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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 computationThu, 03 Dec 2009 08:50:26 -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/03/t12598555339gu1g1qxvzzgny6.htm/, Retrieved Tue, 23 Apr 2024 23:57:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62855, Retrieved Tue, 23 Apr 2024 23:57:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [] [2009-11-27 14:46:03] [b98453cac15ba1066b407e146608df68]
- R PD      [(Partial) Autocorrelation Function] [] [2009-12-03 15:50:26] [faa1ded5041cd5a0e2be04844f08502a] [Current]
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Dataseries X:
24
22
25
24
29
26
26
21
23
22
21
16
19
16
25
27
23
22
23
20
24
23
20
21
22
17
21
19
23
22
15
23
21
18
18
18
18
10
13
10
9
9
6
11
9
10
9
16
10
7
7
14
11
10
6
8
13
12
15
16
16




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62855&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62855&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62855&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'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8200016.40440
20.7765816.06530
30.7186365.61270
40.6958235.43461e-06
50.6259584.88894e-06
60.5533874.32212.9e-05
70.4823113.7670.000187
80.4667123.64510.000277
90.4188993.27170.000881
100.3913093.05620.001662
110.3783872.95530.002217
120.3870123.02270.00183
130.3138352.45110.008561
140.2922762.28270.012972
150.2366451.84830.034707
160.1770331.38270.085903
170.1081290.84450.20084
180.0445590.3480.364514
19-0.006031-0.04710.481291
20-0.042722-0.33370.369887
21-0.118889-0.92860.178391
22-0.155964-1.21810.113935
23-0.157422-1.22950.111803
24-0.163031-1.27330.103869
25-0.192743-1.50540.068695
26-0.20004-1.56240.061688
27-0.181225-1.41540.081016
28-0.204351-1.5960.057825
29-0.208387-1.62760.054387
30-0.231413-1.80740.037816
31-0.243224-1.89960.031105
32-0.271897-2.12360.018885
33-0.314155-2.45360.008507
34-0.365514-2.85480.002939
35-0.368418-2.87740.002759
36-0.373542-2.91750.002467

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.820001 & 6.4044 & 0 \tabularnewline
2 & 0.776581 & 6.0653 & 0 \tabularnewline
3 & 0.718636 & 5.6127 & 0 \tabularnewline
4 & 0.695823 & 5.4346 & 1e-06 \tabularnewline
5 & 0.625958 & 4.8889 & 4e-06 \tabularnewline
6 & 0.553387 & 4.3221 & 2.9e-05 \tabularnewline
7 & 0.482311 & 3.767 & 0.000187 \tabularnewline
8 & 0.466712 & 3.6451 & 0.000277 \tabularnewline
9 & 0.418899 & 3.2717 & 0.000881 \tabularnewline
10 & 0.391309 & 3.0562 & 0.001662 \tabularnewline
11 & 0.378387 & 2.9553 & 0.002217 \tabularnewline
12 & 0.387012 & 3.0227 & 0.00183 \tabularnewline
13 & 0.313835 & 2.4511 & 0.008561 \tabularnewline
14 & 0.292276 & 2.2827 & 0.012972 \tabularnewline
