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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 computationFri, 04 Dec 2009 02:36:56 -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/04/t1259919448kex6yacqfaxcbaq.htm/, Retrieved Sat, 27 Apr 2024 18:40:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63211, Retrieved Sat, 27 Apr 2024 18:40:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130

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 12:26:39] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [WS 8 Methode 1: A...] [2009-11-25 13:07:25] [b103a1dc147def8132c7f643ad8c8f84]
-                 [(Partial) Autocorrelation Function] [WS 8 review] [2009-12-04 09:36:56] [51118f1042b56b16d340924f16263174] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
14.2
13.5
11.9
14.6
15.6
14.1
14.9
14.2
14.6
17.2
15.4
14.3
17.5
14.5
14.4
16.6
16.7
16.6
16.9
15.7
16.4
18.4
16.9
16.5
18.3
15.1
15.7
18.1
16.8
18.9
19
18.1
17.8
21.5
17.1
18.7
19
16.4
16.9
18.6
19.3
19.4
17.6
18.6
18.1
20.4
18.1
19.6
19.9
19.2
17.8
19.2
22
21.1
19.5
22.2
20.9
22.2
23.5
21.5
24.3
22.8
20.3
23.7
23.3
19.6
18
17.3
16.8
18.2
16.5
16
18.4

Tables (Output of Computation)





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=63211&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=63211&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63211&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.374032-3.17380.001107
2-0.257557-2.18540.016055
30.3772493.20110.001019
4-0.194689-1.6520.051445
5-0.052555-0.44590.328489
60.2989012.53630.006687
7-0.321533-2.72830.003997
80.0225690.19150.424334
90.2507682.12780.018388
10-0.345269-2.92970.002271
11-0.080092-0.67960.249468
120.4845814.11185.1e-05
13-0.276666-2.34760.010824
14-0.094496-0.80180.212645
150.1243361.0550.147471
16-0.092851-0.78790.216681
170.0305650.25940.398051
180.0645830.5480.292692
19-0.077411-0.65690.256684
200.0280690.23820.406213
210.0635880.53960.295582
22-0.14445-1.22570.112152
23-0.027436-0.23280.408287
240.2072171.75830.041474
250.0016180.01370.494543
26-0.17119-1.45260.07534
270.037750.32030.374826
280.0688210.5840.280535
29-0.047722-0.40490.343364
30-0.007997-0.06790.473044
310.1198361.01680.156316
32-0.096899-0.82220.206835
330.0202920.17220.431889
340.0368280.31250.377783
35-0.154593-1.31180.096884
360.1611181.36710.087919

