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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 computationFri, 27 Nov 2009 15:43:45 -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/27/t1259361852bayfmyo11exo73c.htm/, Retrieved Mon, 29 Apr 2024 23:52:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61322, Retrieved Mon, 29 Apr 2024 23:52:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [ACF 2a] [2009-11-27 22:43:45] [b42c0aeada8a5fa89825c81e73c10645] [Current]
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Dataseries X:
12.3
14.6
17.7
15.2
22.3
14.8
10
2.9
5.6
16.1
23.7
26.5
20.9
15.9
13
7.8
17.5
24.4
33.7
32.3
33.4
22.2
21.7
12.8
15.2
17.1
17.6
17.5
14.7
12.9
12
11.1
12.3
18.9
24
29.6
30.9
33
34.9
40.1
30.8
31
23.8
30.8
27.6
30.2
22.2
19.9
18.3
15.2
10.1
6.5
1.9
2
4.3
4.8
4.9
2.1
5.5
10.6




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=61322&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=61322&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61322&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
10.8776226.08030
20.683924.73831e-05
30.4324652.99620.002158
40.2778421.92490.030087
50.1862971.29070.101494
60.1481841.02670.154865
70.086690.60060.275465
8-0.00787-0.05450.478372
9-0.158075-1.09520.139452
10-0.318755-2.20840.016013
11-0.452841-3.13740.001456
12-0.518364-3.59130.000386
13-0.482102-3.34010.000813
14-0.387495-2.68460.004968
15-0.251154-1.740.04413
16-0.14548-1.00790.159275
17-0.051954-0.35990.360233
180.0057790.040.484116
190.0695770.4820.315984
200.0991070.68660.247808
210.1475881.02250.155831
220.1577711.09310.13991
230.1947871.34950.091749
240.1986941.37660.087513
250.2021581.40060.083884
260.1621131.12320.13348
270.1025180.71030.240488
280.0150930.10460.458577
29-0.06097-0.42240.337306
30-0.125371-0.86860.194695
31-0.160634-1.11290.135646
32-0.171249-1.18640.120643
33-0.168921-1.17030.123826
34-0.152473-1.05640.148045
35-0.15039-1.04190.151331
36-0.151454-1.04930.149646

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.877622 & 6.0803 & 0 \tabularnewline
2 & 0.68392 & 4.7383 & 1e-05 \tabularnewline
3 & 0.432465 & 2.9962 & 0.002158 \tabularnewline
4 & 0.277842 & 1.9249 & 0.030087 \tabularnewline
5 & 0.186297 & 1.2907 & 0.101494 \tabularnewline
6 & 0.148184 & 1.0267 & 0.154865 \tabularnewline
7 & 0.08669 & 0.6006 & 0.275465 \tabularnewline
8 & -0.00787 & -0.0545 & 0.478372 \tabularnewline
9 & -0.158075 & -1.0952 & 0.139452 \tabularnewline
10 & -0.318755 & -2.2084 & 0.016013 \tabularnewline
11 & -0.452841 & -3.1374 & 0.001456 \tabularnewline
12 & -0.518364 & -3.5913 & 0.000386 \tabularnewline
13 & -0.482102 & -3.3401 & 0.000813 \tabularnewline
14 & -0.387495 & -2.6846 & 0.004968 \tabularnewline
15 & -0.251154 & -1.74 & 0.04413 \tabularnewline
