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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 computationTue, 21 Dec 2010 19:24:48 +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/21/t1292959354rzqwmkpwz2p6us7.htm/, Retrieved Thu, 31 Oct 2024 23:31:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=113869, Retrieved Thu, 31 Oct 2024 23:31:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact162
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [Partial autocorre...] [2008-12-09 20:18:51] [12d343c4448a5f9e527bb31caeac580b]
-   P   [(Partial) Autocorrelation Function] [Partial autocorre...] [2008-12-09 20:27:26] [12d343c4448a5f9e527bb31caeac580b]
-  MPD    [(Partial) Autocorrelation Function] [] [2009-12-11 11:51:14] [cf890101a20378422561610e0d41fd9c]
- R PD        [(Partial) Autocorrelation Function] [] [2010-12-21 19:24:48] [7131fefee4115a2a717140ef0bdd6369] [Current]
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Dataseries X:
627
696
825
677
656
785
412
352
839
729
696
641
695
638
762
635
721
854
418
367
824
687
601
676
740
691
683
594
729
731
386
331
707
715
657
653
642
643
718
654
632
731
392
344
792
852
649
629
685
617
715
715
629
916
531
357
917
828
708
858
775
785
1006
789
734
906
532
387
991
841




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113869&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113869&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113869&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3871072.94810.0023
20.2188751.66690.050463
30.3208722.44370.008801
40.0764460.58220.281345
50.2141291.63080.05418
60.2986162.27420.013335
70.1459521.11150.135462
80.3339512.54330.006835
90.2495931.90080.031148
100.102520.78080.219057
110.1603111.22090.113534
12-0.072619-0.55310.291177
13-0.106655-0.81230.209981
140.1398231.06490.145677
150.0717490.54640.293435
16-0.019071-0.14520.442512
170.0909290.69250.245694
180.0291970.22240.412409
19-0.070134-0.53410.297649
200.0114340.08710.465455
21-0.082271-0.62660.266703
22-0.141426-1.07710.142955
23-0.089439-0.68110.249244
24-0.231911-1.76620.041314
25-0.121553-0.92570.179213
26-0.120291-0.91610.181701
27-0.178938-1.36280.089114
28-0.047274-0.360.360068
29-0.080777-0.61520.270421
30-0.240257-1.82970.036215
31-0.193563-1.47410.072927
32-0.261882-1.99440.025406
33-0.198104-1.50870.0684
34-0.080788-0.61530.270393
35-0.099017-0.75410.226923
36-0.055934-0.4260.335849

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.387107 & 2.9481 & 0.0023 \tabularnewline
2 & 0.218875 & 1.6669 & 0.050463 \tabularnewline
3 & 0.320872 & 2.4437 & 0.008801 \tabularnewline
4 & 0.076446 & 0.5822 & 0.281345 \tabularnewline
5 & 0.214129 & 1.6308 & 0.05418 \tabularnewline
6 & 0.298616 & 2.2742 & 0.013335 \tabularnewline
7 & 0.145952 & 1.1115 & 0.135462 \tabularnewline
8 & 0.333951 & 2.5433 & 0.006835 \tabularnewline
