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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 computationMon, 06 Dec 2010 19:55:19 +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/06/t1291665220up2p4drst8k1kmv.htm/, Retrieved Sun, 28 Apr 2024 22:36:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105836, Retrieved Sun, 28 Apr 2024 22:36:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152
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] [ws8_2] [2009-11-24 20:22:15] [8b1aef4e7013bd33fbc2a5833375c5f5]
-   P           [(Partial) Autocorrelation Function] [WS8_seizonaliteit1] [2009-11-25 17:44:58] [8b1aef4e7013bd33fbc2a5833375c5f5]
-    D              [(Partial) Autocorrelation Function] [paper timeserie A...] [2010-12-06 19:55:19] [da925928e5a77063c5ecc7b801d712e1] [Current]
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Dataseries X:
194,9
195,5
196
196,2
196,2
196,2
196,2
197
197,7
198
198,2
198,5
198,6
199,5
200
201,3
202,2
202,9
203,5
203,5
204
204,1
204,3
204,5
204,8
205,1
205,7
206,5
206,9
207,1
207,8
208
208,5
208,6
209
209,1
209,7
209,8
209,9
210
210,8
211,4
211,7
212
212,2
212,4
212,9
213,4
213,7
214
214,3
214,8
215
215,9
216,4
216,9
217,2
217,5
217,9
218,1
218,6
218,9
219,3
220,4
220,9
221
221,8
222
222,2
222,5
222,9
223,1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105836&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105836&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105836&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1441631.10730.136321
20.1147670.88150.1908
3-0.047313-0.36340.358797
4-0.038607-0.29650.383927
5-0.123433-0.94810.173471
60.0931640.71560.238528
7-0.035003-0.26890.394485
8-0.041581-0.31940.375281
90.0248120.19060.424753
100.0577320.44340.329531
11-0.164885-1.26650.105155
12-0.295979-2.27350.013327
130.038020.2920.385641
14-0.054571-0.41920.338307
150.0177310.13620.446064
16-0.022815-0.17520.430742
170.0971330.74610.229287
18-0.077093-0.59220.278003
190.1035270.79520.214842
200.0105720.08120.467778
21-0.097952-0.75240.227405
22-0.223404-1.7160.045705
230.0848690.65190.258502
24-0.155555-1.19480.118465
250.0017480.01340.494666
26-0.070397-0.54070.295366
27-0.018904-0.14520.442522
28-0.066107-0.50780.306751
290.0106910.08210.467416
300.0492730.37850.35322
31-0.00145-0.01110.495576
320.0404980.31110.37842
330.0649070.49860.309971
34-0.02755-0.21160.416567
35-0.07789-0.59830.27597
360.0066920.05140.479589

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.144163 & 1.1073 & 0.136321 \tabularnewline
2 & 0.114767 & 0.8815 & 0.1908 \tabularnewline
3 & -0.047313 & -0.3634 & 0.358797 \tabularnewline
4 & -0.038607 & -0.2965 & 0.383927 \tabularnewline
5 & -0.123433 & -0.9481 & 0.173471 \tabularnewline
6 & 0.093164 & 0.7156 & 0.238528 \tabularnewline
7 & -0.035003 & -0.2689 & 0.394485 \tabularnewline
