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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, 13 Dec 2009 02:34:23 -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/13/t1260696907yx1yjy1jw1sdg9h.htm/, Retrieved Sun, 28 Apr 2024 02:51:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67174, Retrieved Sun, 28 Apr 2024 02:51:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact168

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] [SHWWS8methode1a] [2009-11-24 16:42:45] [a66d3a79ef9e5308cd94a469bc5ca464]
-    D            [(Partial) Autocorrelation Function] [PAPER] [2009-12-13 09:34:23] [db49399df1e4a3dbe31268849cebfd7f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
452
462
455
461
461
463
462
456
455
456
472
472
471
465
459
465
468
467
463
460
462
461
476
476
471
453
443
442
444
438
427
424
416
406
431
434
418
412
404
409
412
406
398
397
385
390
413
413
401
397
397
409
419
424
428
430
424
433
456
459

Tables (Output of Computation)





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=67174&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=67174&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67174&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9371337.2590
20.8517976.5980
30.8060866.24390
40.7825816.06180
50.7668665.94010
60.7293025.64920
70.6532335.05992e-06
80.558134.32332.9e-05
90.4806813.72330.000218
100.4357733.37550.000649
110.4200313.25350.000937
120.3806092.94820.002275
130.2682372.07780.021009
140.1575741.22060.113513
150.0864150.66940.252915
160.0379020.29360.385043
170.0018540.01440.494295
18-0.042097-0.32610.372748
19-0.109897-0.85130.199005
20-0.194321-1.50520.068759
21-0.254627-1.97230.026593
22-0.282409-2.18750.016305
23-0.292449-2.26530.013559
24-0.31993-2.47820.008018
25-0.38759-3.00230.001951
26-0.441258-3.4180.000569
27-0.455308-3.52680.000407
28-0.45272-3.50680.000433
29-0.436247-3.37920.000641
30-0.419463-3.24910.000949
31-0.416407-3.22550.001019
32-0.423909-3.28360.000856
33-0.404935-3.13660.001324
34-0.366613-2.83980.003077
35-0.333783-2.58550.006086
36-0.315501-2.44390.008744

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.937133 & 7.259 & 0 \tabularnewline
2 & 0.851797 & 6.598 & 0 \tabularnewline
3 & 0.806086 & 6.2439 & 0 \tabularnewline
4 & 0.782581 & 6.0618 & 0 \tabularnewline
5 & 0.766866 & 5.9401 & 0 \tabularnewline
6 & 0.729302 & 5.6492 & 0 \tabularnewline
7 & 0.653233 & 5.0599 & 2e-06 \tabularnewline
8 & 0.55813 & 4.3233 & 2.9e-05 \tabularnewline
9 & 0.480681 & 3.7233 & 0.000218 \tabularnewline
10 & 0.435773 & 3.3755 & 0.000649 \tabularnewline
11 & 0.420031 & 3.2535 & 0.000937 \tabularnewline
12 & 0.380609 & 2.9482 & 0.002275 \tabularnewline
13 & 0.268237 & 2.0778 & 0.021009 \tabularnewline
