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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 05:14:14 -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/t1259842544d1vvbw9kz6vz169.htm/, Retrieved Thu, 28 Mar 2024 19:26:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62691, Retrieved Thu, 28 Mar 2024 19:26:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact113
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2009-12-03 12:14:14] [4f23cd6f600e6b4b5336072a0ca6bd10] [Current]
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Dataseries X:
8.7
8.2
8.3
8.5
8.6
8.5
8.2
8.1
7.9
8.6
8.7
8.7
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8
8.2
8.1
8.1
8
7.9
7.9
8
8
7.9
8
7.7
7.2
7.5
7.3
7
7
7
7.2
7.3
7.1
6.8
6.4
6.1
6.5
7.7
7.9
7.5
6.9
6.6
6.9
7.7
8
8
7.7
7.3
7.4
8.1
8.3
8.2




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=62691&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=62691&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62691&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
10.3082792.36790.010592
2-0.310073-2.38170.010238
3-0.535139-4.11056.2e-05
4-0.355399-2.72990.00417
50.1480531.13720.130022
60.5364914.12096e-05
70.3598342.76390.003804
8-0.08957-0.6880.247074
9-0.291132-2.23620.014566
10-0.322509-2.47720.008062
11-0.004224-0.03240.487113
120.3715132.85360.002976
130.0770110.59150.278213
14-0.074246-0.57030.285321
15-0.066451-0.51040.305831
16-0.086475-0.66420.254567
17-0.004844-0.03720.485224
180.0963870.74040.231008
190.0127260.09780.461231
20-0.08391-0.64450.260867
21-0.045409-0.34880.364242
22-0.068264-0.52430.301
230.0484980.37250.355421
240.1686411.29540.100121
25-0.11789-0.90550.184434
26-0.153307-1.17760.121847
27-0.058179-0.44690.328298
28-0.01047-0.08040.468088
290.0776490.59640.276584
300.1487241.14240.128957
310.0130260.10010.46032
32-0.174434-1.33990.092716
33-0.147424-1.13240.131027
34-0.012546-0.09640.461777
350.1534221.17850.121674
360.2476151.9020.03103

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.308279 & 2.3679 & 0.010592 \tabularnewline
2 & -0.310073 & -2.3817 & 0.010238 \tabularnewline
3 & -0.535139 & -4.1105 & 6.2e-05 \tabularnewline
4 & -0.355399 & -2.7299 & 0.00417 \tabularnewline
5 & 0.148053 & 1.1372 & 0.130022 \tabularnewline
6 & 0.536491 & 4.1209 & 6e-05 \tabularnewline
7 & 0.359834 & 2.7639 & 0.003804 \tabularnewline
8 & -0.08957 & -0.688 & 0.247074 \tabularnewline
9 & -0.291132 & -2.2362 & 0.014566 \tabularnewline
10 & -0.322509 & -2.4772 & 0.008062 \tabularnewline
11 & -0.004224 & -0.0324 & 0.487113 \tabularnewline
12 & 0.371513 & 2.8536 & 0.002976 \tabularnewline
13 & 0.077011 & 0.5915 & 0.278213 \tabularnewline
14 & -0.074246 & -0.5703 & 0.285321 \tabularnewline
15 & -0.066451 & -0.5104 & 0.305831 \tabularnewline