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.374032 & -3.1738 & 0.001107 \tabularnewline
2 & -0.257557 & -2.1854 & 0.016055 \tabularnewline
3 & 0.377249 & 3.2011 & 0.001019 \tabularnewline
4 & -0.194689 & -1.652 & 0.051445 \tabularnewline
5 & -0.052555 & -0.4459 & 0.328489 \tabularnewline
6 & 0.298901 & 2.5363 & 0.006687 \tabularnewline
7 & -0.321533 & -2.7283 & 0.003997 \tabularnewline
8 & 0.022569 & 0.1915 & 0.424334 \tabularnewline
9 & 0.250768 & 2.1278 & 0.018388 \tabularnewline
10 & -0.345269 & -2.9297 & 0.002271 \tabularnewline
11 & -0.080092 & -0.6796 & 0.249468 \tabularnewline
12 & 0.484581 & 4.1118 & 5.1e-05 \tabularnewline
13 & -0.276666 & -2.3476 & 0.010824 \tabularnewline
14 & -0.094496 & -0.8018 & 0.212645 \tabularnewline
15 & 0.124336 & 1.055 & 0.147471 \tabularnewline
16 & -0.092851 & -0.7879 & 0.216681 \tabularnewline
17 & 0.030565 & 0.2594 & 0.398051 \tabularnewline
18 & 0.064583 & 0.548 & 0.292692 \tabularnewline
19 & -0.077411 & -0.6569 & 0.256684 \tabularnewline
20 & 0.028069 & 0.2382 & 0.406213 \tabularnewline
21 & 0.063588 & 0.5396 & 0.295582 \tabularnewline
22 & -0.14445 & -1.2257 & 0.112152 \tabularnewline
23 & -0.027436 & -0.2328 & 0.408287 \tabularnewline
24 & 0.207217 & 1.7583 & 0.041474 \tabularnewline
25 & 0.001618 & 0.0137 & 0.494543 \tabularnewline
26 & -0.17119 & -1.4526 & 0.07534 \tabularnewline
27 & 0.03775 & 0.3203 & 0.374826 \tabularnewline
28 & 0.068821 & 0.584 & 0.280535 \tabularnewline
29 & -0.047722 & -0.4049 & 0.343364 \tabularnewline
30 & -0.007997 & -0.0679 & 0.473044 \tabularnewline
31 & 0.119836 & 1.0168 & 0.156316 \tabularnewline
32 & -0.096899 & -0.8222 & 0.206835 \tabularnewline
33 & 0.020292 & 0.1722 & 0.431889 \tabularnewline
34 & 0.036828 & 0.3125 & 0.377783 \tabularnewline
35 & -0.154593 & -1.3118 & 0.096884 \tabularnewline
36 & 0.161118 & 1.3671 & 0.087919 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63211&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]-0.374032[/C][C]-3.1738[/C][C]0.001107[/C][/ROW]
[ROW][C]2[/C][C]-0.257557[/C][C]-2.1854[/C][C]0.016055[/C][/ROW]
[ROW][C]3[/C][C]0.377249[/C][C]3.2011[/C][C]0.001019[/C][/ROW]
[ROW][C]4[/C][C]-0.194689[/C][C]-1.652[/C][C]0.051445[/C][/ROW]
[ROW][C]5[/C][C]-0.052555[/C][C]-0.4459[/C][C]0.328489[/C][/ROW]
[ROW][C]6[/C][C]0.298901[/C][C]2.5363[/C][C]0.006687[/C][/ROW]
[ROW][C]7[/C][C]-0.321533[/C][C]-2.7283[/C][C]0.003997[/C][/ROW]
[ROW][C]8[/C][C]0.022569[/C][C]0.1915[/C][C]0.424334[/C][/ROW]
[ROW][C]9[/C][C]0.250768[/C][C]2.1278[/C][C]0.018388[/C][/ROW]
[ROW][C]10[/C][C]-0.345269[/C][C]-2.9297[/C][C]0.002271[/C][/ROW]
[ROW][C]11[/C][C]-0.080092[/C][C]-0.6796[/C][C]0.249468[/C][/ROW]