9 & 0.249593 & 1.9008 & 0.031148 \tabularnewline
10 & 0.10252 & 0.7808 & 0.219057 \tabularnewline
11 & 0.160311 & 1.2209 & 0.113534 \tabularnewline
12 & -0.072619 & -0.5531 & 0.291177 \tabularnewline
13 & -0.106655 & -0.8123 & 0.209981 \tabularnewline
14 & 0.139823 & 1.0649 & 0.145677 \tabularnewline
15 & 0.071749 & 0.5464 & 0.293435 \tabularnewline
16 & -0.019071 & -0.1452 & 0.442512 \tabularnewline
17 & 0.090929 & 0.6925 & 0.245694 \tabularnewline
18 & 0.029197 & 0.2224 & 0.412409 \tabularnewline
19 & -0.070134 & -0.5341 & 0.297649 \tabularnewline
20 & 0.011434 & 0.0871 & 0.465455 \tabularnewline
21 & -0.082271 & -0.6266 & 0.266703 \tabularnewline
22 & -0.141426 & -1.0771 & 0.142955 \tabularnewline
23 & -0.089439 & -0.6811 & 0.249244 \tabularnewline
24 & -0.231911 & -1.7662 & 0.041314 \tabularnewline
25 & -0.121553 & -0.9257 & 0.179213 \tabularnewline
26 & -0.120291 & -0.9161 & 0.181701 \tabularnewline
27 & -0.178938 & -1.3628 & 0.089114 \tabularnewline
28 & -0.047274 & -0.36 & 0.360068 \tabularnewline
29 & -0.080777 & -0.6152 & 0.270421 \tabularnewline
30 & -0.240257 & -1.8297 & 0.036215 \tabularnewline
31 & -0.193563 & -1.4741 & 0.072927 \tabularnewline
32 & -0.261882 & -1.9944 & 0.025406 \tabularnewline
33 & -0.198104 & -1.5087 & 0.0684 \tabularnewline
34 & -0.080788 & -0.6153 & 0.270393 \tabularnewline
35 & -0.099017 & -0.7541 & 0.226923 \tabularnewline
36 & -0.055934 & -0.426 & 0.335849 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113869&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]0.387107[/C][C]2.9481[/C][C]0.0023[/C][/ROW]
[ROW][C]2[/C][C]0.218875[/C][C]1.6669[/C][C]0.050463[/C][/ROW]
[ROW][C]3[/C][C]0.320872[/C][C]2.4437[/C][C]0.008801[/C][/ROW]
[ROW][C]4[/C][C]0.076446[/C][C]0.5822[/C][C]0.281345[/C][/ROW]
[ROW][C]5[/C][C]0.214129[/C][C]1.6308[/C][C]0.05418[/C][/ROW]
[ROW][C]6[/C][C]0.298616[/C][C]2.2742[/C][C]0.013335[/C][/ROW]
[ROW][C]7[/C][C]0.145952[/C][C]1.1115[/C][C]0.135462[/C][/ROW]
[ROW][C]8[/C][C]0.333951[/C][C]2.5433[/C][C]0.006835[/C][/ROW]
[ROW][C]9[/C][C]0.249593[/C][C]1.9008[/C][C]0.031148[/C][/ROW]
[ROW][C]10[/C][C]0.10252[/C][C]0.7808[/C][C]0.219057[/C][/ROW]
[ROW][C]11[/C][C]0.160311[/C][C]1.2209[/C][C]0.113534[/C][/ROW]
[ROW][C]12[/C][C]-0.072619[/C][C]-0.5531[/C][C]0.291177[/C][/ROW]
[ROW][C]13[/C][C]-0.106655[/C][C]-0.8123[/C][C]0.209981[/C][/ROW]
[ROW][C]14[/C][C]0.139823[/C][C]1.0649[/C][C]0.145677[/C][/ROW]
[ROW][C]15[/C][C]0.071749[/C][C]0.5464[/C][C]0.293435[/C][/ROW]
[ROW][C]16[/C][C]-0.019071[/C][C]-0.1452[/C][C]0.442512[/C][/ROW]
[ROW][C]17[/C][C]0.090929[/C][C]0.6925[/C][C]0.245694[/C][/ROW]
[ROW][C]18[/C][C]0.029197[/C][C]0.2224[/C][C]0.412409[/C][/ROW]
[ROW][C]19[/C][C]-0.070134[/C][C]-0.5341[/C][C]0.297649[/C][/ROW]
[ROW][C]20[/C][C]0.011434[/C][C]0.0871[/C][C]0.465455[/C][/ROW]
[ROW][C]21[/C][C]-0.082271[/C][C]-0.6266[/C][C]0.266703[/C][/ROW]