14 & 0.157574 & 1.2206 & 0.113513 \tabularnewline
15 & 0.086415 & 0.6694 & 0.252915 \tabularnewline
16 & 0.037902 & 0.2936 & 0.385043 \tabularnewline
17 & 0.001854 & 0.0144 & 0.494295 \tabularnewline
18 & -0.042097 & -0.3261 & 0.372748 \tabularnewline
19 & -0.109897 & -0.8513 & 0.199005 \tabularnewline
20 & -0.194321 & -1.5052 & 0.068759 \tabularnewline
21 & -0.254627 & -1.9723 & 0.026593 \tabularnewline
22 & -0.282409 & -2.1875 & 0.016305 \tabularnewline
23 & -0.292449 & -2.2653 & 0.013559 \tabularnewline
24 & -0.31993 & -2.4782 & 0.008018 \tabularnewline
25 & -0.38759 & -3.0023 & 0.001951 \tabularnewline
26 & -0.441258 & -3.418 & 0.000569 \tabularnewline
27 & -0.455308 & -3.5268 & 0.000407 \tabularnewline
28 & -0.45272 & -3.5068 & 0.000433 \tabularnewline
29 & -0.436247 & -3.3792 & 0.000641 \tabularnewline
30 & -0.419463 & -3.2491 & 0.000949 \tabularnewline
31 & -0.416407 & -3.2255 & 0.001019 \tabularnewline
32 & -0.423909 & -3.2836 & 0.000856 \tabularnewline
33 & -0.404935 & -3.1366 & 0.001324 \tabularnewline
34 & -0.366613 & -2.8398 & 0.003077 \tabularnewline
35 & -0.333783 & -2.5855 & 0.006086 \tabularnewline
36 & -0.315501 & -2.4439 & 0.008744 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67174&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]0.937133[/C][C]7.259[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.851797[/C][C]6.598[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.806086[/C][C]6.2439[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.782581[/C][C]6.0618[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.766866[/C][C]5.9401[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.729302[/C][C]5.6492[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.653233[/C][C]5.0599[/C][C]2e-06[/C][/ROW]
[ROW][C]8[/C][C]0.55813[/C][C]4.3233[/C][C]2.9e-05[/C][/ROW]
[ROW][C]9[/C][C]0.480681[/C][C]3.7233[/C][C]0.000218[/C][/ROW]
[ROW][C]10[/C][C]0.435773[/C][C]3.3755[/C][C]0.000649[/C][/ROW]
[ROW][C]11[/C][C]0.420031[/C][C]3.2535[/C][C]0.000937[/C][/ROW]
[ROW][C]12[/C][C]0.380609[/C][C]2.9482[/C][C]0.002275[/C][/ROW]
[ROW][C]13[/C][C]0.268237[/C][C]2.0778[/C][C]0.021009[/C][/ROW]
[ROW][C]14[/C][C]0.157574[/C][C]1.2206[/C][C]0.113513[/C][/ROW]
[ROW][C]15[/C][C]0.086415[/C][C]0.6694[/C][C]0.252915[/C][/ROW]
[ROW][C]16[/C][C]0.037902[/C][C]0.2936[/C][C]0.385043[/C][/ROW]
[ROW][C]17[/C][C]0.001854[/C][C]0.0144[/C][C]0.494295[/C][/ROW]
[ROW][C]18[/C][C]-0.042097[/C][C]-0.3261[/C][C]0.372748[/C][/ROW]
[ROW][C]19[/C][C]-0.109897[/C][C]-0.8513[/C][C]0.199005[/C][/ROW]
[ROW][C]20[/C][C]-0.194321[/C][C]-1.5052[/C][C]0.068759[/C][/ROW]
[ROW][C]21[/C][C]-0.254627[/C][C]-1.9723[/C][C]0.026593[/C][/ROW]
[ROW][C]22[/C][C]-0.282409[/C][C]-2.1875[/C][C]0.016305[/C][/ROW]
[ROW][C]23[/C][C]-0.292449[/C][C]-2.2653[/C][C]0.013559[/C][/ROW]
