Free Statistics

of Irreproducible Research!

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 computationTue, 24 Nov 2009 11:25:10 -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/Nov/24/t1259087183nj4i4o1nalzvy9a.htm/, Retrieved Fri, 19 Apr 2024 14:57:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59207, Retrieved Fri, 19 Apr 2024 14:57:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact150
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]
- R PD          [(Partial) Autocorrelation Function] [autocorrelatie; D...] [2009-11-24 18:25:10] [a931a0a30926b49d162330b43e89b999] [Current]
Feedback Forum

Post a new message
Dataseries X:
325412
326011
328282
317480
317539
313737
312276
309391
302950
300316
304035
333476
337698
335932
323931
313927
314485
313218
309664
302963
298989
298423
310631
329765
335083
327616
309119
295916
291413
291542
284678
276475
272566
264981
263290
296806
303598
286994
276427
266424
267153
268381
262522
255542
253158
243803
250741
280445
285257
270976
261076
255603
260376
263903
264291
263276
262572
256167
264221
293860
300713
287224




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59207&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59207&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59207&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'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8895456.290
20.7900115.58620
30.7246435.1242e-06
40.6312824.46382.3e-05
50.5313463.75720.000225
60.4213442.97930.002225
70.3161322.23540.014944
80.22991.62560.055157
90.1524281.07780.143142
100.0697330.49310.312054
11-0.014575-0.10310.459163
12-0.103134-0.72930.234621
13-0.165924-1.17330.123125
14-0.21593-1.52690.066549
15-0.282258-1.99590.025705
16-0.345091-2.44020.009134
17-0.385826-2.72820.004382
18-0.429181-3.03480.001907
19-0.4623-3.2690.000978
20-0.501487-3.5460.00043
21-0.54968-3.88680.00015
22-0.555166-3.92560.000133
23-0.522035-3.69130.000276
24-0.505125-3.57180.000398
25-0.465315-3.29030.000919
26-0.41961-2.96710.002301
27-0.368683-2.6070.006004
28-0.278142-1.96680.027386
29-0.216534-1.53110.066021
30-0.166784-1.17930.121923
31-0.112668-0.79670.2147
32-0.061264-0.43320.333366
33-0.007082-0.05010.480131
340.0495870.35060.363668
350.076140.53840.296349
360.1051930.74380.230232

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.889545 & 6.29 & 0 \tabularnewline
2 & 0.790011 & 5.5862 & 0 \tabularnewline
3 & 0.724643 & 5.124 & 2e-06 \tabularnewline
4 & 0.631282 & 4.4638 & 2.3e-05 \tabularnewline
5 & 0.531346 & 3.7572 & 0.000225 \tabularnewline
6 & 0.421344 & 2.9793 & 0.002225 \tabularnewline
7 & 0.316132 & 2.2354 & 0.014944 \tabularnewline
8 & 0.2299 & 1.6256 & 0.055157 \tabularnewline
9 & 0.152428 & 1.0778 & 0.143142 \tabularnewline
10 & 0.069733 & 0.4931 & 0.312054 \tabularnewline