16 & -0.086475 & -0.6642 & 0.254567 \tabularnewline
17 & -0.004844 & -0.0372 & 0.485224 \tabularnewline
18 & 0.096387 & 0.7404 & 0.231008 \tabularnewline
19 & 0.012726 & 0.0978 & 0.461231 \tabularnewline
20 & -0.08391 & -0.6445 & 0.260867 \tabularnewline
21 & -0.045409 & -0.3488 & 0.364242 \tabularnewline
22 & -0.068264 & -0.5243 & 0.301 \tabularnewline
23 & 0.048498 & 0.3725 & 0.355421 \tabularnewline
24 & 0.168641 & 1.2954 & 0.100121 \tabularnewline
25 & -0.11789 & -0.9055 & 0.184434 \tabularnewline
26 & -0.153307 & -1.1776 & 0.121847 \tabularnewline
27 & -0.058179 & -0.4469 & 0.328298 \tabularnewline
28 & -0.01047 & -0.0804 & 0.468088 \tabularnewline
29 & 0.077649 & 0.5964 & 0.276584 \tabularnewline
30 & 0.148724 & 1.1424 & 0.128957 \tabularnewline
31 & 0.013026 & 0.1001 & 0.46032 \tabularnewline
32 & -0.174434 & -1.3399 & 0.092716 \tabularnewline
33 & -0.147424 & -1.1324 & 0.131027 \tabularnewline
34 & -0.012546 & -0.0964 & 0.461777 \tabularnewline
35 & 0.153422 & 1.1785 & 0.121674 \tabularnewline
36 & 0.247615 & 1.902 & 0.03103 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62691&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]0.308279[/C][C]2.3679[/C][C]0.010592[/C][/ROW]
[ROW][C]2[/C][C]-0.310073[/C][C]-2.3817[/C][C]0.010238[/C][/ROW]
[ROW][C]3[/C][C]-0.535139[/C][C]-4.1105[/C][C]6.2e-05[/C][/ROW]
[ROW][C]4[/C][C]-0.355399[/C][C]-2.7299[/C][C]0.00417[/C][/ROW]
[ROW][C]5[/C][C]0.148053[/C][C]1.1372[/C][C]0.130022[/C][/ROW]
[ROW][C]6[/C][C]0.536491[/C][C]4.1209[/C][C]6e-05[/C][/ROW]
[ROW][C]7[/C][C]0.359834[/C][C]2.7639[/C][C]0.003804[/C][/ROW]
[ROW][C]8[/C][C]-0.08957[/C][C]-0.688[/C][C]0.247074[/C][/ROW]
[ROW][C]9[/C][C]-0.291132[/C][C]-2.2362[/C][C]0.014566[/C][/ROW]
[ROW][C]10[/C][C]-0.322509[/C][C]-2.4772[/C][C]0.008062[/C][/ROW]
[ROW][C]11[/C][C]-0.004224[/C][C]-0.0324[/C][C]0.487113[/C][/ROW]
[ROW][C]12[/C][C]0.371513[/C][C]2.8536[/C][C]0.002976[/C][/ROW]
[ROW][C]13[/C][C]0.077011[/C][C]0.5915[/C][C]0.278213[/C][/ROW]
[ROW][C]14[/C][C]-0.074246[/C][C]-0.5703[/C][C]0.285321[/C][/ROW]
[ROW][C]15[/C][C]-0.066451[/C][C]-0.5104[/C][C]0.305831[/C][/ROW]
[ROW][C]16[/C][C]-0.086475[/C][C]-0.6642[/C][C]0.254567[/C][/ROW]
[ROW][C]17[/C][C]-0.004844[/C][C]-0.0372[/C][C]0.485224[/C][/ROW]
[ROW][C]18[/C][C]0.096387[/C][C]0.7404[/C][C]0.231008[/C][/ROW]
[ROW][C]19[/C][C]0.012726[/C][C]0.0978[/C][C]0.461231[/C][/ROW]
[ROW][C]20[/C][C]-0.08391[/C][C]-0.6445[/C][C]0.260867[/C][/ROW]
[ROW][C]21[/C][C]-0.045409[/C][C]-0.3488[/C][C]0.364242[/C][/ROW]
[ROW][C]22[/C][C]-0.068264[/C][C]-0.5243[/C][C]0.301[/C][/ROW]
[ROW][C]23[/C][C]0.048498[/C][C]0.3725[/C][C]0.355421[/C][/ROW]
[ROW][C]24[/C][C]0.168641[/C][C]1.2954[/C][C]0.100121[/C][/ROW]
[ROW][C]25[/C][C]-0.11789[/C][C]-0.9055[/C][C]0.184434[/C][/ROW]
