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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 computationWed, 16 Dec 2009 06:38:30 -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/16/t1260970765alppsmx88uxp2vk.htm/, Retrieved Tue, 30 Apr 2024 11:31:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68323, Retrieved Tue, 30 Apr 2024 11:31:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [ACF (d=0;D=0)] [2009-12-16 13:38:30] [91da2e1ebdd83187f2515f461585cbee] [Current]
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Dataseries X:
8715.1
8919.9
10085.8
9511.7
8991.3
10311.2
8895.4
7449.8
10084.0
9859.4
9100.1
8920.8
8502.7
8599.6
10394.4
9290.4
8742.2
10217.3
8639.0
8139.6
10779.1
10427.7
10349.1
10036.4
9492.1
10638.8
12054.5
10324.7
11817.3
11008.9
9996.6
9419.5
11958.8
12594.6
11890.6
10871.7
11835.7
11542.2
13093.7
11180.2
12035.7
12112.0
10875.2
9897.3
11672.1
12385.7
11405.6
9830.9
11025.1
10853.8
12252.6
11839.4
11669.1
11601.4
11178.4
9516.4
12102.8
12989.0
11610.2
10205.5
11356.2
11307.1
12648.6
11947.2
11714.1
12192.5
11268.8
9097.4
12639.8
13040.1
11687.3
11191.7
11391.9
11793.1
13933.2
12778.1
11810.3
13698.4
11956.6
10723.8
13938.9
13979.8
13807.4
12973.9
12509.8
12934.1
14908.3
13772.1
13012.6
14049.9
11816.5
11593.2
14466.2
13615.9
14733.9
13880.7
13527.5
13584.0
16170.2
13260.6
14741.9
15486.5
13154.5
12621.2
15031.6
15452.4
15428.0
13105.9
14716.8
14180.0
16202.2
14392.4
15140.6
15960.1
14351.3
13230.2
15202.1
17056.0
16077.7
13348.2
16402.4
16559.1
16579.0
17561.2
16129.6
18484.3
16402.6
14032.3
17109.1
17157.2
13879.8
12362.4




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=68323&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=68323&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68323&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
10.7948449.13210
20.6984788.02490
30.7505418.62310
40.7467368.57930
50.7193358.26450
60.743088.53730
70.6609697.5940
80.6467617.43070
90.5836526.70560
100.5099395.85880
110.5765316.62380
120.6848127.86790
130.5108155.86880
140.4215764.84352e-06
150.4450515.11321e-06
160.4534645.20990
170.4323334.96711e-06
180.4420575.07891e-06
190.3791424.3561.3e-05
200.3667044.21312.3e-05
210.2985523.43010.000403
220.2535292.91280.002104
230.325293.73730.000138
240.3990164.58435e-06
250.2728633.1350.001059
260.1967772.26080.012704
270.2108382.42230.008389
280.2440992.80450.002901
290.2253392.58890.005353
300.2352442.70270.003891
310.2035012.3380.010444
320.1763742.02640.02237
330.1237261.42150.078765
340.1044411.19990.116156
350.1543931.77380.039198
360.2297262.63940.004653

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.794844 & 9.1321 & 0 \tabularnewline
2 & 0.698478 & 8.0249 & 0 \tabularnewline
3 & 0.750541 & 8.6231 & 0 \tabularnewline
4 & 0.746736 & 8.5793 & 0 \tabularnewline