16 & -0.14548 & -1.0079 & 0.159275 \tabularnewline
17 & -0.051954 & -0.3599 & 0.360233 \tabularnewline
18 & 0.005779 & 0.04 & 0.484116 \tabularnewline
19 & 0.069577 & 0.482 & 0.315984 \tabularnewline
20 & 0.099107 & 0.6866 & 0.247808 \tabularnewline
21 & 0.147588 & 1.0225 & 0.155831 \tabularnewline
22 & 0.157771 & 1.0931 & 0.13991 \tabularnewline
23 & 0.194787 & 1.3495 & 0.091749 \tabularnewline
24 & 0.198694 & 1.3766 & 0.087513 \tabularnewline
25 & 0.202158 & 1.4006 & 0.083884 \tabularnewline
26 & 0.162113 & 1.1232 & 0.13348 \tabularnewline
27 & 0.102518 & 0.7103 & 0.240488 \tabularnewline
28 & 0.015093 & 0.1046 & 0.458577 \tabularnewline
29 & -0.06097 & -0.4224 & 0.337306 \tabularnewline
30 & -0.125371 & -0.8686 & 0.194695 \tabularnewline
31 & -0.160634 & -1.1129 & 0.135646 \tabularnewline
32 & -0.171249 & -1.1864 & 0.120643 \tabularnewline
33 & -0.168921 & -1.1703 & 0.123826 \tabularnewline
34 & -0.152473 & -1.0564 & 0.148045 \tabularnewline
35 & -0.15039 & -1.0419 & 0.151331 \tabularnewline
36 & -0.151454 & -1.0493 & 0.149646 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61322&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]0.877622[/C][C]6.0803[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.68392[/C][C]4.7383[/C][C]1e-05[/C][/ROW]
[ROW][C]3[/C][C]0.432465[/C][C]2.9962[/C][C]0.002158[/C][/ROW]
[ROW][C]4[/C][C]0.277842[/C][C]1.9249[/C][C]0.030087[/C][/ROW]
[ROW][C]5[/C][C]0.186297[/C][C]1.2907[/C][C]0.101494[/C][/ROW]
[ROW][C]6[/C][C]0.148184[/C][C]1.0267[/C][C]0.154865[/C][/ROW]
[ROW][C]7[/C][C]0.08669[/C][C]0.6006[/C][C]0.275465[/C][/ROW]
[ROW][C]8[/C][C]-0.00787[/C][C]-0.0545[/C][C]0.478372[/C][/ROW]
[ROW][C]9[/C][C]-0.158075[/C][C]-1.0952[/C][C]0.139452[/C][/ROW]
[ROW][C]10[/C][C]-0.318755[/C][C]-2.2084[/C][C]0.016013[/C][/ROW]
[ROW][C]11[/C][C]-0.452841[/C][C]-3.1374[/C][C]0.001456[/C][/ROW]
[ROW][C]12[/C][C]-0.518364[/C][C]-3.5913[/C][C]0.000386[/C][/ROW]
[ROW][C]13[/C][C]-0.482102[/C][C]-3.3401[/C][C]0.000813[/C][/ROW]
[ROW][C]14[/C][C]-0.387495[/C][C]-2.6846[/C][C]0.004968[/C][/ROW]
[ROW][C]15[/C][C]-0.251154[/C][C]-1.74[/C][C]0.04413[/C][/ROW]
[ROW][C]16[/C][C]-0.14548[/C][C]-1.0079[/C][C]0.159275[/C][/ROW]
[ROW][C]17[/C][C]-0.051954[/C][C]-0.3599[/C][C]0.360233[/C][/ROW]
[ROW][C]18[/C][C]0.005779[/C][C]0.04[/C][C]0.484116[/C][/ROW]
[ROW][C]19[/C][C]0.069577[/C][C]0.482[/C][C]0.315984[/C][/ROW]
[ROW][C]20[/C][C]0.099107[/C][C]0.6866[/C][C]0.247808[/C][/ROW]
[ROW][C]21[/C][C]0.147588[/C][C]1.0225[/C][C]0.155831[/C][/ROW]
[ROW][C]22[/C][C]0.157771[/C][C]1.0931[/C][C]0.13991[/C][/ROW]
[ROW][C]23[/C][C]0.194787[/C][C]1.3495[/C][C]0.091749[/C][/ROW]
[ROW][C]24[/C][C]0.198694[/C][C]1.3766[/C][C]0.087513[/C][/ROW]
[ROW][C]25[/C][C]0.202158[/C][C]1.4006[/C][C]0.083884[/C][/ROW]