[ROW][C]26[/C][C]-0.153307[/C][C]-1.1776[/C][C]0.121847[/C][/ROW]
[ROW][C]27[/C][C]-0.058179[/C][C]-0.4469[/C][C]0.328298[/C][/ROW]
[ROW][C]28[/C][C]-0.01047[/C][C]-0.0804[/C][C]0.468088[/C][/ROW]
[ROW][C]29[/C][C]0.077649[/C][C]0.5964[/C][C]0.276584[/C][/ROW]
[ROW][C]30[/C][C]0.148724[/C][C]1.1424[/C][C]0.128957[/C][/ROW]
[ROW][C]31[/C][C]0.013026[/C][C]0.1001[/C][C]0.46032[/C][/ROW]
[ROW][C]32[/C][C]-0.174434[/C][C]-1.3399[/C][C]0.092716[/C][/ROW]
[ROW][C]33[/C][C]-0.147424[/C][C]-1.1324[/C][C]0.131027[/C][/ROW]
[ROW][C]34[/C][C]-0.012546[/C][C]-0.0964[/C][C]0.461777[/C][/ROW]
[ROW][C]35[/C][C]0.153422[/C][C]1.1785[/C][C]0.121674[/C][/ROW]
[ROW][C]36[/C][C]0.247615[/C][C]1.902[/C][C]0.03103[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62691&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62691&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
10.3082792.36790.010592
2-0.310073-2.38170.010238
3-0.535139-4.11056.2e-05
4-0.355399-2.72990.00417
50.1480531.13720.130022
60.5364914.12096e-05
70.3598342.76390.003804
8-0.08957-0.6880.247074
9-0.291132-2.23620.014566
10-0.322509-2.47720.008062
11-0.004224-0.03240.487113
120.3715132.85360.002976
130.0770110.59150.278213
14-0.074246-0.57030.285321
15-0.066451-0.51040.305831
16-0.086475-0.66420.254567
17-0.004844-0.03720.485224
180.0963870.74040.231008
190.0127260.09780.461231
20-0.08391-0.64450.260867
21-0.045409-0.34880.364242
22-0.068264-0.52430.301
230.0484980.37250.355421
240.1686411.29540.100121
25-0.11789-0.90550.184434
26-0.153307-1.17760.121847
27-0.058179-0.44690.328298
28-0.01047-0.08040.468088
290.0776490.59640.276584
300.1487241.14240.128957
310.0130260.10010.46032
32-0.174434-1.33990.092716
33-0.147424-1.13240.131027
34-0.012546-0.09640.461777
350.1534221.17850.121674
360.2476151.9020.03103







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3082792.36790.010592
2-0.447652-3.43850.00054
3-0.357589-2.74670.003985
4-0.28732-2.20690.015611
50.0310920.23880.406036
60.2379321.82760.036335
70.0803740.61740.269686
80.0289880.22270.412284
90.1857171.42650.079494
10-0.042248-0.32450.373349
110.085780.65890.256266
120.1808061.38880.085057
13-0.430427-3.30620.000807
140.0506040.38870.349451
150.1062680.81630.208816
16-0.084759-0.6510.258773
17-0.01397-0.10730.457455
18-0.041499-0.31880.375516
190.0379810.29170.385755
200.0263570.20250.42013
21-0.148183-1.13820.129815
22-0.076852-0.59030.278618
239.6e-057e-040.499707
240.0310040.23810.406298
25-0.162782-1.25030.108054
26-0.082212-0.63150.265083
27-0.064939-0.49880.309884
28-0.000792-0.00610.497582
290.0013220.01020.495967
300.0093570.07190.471473
310.0370790.28480.388394
32-0.076336-0.58630.279939
33-0.014982-0.11510.454386
340.1933181.48490.071447
35-0.052914-0.40640.342944
360.0764510.58720.279645