15 & 0.236645 & 1.8483 & 0.034707 \tabularnewline
16 & 0.177033 & 1.3827 & 0.085903 \tabularnewline
17 & 0.108129 & 0.8445 & 0.20084 \tabularnewline
18 & 0.044559 & 0.348 & 0.364514 \tabularnewline
19 & -0.006031 & -0.0471 & 0.481291 \tabularnewline
20 & -0.042722 & -0.3337 & 0.369887 \tabularnewline
21 & -0.118889 & -0.9286 & 0.178391 \tabularnewline
22 & -0.155964 & -1.2181 & 0.113935 \tabularnewline
23 & -0.157422 & -1.2295 & 0.111803 \tabularnewline
24 & -0.163031 & -1.2733 & 0.103869 \tabularnewline
25 & -0.192743 & -1.5054 & 0.068695 \tabularnewline
26 & -0.20004 & -1.5624 & 0.061688 \tabularnewline
27 & -0.181225 & -1.4154 & 0.081016 \tabularnewline
28 & -0.204351 & -1.596 & 0.057825 \tabularnewline
29 & -0.208387 & -1.6276 & 0.054387 \tabularnewline
30 & -0.231413 & -1.8074 & 0.037816 \tabularnewline
31 & -0.243224 & -1.8996 & 0.031105 \tabularnewline
32 & -0.271897 & -2.1236 & 0.018885 \tabularnewline
33 & -0.314155 & -2.4536 & 0.008507 \tabularnewline
34 & -0.365514 & -2.8548 & 0.002939 \tabularnewline
35 & -0.368418 & -2.8774 & 0.002759 \tabularnewline
36 & -0.373542 & -2.9175 & 0.002467 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62855&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]0.820001[/C][C]6.4044[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.776581[/C][C]6.0653[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.718636[/C][C]5.6127[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.695823[/C][C]5.4346[/C][C]1e-06[/C][/ROW]
[ROW][C]5[/C][C]0.625958[/C][C]4.8889[/C][C]4e-06[/C][/ROW]
[ROW][C]6[/C][C]0.553387[/C][C]4.3221[/C][C]2.9e-05[/C][/ROW]
[ROW][C]7[/C][C]0.482311[/C][C]3.767[/C][C]0.000187[/C][/ROW]
[ROW][C]8[/C][C]0.466712[/C][C]3.6451[/C][C]0.000277[/C][/ROW]
[ROW][C]9[/C][C]0.418899[/C][C]3.2717[/C][C]0.000881[/C][/ROW]
[ROW][C]10[/C][C]0.391309[/C][C]3.0562[/C][C]0.001662[/C][/ROW]
[ROW][C]11[/C][C]0.378387[/C][C]2.9553[/C][C]0.002217[/C][/ROW]
[ROW][C]12[/C][C]0.387012[/C][C]3.0227[/C][C]0.00183[/C][/ROW]
[ROW][C]13[/C][C]0.313835[/C][C]2.4511[/C][C]0.008561[/C][/ROW]
[ROW][C]14[/C][C]0.292276[/C][C]2.2827[/C][C]0.012972[/C][/ROW]
[ROW][C]15[/C][C]0.236645[/C][C]1.8483[/C][C]0.034707[/C][/ROW]
[ROW][C]16[/C][C]0.177033[/C][C]1.3827[/C][C]0.085903[/C][/ROW]
[ROW][C]17[/C][C]0.108129[/C][C]0.8445[/C][C]0.20084[/C][/ROW]
[ROW][C]18[/C][C]0.044559[/C][C]0.348[/C][C]0.364514[/C][/ROW]
[ROW][C]19[/C][C]-0.006031[/C][C]-0.0471[/C][C]0.481291[/C][/ROW]
[ROW][C]20[/C][C]-0.042722[/C][C]-0.3337[/C][C]0.369887[/C][/ROW]
[ROW][C]21[/C][C]-0.118889[/C][C]-0.9286[/C][C]0.178391[/C][/ROW]
[ROW][C]22[/C][C]-0.155964[/C][C]-1.2181[/C][C]0.113935[/C][/ROW]
[ROW][C]23[/C][C]-0.157422[/C][C]-1.2295[/C][C]0.111803[/C][/ROW]
[ROW][C]24[/C][C]-0.163031[/C][C]-1.2733[/C][C]0.103869[/C][/ROW]
