[/C][C]0.0403[/C][C]0.483963[/C][/ROW]
[ROW][C]8[/C][C]-0.16201[/C][C]-1.4216[/C][C]0.079586[/C][/ROW]
[ROW][C]9[/C][C]0.121549[/C][C]1.0666[/C][C]0.144745[/C][/ROW]
[ROW][C]10[/C][C]-0.046782[/C][C]-0.4105[/C][C]0.341287[/C][/ROW]
[ROW][C]11[/C][C]0.099995[/C][C]0.8774[/C][C]0.191486[/C][/ROW]
[ROW][C]12[/C][C]-0.429761[/C][C]-3.7711[/C][C]0.000159[/C][/ROW]
[ROW][C]13[/C][C]0.065059[/C][C]0.5709[/C][C]0.284869[/C][/ROW]
[ROW][C]14[/C][C]-0.141638[/C][C]-1.2429[/C][C]0.108843[/C][/ROW]
[ROW][C]15[/C][C]-0.027745[/C][C]-0.2435[/C][C]0.404149[/C][/ROW]
[ROW][C]16[/C][C]0.105394[/C][C]0.9248[/C][C]0.178972[/C][/ROW]
[ROW][C]17[/C][C]-0.046806[/C][C]-0.4107[/C][C]0.341208[/C][/ROW]
[ROW][C]18[/C][C]0.101031[/C][C]0.8865[/C][C]0.189044[/C][/ROW]
[ROW][C]19[/C][C]-0.060612[/C][C]-0.5319[/C][C]0.298174[/C][/ROW]
[ROW][C]20[/C][C]0.029434[/C][C]0.2583[/C][C]0.398439[/C][/ROW]
[ROW][C]21[/C][C]-0.045762[/C][C]-0.4016[/C][C]0.344559[/C][/ROW]
[ROW][C]22[/C][C]0.056427[/C][C]0.4951[/C][C]0.310955[/C][/ROW]
[ROW][C]23[/C][C]0.060295[/C][C]0.5291[/C][C]0.299135[/C][/ROW]
[ROW][C]24[/C][C]0.111324[/C][C]0.9769[/C][C]0.165847[/C][/ROW]
[ROW][C]25[/C][C]-0.008412[/C][C]-0.0738[/C][C]0.470674[/C][/ROW]
[ROW][C]26[/C][C]-0.001104[/C][C]-0.0097[/C][C]0.496147[/C][/ROW]
[ROW][C]27[/C][C]0.088661[/C][C]0.778[/C][C]0.219478[/C][/ROW]
[ROW][C]28[/C][C]0.053766[/C][C]0.4718[/C][C]0.319204[/C][/ROW]
[ROW][C]29[/C][C]-0.017853[/C][C]-0.1567[/C][C]0.437961[/C][/ROW]
[ROW][C]30[/C][C]-0.080481[/C][C]-0.7062[/C][C]0.241092[/C][/ROW]
[ROW][C]31[/C][C]0.012081[/C][C]0.106[/C][C]0.457926[/C][/ROW]
[ROW][C]32[/C][C]0.025333[/C][C]0.2223[/C][C]0.412337[/C][/ROW]
[ROW][C]33[/C][C]0.062753[/C][C]0.5507[/C][C]0.291733[/C][/ROW]
[ROW][C]34[/C][C]0.047213[/C][C]0.4143[/C][C]0.339907[/C][/ROW]
[ROW][C]35[/C][C]-0.132884[/C][C]-1.1661[/C][C]0.123596[/C][/ROW]
[ROW][C]36[/C][C]-0.06235[/C][C]-0.5471[/C][C]0.292939[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116769&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116769&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
1-0.172704-1.51550.066873
2-0.018221-0.15990.436694
3-0.071419-0.62670.266355
40.0289140.25370.400196
50.1030060.90390.184441
60.0017350.01520.493948
70.0045970.04030.483963
8-0.16201-1.42160.079586
90.1215491.06660.144745
10-0.046782-0.41050.341287
110.0999950.87740.191486
12-0.429761-3.77110.000159
130.0650590.57090.284869
14-0.141638-1.24290.108843
15-0.027745-0.24350.404149
160.1053940.92480.178972
17-0.046806-0.41070.341208
180.1010310.88650.189044
19-0.060612-0.53190.298174
200.0294340.25830.398439
21-0.045762-0.40160.344559
220.0564270.49510.310955
230.0602950.52910.299135
240.1113240.97690.165847
25-0.008412-0.07380.470674
26-0.001104-0.00970.496147
270.0886610.7780.219478
280.0537660.47180.319204
29-0.017853-0.15670.437961
30-0.080481-0.70620.241092
310.0120810.1060.457926
320.0253330.22230.412337
330.0627530.55070.291733
340.0472130.41430.339907
35-0.132884-1.16610.123596
36-0.06235-0.54710.292939







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.172704-1.51550.066873
2-0.049525-0.43460.332542