[ROW][C]12[/C][C]0.484581[/C][C]4.1118[/C][C]5.1e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.276666[/C][C]-2.3476[/C][C]0.010824[/C][/ROW]
[ROW][C]14[/C][C]-0.094496[/C][C]-0.8018[/C][C]0.212645[/C][/ROW]
[ROW][C]15[/C][C]0.124336[/C][C]1.055[/C][C]0.147471[/C][/ROW]
[ROW][C]16[/C][C]-0.092851[/C][C]-0.7879[/C][C]0.216681[/C][/ROW]
[ROW][C]17[/C][C]0.030565[/C][C]0.2594[/C][C]0.398051[/C][/ROW]
[ROW][C]18[/C][C]0.064583[/C][C]0.548[/C][C]0.292692[/C][/ROW]
[ROW][C]19[/C][C]-0.077411[/C][C]-0.6569[/C][C]0.256684[/C][/ROW]
[ROW][C]20[/C][C]0.028069[/C][C]0.2382[/C][C]0.406213[/C][/ROW]
[ROW][C]21[/C][C]0.063588[/C][C]0.5396[/C][C]0.295582[/C][/ROW]
[ROW][C]22[/C][C]-0.14445[/C][C]-1.2257[/C][C]0.112152[/C][/ROW]
[ROW][C]23[/C][C]-0.027436[/C][C]-0.2328[/C][C]0.408287[/C][/ROW]
[ROW][C]24[/C][C]0.207217[/C][C]1.7583[/C][C]0.041474[/C][/ROW]
[ROW][C]25[/C][C]0.001618[/C][C]0.0137[/C][C]0.494543[/C][/ROW]
[ROW][C]26[/C][C]-0.17119[/C][C]-1.4526[/C][C]0.07534[/C][/ROW]
[ROW][C]27[/C][C]0.03775[/C][C]0.3203[/C][C]0.374826[/C][/ROW]
[ROW][C]28[/C][C]0.068821[/C][C]0.584[/C][C]0.280535[/C][/ROW]
[ROW][C]29[/C][C]-0.047722[/C][C]-0.4049[/C][C]0.343364[/C][/ROW]
[ROW][C]30[/C][C]-0.007997[/C][C]-0.0679[/C][C]0.473044[/C][/ROW]
[ROW][C]31[/C][C]0.119836[/C][C]1.0168[/C][C]0.156316[/C][/ROW]
[ROW][C]32[/C][C]-0.096899[/C][C]-0.8222[/C][C]0.206835[/C][/ROW]
[ROW][C]33[/C][C]0.020292[/C][C]0.1722[/C][C]0.431889[/C][/ROW]
[ROW][C]34[/C][C]0.036828[/C][C]0.3125[/C][C]0.377783[/C][/ROW]
[ROW][C]35[/C][C]-0.154593[/C][C]-1.3118[/C][C]0.096884[/C][/ROW]
[ROW][C]36[/C][C]0.161118[/C][C]1.3671[/C][C]0.087919[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63211&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63211&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
1-0.374032-3.17380.001107
2-0.257557-2.18540.016055
30.3772493.20110.001019
4-0.194689-1.6520.051445
5-0.052555-0.44590.328489
60.2989012.53630.006687
7-0.321533-2.72830.003997
80.0225690.19150.424334
90.2507682.12780.018388
10-0.345269-2.92970.002271
11-0.080092-0.67960.249468
120.4845814.11185.1e-05
13-0.276666-2.34760.010824
14-0.094496-0.80180.212645
150.1243361.0550.147471
16-0.092851-0.78790.216681
170.0305650.25940.398051
180.0645830.5480.292692
19-0.077411-0.65690.256684
200.0280690.23820.406213
210.0635880.53960.295582
22-0.14445-1.22570.112152
23-0.027436-0.23280.408287
240.2072171.75830.041474
250.0016180.01370.494543
26-0.17119-1.45260.07534
270.037750.32030.374826
280.0688210.5840.280535
29-0.047722-0.40490.343364
30-0.007997-0.06790.473044
310.1198361.01680.156316
32-0.096899-0.82220.206835
330.0202920.17220.431889
340.0368280.31250.377783
35-0.154593-1.31180.096884
360.1611181.36710.087919