5 & 0.719335 & 8.2645 & 0 \tabularnewline
6 & 0.74308 & 8.5373 & 0 \tabularnewline
7 & 0.660969 & 7.594 & 0 \tabularnewline
8 & 0.646761 & 7.4307 & 0 \tabularnewline
9 & 0.583652 & 6.7056 & 0 \tabularnewline
10 & 0.509939 & 5.8588 & 0 \tabularnewline
11 & 0.576531 & 6.6238 & 0 \tabularnewline
12 & 0.684812 & 7.8679 & 0 \tabularnewline
13 & 0.510815 & 5.8688 & 0 \tabularnewline
14 & 0.421576 & 4.8435 & 2e-06 \tabularnewline
15 & 0.445051 & 5.1132 & 1e-06 \tabularnewline
16 & 0.453464 & 5.2099 & 0 \tabularnewline
17 & 0.432333 & 4.9671 & 1e-06 \tabularnewline
18 & 0.442057 & 5.0789 & 1e-06 \tabularnewline
19 & 0.379142 & 4.356 & 1.3e-05 \tabularnewline
20 & 0.366704 & 4.2131 & 2.3e-05 \tabularnewline
21 & 0.298552 & 3.4301 & 0.000403 \tabularnewline
22 & 0.253529 & 2.9128 & 0.002104 \tabularnewline
23 & 0.32529 & 3.7373 & 0.000138 \tabularnewline
24 & 0.399016 & 4.5843 & 5e-06 \tabularnewline
25 & 0.272863 & 3.135 & 0.001059 \tabularnewline
26 & 0.196777 & 2.2608 & 0.012704 \tabularnewline
27 & 0.210838 & 2.4223 & 0.008389 \tabularnewline
28 & 0.244099 & 2.8045 & 0.002901 \tabularnewline
29 & 0.225339 & 2.5889 & 0.005353 \tabularnewline
30 & 0.235244 & 2.7027 & 0.003891 \tabularnewline
31 & 0.203501 & 2.338 & 0.010444 \tabularnewline
32 & 0.176374 & 2.0264 & 0.02237 \tabularnewline
33 & 0.123726 & 1.4215 & 0.078765 \tabularnewline
34 & 0.104441 & 1.1999 & 0.116156 \tabularnewline
35 & 0.154393 & 1.7738 & 0.039198 \tabularnewline
36 & 0.229726 & 2.6394 & 0.004653 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68323&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]0.794844[/C][C]9.1321[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.698478[/C][C]8.0249[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.750541[/C][C]8.6231[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.746736[/C][C]8.5793[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.719335[/C][C]8.2645[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.74308[/C][C]8.5373[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.660969[/C][C]7.594[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.646761[/C][C]7.4307[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.583652[/C][C]6.7056[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.509939[/C][C]5.8588[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.576531[/C][C]6.6238[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.684812[/C][C]7.8679[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.510815[/C][C]5.8688[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.421576[/C][C]4.8435[/C][C]2e-06[/C][/ROW]
[ROW][C]15[/C][C]0.445051[/C][C]5.1132[/C][C]1e-06[/C][/ROW]
[ROW][C]16[/C][C]0.453464[/C][C]5.2099[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.432333[/C][C]4.9671[/C][C]1e-06[/C][/ROW]
[ROW][C]18[/C][C]0.442057[/C][C]5.0789[/C][C]1e-06[/C][/ROW]