11 & -0.014575 & -0.1031 & 0.459163 \tabularnewline
12 & -0.103134 & -0.7293 & 0.234621 \tabularnewline
13 & -0.165924 & -1.1733 & 0.123125 \tabularnewline
14 & -0.21593 & -1.5269 & 0.066549 \tabularnewline
15 & -0.282258 & -1.9959 & 0.025705 \tabularnewline
16 & -0.345091 & -2.4402 & 0.009134 \tabularnewline
17 & -0.385826 & -2.7282 & 0.004382 \tabularnewline
18 & -0.429181 & -3.0348 & 0.001907 \tabularnewline
19 & -0.4623 & -3.269 & 0.000978 \tabularnewline
20 & -0.501487 & -3.546 & 0.00043 \tabularnewline
21 & -0.54968 & -3.8868 & 0.00015 \tabularnewline
22 & -0.555166 & -3.9256 & 0.000133 \tabularnewline
23 & -0.522035 & -3.6913 & 0.000276 \tabularnewline
24 & -0.505125 & -3.5718 & 0.000398 \tabularnewline
25 & -0.465315 & -3.2903 & 0.000919 \tabularnewline
26 & -0.41961 & -2.9671 & 0.002301 \tabularnewline
27 & -0.368683 & -2.607 & 0.006004 \tabularnewline
28 & -0.278142 & -1.9668 & 0.027386 \tabularnewline
29 & -0.216534 & -1.5311 & 0.066021 \tabularnewline
30 & -0.166784 & -1.1793 & 0.121923 \tabularnewline
31 & -0.112668 & -0.7967 & 0.2147 \tabularnewline
32 & -0.061264 & -0.4332 & 0.333366 \tabularnewline
33 & -0.007082 & -0.0501 & 0.480131 \tabularnewline
34 & 0.049587 & 0.3506 & 0.363668 \tabularnewline
35 & 0.07614 & 0.5384 & 0.296349 \tabularnewline
36 & 0.105193 & 0.7438 & 0.230232 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59207&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]0.889545[/C][C]6.29[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.790011[/C][C]5.5862[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.724643[/C][C]5.124[/C][C]2e-06[/C][/ROW]
[ROW][C]4[/C][C]0.631282[/C][C]4.4638[/C][C]2.3e-05[/C][/ROW]
[ROW][C]5[/C][C]0.531346[/C][C]3.7572[/C][C]0.000225[/C][/ROW]
[ROW][C]6[/C][C]0.421344[/C][C]2.9793[/C][C]0.002225[/C][/ROW]
[ROW][C]7[/C][C]0.316132[/C][C]2.2354[/C][C]0.014944[/C][/ROW]
[ROW][C]8[/C][C]0.2299[/C][C]1.6256[/C][C]0.055157[/C][/ROW]
[ROW][C]9[/C][C]0.152428[/C][C]1.0778[/C][C]0.143142[/C][/ROW]
[ROW][C]10[/C][C]0.069733[/C][C]0.4931[/C][C]0.312054[/C][/ROW]
[ROW][C]11[/C][C]-0.014575[/C][C]-0.1031[/C][C]0.459163[/C][/ROW]
[ROW][C]12[/C][C]-0.103134[/C][C]-0.7293[/C][C]0.234621[/C][/ROW]
[ROW][C]13[/C][C]-0.165924[/C][C]-1.1733[/C][C]0.123125[/C][/ROW]
[ROW][C]14[/C][C]-0.21593[/C][C]-1.5269[/C][C]0.066549[/C][/ROW]
[ROW][C]15[/C][C]-0.282258[/C][C]-1.9959[/C][C]0.025705[/C][/ROW]
[ROW][C]16[/C][C]-0.345091[/C][C]-2.4402[/C][C]0.009134[/C][/ROW]
[ROW][C]17[/C][C]-0.385826[/C][C]-2.7282[/C][C]0.004382[/C][/ROW]
[ROW][C]18[/C][C]-0.429181[/C][C]-3.0348[/C][C]0.001907[/C][/ROW]
[ROW][C]19[/C][C]-0.4623[/C][C]-3.269[/C][C]0.000978[/C][/ROW]
[ROW][C]20[/C][C]-0.501487[/C][C]-3.546[/C][C]0.00043[/C][/ROW]
[ROW][C]21[/C][C]-0.54968[/C][C]-3.8868[/C][C]0.00015[/C][/ROW]
[ROW][C]22[/C][C]-0.555166[/C][C]-3.9256[/C][C]0.000133[/C][/ROW]
