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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 computationSun, 13 Dec 2009 05:15:54 -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/13/t12607066727443py20xtludgw.htm/, Retrieved Sun, 28 Apr 2024 16:42:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67236, Retrieved Sun, 28 Apr 2024 16:42:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116

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 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [workshop 8] [2009-11-27 08:36:27] [f1a50df816abcbb519e7637ff6b72fa0]
-   PD            [(Partial) Autocorrelation Function] [paper - ACF link 1] [2009-12-13 12:15:54] [a18540c86166a2b66550d1fef0503cc2] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1213,8
1245,6
1306,3
1255,8
1257,6
1287,8
1300,4
1320,9
1370,8
1327,3
1320
1345,3
1346,7
1395,4
1462
1491,6
1461,8
1477,9
1490,3
1521,1
1561,9
1552,6
1523,6
1548,3
1552,4
1587
1621,3
1648,7
1641,8
1650,6
1688,6
1670,7
1682,2
1678,9
1650,6
1662,4
1664,5
1683,2
1736,2
1747,6
1749
1759,7
1793,6
1817,4
1858,4
1839,9
1809,1
1877,7
1880,3
1930,9
2039,3
1992,7
1987,8
1984,4
2016,5
2016,7
2064,1
2031,5
2000,3
2057,8
2041,2
2093,2
2158,3
2128,8
2131,9
2170,3
2190,8
2217,7
2254,4
2223,3
2210,5
2250,8
2249,1
2288,6
2329,2
2313,8
2309,8
2345,9
2361,3
2372
2410,4
2398,5
2362,3
2419,1
2421,6
2465
2480,5
2506,1
2506,6
2525,8
2550
2578,3
2807,8
2815,3
2767,7
2815,4
2838,8
2864
2948,6
2922,8
2917,2
2936,8
2993,4
3007,8
3046,3
3011,5
2958,6
3019,8
2998,5
3040,4
3166
3110
3099,2
3150,3
3163,6
3182,6
3244,4
3223,2
3143,6
3217
3182,3
3217,2
3262,5
3227,9
3171,6
3219
3195,4
3221,6
3262,1
3179,5
3133,6
3219,2
3245
3265,3
3312,5
3383,6
3386,3
3411,1
3467,2
3487,7
3575,5
3571,5
3582,3
3637,1
3685

Tables (Output of Computation)





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=67236&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=67236&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67236&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.97690711.76350
20.95500911.49980
30.9353211.26270
40.91386411.00440
50.8925310.74750
60.87282210.51020
70.85163710.25510
80.83143310.01180
90.8129079.78870
100.7927119.54550
110.7738959.31890
120.7562699.10670
130.7368088.87230
140.7185138.6520
150.7033198.46910
160.686818.27030
170.6687758.05310
180.6513667.84350
190.6328177.62010
200.6140547.39420
210.5973017.19250
220.5784486.96540
230.5585346.72560
240.5395466.4970
250.5194736.25530
260.4989396.0080
270.4806075.78730
280.4604515.54460
290.4399615.29780
300.4203525.06171e-06
310.4001664.81862e-06
320.3796164.57125e-06
330.3606584.34291.3e-05
340.3406094.10153.4e-05
350.319163.84329.1e-05
360.2999773.61220.000209