[ROW][C]22[/C][C]-0.141426[/C][C]-1.0771[/C][C]0.142955[/C][/ROW]
[ROW][C]23[/C][C]-0.089439[/C][C]-0.6811[/C][C]0.249244[/C][/ROW]
[ROW][C]24[/C][C]-0.231911[/C][C]-1.7662[/C][C]0.041314[/C][/ROW]
[ROW][C]25[/C][C]-0.121553[/C][C]-0.9257[/C][C]0.179213[/C][/ROW]
[ROW][C]26[/C][C]-0.120291[/C][C]-0.9161[/C][C]0.181701[/C][/ROW]
[ROW][C]27[/C][C]-0.178938[/C][C]-1.3628[/C][C]0.089114[/C][/ROW]
[ROW][C]28[/C][C]-0.047274[/C][C]-0.36[/C][C]0.360068[/C][/ROW]
[ROW][C]29[/C][C]-0.080777[/C][C]-0.6152[/C][C]0.270421[/C][/ROW]
[ROW][C]30[/C][C]-0.240257[/C][C]-1.8297[/C][C]0.036215[/C][/ROW]
[ROW][C]31[/C][C]-0.193563[/C][C]-1.4741[/C][C]0.072927[/C][/ROW]
[ROW][C]32[/C][C]-0.261882[/C][C]-1.9944[/C][C]0.025406[/C][/ROW]
[ROW][C]33[/C][C]-0.198104[/C][C]-1.5087[/C][C]0.0684[/C][/ROW]
[ROW][C]34[/C][C]-0.080788[/C][C]-0.6153[/C][C]0.270393[/C][/ROW]
[ROW][C]35[/C][C]-0.099017[/C][C]-0.7541[/C][C]0.226923[/C][/ROW]
[ROW][C]36[/C][C]-0.055934[/C][C]-0.426[/C][C]0.335849[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113869&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113869&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
10.3871072.94810.0023
20.2188751.66690.050463
30.3208722.44370.008801
40.0764460.58220.281345
50.2141291.63080.05418
60.2986162.27420.013335
70.1459521.11150.135462
80.3339512.54330.006835
90.2495931.90080.031148
100.102520.78080.219057
110.1603111.22090.113534
12-0.072619-0.55310.291177
13-0.106655-0.81230.209981
140.1398231.06490.145677
150.0717490.54640.293435
16-0.019071-0.14520.442512
170.0909290.69250.245694
180.0291970.22240.412409
19-0.070134-0.53410.297649
200.0114340.08710.465455
21-0.082271-0.62660.266703
22-0.141426-1.07710.142955
23-0.089439-0.68110.249244
24-0.231911-1.76620.041314
25-0.121553-0.92570.179213
26-0.120291-0.91610.181701
27-0.178938-1.36280.089114
28-0.047274-0.360.360068
29-0.080777-0.61520.270421
30-0.240257-1.82970.036215
31-0.193563-1.47410.072927
32-0.261882-1.99440.025406
33-0.198104-1.50870.0684
34-0.080788-0.61530.270393
35-0.099017-0.75410.226923
36-0.055934-0.4260.335849







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3871072.94810.0023
20.0811890.61830.269394
30.2505421.90810.030668
4-0.159698-1.21620.114413
50.2380851.81320.037488
60.1105120.84160.201725
70.0184390.14040.444406
80.2262951.72340.045071
9-0.021546-0.16410.435116
10-0.002356-0.01790.492872
11-0.056377-0.42940.334629
12-0.232899-1.77370.040681
13-0.106979-0.81470.20928
140.1113180.84780.200025
150.0441380.33610.368986
16-0.160923-1.22560.11266
170.0637350.48540.314612
180.0940730.71640.238297
19-0.108359-0.82520.20631
200.0818350.62320.267787
21-0.023417-0.17830.429539
22-0.118905-0.90560.184459
23-0.109379-0.8330.20413
24-0.220732-1.6810.049066
250.0108190.08240.467308
26-0.126788-0.96560.16913
270.1378581.04990.14906