[ROW][C]23[/C][C]-0.522035[/C][C]-3.6913[/C][C]0.000276[/C][/ROW]
[ROW][C]24[/C][C]-0.505125[/C][C]-3.5718[/C][C]0.000398[/C][/ROW]
[ROW][C]25[/C][C]-0.465315[/C][C]-3.2903[/C][C]0.000919[/C][/ROW]
[ROW][C]26[/C][C]-0.41961[/C][C]-2.9671[/C][C]0.002301[/C][/ROW]
[ROW][C]27[/C][C]-0.368683[/C][C]-2.607[/C][C]0.006004[/C][/ROW]
[ROW][C]28[/C][C]-0.278142[/C][C]-1.9668[/C][C]0.027386[/C][/ROW]
[ROW][C]29[/C][C]-0.216534[/C][C]-1.5311[/C][C]0.066021[/C][/ROW]
[ROW][C]30[/C][C]-0.166784[/C][C]-1.1793[/C][C]0.121923[/C][/ROW]
[ROW][C]31[/C][C]-0.112668[/C][C]-0.7967[/C][C]0.2147[/C][/ROW]
[ROW][C]32[/C][C]-0.061264[/C][C]-0.4332[/C][C]0.333366[/C][/ROW]
[ROW][C]33[/C][C]-0.007082[/C][C]-0.0501[/C][C]0.480131[/C][/ROW]
[ROW][C]34[/C][C]0.049587[/C][C]0.3506[/C][C]0.363668[/C][/ROW]
[ROW][C]35[/C][C]0.07614[/C][C]0.5384[/C][C]0.296349[/C][/ROW]
[ROW][C]36[/C][C]0.105193[/C][C]0.7438[/C][C]0.230232[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59207&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59207&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
10.8895456.290
20.7900115.58620
30.7246435.1242e-06
40.6312824.46382.3e-05
50.5313463.75720.000225
60.4213442.97930.002225
70.3161322.23540.014944
80.22991.62560.055157
90.1524281.07780.143142
100.0697330.49310.312054
11-0.014575-0.10310.459163
12-0.103134-0.72930.234621
13-0.165924-1.17330.123125
14-0.21593-1.52690.066549
15-0.282258-1.99590.025705
16-0.345091-2.44020.009134
17-0.385826-2.72820.004382
18-0.429181-3.03480.001907
19-0.4623-3.2690.000978
20-0.501487-3.5460.00043
21-0.54968-3.88680.00015
22-0.555166-3.92560.000133
23-0.522035-3.69130.000276
24-0.505125-3.57180.000398
25-0.465315-3.29030.000919
26-0.41961-2.96710.002301
27-0.368683-2.6070.006004
28-0.278142-1.96680.027386
29-0.216534-1.53110.066021
30-0.166784-1.17930.121923
31-0.112668-0.79670.2147
32-0.061264-0.43320.333366
33-0.007082-0.05010.480131
340.0495870.35060.363668
350.076140.53840.296349
360.1051930.74380.230232







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8895456.290
2-0.00613-0.04330.482798
30.1103830.78050.219381
4-0.160374-1.1340.131098
5-0.074937-0.52990.299268
6-0.154867-1.09510.139365
7-0.053032-0.3750.354625
80.0015380.01090.495682
90.0050520.03570.485823
10-0.065555-0.46350.322494
11-0.086171-0.60930.272535
12-0.135706-0.95960.170941
130.0174520.12340.45114
14-0.017665-0.12490.450547
15-0.098696-0.69790.244241
16-0.082575-0.58390.28096
17-0.020929-0.1480.441473
18-0.107086-0.75720.226238
19-0.029852-0.21110.41684
20-0.13266-0.9380.176364
21-0.135244-0.95630.171757
220.0505090.35720.36124
230.1250110.8840.190474
24-0.062313-0.44060.330694
250.0866380.61260.271451
26-0.064629-0.4570.324826
27-0.014939-0.10560.458147
280.1276610.90270.185508
29-0.080623-0.57010.285585
30-0.017036-0.12050.4523