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.976907 & 11.7635 & 0 \tabularnewline
2 & 0.955009 & 11.4998 & 0 \tabularnewline
3 & 0.93532 & 11.2627 & 0 \tabularnewline
4 & 0.913864 & 11.0044 & 0 \tabularnewline
5 & 0.89253 & 10.7475 & 0 \tabularnewline
6 & 0.872822 & 10.5102 & 0 \tabularnewline
7 & 0.851637 & 10.2551 & 0 \tabularnewline
8 & 0.831433 & 10.0118 & 0 \tabularnewline
9 & 0.812907 & 9.7887 & 0 \tabularnewline
10 & 0.792711 & 9.5455 & 0 \tabularnewline
11 & 0.773895 & 9.3189 & 0 \tabularnewline
12 & 0.756269 & 9.1067 & 0 \tabularnewline
13 & 0.736808 & 8.8723 & 0 \tabularnewline
14 & 0.718513 & 8.652 & 0 \tabularnewline
15 & 0.703319 & 8.4691 & 0 \tabularnewline
16 & 0.68681 & 8.2703 & 0 \tabularnewline
17 & 0.668775 & 8.0531 & 0 \tabularnewline
18 & 0.651366 & 7.8435 & 0 \tabularnewline
19 & 0.632817 & 7.6201 & 0 \tabularnewline
20 & 0.614054 & 7.3942 & 0 \tabularnewline
21 & 0.597301 & 7.1925 & 0 \tabularnewline
22 & 0.578448 & 6.9654 & 0 \tabularnewline
23 & 0.558534 & 6.7256 & 0 \tabularnewline
24 & 0.539546 & 6.497 & 0 \tabularnewline
25 & 0.519473 & 6.2553 & 0 \tabularnewline
26 & 0.498939 & 6.008 & 0 \tabularnewline
27 & 0.480607 & 5.7873 & 0 \tabularnewline
28 & 0.460451 & 5.5446 & 0 \tabularnewline
29 & 0.439961 & 5.2978 & 0 \tabularnewline
30 & 0.420352 & 5.0617 & 1e-06 \tabularnewline
31 & 0.400166 & 4.8186 & 2e-06 \tabularnewline
32 & 0.379616 & 4.5712 & 5e-06 \tabularnewline
33 & 0.360658 & 4.3429 & 1.3e-05 \tabularnewline
34 & 0.340609 & 4.1015 & 3.4e-05 \tabularnewline
35 & 0.31916 & 3.8432 & 9.1e-05 \tabularnewline
36 & 0.299977 & 3.6122 & 0.000209 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67236&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]0.976907[/C][C]11.7635[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.955009[/C][C]11.4998[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.93532[/C][C]11.2627[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.913864[/C][C]11.0044[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.89253[/C][C]10.7475[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.872822[/C][C]10.5102[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.851637[/C][C]10.2551[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.831433[/C][C]10.0118[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.812907[/C][C]9.7887[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.792711[/C][C]9.5455[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.773895[/C][C]9.3189[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.756269[/C][C]9.1067[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.736808[/C][C]8.8723[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.718513[/C][C]8.652[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.703319[/C][C]8.4691[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.68681[/C][C]8.2703[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.668775[/C][C]8.0531[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.651366[/C][C]7.8435[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.632817[/C][C]7.6201[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.614054[/C][C]7.3942[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.597301[/C][C]7.1925[/C][C]0[/C][/ROW]
[ROW][C]22[/C][C]0.578448[/C][C]6.9654[/C][C]0[/C][/ROW]
[ROW][C]23[/C][C]0.558534[/C][C]6.7256[/C][C]0[/C][/ROW]
[ROW][C]24[/C][C]0.539546[/C][C]6.497[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.519473[/C][C]6.2553[/C][C]0[/C][/ROW]
[ROW][C]26[/C][C]0.498939[/C][C]6.008[/C][C]0[/C][/ROW]
[ROW][C]27[/C][C]0.480607[/C][C]5.7873[/C][C]0[/C][/ROW]
[ROW][C]28[/C][C]0.460451[/C][C]5.5446[/C][C]0[/C][/ROW]
[ROW][C]29[/C][C]0.439961[/C][C]5.2978[/C][C]0[/C][/ROW]
[ROW][C]30[/C][C]0.420352[/C][C]5.0617[/C][C]1e-06[/C][/ROW]
[ROW][C]31[/C][C]0.400166[/C][C]4.8186[/C][C]2e-06[/C][/ROW]
[ROW][C]32[/C][C]0.379616[/C][C]4.5712[/C][C]5e-06[/C][/ROW]
[ROW][C]33[/C][C]0.360658[/C][C]4.3429[/C][C]1.3e-05[/C][/ROW]
[ROW][C]34[/C][C]0.340609[/C][C]4.1015[/C][C]3.4e-05[/C][/ROW]
[ROW][C]35[/C][C]0.31916[/C][C]3.8432[/C][C]9.1e-05[/C][/ROW]
[ROW][C]36[/C][C]0.299977[/C][C]3.6122[/C][C]0.000209[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67236&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67236&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
10.97690711.76350
20.95500911.49980
30.9353211.26270
40.91386411.00440
50.8925310.74750
60.87282210.51020
70.85163710.25510
80.83143310.01180
90.8129079.78870
100.7927119.54550
110.7738959.31890
120.7562699.10670
130.7368088.87230
140.7185138.6520
150.7033198.46910
160.686818.27030
170.6687758.05310
180.6513667.84350
190.6328177.62010
200.6140547.39420
210.5973017.19250
220.5784486.96540
230.5585346.72560
240.5395466.4970
250.5194736.25530
260.4989396.0080
270.4806075.78730
280.4604515.54460
290.4399615.29780
300.4203525.06171e-06
310.4001664.81862e-06
320.3796164.57125e-06
330.3606584.34291.3e-05
340.3406094.10153.4e-05
350.319163.84329.1e-05
360.2999773.61220.000209