8 & -0.041581 & -0.3194 & 0.375281 \tabularnewline
9 & 0.024812 & 0.1906 & 0.424753 \tabularnewline
10 & 0.057732 & 0.4434 & 0.329531 \tabularnewline
11 & -0.164885 & -1.2665 & 0.105155 \tabularnewline
12 & -0.295979 & -2.2735 & 0.013327 \tabularnewline
13 & 0.03802 & 0.292 & 0.385641 \tabularnewline
14 & -0.054571 & -0.4192 & 0.338307 \tabularnewline
15 & 0.017731 & 0.1362 & 0.446064 \tabularnewline
16 & -0.022815 & -0.1752 & 0.430742 \tabularnewline
17 & 0.097133 & 0.7461 & 0.229287 \tabularnewline
18 & -0.077093 & -0.5922 & 0.278003 \tabularnewline
19 & 0.103527 & 0.7952 & 0.214842 \tabularnewline
20 & 0.010572 & 0.0812 & 0.467778 \tabularnewline
21 & -0.097952 & -0.7524 & 0.227405 \tabularnewline
22 & -0.223404 & -1.716 & 0.045705 \tabularnewline
23 & 0.084869 & 0.6519 & 0.258502 \tabularnewline
24 & -0.155555 & -1.1948 & 0.118465 \tabularnewline
25 & 0.001748 & 0.0134 & 0.494666 \tabularnewline
26 & -0.070397 & -0.5407 & 0.295366 \tabularnewline
27 & -0.018904 & -0.1452 & 0.442522 \tabularnewline
28 & -0.066107 & -0.5078 & 0.306751 \tabularnewline
29 & 0.010691 & 0.0821 & 0.467416 \tabularnewline
30 & 0.049273 & 0.3785 & 0.35322 \tabularnewline
31 & -0.00145 & -0.0111 & 0.495576 \tabularnewline
32 & 0.040498 & 0.3111 & 0.37842 \tabularnewline
33 & 0.064907 & 0.4986 & 0.309971 \tabularnewline
34 & -0.02755 & -0.2116 & 0.416567 \tabularnewline
35 & -0.07789 & -0.5983 & 0.27597 \tabularnewline
36 & 0.006692 & 0.0514 & 0.479589 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105836&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]0.144163[/C][C]1.1073[/C][C]0.136321[/C][/ROW]
[ROW][C]2[/C][C]0.114767[/C][C]0.8815[/C][C]0.1908[/C][/ROW]
[ROW][C]3[/C][C]-0.047313[/C][C]-0.3634[/C][C]0.358797[/C][/ROW]
[ROW][C]4[/C][C]-0.038607[/C][C]-0.2965[/C][C]0.383927[/C][/ROW]
[ROW][C]5[/C][C]-0.123433[/C][C]-0.9481[/C][C]0.173471[/C][/ROW]
[ROW][C]6[/C][C]0.093164[/C][C]0.7156[/C][C]0.238528[/C][/ROW]
[ROW][C]7[/C][C]-0.035003[/C][C]-0.2689[/C][C]0.394485[/C][/ROW]
[ROW][C]8[/C][C]-0.041581[/C][C]-0.3194[/C][C]0.375281[/C][/ROW]
[ROW][C]9[/C][C]0.024812[/C][C]0.1906[/C][C]0.424753[/C][/ROW]
[ROW][C]10[/C][C]0.057732[/C][C]0.4434[/C][C]0.329531[/C][/ROW]
[ROW][C]11[/C][C]-0.164885[/C][C]-1.2665[/C][C]0.105155[/C][/ROW]
[ROW][C]12[/C][C]-0.295979[/C][C]-2.2735[/C][C]0.013327[/C][/ROW]
[ROW][C]13[/C][C]0.03802[/C][C]0.292[/C][C]0.385641[/C][/ROW]
[ROW][C]14[/C][C]-0.054571[/C][C]-0.4192[/C][C]0.338307[/C][/ROW]
[ROW][C]15[/C][C]0.017731[/C][C]0.1362[/C][C]0.446064[/C][/ROW]
[ROW][C]16[/C][C]-0.022815[/C][C]-0.1752[/C][C]0.430742[/C][/ROW]
[ROW][C]17[/C][C]0.097133[/C][C]0.7461[/C][C]0.229287[/C][/ROW]
[ROW][C]18[/C][C]-0.077093[/C][C]-0.5922[/C][C]0.278003[/C][/ROW]
[ROW][C]19[/C][C]0.103527[/C][C]0.7952[/C][C]0.214842[/C][/ROW]
[ROW][C]20[/C][C]0.010572[/C][C]0.0812[/C][C]0.467778[/C][/ROW]