31-0.056725-0.40110.345024
32-0.033691-0.23820.406337
33-0.017056-0.12060.452245
340.0596680.42190.337449
35-0.080464-0.5690.285964
36-0.019512-0.1380.445408

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.889545 & 6.29 & 0 \tabularnewline
2 & -0.00613 & -0.0433 & 0.482798 \tabularnewline
3 & 0.110383 & 0.7805 & 0.219381 \tabularnewline
4 & -0.160374 & -1.134 & 0.131098 \tabularnewline
5 & -0.074937 & -0.5299 & 0.299268 \tabularnewline
6 & -0.154867 & -1.0951 & 0.139365 \tabularnewline
7 & -0.053032 & -0.375 & 0.354625 \tabularnewline
8 & 0.001538 & 0.0109 & 0.495682 \tabularnewline
9 & 0.005052 & 0.0357 & 0.485823 \tabularnewline
10 & -0.065555 & -0.4635 & 0.322494 \tabularnewline
11 & -0.086171 & -0.6093 & 0.272535 \tabularnewline
12 & -0.135706 & -0.9596 & 0.170941 \tabularnewline
13 & 0.017452 & 0.1234 & 0.45114 \tabularnewline
14 & -0.017665 & -0.1249 & 0.450547 \tabularnewline
15 & -0.098696 & -0.6979 & 0.244241 \tabularnewline
16 & -0.082575 & -0.5839 & 0.28096 \tabularnewline
17 & -0.020929 & -0.148 & 0.441473 \tabularnewline
18 & -0.107086 & -0.7572 & 0.226238 \tabularnewline
19 & -0.029852 & -0.2111 & 0.41684 \tabularnewline
20 & -0.13266 & -0.938 & 0.176364 \tabularnewline
21 & -0.135244 & -0.9563 & 0.171757 \tabularnewline
22 & 0.050509 & 0.3572 & 0.36124 \tabularnewline
23 & 0.125011 & 0.884 & 0.190474 \tabularnewline
24 & -0.062313 & -0.4406 & 0.330694 \tabularnewline
25 & 0.086638 & 0.6126 & 0.271451 \tabularnewline
26 & -0.064629 & -0.457 & 0.324826 \tabularnewline
27 & -0.014939 & -0.1056 & 0.458147 \tabularnewline
28 & 0.127661 & 0.9027 & 0.185508 \tabularnewline
29 & -0.080623 & -0.5701 & 0.285585 \tabularnewline
30 & -0.017036 & -0.1205 & 0.4523 \tabularnewline
31 & -0.056725 & -0.4011 & 0.345024 \tabularnewline
32 & -0.033691 & -0.2382 & 0.406337 \tabularnewline
33 & -0.017056 & -0.1206 & 0.452245 \tabularnewline
34 & 0.059668 & 0.4219 & 0.337449 \tabularnewline
35 & -0.080464 & -0.569 & 0.285964 \tabularnewline
36 & -0.019512 & -0.138 & 0.445408 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59207&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]0.889545[/C][C]6.29[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.00613[/C][C]-0.0433[/C][C]0.482798[/C][/ROW]
[ROW][C]3[/C][C]0.110383[/C][C]0.7805[/C][C]0.219381[/C][/ROW]
[ROW][C]4[/C][C]-0.160374[/C][C]-1.134[/C][C]0.131098[/C][/ROW]
[ROW][C]5[/C][C]-0.074937[/C][C]-0.5299[/C][C]0.299268[/C][/ROW]
[ROW][C]6[/C][C]-0.154867[/C][C]-1.0951[/C][C]0.139365[/C][/ROW]
[ROW][C]7[/C][C]-0.053032[/C][C]-0.375[/C][C]0.354625[/C][/ROW]
[ROW][C]8[/C][C]0.001538[/C][C]0.0109[/C][C]0.495682[/C][/ROW]
[ROW][C]9[/C][C]0.005052[/C][C]0.0357[/C][C]0.485823[/C][/ROW]
[ROW][C]10[/C][C]-0.065555[/C][C]-0.4635[/C][C]0.322494[/C][/ROW]
[ROW][C]11[/C][C]-0.086171[/C][C]-0.6093[/C][C]0.272535[/C][/ROW]