3-0.086046-0.75510.22626
4-0.000399-0.00350.498608
50.1062640.93250.177007
60.0373880.32810.371871
70.0242720.2130.415949
8-0.14839-1.30210.098379
90.0674950.59230.277705
10-0.039-0.34220.366558
110.075210.660.255624
12-0.420107-3.68640.000211
13-0.043951-0.38570.350403
14-0.244749-2.14770.017443
15-0.147323-1.29280.099981
160.0080650.07080.471881
170.0751520.65950.255786
180.1503791.31960.095444
190.0992270.87070.193308
20-0.056411-0.4950.311004
210.0354090.31070.378428
22-0.071076-0.62370.267337
230.1153651.01230.157278
24-0.048275-0.42360.336517
250.0436720.38320.351305
26-0.156852-1.37640.086348
27-0.012246-0.10750.457353
280.0879840.77210.221222
290.0086210.07570.469947
300.0802470.70420.241728
310.0979290.85930.196415
320.0448290.39340.347566
330.1052510.92360.179297
340.0434860.38160.351908
35-0.004226-0.03710.485257
36-0.067148-0.58920.27872

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.172704 & -1.5155 & 0.066873 \tabularnewline
2 & -0.049525 & -0.4346 & 0.332542 \tabularnewline
3 & -0.086046 & -0.7551 & 0.22626 \tabularnewline
4 & -0.000399 & -0.0035 & 0.498608 \tabularnewline
5 & 0.106264 & 0.9325 & 0.177007 \tabularnewline
6 & 0.037388 & 0.3281 & 0.371871 \tabularnewline
7 & 0.024272 & 0.213 & 0.415949 \tabularnewline
8 & -0.14839 & -1.3021 & 0.098379 \tabularnewline
9 & 0.067495 & 0.5923 & 0.277705 \tabularnewline
10 & -0.039 & -0.3422 & 0.366558 \tabularnewline
11 & 0.07521 & 0.66 & 0.255624 \tabularnewline
12 & -0.420107 & -3.6864 & 0.000211 \tabularnewline
13 & -0.043951 & -0.3857 & 0.350403 \tabularnewline
14 & -0.244749 & -2.1477 & 0.017443 \tabularnewline
15 & -0.147323 & -1.2928 & 0.099981 \tabularnewline
16 & 0.008065 & 0.0708 & 0.471881 \tabularnewline
17 & 0.075152 & 0.6595 & 0.255786 \tabularnewline
18 & 0.150379 & 1.3196 & 0.095444 \tabularnewline
19 & 0.099227 & 0.8707 & 0.193308 \tabularnewline
20 & -0.056411 & -0.495 & 0.311004 \tabularnewline
21 & 0.035409 & 0.3107 & 0.378428 \tabularnewline
22 & -0.071076 & -0.6237 & 0.267337 \tabularnewline
23 & 0.115365 & 1.0123 & 0.157278 \tabularnewline
24 & -0.048275 & -0.4236 & 0.336517 \tabularnewline
25 & 0.043672 & 0.3832 & 0.351305 \tabularnewline
26 & -0.156852 & -1.3764 & 0.086348 \tabularnewline
27 & -0.012246 & -0.1075 & 0.457353 \tabularnewline
28 & 0.087984 & 0.7721 & 0.221222 \tabularnewline
29 & 0.008621 & 0.0757 & 0.469947 \tabularnewline
30 & 0.080247 & 0.7042 & 0.241728 \tabularnewline
31 & 0.097929 & 0.8593 & 0.196415 \tabularnewline
32 & 0.044829 & 0.3934 & 0.347566 \tabularnewline
33 & 0.105251 & 0.9236 & 0.179297 \tabularnewline
34 & 0.043486 & 0.3816 & 0.351908 \tabularnewline
35 & -0.004226 & -0.0371 & 0.485257 \tabularnewline
36 & -0.067148 & -0.5892 & 0.27872 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116769&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]-0.172704[/C][C]-1.5155[/C][C]0.066873[/C][/ROW]
[ROW][C]2[/C][C]-0.049525[/C][C]-0.4346[/C][C]0.332542[/C][/ROW]
[ROW][C]3[/C][C]-0.086046[/C][C]-0.7551[/C][C]0.22626[/C][/ROW]
[ROW][C]4[/C][C]-0.000399[/C][C]-0.0035[/C][C]0.498608[/C][/ROW]
[ROW][C]5[/C][C]0.106264[/C][C]0.9325[/C][C]0.177007[/C][/ROW]