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.97690711.76350
20.0144770.17430.430928
30.0378740.45610.324511
4-0.046471-0.55960.288312
5-0.008098-0.09750.461225
60.021070.25370.400038
7-0.039735-0.47850.316515
80.0116540.14030.444295
90.021730.26170.396978
10-0.041103-0.49490.310693
110.0203030.24450.4036
120.0096430.11610.453862
13-0.042193-0.50810.306087
140.0140810.16960.432797
150.0506030.60930.271625
16-0.025762-0.31020.378419
17-0.041071-0.49460.310828
18-0.008729-0.10510.458214
19-0.029503-0.35530.361455
20-0.013591-0.16370.435115
210.0241660.2910.385734
22-0.047779-0.57530.282976
23-0.031561-0.380.352234
24-0.006858-0.08260.467147
25-0.029092-0.35030.363304
26-0.01817-0.21880.413558
270.0205340.24730.402528
28-0.044178-0.5320.297779
29-0.012153-0.14630.441927
30-0.01266-0.15240.439524
31-0.02271-0.27350.392441
32-0.017484-0.21050.416773
330.0062470.07520.470069
34-0.029574-0.35610.361133
35-0.037682-0.45370.325344
360.015830.19060.424544

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.976907 & 11.7635 & 0 \tabularnewline
2 & 0.014477 & 0.1743 & 0.430928 \tabularnewline
3 & 0.037874 & 0.4561 & 0.324511 \tabularnewline
4 & -0.046471 & -0.5596 & 0.288312 \tabularnewline
5 & -0.008098 & -0.0975 & 0.461225 \tabularnewline
6 & 0.02107 & 0.2537 & 0.400038 \tabularnewline
7 & -0.039735 & -0.4785 & 0.316515 \tabularnewline
8 & 0.011654 & 0.1403 & 0.444295 \tabularnewline
9 & 0.02173 & 0.2617 & 0.396978 \tabularnewline
10 & -0.041103 & -0.4949 & 0.310693 \tabularnewline
11 & 0.020303 & 0.2445 & 0.4036 \tabularnewline
12 & 0.009643 & 0.1161 & 0.453862 \tabularnewline
13 & -0.042193 & -0.5081 & 0.306087 \tabularnewline
14 & 0.014081 & 0.1696 & 0.432797 \tabularnewline
15 & 0.050603 & 0.6093 & 0.271625 \tabularnewline
16 & -0.025762 & -0.3102 & 0.378419 \tabularnewline
17 & -0.041071 & -0.4946 & 0.310828 \tabularnewline
18 & -0.008729 & -0.1051 & 0.458214 \tabularnewline
19 & -0.029503 & -0.3553 & 0.361455 \tabularnewline
20 & -0.013591 & -0.1637 & 0.435115 \tabularnewline
21 & 0.024166 & 0.291 & 0.385734 \tabularnewline
22 & -0.047779 & -0.5753 & 0.282976 \tabularnewline
23 & -0.031561 & -0.38 & 0.352234 \tabularnewline
24 & -0.006858 & -0.0826 & 0.467147 \tabularnewline
25 & -0.029092 & -0.3503 & 0.363304 \tabularnewline
26 & -0.01817 & -0.2188 & 0.413558 \tabularnewline
27 & 0.020534 & 0.2473 & 0.402528 \tabularnewline
28 & -0.044178 & -0.532 & 0.297779 \tabularnewline
29 & -0.012153 & -0.1463 & 0.441927 \tabularnewline
30 & -0.01266 & -0.1524 & 0.439524 \tabularnewline
31 & -0.02271 & -0.2735 & 0.392441 \tabularnewline
32 & -0.017484 & -0.2105 & 0.416773 \tabularnewline
33 & 0.006247 & 0.0752 & 0.470069 \tabularnewline
34 & -0.029574 & -0.3561 & 0.361133 \tabularnewline
35 & -0.037682 & -0.4537 & 0.325344 \tabularnewline
36 & 0.01583 & 0.1906 & 0.424544 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67236&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]0.976907[/C][C]11.7635[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.014477[/C][C]0.1743[/C][C]0.430928[/C][/ROW]
[ROW][C]3[/C][C]0.037874[/C][C]0.4561[/C][C]0.324511[/C][/ROW]
[ROW][C]4[/C][C]-0.046471[/C][C]-0.5596[/C][C]0.288312[/C][/ROW]
[ROW][C]5[/C][C]-0.008098[/C][C]-0.0975[/C][C]0.461225[/C][/ROW]