[ROW][C]24[/C][C]-0.31993[/C][C]-2.4782[/C][C]0.008018[/C][/ROW]
[ROW][C]25[/C][C]-0.38759[/C][C]-3.0023[/C][C]0.001951[/C][/ROW]
[ROW][C]26[/C][C]-0.441258[/C][C]-3.418[/C][C]0.000569[/C][/ROW]
[ROW][C]27[/C][C]-0.455308[/C][C]-3.5268[/C][C]0.000407[/C][/ROW]
[ROW][C]28[/C][C]-0.45272[/C][C]-3.5068[/C][C]0.000433[/C][/ROW]
[ROW][C]29[/C][C]-0.436247[/C][C]-3.3792[/C][C]0.000641[/C][/ROW]
[ROW][C]30[/C][C]-0.419463[/C][C]-3.2491[/C][C]0.000949[/C][/ROW]
[ROW][C]31[/C][C]-0.416407[/C][C]-3.2255[/C][C]0.001019[/C][/ROW]
[ROW][C]32[/C][C]-0.423909[/C][C]-3.2836[/C][C]0.000856[/C][/ROW]
[ROW][C]33[/C][C]-0.404935[/C][C]-3.1366[/C][C]0.001324[/C][/ROW]
[ROW][C]34[/C][C]-0.366613[/C][C]-2.8398[/C][C]0.003077[/C][/ROW]
[ROW][C]35[/C][C]-0.333783[/C][C]-2.5855[/C][C]0.006086[/C][/ROW]
[ROW][C]36[/C][C]-0.315501[/C][C]-2.4439[/C][C]0.008744[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67174&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67174&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
10.9371337.2590
20.8517976.5980
30.8060866.24390
40.7825816.06180
50.7668665.94010
60.7293025.64920
70.6532335.05992e-06
80.558134.32332.9e-05
90.4806813.72330.000218
100.4357733.37550.000649
110.4200313.25350.000937
120.3806092.94820.002275
130.2682372.07780.021009
140.1575741.22060.113513
150.0864150.66940.252915
160.0379020.29360.385043
170.0018540.01440.494295
18-0.042097-0.32610.372748
19-0.109897-0.85130.199005
20-0.194321-1.50520.068759
21-0.254627-1.97230.026593
22-0.282409-2.18750.016305
23-0.292449-2.26530.013559
24-0.31993-2.47820.008018
25-0.38759-3.00230.001951
26-0.441258-3.4180.000569
27-0.455308-3.52680.000407
28-0.45272-3.50680.000433
29-0.436247-3.37920.000641
30-0.419463-3.24910.000949
31-0.416407-3.22550.001019
32-0.423909-3.28360.000856
33-0.404935-3.13660.001324
34-0.366613-2.83980.003077
35-0.333783-2.58550.006086
36-0.315501-2.44390.008744






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9371337.2590
2-0.216946-1.68050.049034
30.3271782.53430.006947
40.020130.15590.438308
50.1281840.99290.16237
6-0.189882-1.47080.073283
7-0.229743-1.77960.040104
8-0.221172-1.71320.045921
9-0.034165-0.26460.396096
100.0528070.4090.341982
110.2324351.80040.03841
12-0.1598-1.23780.110305
13-0.46093-3.57030.000355
140.1124050.87070.193699
15-0.096545-0.74780.228742
160.0131540.10190.459593
170.0100430.07780.469124
180.0928110.71890.237494
190.0339390.26290.396768
20-0.132026-1.02270.155284
210.0131880.10220.459488
22-0.127669-0.98890.163338
23-0.033374-0.25850.398448
24-0.02982-0.2310.409055
25-0.005551-0.0430.482924
260.0862630.66820.253287
270.1140550.88350.190255
28-0.030717-0.23790.406372
290.0948150.73440.232771
30-0.001439-0.01110.495573
310.0862640.66820.253284