[ROW][C]26[/C][C]0.162113[/C][C]1.1232[/C][C]0.13348[/C][/ROW]
[ROW][C]27[/C][C]0.102518[/C][C]0.7103[/C][C]0.240488[/C][/ROW]
[ROW][C]28[/C][C]0.015093[/C][C]0.1046[/C][C]0.458577[/C][/ROW]
[ROW][C]29[/C][C]-0.06097[/C][C]-0.4224[/C][C]0.337306[/C][/ROW]
[ROW][C]30[/C][C]-0.125371[/C][C]-0.8686[/C][C]0.194695[/C][/ROW]
[ROW][C]31[/C][C]-0.160634[/C][C]-1.1129[/C][C]0.135646[/C][/ROW]
[ROW][C]32[/C][C]-0.171249[/C][C]-1.1864[/C][C]0.120643[/C][/ROW]
[ROW][C]33[/C][C]-0.168921[/C][C]-1.1703[/C][C]0.123826[/C][/ROW]
[ROW][C]34[/C][C]-0.152473[/C][C]-1.0564[/C][C]0.148045[/C][/ROW]
[ROW][C]35[/C][C]-0.15039[/C][C]-1.0419[/C][C]0.151331[/C][/ROW]
[ROW][C]36[/C][C]-0.151454[/C][C]-1.0493[/C][C]0.149646[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61322&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61322&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
10.8776226.08030
20.683924.73831e-05
30.4324652.99620.002158
40.2778421.92490.030087
50.1862971.29070.101494
60.1481841.02670.154865
70.086690.60060.275465
8-0.00787-0.05450.478372
9-0.158075-1.09520.139452
10-0.318755-2.20840.016013
11-0.452841-3.13740.001456
12-0.518364-3.59130.000386
13-0.482102-3.34010.000813
14-0.387495-2.68460.004968
15-0.251154-1.740.04413
16-0.14548-1.00790.159275
17-0.051954-0.35990.360233
180.0057790.040.484116
190.0695770.4820.315984
200.0991070.68660.247808
210.1475881.02250.155831
220.1577711.09310.13991
230.1947871.34950.091749
240.1986941.37660.087513
250.2021581.40060.083884
260.1621131.12320.13348
270.1025180.71030.240488
280.0150930.10460.458577
29-0.06097-0.42240.337306
30-0.125371-0.86860.194695
31-0.160634-1.11290.135646
32-0.171249-1.18640.120643
33-0.168921-1.17030.123826
34-0.152473-1.05640.148045
35-0.15039-1.04190.151331
36-0.151454-1.04930.149646







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8776226.08030
2-0.375578-2.60210.006143
3-0.322105-2.23160.015173
40.4617363.1990.001222
5-0.013155-0.09110.46388
6-0.295973-2.05060.022896
7-0.113934-0.78940.216892
8-0.020192-0.13990.444663
9-0.278515-1.92960.029789
10-0.197222-1.36640.089091
110.0845770.5860.280322
12-0.012738-0.08830.465023
130.1674111.15990.125921
140.0081520.05650.477597
150.0967810.67050.252869
160.0622810.43150.33402
170.1575011.09120.140317
18-0.006749-0.04680.481451
19-0.066198-0.45860.324284
20-0.257666-1.78520.040277
210.0887920.61520.270675
22-0.18813-1.30340.099327
23-0.016897-0.11710.453648
240.0277370.19220.42421
25-0.007564-0.05240.479211
260.0226370.15680.438017
270.0615970.42680.335733
28-0.01147-0.07950.468497
290.0798120.5530.291431
300.0400990.27780.391174
31-0.094105-0.6520.258762
32-0.036852-0.25530.399784
33-0.012806-0.08870.464836
34-0.074024-0.51290.305203
35-0.064292-0.44540.329008