[ROW][C]19[/C][C]0.379142[/C][C]4.356[/C][C]1.3e-05[/C][/ROW]
[ROW][C]20[/C][C]0.366704[/C][C]4.2131[/C][C]2.3e-05[/C][/ROW]
[ROW][C]21[/C][C]0.298552[/C][C]3.4301[/C][C]0.000403[/C][/ROW]
[ROW][C]22[/C][C]0.253529[/C][C]2.9128[/C][C]0.002104[/C][/ROW]
[ROW][C]23[/C][C]0.32529[/C][C]3.7373[/C][C]0.000138[/C][/ROW]
[ROW][C]24[/C][C]0.399016[/C][C]4.5843[/C][C]5e-06[/C][/ROW]
[ROW][C]25[/C][C]0.272863[/C][C]3.135[/C][C]0.001059[/C][/ROW]
[ROW][C]26[/C][C]0.196777[/C][C]2.2608[/C][C]0.012704[/C][/ROW]
[ROW][C]27[/C][C]0.210838[/C][C]2.4223[/C][C]0.008389[/C][/ROW]
[ROW][C]28[/C][C]0.244099[/C][C]2.8045[/C][C]0.002901[/C][/ROW]
[ROW][C]29[/C][C]0.225339[/C][C]2.5889[/C][C]0.005353[/C][/ROW]
[ROW][C]30[/C][C]0.235244[/C][C]2.7027[/C][C]0.003891[/C][/ROW]
[ROW][C]31[/C][C]0.203501[/C][C]2.338[/C][C]0.010444[/C][/ROW]
[ROW][C]32[/C][C]0.176374[/C][C]2.0264[/C][C]0.02237[/C][/ROW]
[ROW][C]33[/C][C]0.123726[/C][C]1.4215[/C][C]0.078765[/C][/ROW]
[ROW][C]34[/C][C]0.104441[/C][C]1.1999[/C][C]0.116156[/C][/ROW]
[ROW][C]35[/C][C]0.154393[/C][C]1.7738[/C][C]0.039198[/C][/ROW]
[ROW][C]36[/C][C]0.229726[/C][C]2.6394[/C][C]0.004653[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68323&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68323&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
10.7948449.13210
20.6984788.02490
30.7505418.62310
40.7467368.57930
50.7193358.26450
60.743088.53730
70.6609697.5940
80.6467617.43070
90.5836526.70560
100.5099395.85880
110.5765316.62380
120.6848127.86790
130.5108155.86880
140.4215764.84352e-06
150.4450515.11321e-06
160.4534645.20990
170.4323334.96711e-06
180.4420575.07891e-06
190.3791424.3561.3e-05
200.3667044.21312.3e-05
210.2985523.43010.000403
220.2535292.91280.002104
230.325293.73730.000138
240.3990164.58435e-06
250.2728633.1350.001059
260.1967772.26080.012704
270.2108382.42230.008389
280.2440992.80450.002901
290.2253392.58890.005353
300.2352442.70270.003891
310.2035012.3380.010444
320.1763742.02640.02237
330.1237261.42150.078765
340.1044411.19990.116156
350.1543931.77380.039198
360.2297262.63940.004653







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7948449.13210
20.1811442.08120.019675
30.4266474.90181e-06
40.1529571.75730.040589
50.1505511.72970.043011
60.203212.33470.010534
7-0.204815-2.35320.010046
80.0943291.08380.140224
9-0.369489-4.24512e-05
10-0.188913-2.17040.015881
110.2172442.49590.006897
120.4613325.30030
13-0.290797-3.3410.000543
14-0.178488-2.05070.021139
15-0.150493-1.7290.04307
160.1015551.16680.122701
170.0268740.30880.378998
180.0364050.41830.338219
190.0028140.03230.487129
20-0.004976-0.05720.477249
21-0.042024-0.48280.315013
220.0027730.03190.487315
230.0408680.46950.319732
240.0336020.38610.350038
250.0605030.69510.244099
26-0.085206-0.97890.164698
27-0.038414-0.44130.329845
280.013570.15590.438171