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.308279 & 2.3679 & 0.010592 \tabularnewline
2 & -0.447652 & -3.4385 & 0.00054 \tabularnewline
3 & -0.357589 & -2.7467 & 0.003985 \tabularnewline
4 & -0.28732 & -2.2069 & 0.015611 \tabularnewline
5 & 0.031092 & 0.2388 & 0.406036 \tabularnewline
6 & 0.237932 & 1.8276 & 0.036335 \tabularnewline
7 & 0.080374 & 0.6174 & 0.269686 \tabularnewline
8 & 0.028988 & 0.2227 & 0.412284 \tabularnewline
9 & 0.185717 & 1.4265 & 0.079494 \tabularnewline
10 & -0.042248 & -0.3245 & 0.373349 \tabularnewline
11 & 0.08578 & 0.6589 & 0.256266 \tabularnewline
12 & 0.180806 & 1.3888 & 0.085057 \tabularnewline
13 & -0.430427 & -3.3062 & 0.000807 \tabularnewline
14 & 0.050604 & 0.3887 & 0.349451 \tabularnewline
15 & 0.106268 & 0.8163 & 0.208816 \tabularnewline
16 & -0.084759 & -0.651 & 0.258773 \tabularnewline
17 & -0.01397 & -0.1073 & 0.457455 \tabularnewline
18 & -0.041499 & -0.3188 & 0.375516 \tabularnewline
19 & 0.037981 & 0.2917 & 0.385755 \tabularnewline
20 & 0.026357 & 0.2025 & 0.42013 \tabularnewline
21 & -0.148183 & -1.1382 & 0.129815 \tabularnewline
22 & -0.076852 & -0.5903 & 0.278618 \tabularnewline
23 & 9.6e-05 & 7e-04 & 0.499707 \tabularnewline
24 & 0.031004 & 0.2381 & 0.406298 \tabularnewline
25 & -0.162782 & -1.2503 & 0.108054 \tabularnewline
26 & -0.082212 & -0.6315 & 0.265083 \tabularnewline
27 & -0.064939 & -0.4988 & 0.309884 \tabularnewline
28 & -0.000792 & -0.0061 & 0.497582 \tabularnewline
29 & 0.001322 & 0.0102 & 0.495967 \tabularnewline
30 & 0.009357 & 0.0719 & 0.471473 \tabularnewline
31 & 0.037079 & 0.2848 & 0.388394 \tabularnewline
32 & -0.076336 & -0.5863 & 0.279939 \tabularnewline
33 & -0.014982 & -0.1151 & 0.454386 \tabularnewline
34 & 0.193318 & 1.4849 & 0.071447 \tabularnewline
35 & -0.052914 & -0.4064 & 0.342944 \tabularnewline
36 & 0.076451 & 0.5872 & 0.279645 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62691&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]0.308279[/C][C]2.3679[/C][C]0.010592[/C][/ROW]
[ROW][C]2[/C][C]-0.447652[/C][C]-3.4385[/C][C]0.00054[/C][/ROW]
[ROW][C]3[/C][C]-0.357589[/C][C]-2.7467[/C][C]0.003985[/C][/ROW]
[ROW][C]4[/C][C]-0.28732[/C][C]-2.2069[/C][C]0.015611[/C][/ROW]
[ROW][C]5[/C][C]0.031092[/C][C]0.2388[/C][C]0.406036[/C][/ROW]
[ROW][C]6[/C][C]0.237932[/C][C]1.8276[/C][C]0.036335[/C][/ROW]
[ROW][C]7[/C][C]0.080374[/C][C]0.6174[/C][C]0.269686[/C][/ROW]
[ROW][C]8[/C][C]0.028988[/C][C]0.2227[/C][C]0.412284[/C][/ROW]
[ROW][C]9[/C][C]0.185717[/C][C]1.4265[/C][C]0.079494[/C][/ROW]
[ROW][C]10[/C][C]-0.042248[/C][C]-0.3245[/C][C]0.373349[/C][/ROW]
[ROW][C]11[/C][C]0.08578[/C][C]0.6589[/C][C]0.256266[/C][/ROW]
[ROW][C]12[/C][C]0.180806[/C][C]1.3888[/C][C]0.085057[/C][/ROW]
[ROW][C]13[/C][C]-0.430427[/C][C]-3.3062[/C][C]0.000807[/C][/ROW]