280.0153580.1170.453645
290.0319360.24320.404347
30-0.016322-0.12430.450753
31-0.090842-0.69180.245902
32-0.073099-0.55670.289934
330.0924060.70370.242205
340.0273010.20790.41801
35-0.018696-0.14240.443636
36-0.041248-0.31410.377273

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.387107 & 2.9481 & 0.0023 \tabularnewline
2 & 0.081189 & 0.6183 & 0.269394 \tabularnewline
3 & 0.250542 & 1.9081 & 0.030668 \tabularnewline
4 & -0.159698 & -1.2162 & 0.114413 \tabularnewline
5 & 0.238085 & 1.8132 & 0.037488 \tabularnewline
6 & 0.110512 & 0.8416 & 0.201725 \tabularnewline
7 & 0.018439 & 0.1404 & 0.444406 \tabularnewline
8 & 0.226295 & 1.7234 & 0.045071 \tabularnewline
9 & -0.021546 & -0.1641 & 0.435116 \tabularnewline
10 & -0.002356 & -0.0179 & 0.492872 \tabularnewline
11 & -0.056377 & -0.4294 & 0.334629 \tabularnewline
12 & -0.232899 & -1.7737 & 0.040681 \tabularnewline
13 & -0.106979 & -0.8147 & 0.20928 \tabularnewline
14 & 0.111318 & 0.8478 & 0.200025 \tabularnewline
15 & 0.044138 & 0.3361 & 0.368986 \tabularnewline
16 & -0.160923 & -1.2256 & 0.11266 \tabularnewline
17 & 0.063735 & 0.4854 & 0.314612 \tabularnewline
18 & 0.094073 & 0.7164 & 0.238297 \tabularnewline
19 & -0.108359 & -0.8252 & 0.20631 \tabularnewline
20 & 0.081835 & 0.6232 & 0.267787 \tabularnewline
21 & -0.023417 & -0.1783 & 0.429539 \tabularnewline
22 & -0.118905 & -0.9056 & 0.184459 \tabularnewline
23 & -0.109379 & -0.833 & 0.20413 \tabularnewline
24 & -0.220732 & -1.681 & 0.049066 \tabularnewline
25 & 0.010819 & 0.0824 & 0.467308 \tabularnewline
26 & -0.126788 & -0.9656 & 0.16913 \tabularnewline
27 & 0.137858 & 1.0499 & 0.14906 \tabularnewline
28 & 0.015358 & 0.117 & 0.453645 \tabularnewline
29 & 0.031936 & 0.2432 & 0.404347 \tabularnewline
30 & -0.016322 & -0.1243 & 0.450753 \tabularnewline
31 & -0.090842 & -0.6918 & 0.245902 \tabularnewline
32 & -0.073099 & -0.5567 & 0.289934 \tabularnewline
33 & 0.092406 & 0.7037 & 0.242205 \tabularnewline
34 & 0.027301 & 0.2079 & 0.41801 \tabularnewline
35 & -0.018696 & -0.1424 & 0.443636 \tabularnewline
36 & -0.041248 & -0.3141 & 0.377273 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113869&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]0.387107[/C][C]2.9481[/C][C]0.0023[/C][/ROW]
[ROW][C]2[/C][C]0.081189[/C][C]0.6183[/C][C]0.269394[/C][/ROW]
[ROW][C]3[/C][C]0.250542[/C][C]1.9081[/C][C]0.030668[/C][/ROW]
[ROW][C]4[/C][C]-0.159698[/C][C]-1.2162[/C][C]0.114413[/C][/ROW]
[ROW][C]5[/C][C]0.238085[/C][C]1.8132[/C][C]0.037488[/C][/ROW]
[ROW][C]6[/C][C]0.110512[/C][C]0.8416[/C][C]0.201725[/C][/ROW]
[ROW][C]7[/C][C]0.018439[/C][C]0.1404[/C][C]0.444406[/C][/ROW]
[ROW][C]8[/C][C]0.226295[/C][C]1.7234[/C][C]0.045071[/C][/ROW]
[ROW][C]9[/C][C]-0.021546[/C][C]-0.1641[/C][C]0.435116[/C][/ROW]
[ROW][C]10[/C][C]-0.002356[/C][C]-0.0179[/C][C]0.492872[/C][/ROW]
[ROW][C]11[/C][C]-0.056377[/C][C]-0.4294[/C][C]0.334629[/C][/ROW]