[ROW][C]6[/C][C]0.037388[/C][C]0.3281[/C][C]0.371871[/C][/ROW]
[ROW][C]7[/C][C]0.024272[/C][C]0.213[/C][C]0.415949[/C][/ROW]
[ROW][C]8[/C][C]-0.14839[/C][C]-1.3021[/C][C]0.098379[/C][/ROW]
[ROW][C]9[/C][C]0.067495[/C][C]0.5923[/C][C]0.277705[/C][/ROW]
[ROW][C]10[/C][C]-0.039[/C][C]-0.3422[/C][C]0.366558[/C][/ROW]
[ROW][C]11[/C][C]0.07521[/C][C]0.66[/C][C]0.255624[/C][/ROW]
[ROW][C]12[/C][C]-0.420107[/C][C]-3.6864[/C][C]0.000211[/C][/ROW]
[ROW][C]13[/C][C]-0.043951[/C][C]-0.3857[/C][C]0.350403[/C][/ROW]
[ROW][C]14[/C][C]-0.244749[/C][C]-2.1477[/C][C]0.017443[/C][/ROW]
[ROW][C]15[/C][C]-0.147323[/C][C]-1.2928[/C][C]0.099981[/C][/ROW]
[ROW][C]16[/C][C]0.008065[/C][C]0.0708[/C][C]0.471881[/C][/ROW]
[ROW][C]17[/C][C]0.075152[/C][C]0.6595[/C][C]0.255786[/C][/ROW]
[ROW][C]18[/C][C]0.150379[/C][C]1.3196[/C][C]0.095444[/C][/ROW]
[ROW][C]19[/C][C]0.099227[/C][C]0.8707[/C][C]0.193308[/C][/ROW]
[ROW][C]20[/C][C]-0.056411[/C][C]-0.495[/C][C]0.311004[/C][/ROW]
[ROW][C]21[/C][C]0.035409[/C][C]0.3107[/C][C]0.378428[/C][/ROW]
[ROW][C]22[/C][C]-0.071076[/C][C]-0.6237[/C][C]0.267337[/C][/ROW]
[ROW][C]23[/C][C]0.115365[/C][C]1.0123[/C][C]0.157278[/C][/ROW]
[ROW][C]24[/C][C]-0.048275[/C][C]-0.4236[/C][C]0.336517[/C][/ROW]
[ROW][C]25[/C][C]0.043672[/C][C]0.3832[/C][C]0.351305[/C][/ROW]
[ROW][C]26[/C][C]-0.156852[/C][C]-1.3764[/C][C]0.086348[/C][/ROW]
[ROW][C]27[/C][C]-0.012246[/C][C]-0.1075[/C][C]0.457353[/C][/ROW]
[ROW][C]28[/C][C]0.087984[/C][C]0.7721[/C][C]0.221222[/C][/ROW]
[ROW][C]29[/C][C]0.008621[/C][C]0.0757[/C][C]0.469947[/C][/ROW]
[ROW][C]30[/C][C]0.080247[/C][C]0.7042[/C][C]0.241728[/C][/ROW]
[ROW][C]31[/C][C]0.097929[/C][C]0.8593[/C][C]0.196415[/C][/ROW]
[ROW][C]32[/C][C]0.044829[/C][C]0.3934[/C][C]0.347566[/C][/ROW]
[ROW][C]33[/C][C]0.105251[/C][C]0.9236[/C][C]0.179297[/C][/ROW]
[ROW][C]34[/C][C]0.043486[/C][C]0.3816[/C][C]0.351908[/C][/ROW]
[ROW][C]35[/C][C]-0.004226[/C][C]-0.0371[/C][C]0.485257[/C][/ROW]
[ROW][C]36[/C][C]-0.067148[/C][C]-0.5892[/C][C]0.27872[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116769&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116769&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
1-0.172704-1.51550.066873
2-0.049525-0.43460.332542
3-0.086046-0.75510.22626
4-0.000399-0.00350.498608
50.1062640.93250.177007
60.0373880.32810.371871
70.0242720.2130.415949
8-0.14839-1.30210.098379
90.0674950.59230.277705
10-0.039-0.34220.366558
110.075210.660.255624
12-0.420107-3.68640.000211
13-0.043951-0.38570.350403
14-0.244749-2.14770.017443
15-0.147323-1.29280.099981
160.0080650.07080.471881
170.0751520.65950.255786
180.1503791.31960.095444
190.0992270.87070.193308
20-0.056411-0.4950.311004
210.0354090.31070.378428
22-0.071076-0.62370.267337
230.1153651.01230.157278
24-0.048275-0.42360.336517
250.0436720.38320.351305
26-0.156852-1.37640.086348
27-0.012246-0.10750.457353
280.0879840.77210.221222
290.0086210.07570.469947
300.0802470.70420.241728
310.0979290.85930.196415
320.0448290.39340.347566
330.1052510.92360.179297
340.0434860.38160.351908
35-0.004226-0.03710.485257
36-0.067148-0.58920.27872



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