36-0.133056-0.92180.180611

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.877622 & 6.0803 & 0 \tabularnewline
2 & -0.375578 & -2.6021 & 0.006143 \tabularnewline
3 & -0.322105 & -2.2316 & 0.015173 \tabularnewline
4 & 0.461736 & 3.199 & 0.001222 \tabularnewline
5 & -0.013155 & -0.0911 & 0.46388 \tabularnewline
6 & -0.295973 & -2.0506 & 0.022896 \tabularnewline
7 & -0.113934 & -0.7894 & 0.216892 \tabularnewline
8 & -0.020192 & -0.1399 & 0.444663 \tabularnewline
9 & -0.278515 & -1.9296 & 0.029789 \tabularnewline
10 & -0.197222 & -1.3664 & 0.089091 \tabularnewline
11 & 0.084577 & 0.586 & 0.280322 \tabularnewline
12 & -0.012738 & -0.0883 & 0.465023 \tabularnewline
13 & 0.167411 & 1.1599 & 0.125921 \tabularnewline
14 & 0.008152 & 0.0565 & 0.477597 \tabularnewline
15 & 0.096781 & 0.6705 & 0.252869 \tabularnewline
16 & 0.062281 & 0.4315 & 0.33402 \tabularnewline
17 & 0.157501 & 1.0912 & 0.140317 \tabularnewline
18 & -0.006749 & -0.0468 & 0.481451 \tabularnewline
19 & -0.066198 & -0.4586 & 0.324284 \tabularnewline
20 & -0.257666 & -1.7852 & 0.040277 \tabularnewline
21 & 0.088792 & 0.6152 & 0.270675 \tabularnewline
22 & -0.18813 & -1.3034 & 0.099327 \tabularnewline
23 & -0.016897 & -0.1171 & 0.453648 \tabularnewline
24 & 0.027737 & 0.1922 & 0.42421 \tabularnewline
25 & -0.007564 & -0.0524 & 0.479211 \tabularnewline
26 & 0.022637 & 0.1568 & 0.438017 \tabularnewline
27 & 0.061597 & 0.4268 & 0.335733 \tabularnewline
28 & -0.01147 & -0.0795 & 0.468497 \tabularnewline
29 & 0.079812 & 0.553 & 0.291431 \tabularnewline
30 & 0.040099 & 0.2778 & 0.391174 \tabularnewline
31 & -0.094105 & -0.652 & 0.258762 \tabularnewline
32 & -0.036852 & -0.2553 & 0.399784 \tabularnewline
33 & -0.012806 & -0.0887 & 0.464836 \tabularnewline
34 & -0.074024 & -0.5129 & 0.305203 \tabularnewline
35 & -0.064292 & -0.4454 & 0.329008 \tabularnewline
36 & -0.133056 & -0.9218 & 0.180611 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61322&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]0.877622[/C][C]6.0803[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.375578[/C][C]-2.6021[/C][C]0.006143[/C][/ROW]
[ROW][C]3[/C][C]-0.322105[/C][C]-2.2316[/C][C]0.015173[/C][/ROW]
[ROW][C]4[/C][C]0.461736[/C][C]3.199[/C][C]0.001222[/C][/ROW]
[ROW][C]5[/C][C]-0.013155[/C][C]-0.0911[/C][C]0.46388[/C][/ROW]
[ROW][C]6[/C][C]-0.295973[/C][C]-2.0506[/C][C]0.022896[/C][/ROW]
[ROW][C]7[/C][C]-0.113934[/C][C]-0.7894[/C][C]0.216892[/C][/ROW]
[ROW][C]8[/C][C]-0.020192[/C][C]-0.1399[/C][C]0.444663[/C][/ROW]
[ROW][C]9[/C][C]-0.278515[/C][C]-1.9296[/C][C]0.029789[/C][/ROW]
[ROW][C]10[/C][C]-0.197222[/C][C]-1.3664[/C][C]0.089091[/C][/ROW]
[ROW][C]11[/C][C]0.084577[/C][C]0.586[/C][C]0.280322[/C][/ROW]
[ROW][C]12[/C][C]-0.012738[/C][C]-0.0883[/C][C]0.465023[/C][/ROW]