[ROW][C]12[/C][C]-0.232899[/C][C]-1.7737[/C][C]0.040681[/C][/ROW]
[ROW][C]13[/C][C]-0.106979[/C][C]-0.8147[/C][C]0.20928[/C][/ROW]
[ROW][C]14[/C][C]0.111318[/C][C]0.8478[/C][C]0.200025[/C][/ROW]
[ROW][C]15[/C][C]0.044138[/C][C]0.3361[/C][C]0.368986[/C][/ROW]
[ROW][C]16[/C][C]-0.160923[/C][C]-1.2256[/C][C]0.11266[/C][/ROW]
[ROW][C]17[/C][C]0.063735[/C][C]0.4854[/C][C]0.314612[/C][/ROW]
[ROW][C]18[/C][C]0.094073[/C][C]0.7164[/C][C]0.238297[/C][/ROW]
[ROW][C]19[/C][C]-0.108359[/C][C]-0.8252[/C][C]0.20631[/C][/ROW]
[ROW][C]20[/C][C]0.081835[/C][C]0.6232[/C][C]0.267787[/C][/ROW]
[ROW][C]21[/C][C]-0.023417[/C][C]-0.1783[/C][C]0.429539[/C][/ROW]
[ROW][C]22[/C][C]-0.118905[/C][C]-0.9056[/C][C]0.184459[/C][/ROW]
[ROW][C]23[/C][C]-0.109379[/C][C]-0.833[/C][C]0.20413[/C][/ROW]
[ROW][C]24[/C][C]-0.220732[/C][C]-1.681[/C][C]0.049066[/C][/ROW]
[ROW][C]25[/C][C]0.010819[/C][C]0.0824[/C][C]0.467308[/C][/ROW]
[ROW][C]26[/C][C]-0.126788[/C][C]-0.9656[/C][C]0.16913[/C][/ROW]
[ROW][C]27[/C][C]0.137858[/C][C]1.0499[/C][C]0.14906[/C][/ROW]
[ROW][C]28[/C][C]0.015358[/C][C]0.117[/C][C]0.453645[/C][/ROW]
[ROW][C]29[/C][C]0.031936[/C][C]0.2432[/C][C]0.404347[/C][/ROW]
[ROW][C]30[/C][C]-0.016322[/C][C]-0.1243[/C][C]0.450753[/C][/ROW]
[ROW][C]31[/C][C]-0.090842[/C][C]-0.6918[/C][C]0.245902[/C][/ROW]
[ROW][C]32[/C][C]-0.073099[/C][C]-0.5567[/C][C]0.289934[/C][/ROW]
[ROW][C]33[/C][C]0.092406[/C][C]0.7037[/C][C]0.242205[/C][/ROW]
[ROW][C]34[/C][C]0.027301[/C][C]0.2079[/C][C]0.41801[/C][/ROW]
[ROW][C]35[/C][C]-0.018696[/C][C]-0.1424[/C][C]0.443636[/C][/ROW]
[ROW][C]36[/C][C]-0.041248[/C][C]-0.3141[/C][C]0.377273[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113869&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113869&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
10.3871072.94810.0023
20.0811890.61830.269394
30.2505421.90810.030668
4-0.159698-1.21620.114413
50.2380851.81320.037488
60.1105120.84160.201725
70.0184390.14040.444406
80.2262951.72340.045071
9-0.021546-0.16410.435116
10-0.002356-0.01790.492872
11-0.056377-0.42940.334629
12-0.232899-1.77370.040681
13-0.106979-0.81470.20928
140.1113180.84780.200025
150.0441380.33610.368986
16-0.160923-1.22560.11266
170.0637350.48540.314612
180.0940730.71640.238297
19-0.108359-0.82520.20631
200.0818350.62320.267787
21-0.023417-0.17830.429539
22-0.118905-0.90560.184459
23-0.109379-0.8330.20413
24-0.220732-1.6810.049066
250.0108190.08240.467308
26-0.126788-0.96560.16913
270.1378581.04990.14906
280.0153580.1170.453645
290.0319360.24320.404347
30-0.016322-0.12430.450753
31-0.090842-0.69180.245902
32-0.073099-0.55670.289934
330.0924060.70370.242205
340.0273010.20790.41801
35-0.018696-0.14240.443636
36-0.041248-0.31410.377273



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; 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')