[ROW][C]14[/C][C]0.050604[/C][C]0.3887[/C][C]0.349451[/C][/ROW]
[ROW][C]15[/C][C]0.106268[/C][C]0.8163[/C][C]0.208816[/C][/ROW]
[ROW][C]16[/C][C]-0.084759[/C][C]-0.651[/C][C]0.258773[/C][/ROW]
[ROW][C]17[/C][C]-0.01397[/C][C]-0.1073[/C][C]0.457455[/C][/ROW]
[ROW][C]18[/C][C]-0.041499[/C][C]-0.3188[/C][C]0.375516[/C][/ROW]
[ROW][C]19[/C][C]0.037981[/C][C]0.2917[/C][C]0.385755[/C][/ROW]
[ROW][C]20[/C][C]0.026357[/C][C]0.2025[/C][C]0.42013[/C][/ROW]
[ROW][C]21[/C][C]-0.148183[/C][C]-1.1382[/C][C]0.129815[/C][/ROW]
[ROW][C]22[/C][C]-0.076852[/C][C]-0.5903[/C][C]0.278618[/C][/ROW]
[ROW][C]23[/C][C]9.6e-05[/C][C]7e-04[/C][C]0.499707[/C][/ROW]
[ROW][C]24[/C][C]0.031004[/C][C]0.2381[/C][C]0.406298[/C][/ROW]
[ROW][C]25[/C][C]-0.162782[/C][C]-1.2503[/C][C]0.108054[/C][/ROW]
[ROW][C]26[/C][C]-0.082212[/C][C]-0.6315[/C][C]0.265083[/C][/ROW]
[ROW][C]27[/C][C]-0.064939[/C][C]-0.4988[/C][C]0.309884[/C][/ROW]
[ROW][C]28[/C][C]-0.000792[/C][C]-0.0061[/C][C]0.497582[/C][/ROW]
[ROW][C]29[/C][C]0.001322[/C][C]0.0102[/C][C]0.495967[/C][/ROW]
[ROW][C]30[/C][C]0.009357[/C][C]0.0719[/C][C]0.471473[/C][/ROW]
[ROW][C]31[/C][C]0.037079[/C][C]0.2848[/C][C]0.388394[/C][/ROW]
[ROW][C]32[/C][C]-0.076336[/C][C]-0.5863[/C][C]0.279939[/C][/ROW]
[ROW][C]33[/C][C]-0.014982[/C][C]-0.1151[/C][C]0.454386[/C][/ROW]
[ROW][C]34[/C][C]0.193318[/C][C]1.4849[/C][C]0.071447[/C][/ROW]
[ROW][C]35[/C][C]-0.052914[/C][C]-0.4064[/C][C]0.342944[/C][/ROW]
[ROW][C]36[/C][C]0.076451[/C][C]0.5872[/C][C]0.279645[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62691&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62691&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
10.3082792.36790.010592
2-0.447652-3.43850.00054
3-0.357589-2.74670.003985
4-0.28732-2.20690.015611
50.0310920.23880.406036
60.2379321.82760.036335
70.0803740.61740.269686
80.0289880.22270.412284
90.1857171.42650.079494
10-0.042248-0.32450.373349
110.085780.65890.256266
120.1808061.38880.085057
13-0.430427-3.30620.000807
140.0506040.38870.349451
150.1062680.81630.208816
16-0.084759-0.6510.258773
17-0.01397-0.10730.457455
18-0.041499-0.31880.375516
190.0379810.29170.385755
200.0263570.20250.42013
21-0.148183-1.13820.129815
22-0.076852-0.59030.278618
239.6e-057e-040.499707
240.0310040.23810.406298
25-0.162782-1.25030.108054
26-0.082212-0.63150.265083
27-0.064939-0.49880.309884
28-0.000792-0.00610.497582
290.0013220.01020.495967
300.0093570.07190.471473
310.0370790.28480.388394
32-0.076336-0.58630.279939
33-0.014982-0.11510.454386
340.1933181.48490.071447
35-0.052914-0.40640.342944
360.0764510.58720.279645



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 6 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 6 ; 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')