[ROW][C]21[/C][C]-0.097952[/C][C]-0.7524[/C][C]0.227405[/C][/ROW]
[ROW][C]22[/C][C]-0.223404[/C][C]-1.716[/C][C]0.045705[/C][/ROW]
[ROW][C]23[/C][C]0.084869[/C][C]0.6519[/C][C]0.258502[/C][/ROW]
[ROW][C]24[/C][C]-0.155555[/C][C]-1.1948[/C][C]0.118465[/C][/ROW]
[ROW][C]25[/C][C]0.001748[/C][C]0.0134[/C][C]0.494666[/C][/ROW]
[ROW][C]26[/C][C]-0.070397[/C][C]-0.5407[/C][C]0.295366[/C][/ROW]
[ROW][C]27[/C][C]-0.018904[/C][C]-0.1452[/C][C]0.442522[/C][/ROW]
[ROW][C]28[/C][C]-0.066107[/C][C]-0.5078[/C][C]0.306751[/C][/ROW]
[ROW][C]29[/C][C]0.010691[/C][C]0.0821[/C][C]0.467416[/C][/ROW]
[ROW][C]30[/C][C]0.049273[/C][C]0.3785[/C][C]0.35322[/C][/ROW]
[ROW][C]31[/C][C]-0.00145[/C][C]-0.0111[/C][C]0.495576[/C][/ROW]
[ROW][C]32[/C][C]0.040498[/C][C]0.3111[/C][C]0.37842[/C][/ROW]
[ROW][C]33[/C][C]0.064907[/C][C]0.4986[/C][C]0.309971[/C][/ROW]
[ROW][C]34[/C][C]-0.02755[/C][C]-0.2116[/C][C]0.416567[/C][/ROW]
[ROW][C]35[/C][C]-0.07789[/C][C]-0.5983[/C][C]0.27597[/C][/ROW]
[ROW][C]36[/C][C]0.006692[/C][C]0.0514[/C][C]0.479589[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105836&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105836&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
10.1441631.10730.136321
20.1147670.88150.1908
3-0.047313-0.36340.358797
4-0.038607-0.29650.383927
5-0.123433-0.94810.173471
60.0931640.71560.238528
7-0.035003-0.26890.394485
8-0.041581-0.31940.375281
90.0248120.19060.424753
100.0577320.44340.329531
11-0.164885-1.26650.105155
12-0.295979-2.27350.013327
130.038020.2920.385641
14-0.054571-0.41920.338307
150.0177310.13620.446064
16-0.022815-0.17520.430742
170.0971330.74610.229287
18-0.077093-0.59220.278003
190.1035270.79520.214842
200.0105720.08120.467778
21-0.097952-0.75240.227405
22-0.223404-1.7160.045705
230.0848690.65190.258502
24-0.155555-1.19480.118465
250.0017480.01340.494666
26-0.070397-0.54070.295366
27-0.018904-0.14520.442522
28-0.066107-0.50780.306751
290.0106910.08210.467416
300.0492730.37850.35322
31-0.00145-0.01110.495576
320.0404980.31110.37842
330.0649070.49860.309971
34-0.02755-0.21160.416567
35-0.07789-0.59830.27597
360.0066920.05140.479589







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1441631.10730.136321
20.0959790.73720.231952
3-0.078444-0.60250.274561
4-0.034188-0.26260.396887
5-0.103444-0.79460.215024
60.1339631.0290.153842
7-0.047787-0.36710.357443
8-0.073428-0.5640.287443
90.057210.43940.330975
100.0534680.41070.341392
11-0.184625-1.41810.080706
12-0.315278-2.42170.00927
130.200861.54280.064109
140.0147330.11320.455143
15-0.084624-0.650.259105
16-0.116903-0.89790.186431
170.1744471.340.092699
180.0104460.08020.468162
19-0.066889-0.51380.30466
20-0.016793-0.1290.448903
21-0.028014-0.21520.415183
22-0.196481-1.50920.068292
23-0.003187-0.02450.490275
24-0.172252-1.32310.095454
250.0899420.69090.246183
26-0.14867-1.1420.129042
27-0.074007-0.56850.285941