29-0.056905-0.65380.257193
300.055950.64280.260728
310.0184760.21230.416112
32-0.056632-0.65060.258203
330.0472340.54270.294134
34-0.037985-0.43640.331623
35-0.058894-0.67660.24991
360.1027521.18050.119957

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.794844 & 9.1321 & 0 \tabularnewline
2 & 0.181144 & 2.0812 & 0.019675 \tabularnewline
3 & 0.426647 & 4.9018 & 1e-06 \tabularnewline
4 & 0.152957 & 1.7573 & 0.040589 \tabularnewline
5 & 0.150551 & 1.7297 & 0.043011 \tabularnewline
6 & 0.20321 & 2.3347 & 0.010534 \tabularnewline
7 & -0.204815 & -2.3532 & 0.010046 \tabularnewline
8 & 0.094329 & 1.0838 & 0.140224 \tabularnewline
9 & -0.369489 & -4.2451 & 2e-05 \tabularnewline
10 & -0.188913 & -2.1704 & 0.015881 \tabularnewline
11 & 0.217244 & 2.4959 & 0.006897 \tabularnewline
12 & 0.461332 & 5.3003 & 0 \tabularnewline
13 & -0.290797 & -3.341 & 0.000543 \tabularnewline
14 & -0.178488 & -2.0507 & 0.021139 \tabularnewline
15 & -0.150493 & -1.729 & 0.04307 \tabularnewline
16 & 0.101555 & 1.1668 & 0.122701 \tabularnewline
17 & 0.026874 & 0.3088 & 0.378998 \tabularnewline
18 & 0.036405 & 0.4183 & 0.338219 \tabularnewline
19 & 0.002814 & 0.0323 & 0.487129 \tabularnewline
20 & -0.004976 & -0.0572 & 0.477249 \tabularnewline
21 & -0.042024 & -0.4828 & 0.315013 \tabularnewline
22 & 0.002773 & 0.0319 & 0.487315 \tabularnewline
23 & 0.040868 & 0.4695 & 0.319732 \tabularnewline
24 & 0.033602 & 0.3861 & 0.350038 \tabularnewline
25 & 0.060503 & 0.6951 & 0.244099 \tabularnewline
26 & -0.085206 & -0.9789 & 0.164698 \tabularnewline
27 & -0.038414 & -0.4413 & 0.329845 \tabularnewline
28 & 0.01357 & 0.1559 & 0.438171 \tabularnewline
29 & -0.056905 & -0.6538 & 0.257193 \tabularnewline
30 & 0.05595 & 0.6428 & 0.260728 \tabularnewline
31 & 0.018476 & 0.2123 & 0.416112 \tabularnewline
32 & -0.056632 & -0.6506 & 0.258203 \tabularnewline
33 & 0.047234 & 0.5427 & 0.294134 \tabularnewline
34 & -0.037985 & -0.4364 & 0.331623 \tabularnewline
35 & -0.058894 & -0.6766 & 0.24991 \tabularnewline
36 & 0.102752 & 1.1805 & 0.119957 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68323&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]0.794844[/C][C]9.1321[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.181144[/C][C]2.0812[/C][C]0.019675[/C][/ROW]
[ROW][C]3[/C][C]0.426647[/C][C]4.9018[/C][C]1e-06[/C][/ROW]
[ROW][C]4[/C][C]0.152957[/C][C]1.7573[/C][C]0.040589[/C][/ROW]
[ROW][C]5[/C][C]0.150551[/C][C]1.7297[/C][C]0.043011[/C][/ROW]
[ROW][C]6[/C][C]0.20321[/C][C]2.3347[/C][C]0.010534[/C][/ROW]
[ROW][C]7[/C][C]-0.204815[/C][C]-2.3532[/C][C]0.010046[/C][/ROW]
[ROW][C]8[/C][C]0.094329[/C][C]1.0838[/C][C]0.140224[/C][/ROW]
[ROW][C]9[/C][C]-0.369489[/C][C]-4.2451[/C][C]2e-05[/C][/ROW]
[ROW][C]10[/C][C]-0.188913[/C][C]-2.1704[/C][C]0.015881[/C][/ROW]
[ROW][C]11[/C][C]0.217244[/C][C]2.4959[/C][C]0.006897[/C][/ROW]