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.374032-3.17380.001107
2-0.462105-3.92111e-04
30.0939580.79730.213962
4-0.112463-0.95430.171566
5-0.012981-0.11010.456299
60.20661.75310.041925
7-0.130861-1.11040.135262
8-0.046325-0.39310.34771
90.0385240.32690.372349
10-0.195511-1.6590.050737
11-0.357962-3.03740.001661
120.2179221.84910.034272
130.1461871.24040.109421
140.031010.26310.396601
15-0.217336-1.84420.034637
160.004570.03880.484588
17-0.086469-0.73370.232754
18-0.231377-1.96330.026737
190.1391931.18110.120727
200.1033350.87680.191748
21-0.033736-0.28630.387751
22-0.094765-0.80410.211992
23-0.007813-0.06630.473663
24-0.106965-0.90760.183551
250.0509330.43220.333452
260.0274210.23270.408337
270.0253490.21510.415152
28-0.043707-0.37090.355913
29-0.005256-0.04460.482277
30-0.078114-0.66280.254783
310.0671010.56940.285438
320.0692690.58780.279263
330.012360.10490.458382
340.084740.7190.237221
35-0.056205-0.47690.317434
36-0.04123-0.34990.363736

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.374032 & -3.1738 & 0.001107 \tabularnewline
2 & -0.462105 & -3.9211 & 1e-04 \tabularnewline
3 & 0.093958 & 0.7973 & 0.213962 \tabularnewline
4 & -0.112463 & -0.9543 & 0.171566 \tabularnewline
5 & -0.012981 & -0.1101 & 0.456299 \tabularnewline
6 & 0.2066 & 1.7531 & 0.041925 \tabularnewline
7 & -0.130861 & -1.1104 & 0.135262 \tabularnewline
8 & -0.046325 & -0.3931 & 0.34771 \tabularnewline
9 & 0.038524 & 0.3269 & 0.372349 \tabularnewline
10 & -0.195511 & -1.659 & 0.050737 \tabularnewline
11 & -0.357962 & -3.0374 & 0.001661 \tabularnewline
12 & 0.217922 & 1.8491 & 0.034272 \tabularnewline
13 & 0.146187 & 1.2404 & 0.109421 \tabularnewline
14 & 0.03101 & 0.2631 & 0.396601 \tabularnewline
15 & -0.217336 & -1.8442 & 0.034637 \tabularnewline
16 & 0.00457 & 0.0388 & 0.484588 \tabularnewline
17 & -0.086469 & -0.7337 & 0.232754 \tabularnewline
18 & -0.231377 & -1.9633 & 0.026737 \tabularnewline
19 & 0.139193 & 1.1811 & 0.120727 \tabularnewline
20 & 0.103335 & 0.8768 & 0.191748 \tabularnewline
21 & -0.033736 & -0.2863 & 0.387751 \tabularnewline
22 & -0.094765 & -0.8041 & 0.211992 \tabularnewline
23 & -0.007813 & -0.0663 & 0.473663 \tabularnewline
24 & -0.106965 & -0.9076 & 0.183551 \tabularnewline
25 & 0.050933 & 0.4322 & 0.333452 \tabularnewline
26 & 0.027421 & 0.2327 & 0.408337 \tabularnewline
27 & 0.025349 & 0.2151 & 0.415152 \tabularnewline
28 & -0.043707 & -0.3709 & 0.355913 \tabularnewline
29 & -0.005256 & -0.0446 & 0.482277 \tabularnewline
30 & -0.078114 & -0.6628 & 0.254783 \tabularnewline
31 & 0.067101 & 0.5694 & 0.285438 \tabularnewline
32 & 0.069269 & 0.5878 & 0.279263 \tabularnewline
33 & 0.01236 & 0.1049 & 0.458382 \tabularnewline
34 & 0.08474 & 0.719 & 0.237221 \tabularnewline
35 & -0.056205 & -0.4769 & 0.317434 \tabularnewline
36 & -0.04123 & -0.3499 & 0.363736 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63211&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]-0.374032[/C][C]-3.1738[/C][C]0.001107[/C][/ROW]
[ROW][C]2[/C][C]-0.462105[/C][C]-3.9211[/C][C]1e-04[/C][/ROW]
[ROW][C]3[/C][C]0.093958[/C][C]0.7973[/C][C]0.213962[/C][/ROW]
[ROW][C]4[/C][C]-0.112463[/C][C]-0.9543[/C][C]0.171566[/C][/ROW]
[ROW][C]5[/C][C]-0.012981[/C][C]-0.1101[/C][C]0.456299[/C][/ROW]