280.0084210.06470.474322
290.0005420.00420.498346
300.033720.2590.398265
310.0061020.04690.481387
320.0212720.16340.435383
33-0.072782-0.5590.289122
34-0.172223-1.32290.095491
350.0008780.00670.49732
36-0.115335-0.88590.189633

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.144163 & 1.1073 & 0.136321 \tabularnewline
2 & 0.095979 & 0.7372 & 0.231952 \tabularnewline
3 & -0.078444 & -0.6025 & 0.274561 \tabularnewline
4 & -0.034188 & -0.2626 & 0.396887 \tabularnewline
5 & -0.103444 & -0.7946 & 0.215024 \tabularnewline
6 & 0.133963 & 1.029 & 0.153842 \tabularnewline
7 & -0.047787 & -0.3671 & 0.357443 \tabularnewline
8 & -0.073428 & -0.564 & 0.287443 \tabularnewline
9 & 0.05721 & 0.4394 & 0.330975 \tabularnewline
10 & 0.053468 & 0.4107 & 0.341392 \tabularnewline
11 & -0.184625 & -1.4181 & 0.080706 \tabularnewline
12 & -0.315278 & -2.4217 & 0.00927 \tabularnewline
13 & 0.20086 & 1.5428 & 0.064109 \tabularnewline
14 & 0.014733 & 0.1132 & 0.455143 \tabularnewline
15 & -0.084624 & -0.65 & 0.259105 \tabularnewline
16 & -0.116903 & -0.8979 & 0.186431 \tabularnewline
17 & 0.174447 & 1.34 & 0.092699 \tabularnewline
18 & 0.010446 & 0.0802 & 0.468162 \tabularnewline
19 & -0.066889 & -0.5138 & 0.30466 \tabularnewline
20 & -0.016793 & -0.129 & 0.448903 \tabularnewline
21 & -0.028014 & -0.2152 & 0.415183 \tabularnewline
22 & -0.196481 & -1.5092 & 0.068292 \tabularnewline
23 & -0.003187 & -0.0245 & 0.490275 \tabularnewline
24 & -0.172252 & -1.3231 & 0.095454 \tabularnewline
25 & 0.089942 & 0.6909 & 0.246183 \tabularnewline
26 & -0.14867 & -1.142 & 0.129042 \tabularnewline
27 & -0.074007 & -0.5685 & 0.285941 \tabularnewline
28 & 0.008421 & 0.0647 & 0.474322 \tabularnewline
29 & 0.000542 & 0.0042 & 0.498346 \tabularnewline
30 & 0.03372 & 0.259 & 0.398265 \tabularnewline
31 & 0.006102 & 0.0469 & 0.481387 \tabularnewline
32 & 0.021272 & 0.1634 & 0.435383 \tabularnewline
33 & -0.072782 & -0.559 & 0.289122 \tabularnewline
34 & -0.172223 & -1.3229 & 0.095491 \tabularnewline
35 & 0.000878 & 0.0067 & 0.49732 \tabularnewline
36 & -0.115335 & -0.8859 & 0.189633 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105836&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]0.144163[/C][C]1.1073[/C][C]0.136321[/C][/ROW]
[ROW][C]2[/C][C]0.095979[/C][C]0.7372[/C][C]0.231952[/C][/ROW]
[ROW][C]3[/C][C]-0.078444[/C][C]-0.6025[/C][C]0.274561[/C][/ROW]
[ROW][C]4[/C][C]-0.034188[/C][C]-0.2626[/C][C]0.396887[/C][/ROW]
[ROW][C]5[/C][C]-0.103444[/C][C]-0.7946[/C][C]0.215024[/C][/ROW]
[ROW][C]6[/C][C]0.133963[/C][C]1.029[/C][C]0.153842[/C][/ROW]
[ROW][C]7[/C][C]-0.047787[/C][C]-0.3671[/C][C]0.357443[/C][/ROW]
[ROW][C]8[/C][C]-0.073428[/C][C]-0.564[/C][C]0.287443[/C][/ROW]
[ROW][C]9[/C][C]0.05721[/C][C]0.4394[/C][C]0.330975[/C][/ROW]
[ROW][C]10[/C][C]0.053468[/C][C]0.4107[/C][C]0.341392[/C][/ROW]