[ROW][C]6[/C][C]0.02107[/C][C]0.2537[/C][C]0.400038[/C][/ROW]
[ROW][C]7[/C][C]-0.039735[/C][C]-0.4785[/C][C]0.316515[/C][/ROW]
[ROW][C]8[/C][C]0.011654[/C][C]0.1403[/C][C]0.444295[/C][/ROW]
[ROW][C]9[/C][C]0.02173[/C][C]0.2617[/C][C]0.396978[/C][/ROW]
[ROW][C]10[/C][C]-0.041103[/C][C]-0.4949[/C][C]0.310693[/C][/ROW]
[ROW][C]11[/C][C]0.020303[/C][C]0.2445[/C][C]0.4036[/C][/ROW]
[ROW][C]12[/C][C]0.009643[/C][C]0.1161[/C][C]0.453862[/C][/ROW]
[ROW][C]13[/C][C]-0.042193[/C][C]-0.5081[/C][C]0.306087[/C][/ROW]
[ROW][C]14[/C][C]0.014081[/C][C]0.1696[/C][C]0.432797[/C][/ROW]
[ROW][C]15[/C][C]0.050603[/C][C]0.6093[/C][C]0.271625[/C][/ROW]
[ROW][C]16[/C][C]-0.025762[/C][C]-0.3102[/C][C]0.378419[/C][/ROW]
[ROW][C]17[/C][C]-0.041071[/C][C]-0.4946[/C][C]0.310828[/C][/ROW]
[ROW][C]18[/C][C]-0.008729[/C][C]-0.1051[/C][C]0.458214[/C][/ROW]
[ROW][C]19[/C][C]-0.029503[/C][C]-0.3553[/C][C]0.361455[/C][/ROW]
[ROW][C]20[/C][C]-0.013591[/C][C]-0.1637[/C][C]0.435115[/C][/ROW]
[ROW][C]21[/C][C]0.024166[/C][C]0.291[/C][C]0.385734[/C][/ROW]
[ROW][C]22[/C][C]-0.047779[/C][C]-0.5753[/C][C]0.282976[/C][/ROW]
[ROW][C]23[/C][C]-0.031561[/C][C]-0.38[/C][C]0.352234[/C][/ROW]
[ROW][C]24[/C][C]-0.006858[/C][C]-0.0826[/C][C]0.467147[/C][/ROW]
[ROW][C]25[/C][C]-0.029092[/C][C]-0.3503[/C][C]0.363304[/C][/ROW]
[ROW][C]26[/C][C]-0.01817[/C][C]-0.2188[/C][C]0.413558[/C][/ROW]
[ROW][C]27[/C][C]0.020534[/C][C]0.2473[/C][C]0.402528[/C][/ROW]
[ROW][C]28[/C][C]-0.044178[/C][C]-0.532[/C][C]0.297779[/C][/ROW]
[ROW][C]29[/C][C]-0.012153[/C][C]-0.1463[/C][C]0.441927[/C][/ROW]
[ROW][C]30[/C][C]-0.01266[/C][C]-0.1524[/C][C]0.439524[/C][/ROW]
[ROW][C]31[/C][C]-0.02271[/C][C]-0.2735[/C][C]0.392441[/C][/ROW]
[ROW][C]32[/C][C]-0.017484[/C][C]-0.2105[/C][C]0.416773[/C][/ROW]
[ROW][C]33[/C][C]0.006247[/C][C]0.0752[/C][C]0.470069[/C][/ROW]
[ROW][C]34[/C][C]-0.029574[/C][C]-0.3561[/C][C]0.361133[/C][/ROW]
[ROW][C]35[/C][C]-0.037682[/C][C]-0.4537[/C][C]0.325344[/C][/ROW]
[ROW][C]36[/C][C]0.01583[/C][C]0.1906[/C][C]0.424544[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67236&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67236&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
10.97690711.76350
20.0144770.17430.430928
30.0378740.45610.324511
4-0.046471-0.55960.288312
5-0.008098-0.09750.461225
60.021070.25370.400038
7-0.039735-0.47850.316515
80.0116540.14030.444295
90.021730.26170.396978
10-0.041103-0.49490.310693
110.0203030.24450.4036
120.0096430.11610.453862
13-0.042193-0.50810.306087
140.0140810.16960.432797
150.0506030.60930.271625
16-0.025762-0.31020.378419
17-0.041071-0.49460.310828
18-0.008729-0.10510.458214
19-0.029503-0.35530.361455
20-0.013591-0.16370.435115
210.0241660.2910.385734
22-0.047779-0.57530.282976
23-0.031561-0.380.352234
24-0.006858-0.08260.467147
25-0.029092-0.35030.363304
26-0.01817-0.21880.413558
270.0205340.24730.402528
28-0.044178-0.5320.297779
29-0.012153-0.14630.441927
30-0.01266-0.15240.439524
31-0.02271-0.27350.392441
32-0.017484-0.21050.416773
330.0062470.07520.470069
34-0.029574-0.35610.361133
35-0.037682-0.45370.325344
360.015830.19060.424544


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Include Monthly Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; 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')