[ROW][C]12[/C][C]-0.135706[/C][C]-0.9596[/C][C]0.170941[/C][/ROW]
[ROW][C]13[/C][C]0.017452[/C][C]0.1234[/C][C]0.45114[/C][/ROW]
[ROW][C]14[/C][C]-0.017665[/C][C]-0.1249[/C][C]0.450547[/C][/ROW]
[ROW][C]15[/C][C]-0.098696[/C][C]-0.6979[/C][C]0.244241[/C][/ROW]
[ROW][C]16[/C][C]-0.082575[/C][C]-0.5839[/C][C]0.28096[/C][/ROW]
[ROW][C]17[/C][C]-0.020929[/C][C]-0.148[/C][C]0.441473[/C][/ROW]
[ROW][C]18[/C][C]-0.107086[/C][C]-0.7572[/C][C]0.226238[/C][/ROW]
[ROW][C]19[/C][C]-0.029852[/C][C]-0.2111[/C][C]0.41684[/C][/ROW]
[ROW][C]20[/C][C]-0.13266[/C][C]-0.938[/C][C]0.176364[/C][/ROW]
[ROW][C]21[/C][C]-0.135244[/C][C]-0.9563[/C][C]0.171757[/C][/ROW]
[ROW][C]22[/C][C]0.050509[/C][C]0.3572[/C][C]0.36124[/C][/ROW]
[ROW][C]23[/C][C]0.125011[/C][C]0.884[/C][C]0.190474[/C][/ROW]
[ROW][C]24[/C][C]-0.062313[/C][C]-0.4406[/C][C]0.330694[/C][/ROW]
[ROW][C]25[/C][C]0.086638[/C][C]0.6126[/C][C]0.271451[/C][/ROW]
[ROW][C]26[/C][C]-0.064629[/C][C]-0.457[/C][C]0.324826[/C][/ROW]
[ROW][C]27[/C][C]-0.014939[/C][C]-0.1056[/C][C]0.458147[/C][/ROW]
[ROW][C]28[/C][C]0.127661[/C][C]0.9027[/C][C]0.185508[/C][/ROW]
[ROW][C]29[/C][C]-0.080623[/C][C]-0.5701[/C][C]0.285585[/C][/ROW]
[ROW][C]30[/C][C]-0.017036[/C][C]-0.1205[/C][C]0.4523[/C][/ROW]
[ROW][C]31[/C][C]-0.056725[/C][C]-0.4011[/C][C]0.345024[/C][/ROW]
[ROW][C]32[/C][C]-0.033691[/C][C]-0.2382[/C][C]0.406337[/C][/ROW]
[ROW][C]33[/C][C]-0.017056[/C][C]-0.1206[/C][C]0.452245[/C][/ROW]
[ROW][C]34[/C][C]0.059668[/C][C]0.4219[/C][C]0.337449[/C][/ROW]
[ROW][C]35[/C][C]-0.080464[/C][C]-0.569[/C][C]0.285964[/C][/ROW]
[ROW][C]36[/C][C]-0.019512[/C][C]-0.138[/C][C]0.445408[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59207&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59207&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
10.8895456.290
2-0.00613-0.04330.482798
30.1103830.78050.219381
4-0.160374-1.1340.131098
5-0.074937-0.52990.299268
6-0.154867-1.09510.139365
7-0.053032-0.3750.354625
80.0015380.01090.495682
90.0050520.03570.485823
10-0.065555-0.46350.322494
11-0.086171-0.60930.272535
12-0.135706-0.95960.170941
130.0174520.12340.45114
14-0.017665-0.12490.450547
15-0.098696-0.69790.244241
16-0.082575-0.58390.28096
17-0.020929-0.1480.441473
18-0.107086-0.75720.226238
19-0.029852-0.21110.41684
20-0.13266-0.9380.176364
21-0.135244-0.95630.171757
220.0505090.35720.36124
230.1250110.8840.190474
24-0.062313-0.44060.330694
250.0866380.61260.271451
26-0.064629-0.4570.324826
27-0.014939-0.10560.458147
280.1276610.90270.185508
29-0.080623-0.57010.285585
30-0.017036-0.12050.4523
31-0.056725-0.40110.345024
32-0.033691-0.23820.406337
33-0.017056-0.12060.452245
340.0596680.42190.337449
35-0.080464-0.5690.285964
36-0.019512-0.1380.445408



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 ;
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')