[ROW][C]11[/C][C]-0.184625[/C][C]-1.4181[/C][C]0.080706[/C][/ROW]
[ROW][C]12[/C][C]-0.315278[/C][C]-2.4217[/C][C]0.00927[/C][/ROW]
[ROW][C]13[/C][C]0.20086[/C][C]1.5428[/C][C]0.064109[/C][/ROW]
[ROW][C]14[/C][C]0.014733[/C][C]0.1132[/C][C]0.455143[/C][/ROW]
[ROW][C]15[/C][C]-0.084624[/C][C]-0.65[/C][C]0.259105[/C][/ROW]
[ROW][C]16[/C][C]-0.116903[/C][C]-0.8979[/C][C]0.186431[/C][/ROW]
[ROW][C]17[/C][C]0.174447[/C][C]1.34[/C][C]0.092699[/C][/ROW]
[ROW][C]18[/C][C]0.010446[/C][C]0.0802[/C][C]0.468162[/C][/ROW]
[ROW][C]19[/C][C]-0.066889[/C][C]-0.5138[/C][C]0.30466[/C][/ROW]
[ROW][C]20[/C][C]-0.016793[/C][C]-0.129[/C][C]0.448903[/C][/ROW]
[ROW][C]21[/C][C]-0.028014[/C][C]-0.2152[/C][C]0.415183[/C][/ROW]
[ROW][C]22[/C][C]-0.196481[/C][C]-1.5092[/C][C]0.068292[/C][/ROW]
[ROW][C]23[/C][C]-0.003187[/C][C]-0.0245[/C][C]0.490275[/C][/ROW]
[ROW][C]24[/C][C]-0.172252[/C][C]-1.3231[/C][C]0.095454[/C][/ROW]
[ROW][C]25[/C][C]0.089942[/C][C]0.6909[/C][C]0.246183[/C][/ROW]
[ROW][C]26[/C][C]-0.14867[/C][C]-1.142[/C][C]0.129042[/C][/ROW]
[ROW][C]27[/C][C]-0.074007[/C][C]-0.5685[/C][C]0.285941[/C][/ROW]
[ROW][C]28[/C][C]0.008421[/C][C]0.0647[/C][C]0.474322[/C][/ROW]
[ROW][C]29[/C][C]0.000542[/C][C]0.0042[/C][C]0.498346[/C][/ROW]
[ROW][C]30[/C][C]0.03372[/C][C]0.259[/C][C]0.398265[/C][/ROW]
[ROW][C]31[/C][C]0.006102[/C][C]0.0469[/C][C]0.481387[/C][/ROW]
[ROW][C]32[/C][C]0.021272[/C][C]0.1634[/C][C]0.435383[/C][/ROW]
[ROW][C]33[/C][C]-0.072782[/C][C]-0.559[/C][C]0.289122[/C][/ROW]
[ROW][C]34[/C][C]-0.172223[/C][C]-1.3229[/C][C]0.095491[/C][/ROW]
[ROW][C]35[/C][C]0.000878[/C][C]0.0067[/C][C]0.49732[/C][/ROW]
[ROW][C]36[/C][C]-0.115335[/C][C]-0.8859[/C][C]0.189633[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105836&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105836&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
10.1441631.10730.136321
20.0959790.73720.231952
3-0.078444-0.60250.274561
4-0.034188-0.26260.396887
5-0.103444-0.79460.215024
60.1339631.0290.153842
7-0.047787-0.36710.357443
8-0.073428-0.5640.287443
90.057210.43940.330975
100.0534680.41070.341392
11-0.184625-1.41810.080706
12-0.315278-2.42170.00927
130.200861.54280.064109
140.0147330.11320.455143
15-0.084624-0.650.259105
16-0.116903-0.89790.186431
170.1744471.340.092699
180.0104460.08020.468162
19-0.066889-0.51380.30466
20-0.016793-0.1290.448903
21-0.028014-0.21520.415183
22-0.196481-1.50920.068292
23-0.003187-0.02450.490275
24-0.172252-1.32310.095454
250.0899420.69090.246183
26-0.14867-1.1420.129042
27-0.074007-0.56850.285941
280.0084210.06470.474322
290.0005420.00420.498346
300.033720.2590.398265
310.0061020.04690.481387
320.0212720.16340.435383
33-0.072782-0.5590.289122
34-0.172223-1.32290.095491
350.0008780.00670.49732
36-0.115335-0.88590.189633



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 ;
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')