[ROW][C]12[/C][C]0.461332[/C][C]5.3003[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.290797[/C][C]-3.341[/C][C]0.000543[/C][/ROW]
[ROW][C]14[/C][C]-0.178488[/C][C]-2.0507[/C][C]0.021139[/C][/ROW]
[ROW][C]15[/C][C]-0.150493[/C][C]-1.729[/C][C]0.04307[/C][/ROW]
[ROW][C]16[/C][C]0.101555[/C][C]1.1668[/C][C]0.122701[/C][/ROW]
[ROW][C]17[/C][C]0.026874[/C][C]0.3088[/C][C]0.378998[/C][/ROW]
[ROW][C]18[/C][C]0.036405[/C][C]0.4183[/C][C]0.338219[/C][/ROW]
[ROW][C]19[/C][C]0.002814[/C][C]0.0323[/C][C]0.487129[/C][/ROW]
[ROW][C]20[/C][C]-0.004976[/C][C]-0.0572[/C][C]0.477249[/C][/ROW]
[ROW][C]21[/C][C]-0.042024[/C][C]-0.4828[/C][C]0.315013[/C][/ROW]
[ROW][C]22[/C][C]0.002773[/C][C]0.0319[/C][C]0.487315[/C][/ROW]
[ROW][C]23[/C][C]0.040868[/C][C]0.4695[/C][C]0.319732[/C][/ROW]
[ROW][C]24[/C][C]0.033602[/C][C]0.3861[/C][C]0.350038[/C][/ROW]
[ROW][C]25[/C][C]0.060503[/C][C]0.6951[/C][C]0.244099[/C][/ROW]
[ROW][C]26[/C][C]-0.085206[/C][C]-0.9789[/C][C]0.164698[/C][/ROW]
[ROW][C]27[/C][C]-0.038414[/C][C]-0.4413[/C][C]0.329845[/C][/ROW]
[ROW][C]28[/C][C]0.01357[/C][C]0.1559[/C][C]0.438171[/C][/ROW]
[ROW][C]29[/C][C]-0.056905[/C][C]-0.6538[/C][C]0.257193[/C][/ROW]
[ROW][C]30[/C][C]0.05595[/C][C]0.6428[/C][C]0.260728[/C][/ROW]
[ROW][C]31[/C][C]0.018476[/C][C]0.2123[/C][C]0.416112[/C][/ROW]
[ROW][C]32[/C][C]-0.056632[/C][C]-0.6506[/C][C]0.258203[/C][/ROW]
[ROW][C]33[/C][C]0.047234[/C][C]0.5427[/C][C]0.294134[/C][/ROW]
[ROW][C]34[/C][C]-0.037985[/C][C]-0.4364[/C][C]0.331623[/C][/ROW]
[ROW][C]35[/C][C]-0.058894[/C][C]-0.6766[/C][C]0.24991[/C][/ROW]
[ROW][C]36[/C][C]0.102752[/C][C]1.1805[/C][C]0.119957[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68323&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68323&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
10.7948449.13210
20.1811442.08120.019675
30.4266474.90181e-06
40.1529571.75730.040589
50.1505511.72970.043011
60.203212.33470.010534
7-0.204815-2.35320.010046
80.0943291.08380.140224
9-0.369489-4.24512e-05
10-0.188913-2.17040.015881
110.2172442.49590.006897
120.4613325.30030
13-0.290797-3.3410.000543
14-0.178488-2.05070.021139
15-0.150493-1.7290.04307
160.1015551.16680.122701
170.0268740.30880.378998
180.0364050.41830.338219
190.0028140.03230.487129
20-0.004976-0.05720.477249
21-0.042024-0.48280.315013
220.0027730.03190.487315
230.0408680.46950.319732
240.0336020.38610.350038
250.0605030.69510.244099
26-0.085206-0.97890.164698
27-0.038414-0.44130.329845
280.013570.15590.438171
29-0.056905-0.65380.257193
300.055950.64280.260728
310.0184760.21230.416112
32-0.056632-0.65060.258203
330.0472340.54270.294134
34-0.037985-0.43640.331623
35-0.058894-0.67660.24991
360.1027521.18050.119957



Parameters (Session):
par1 = 36 ; par2 = 0.0 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 0.0 ; 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')