[ROW][C]25[/C][C]-0.192743[/C][C]-1.5054[/C][C]0.068695[/C][/ROW]
[ROW][C]26[/C][C]-0.20004[/C][C]-1.5624[/C][C]0.061688[/C][/ROW]
[ROW][C]27[/C][C]-0.181225[/C][C]-1.4154[/C][C]0.081016[/C][/ROW]
[ROW][C]28[/C][C]-0.204351[/C][C]-1.596[/C][C]0.057825[/C][/ROW]
[ROW][C]29[/C][C]-0.208387[/C][C]-1.6276[/C][C]0.054387[/C][/ROW]
[ROW][C]30[/C][C]-0.231413[/C][C]-1.8074[/C][C]0.037816[/C][/ROW]
[ROW][C]31[/C][C]-0.243224[/C][C]-1.8996[/C][C]0.031105[/C][/ROW]
[ROW][C]32[/C][C]-0.271897[/C][C]-2.1236[/C][C]0.018885[/C][/ROW]
[ROW][C]33[/C][C]-0.314155[/C][C]-2.4536[/C][C]0.008507[/C][/ROW]
[ROW][C]34[/C][C]-0.365514[/C][C]-2.8548[/C][C]0.002939[/C][/ROW]
[ROW][C]35[/C][C]-0.368418[/C][C]-2.8774[/C][C]0.002759[/C][/ROW]
[ROW][C]36[/C][C]-0.373542[/C][C]-2.9175[/C][C]0.002467[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62855&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62855&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
10.8200016.40440
20.7765816.06530
30.7186365.61270
40.6958235.43461e-06
50.6259584.88894e-06
60.5533874.32212.9e-05
70.4823113.7670.000187
80.4667123.64510.000277
90.4188993.27170.000881
100.3913093.05620.001662
110.3783872.95530.002217
120.3870123.02270.00183
130.3138352.45110.008561
140.2922762.28270.012972
150.2366451.84830.034707
160.1770331.38270.085903
170.1081290.84450.20084
180.0445590.3480.364514
19-0.006031-0.04710.481291
20-0.042722-0.33370.369887
21-0.118889-0.92860.178391
22-0.155964-1.21810.113935
23-0.157422-1.22950.111803
24-0.163031-1.27330.103869
25-0.192743-1.50540.068695
26-0.20004-1.56240.061688
27-0.181225-1.41540.081016
28-0.204351-1.5960.057825
29-0.208387-1.62760.054387
30-0.231413-1.80740.037816
31-0.243224-1.89960.031105
32-0.271897-2.12360.018885
33-0.314155-2.45360.008507
34-0.365514-2.85480.002939
35-0.368418-2.87740.002759
36-0.373542-2.91750.002467







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8200016.40440
20.3180112.48370.007882
30.0800690.62540.267033
40.1175510.91810.181091
5-0.076318-0.59610.276669
6-0.120635-0.94220.174906
7-0.089393-0.69820.243859
80.1050380.82040.207598
90.0082280.06430.474486
100.0480270.37510.354444
110.1076470.84070.201886
120.1019960.79660.214383
13-0.224102-1.75030.042548
14-0.05425-0.42370.336635
15-0.113183-0.8840.190088
16-0.195868-1.52980.065621
17-0.090939-0.71030.240126
18-0.017344-0.13550.446348
190.0290320.22680.410688
200.0354310.27670.391463
21-0.073683-0.57550.283542
22-0.042055-0.32850.371845
230.0491990.38430.351063
240.0046710.03650.485508
25-0.033869-0.26450.396134
260.0027640.02160.491422
270.1322381.03280.152884
28-0.080902-0.63190.264917
290.0202940.15850.437292
300.0052090.04070.48384
31-0.07585-0.59240.277884
32-0.108983-0.85120.198999
33-0.064358-0.50270.308508