32-0.035561-0.27550.391956
330.067210.52060.302277
34-0.124118-0.96140.170102
35-0.14306-1.10810.136113
36-0.015931-0.12340.4511

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.937133 & 7.259 & 0 \tabularnewline
2 & -0.216946 & -1.6805 & 0.049034 \tabularnewline
3 & 0.327178 & 2.5343 & 0.006947 \tabularnewline
4 & 0.02013 & 0.1559 & 0.438308 \tabularnewline
5 & 0.128184 & 0.9929 & 0.16237 \tabularnewline
6 & -0.189882 & -1.4708 & 0.073283 \tabularnewline
7 & -0.229743 & -1.7796 & 0.040104 \tabularnewline
8 & -0.221172 & -1.7132 & 0.045921 \tabularnewline
9 & -0.034165 & -0.2646 & 0.396096 \tabularnewline
10 & 0.052807 & 0.409 & 0.341982 \tabularnewline
11 & 0.232435 & 1.8004 & 0.03841 \tabularnewline
12 & -0.1598 & -1.2378 & 0.110305 \tabularnewline
13 & -0.46093 & -3.5703 & 0.000355 \tabularnewline
14 & 0.112405 & 0.8707 & 0.193699 \tabularnewline
15 & -0.096545 & -0.7478 & 0.228742 \tabularnewline
16 & 0.013154 & 0.1019 & 0.459593 \tabularnewline
17 & 0.010043 & 0.0778 & 0.469124 \tabularnewline
18 & 0.092811 & 0.7189 & 0.237494 \tabularnewline
19 & 0.033939 & 0.2629 & 0.396768 \tabularnewline
20 & -0.132026 & -1.0227 & 0.155284 \tabularnewline
21 & 0.013188 & 0.1022 & 0.459488 \tabularnewline
22 & -0.127669 & -0.9889 & 0.163338 \tabularnewline
23 & -0.033374 & -0.2585 & 0.398448 \tabularnewline
24 & -0.02982 & -0.231 & 0.409055 \tabularnewline
25 & -0.005551 & -0.043 & 0.482924 \tabularnewline
26 & 0.086263 & 0.6682 & 0.253287 \tabularnewline
27 & 0.114055 & 0.8835 & 0.190255 \tabularnewline
28 & -0.030717 & -0.2379 & 0.406372 \tabularnewline
29 & 0.094815 & 0.7344 & 0.232771 \tabularnewline
30 & -0.001439 & -0.0111 & 0.495573 \tabularnewline
31 & 0.086264 & 0.6682 & 0.253284 \tabularnewline
32 & -0.035561 & -0.2755 & 0.391956 \tabularnewline
33 & 0.06721 & 0.5206 & 0.302277 \tabularnewline
34 & -0.124118 & -0.9614 & 0.170102 \tabularnewline
35 & -0.14306 & -1.1081 & 0.136113 \tabularnewline
36 & -0.015931 & -0.1234 & 0.4511 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67174&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]0.937133[/C][C]7.259[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.216946[/C][C]-1.6805[/C][C]0.049034[/C][/ROW]
[ROW][C]3[/C][C]0.327178[/C][C]2.5343[/C][C]0.006947[/C][/ROW]
[ROW][C]4[/C][C]0.02013[/C][C]0.1559[/C][C]0.438308[/C][/ROW]
[ROW][C]5[/C][C]0.128184[/C][C]0.9929[/C][C]0.16237[/C][/ROW]
[ROW][C]6[/C][C]-0.189882[/C][C]-1.4708[/C][C]0.073283[/C][/ROW]
[ROW][C]7[/C][C]-0.229743[/C][C]-1.7796[/C][C]0.040104[/C][/ROW]
[ROW][C]8[/C][C]-0.221172[/C][C]-1.7132[/C][C]0.045921[/C][/ROW]
[ROW][C]9[/C][C]-0.034165[/C][C]-0.2646[/C][C]0.396096[/C][/ROW]
[ROW][C]10[/C][C]0.052807[/C][C]0.409[/C][C]0.341982[/C][/ROW]
[ROW][C]11[/C][C]0.232435[/C][C]1.8004[/C][C]0.03841[/C][/ROW]