[ROW][C]13[/C][C]0.167411[/C][C]1.1599[/C][C]0.125921[/C][/ROW]
[ROW][C]14[/C][C]0.008152[/C][C]0.0565[/C][C]0.477597[/C][/ROW]
[ROW][C]15[/C][C]0.096781[/C][C]0.6705[/C][C]0.252869[/C][/ROW]
[ROW][C]16[/C][C]0.062281[/C][C]0.4315[/C][C]0.33402[/C][/ROW]
[ROW][C]17[/C][C]0.157501[/C][C]1.0912[/C][C]0.140317[/C][/ROW]
[ROW][C]18[/C][C]-0.006749[/C][C]-0.0468[/C][C]0.481451[/C][/ROW]
[ROW][C]19[/C][C]-0.066198[/C][C]-0.4586[/C][C]0.324284[/C][/ROW]
[ROW][C]20[/C][C]-0.257666[/C][C]-1.7852[/C][C]0.040277[/C][/ROW]
[ROW][C]21[/C][C]0.088792[/C][C]0.6152[/C][C]0.270675[/C][/ROW]
[ROW][C]22[/C][C]-0.18813[/C][C]-1.3034[/C][C]0.099327[/C][/ROW]
[ROW][C]23[/C][C]-0.016897[/C][C]-0.1171[/C][C]0.453648[/C][/ROW]
[ROW][C]24[/C][C]0.027737[/C][C]0.1922[/C][C]0.42421[/C][/ROW]
[ROW][C]25[/C][C]-0.007564[/C][C]-0.0524[/C][C]0.479211[/C][/ROW]
[ROW][C]26[/C][C]0.022637[/C][C]0.1568[/C][C]0.438017[/C][/ROW]
[ROW][C]27[/C][C]0.061597[/C][C]0.4268[/C][C]0.335733[/C][/ROW]
[ROW][C]28[/C][C]-0.01147[/C][C]-0.0795[/C][C]0.468497[/C][/ROW]
[ROW][C]29[/C][C]0.079812[/C][C]0.553[/C][C]0.291431[/C][/ROW]
[ROW][C]30[/C][C]0.040099[/C][C]0.2778[/C][C]0.391174[/C][/ROW]
[ROW][C]31[/C][C]-0.094105[/C][C]-0.652[/C][C]0.258762[/C][/ROW]
[ROW][C]32[/C][C]-0.036852[/C][C]-0.2553[/C][C]0.399784[/C][/ROW]
[ROW][C]33[/C][C]-0.012806[/C][C]-0.0887[/C][C]0.464836[/C][/ROW]
[ROW][C]34[/C][C]-0.074024[/C][C]-0.5129[/C][C]0.305203[/C][/ROW]
[ROW][C]35[/C][C]-0.064292[/C][C]-0.4454[/C][C]0.329008[/C][/ROW]
[ROW][C]36[/C][C]-0.133056[/C][C]-0.9218[/C][C]0.180611[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61322&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61322&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
10.8776226.08030
2-0.375578-2.60210.006143
3-0.322105-2.23160.015173
40.4617363.1990.001222
5-0.013155-0.09110.46388
6-0.295973-2.05060.022896
7-0.113934-0.78940.216892
8-0.020192-0.13990.444663
9-0.278515-1.92960.029789
10-0.197222-1.36640.089091
110.0845770.5860.280322
12-0.012738-0.08830.465023
130.1674111.15990.125921
140.0081520.05650.477597
150.0967810.67050.252869
160.0622810.43150.33402
170.1575011.09120.140317
18-0.006749-0.04680.481451
19-0.066198-0.45860.324284
20-0.257666-1.78520.040277
210.0887920.61520.270675
22-0.18813-1.30340.099327
23-0.016897-0.11710.453648
240.0277370.19220.42421
25-0.007564-0.05240.479211
260.0226370.15680.438017
270.0615970.42680.335733
28-0.01147-0.07950.468497
290.0798120.5530.291431
300.0400990.27780.391174
31-0.094105-0.6520.258762
32-0.036852-0.25530.399784
33-0.012806-0.08870.464836
34-0.074024-0.51290.305203
35-0.064292-0.44540.329008
36-0.133056-0.92180.180611



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 ;
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')