[ROW][C]6[/C][C]0.2066[/C][C]1.7531[/C][C]0.041925[/C][/ROW]
[ROW][C]7[/C][C]-0.130861[/C][C]-1.1104[/C][C]0.135262[/C][/ROW]
[ROW][C]8[/C][C]-0.046325[/C][C]-0.3931[/C][C]0.34771[/C][/ROW]
[ROW][C]9[/C][C]0.038524[/C][C]0.3269[/C][C]0.372349[/C][/ROW]
[ROW][C]10[/C][C]-0.195511[/C][C]-1.659[/C][C]0.050737[/C][/ROW]
[ROW][C]11[/C][C]-0.357962[/C][C]-3.0374[/C][C]0.001661[/C][/ROW]
[ROW][C]12[/C][C]0.217922[/C][C]1.8491[/C][C]0.034272[/C][/ROW]
[ROW][C]13[/C][C]0.146187[/C][C]1.2404[/C][C]0.109421[/C][/ROW]
[ROW][C]14[/C][C]0.03101[/C][C]0.2631[/C][C]0.396601[/C][/ROW]
[ROW][C]15[/C][C]-0.217336[/C][C]-1.8442[/C][C]0.034637[/C][/ROW]
[ROW][C]16[/C][C]0.00457[/C][C]0.0388[/C][C]0.484588[/C][/ROW]
[ROW][C]17[/C][C]-0.086469[/C][C]-0.7337[/C][C]0.232754[/C][/ROW]
[ROW][C]18[/C][C]-0.231377[/C][C]-1.9633[/C][C]0.026737[/C][/ROW]
[ROW][C]19[/C][C]0.139193[/C][C]1.1811[/C][C]0.120727[/C][/ROW]
[ROW][C]20[/C][C]0.103335[/C][C]0.8768[/C][C]0.191748[/C][/ROW]
[ROW][C]21[/C][C]-0.033736[/C][C]-0.2863[/C][C]0.387751[/C][/ROW]
[ROW][C]22[/C][C]-0.094765[/C][C]-0.8041[/C][C]0.211992[/C][/ROW]
[ROW][C]23[/C][C]-0.007813[/C][C]-0.0663[/C][C]0.473663[/C][/ROW]
[ROW][C]24[/C][C]-0.106965[/C][C]-0.9076[/C][C]0.183551[/C][/ROW]
[ROW][C]25[/C][C]0.050933[/C][C]0.4322[/C][C]0.333452[/C][/ROW]
[ROW][C]26[/C][C]0.027421[/C][C]0.2327[/C][C]0.408337[/C][/ROW]
[ROW][C]27[/C][C]0.025349[/C][C]0.2151[/C][C]0.415152[/C][/ROW]
[ROW][C]28[/C][C]-0.043707[/C][C]-0.3709[/C][C]0.355913[/C][/ROW]
[ROW][C]29[/C][C]-0.005256[/C][C]-0.0446[/C][C]0.482277[/C][/ROW]
[ROW][C]30[/C][C]-0.078114[/C][C]-0.6628[/C][C]0.254783[/C][/ROW]
[ROW][C]31[/C][C]0.067101[/C][C]0.5694[/C][C]0.285438[/C][/ROW]
[ROW][C]32[/C][C]0.069269[/C][C]0.5878[/C][C]0.279263[/C][/ROW]
[ROW][C]33[/C][C]0.01236[/C][C]0.1049[/C][C]0.458382[/C][/ROW]
[ROW][C]34[/C][C]0.08474[/C][C]0.719[/C][C]0.237221[/C][/ROW]
[ROW][C]35[/C][C]-0.056205[/C][C]-0.4769[/C][C]0.317434[/C][/ROW]
[ROW][C]36[/C][C]-0.04123[/C][C]-0.3499[/C][C]0.363736[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63211&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63211&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
1-0.374032-3.17380.001107
2-0.462105-3.92111e-04
30.0939580.79730.213962
4-0.112463-0.95430.171566
5-0.012981-0.11010.456299
60.20661.75310.041925
7-0.130861-1.11040.135262
8-0.046325-0.39310.34771
90.0385240.32690.372349
10-0.195511-1.6590.050737
11-0.357962-3.03740.001661
120.2179221.84910.034272
130.1461871.24040.109421
140.031010.26310.396601
15-0.217336-1.84420.034637
160.004570.03880.484588
17-0.086469-0.73370.232754
18-0.231377-1.96330.026737
190.1391931.18110.120727
200.1033350.87680.191748
21-0.033736-0.28630.387751
22-0.094765-0.80410.211992
23-0.007813-0.06630.473663
24-0.106965-0.90760.183551
250.0509330.43220.333452
260.0274210.23270.408337
270.0253490.21510.415152
28-0.043707-0.37090.355913
29-0.005256-0.04460.482277
30-0.078114-0.66280.254783
310.0671010.56940.285438
320.0692690.58780.279263
330.012360.10490.458382
340.084740.7190.237221
35-0.056205-0.47690.317434
36-0.04123-0.34990.363736


Figures (Output of Computation)

Input Parameters & R Code

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