[ROW][C]12[/C][C]-0.1598[/C][C]-1.2378[/C][C]0.110305[/C][/ROW]
[ROW][C]13[/C][C]-0.46093[/C][C]-3.5703[/C][C]0.000355[/C][/ROW]
[ROW][C]14[/C][C]0.112405[/C][C]0.8707[/C][C]0.193699[/C][/ROW]
[ROW][C]15[/C][C]-0.096545[/C][C]-0.7478[/C][C]0.228742[/C][/ROW]
[ROW][C]16[/C][C]0.013154[/C][C]0.1019[/C][C]0.459593[/C][/ROW]
[ROW][C]17[/C][C]0.010043[/C][C]0.0778[/C][C]0.469124[/C][/ROW]
[ROW][C]18[/C][C]0.092811[/C][C]0.7189[/C][C]0.237494[/C][/ROW]
[ROW][C]19[/C][C]0.033939[/C][C]0.2629[/C][C]0.396768[/C][/ROW]
[ROW][C]20[/C][C]-0.132026[/C][C]-1.0227[/C][C]0.155284[/C][/ROW]
[ROW][C]21[/C][C]0.013188[/C][C]0.1022[/C][C]0.459488[/C][/ROW]
[ROW][C]22[/C][C]-0.127669[/C][C]-0.9889[/C][C]0.163338[/C][/ROW]
[ROW][C]23[/C][C]-0.033374[/C][C]-0.2585[/C][C]0.398448[/C][/ROW]
[ROW][C]24[/C][C]-0.02982[/C][C]-0.231[/C][C]0.409055[/C][/ROW]
[ROW][C]25[/C][C]-0.005551[/C][C]-0.043[/C][C]0.482924[/C][/ROW]
[ROW][C]26[/C][C]0.086263[/C][C]0.6682[/C][C]0.253287[/C][/ROW]
[ROW][C]27[/C][C]0.114055[/C][C]0.8835[/C][C]0.190255[/C][/ROW]
[ROW][C]28[/C][C]-0.030717[/C][C]-0.2379[/C][C]0.406372[/C][/ROW]
[ROW][C]29[/C][C]0.094815[/C][C]0.7344[/C][C]0.232771[/C][/ROW]
[ROW][C]30[/C][C]-0.001439[/C][C]-0.0111[/C][C]0.495573[/C][/ROW]
[ROW][C]31[/C][C]0.086264[/C][C]0.6682[/C][C]0.253284[/C][/ROW]
[ROW][C]32[/C][C]-0.035561[/C][C]-0.2755[/C][C]0.391956[/C][/ROW]
[ROW][C]33[/C][C]0.06721[/C][C]0.5206[/C][C]0.302277[/C][/ROW]
[ROW][C]34[/C][C]-0.124118[/C][C]-0.9614[/C][C]0.170102[/C][/ROW]
[ROW][C]35[/C][C]-0.14306[/C][C]-1.1081[/C][C]0.136113[/C][/ROW]
[ROW][C]36[/C][C]-0.015931[/C][C]-0.1234[/C][C]0.4511[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67174&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67174&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
10.9371337.2590
2-0.216946-1.68050.049034
30.3271782.53430.006947
40.020130.15590.438308
50.1281840.99290.16237
6-0.189882-1.47080.073283
7-0.229743-1.77960.040104
8-0.221172-1.71320.045921
9-0.034165-0.26460.396096
100.0528070.4090.341982
110.2324351.80040.03841
12-0.1598-1.23780.110305
13-0.46093-3.57030.000355
140.1124050.87070.193699
15-0.096545-0.74780.228742
160.0131540.10190.459593
170.0100430.07780.469124
180.0928110.71890.237494
190.0339390.26290.396768
20-0.132026-1.02270.155284
210.0131880.10220.459488
22-0.127669-0.98890.163338
23-0.033374-0.25850.398448
24-0.02982-0.2310.409055
25-0.005551-0.0430.482924
260.0862630.66820.253287
270.1140550.88350.190255
28-0.030717-0.23790.406372
290.0948150.73440.232771
30-0.001439-0.01110.495573
310.0862640.66820.253284
32-0.035561-0.27550.391956
330.067210.52060.302277
34-0.124118-0.96140.170102
35-0.14306-1.10810.136113
36-0.015931-0.12340.4511


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')