34-0.163891-1.280.102691
35-0.025828-0.20170.420403
360.1020720.79720.214211

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.820001 & 6.4044 & 0 \tabularnewline
2 & 0.318011 & 2.4837 & 0.007882 \tabularnewline
3 & 0.080069 & 0.6254 & 0.267033 \tabularnewline
4 & 0.117551 & 0.9181 & 0.181091 \tabularnewline
5 & -0.076318 & -0.5961 & 0.276669 \tabularnewline
6 & -0.120635 & -0.9422 & 0.174906 \tabularnewline
7 & -0.089393 & -0.6982 & 0.243859 \tabularnewline
8 & 0.105038 & 0.8204 & 0.207598 \tabularnewline
9 & 0.008228 & 0.0643 & 0.474486 \tabularnewline
10 & 0.048027 & 0.3751 & 0.354444 \tabularnewline
11 & 0.107647 & 0.8407 & 0.201886 \tabularnewline
12 & 0.101996 & 0.7966 & 0.214383 \tabularnewline
13 & -0.224102 & -1.7503 & 0.042548 \tabularnewline
14 & -0.05425 & -0.4237 & 0.336635 \tabularnewline
15 & -0.113183 & -0.884 & 0.190088 \tabularnewline
16 & -0.195868 & -1.5298 & 0.065621 \tabularnewline
17 & -0.090939 & -0.7103 & 0.240126 \tabularnewline
18 & -0.017344 & -0.1355 & 0.446348 \tabularnewline
19 & 0.029032 & 0.2268 & 0.410688 \tabularnewline
20 & 0.035431 & 0.2767 & 0.391463 \tabularnewline
21 & -0.073683 & -0.5755 & 0.283542 \tabularnewline
22 & -0.042055 & -0.3285 & 0.371845 \tabularnewline
23 & 0.049199 & 0.3843 & 0.351063 \tabularnewline
24 & 0.004671 & 0.0365 & 0.485508 \tabularnewline
25 & -0.033869 & -0.2645 & 0.396134 \tabularnewline
26 & 0.002764 & 0.0216 & 0.491422 \tabularnewline
27 & 0.132238 & 1.0328 & 0.152884 \tabularnewline
28 & -0.080902 & -0.6319 & 0.264917 \tabularnewline
29 & 0.020294 & 0.1585 & 0.437292 \tabularnewline
30 & 0.005209 & 0.0407 & 0.48384 \tabularnewline
31 & -0.07585 & -0.5924 & 0.277884 \tabularnewline
32 & -0.108983 & -0.8512 & 0.198999 \tabularnewline
33 & -0.064358 & -0.5027 & 0.308508 \tabularnewline
34 & -0.163891 & -1.28 & 0.102691 \tabularnewline
35 & -0.025828 & -0.2017 & 0.420403 \tabularnewline
36 & 0.102072 & 0.7972 & 0.214211 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62855&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]0.820001[/C][C]6.4044[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.318011[/C][C]2.4837[/C][C]0.007882[/C][/ROW]
[ROW][C]3[/C][C]0.080069[/C][C]0.6254[/C][C]0.267033[/C][/ROW]
[ROW][C]4[/C][C]0.117551[/C][C]0.9181[/C][C]0.181091[/C][/ROW]
[ROW][C]5[/C][C]-0.076318[/C][C]-0.5961[/C][C]0.276669[/C][/ROW]
[ROW][C]6[/C][C]-0.120635[/C][C]-0.9422[/C][C]0.174906[/C][/ROW]
[ROW][C]7[/C][C]-0.089393[/C][C]-0.6982[/C][C]0.243859[/C][/ROW]
[ROW][C]8[/C][C]0.105038[/C][C]0.8204[/C][C]0.207598[/C][/ROW]
[ROW][C]9[/C][C]0.008228[/C][C]0.0643[/C][C]0.474486[/C][/ROW]
[ROW][C]10[/C][C]0.048027[/C][C]0.3751[/C][C]0.354444[/C][/ROW]
[ROW][C]11[/C][C]0.107647[/C][C]0.8407[/C][C]0.201886[/C][/ROW]
[ROW][C]12[/C][C]0.101996[/C][C]0.7966[/C][C]0.214383[/C][/ROW]
[ROW][C]13[/C][C]-0.224102[/C][C]-1.7503[/C][C]0.042548[/C][/ROW]
[ROW][C]14[/C][C]-0.05425[/C][C]-0.4237[/C][C]0.336635[/C][/ROW]
[ROW][C]15[/C][C]-0.113183[/C][C]-0.884[/C][C]0.190088[/C][/ROW]
[ROW][C]16[/C][C]-0.195868[/C][C]-1.5298[/C][C]0.065621[/C][/ROW]
[ROW][C]17[/C][C]-0.090939[/C][C]-0.7103[/C][C]0.240126[/C][/ROW]
[ROW][C]18[/C][C]-0.017344[/C][C]-0.1355[/C][C]0.446348[/C][/ROW]
[ROW][C]19[/C][C]0.029032[/C][C]0.2268[/C][C]0.410688[/C][/ROW]
[ROW][C]20[/C][C]0.035431[/C][C]0.2767[/C][C]0.391463[/C][/ROW]
[ROW][C]21[/C][C]-0.073683[/C][C]-0.5755[/C][C]0.283542[/C][/ROW]
[ROW][C]22[/C][C]-0.042055[/C][C]-0.3285[/C][C]0.371845[/C][/ROW]
[ROW][C]23[/C][C]0.049199[/C][C]0.3843[/C][C]0.351063[/C][/ROW]
[ROW][C]24[/C][C]0.004671[/C][C]0.0365[/C][C]0.485508[/C][/ROW]
[ROW][C]25[/C][C]-0.033869[/C][C]-0.2645[/C][C]0.396134[/C][/ROW]
[ROW][C]26[/C][C]0.002764[/C][C]0.0216[/C][C]0.491422[/C][/ROW]
[ROW][C]27[/C][C]0.132238[/C][C]1.0328[/C][C]0.152884[/C][/ROW]
[ROW][C]28[/C][C]-0.080902[/C][C]-0.6319[/C][C]0.264917[/C][/ROW]
[ROW][C]29[/C][C]0.020294[/C][C]0.1585[/C][C]0.437292[/C][/ROW]
[ROW][C]30[/C][C]0.005209[/C][C]0.0407[/C][C]0.48384[/C][/ROW]
[ROW][C]31[/C][C]-0.07585[/C][C]-0.5924[/C][C]0.277884[/C][/ROW]
[ROW][C]32[/C][C]-0.108983[/C][C]-0.8512[/C][C]0.198999[/C][/ROW]
[ROW][C]33[/C][C]-0.064358[/C][C]-0.5027[/C][C]0.308508[/C][/ROW]
[ROW][C]34[/C][C]-0.163891[/C][C]-1.28[/C][C]0.102691[/C][/ROW]
[ROW][C]35[/C][C]-0.025828[/C][C]-0.2017[/C][C]0.420403[/C][/ROW]
[ROW][C]36[/C][C]0.102072[/C][C]0.7972[/C][C]0.214211[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62855&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62855&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
10.8200016.40440
20.3180112.48370.007882
30.0800690.62540.267033
40.1175510.91810.181091
5-0.076318-0.59610.276669
6-0.120635-0.94220.174906
7-0.089393-0.69820.243859
80.1050380.82040.207598
90.0082280.06430.474486
100.0480270.37510.354444
110.1076470.84070.201886
120.1019960.79660.214383
13-0.224102-1.75030.042548
14-0.05425-0.42370.336635
15-0.113183-0.8840.190088
16-0.195868-1.52980.065621
17-0.090939-0.71030.240126
18-0.017344-0.13550.446348
190.0290320.22680.410688
200.0354310.27670.391463
21-0.073683-0.57550.283542
22-0.042055-0.32850.371845
230.0491990.38430.351063
240.0046710.03650.485508
25-0.033869-0.26450.396134
260.0027640.02160.491422
270.1322381.03280.152884
28-0.080902-0.63190.264917
290.0202940.15850.437292
300.0052090.04070.48384
31-0.07585-0.59240.277884
32-0.108983-0.85120.198999
33-0.064358-0.50270.308508
34-0.163891-1.280.102691
35-0.025828-0.20170.420403
360.1020720.79720.214211



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