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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, 27 Nov 2009 08:55:59 -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/t12593374264dugmoo3dw0kzs6.htm/, Retrieved Mon, 29 Apr 2024 03:34:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60921, Retrieved Mon, 29 Apr 2024 03:34:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact136

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]
- R  D          [(Partial) Autocorrelation Function] [ACF d=0,D=0] [2009-11-27 15:55:59] [18c0746232b29e9668aa6bedcb8dd698] [Current]
-   PD            [(Partial) Autocorrelation Function] [d=1,D=0] [2009-12-19 16:12:58] [fa71ec4c741ffec745cb91dcbd756720]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12,6
15,7
13,2
20,3
12,8
8
0,9
3,6
14,1
21,7
24,5
18,9
13,9
11
5,8
15,5
22,4
31,7
30,3
31,4
20,2
19,7
10,8
13,2
15,1
15,6
15,5
12,7
10,9
10
9,1
10,3
16,9
22
27,6
28,9
31
32,9
38,1
28,8
29
21,8
28,8
25,6
28,2
20,2
17,9
16,3
13,2
8,1
4,5
-0,1
0
2,3
2,8
2,9
0,1
3,5
8,6
13,8

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=60921&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=60921&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60921&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
10.8637936.69090
20.6820495.28311e-06
30.4298363.32950.000746
40.3003332.32640.011697
50.212571.64660.052438
60.1832611.41950.08046
70.1184830.91780.181207
80.0286910.22220.412441
9-0.115036-0.89110.188227
10-0.272688-2.11220.019419
11-0.412092-3.19210.001125
12-0.483303-3.74370.000204
13-0.48033-3.72060.00022
14-0.408538-3.16450.00122
15-0.317849-2.4620.008352
16-0.230294-1.78390.039753
17-0.174139-1.34890.091223
18-0.13225-1.02440.154878
19-0.085663-0.66350.254763
20-0.037086-0.28730.387449
210.0280740.21750.414293
220.0664650.51480.30428
230.1234540.95630.171386
240.1446251.12030.133533
250.1766651.36840.088138
260.1531831.18660.12004
270.1183910.91710.181393
280.0469070.36330.358814
29-0.021435-0.1660.434344
30-0.105568-0.81770.208374
31-0.165812-1.28440.101974
32-0.201615-1.56170.061809
33-0.200354-1.55190.062968
34-0.185375-1.43590.078111
35-0.176862-1.370.087901
36-0.189636-1.46890.073539

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.863793 & 6.6909 & 0 \tabularnewline
2 & 0.682049 & 5.2831 & 1e-06 \tabularnewline
3 & 0.429836 & 3.3295 & 0.000746 \tabularnewline
4 & 0.300333 & 2.3264 & 0.011697 \tabularnewline
5 & 0.21257 & 1.6466 & 0.052438 \tabularnewline
6 & 0.183261 & 1.4195 & 0.08046 \tabularnewline
7 & 0.118483 & 0.9178 & 0.181207 \tabularnewline
8 & 0.028691 & 0.2222 & 0.412441 \tabularnewline
9 & -0.115036 & -0.8911 & 0.188227 \tabularnewline
10 & -0.272688 & -2.1122 & 0.019419 \tabularnewline
11 & -0.412092 & -3.1921 & 0.001125 \tabularnewline
12 & -0.483303 & -3.7437 & 0.000204 \tabularnewline
13 & -0.48033 & -3.7206 & 0.00022 \tabularnewline
14 & -0.408538 & -3.1645 & 0.00122 \tabularnewline
15 & -0.317849 & -2.462 & 0.008352 \tabularnewline
16 & -0.230294 & -1.7839 & 0.039753 \tabularnewline
17 & -0.174139 & -1.3489 & 0.091223 \tabularnewline
18 & -0.13225 & -1.0244 & 0.154878 \tabularnewline
19 & -0.085663 & -0.6635 & 0.254763 \tabularnewline
20 & -0.037086 & -0.2873 & 0.387449 \tabularnewline
21 & 0.028074 & 0.2175 & 0.414293 \tabularnewline
22 & 0.066465 & 0.5148 & 0.30428 \tabularnewline
23 & 0.123454 & 0.9563 & 0.171386 \tabularnewline
24 & 0.144625 & 1.1203 & 0.133533 \tabularnewline
25 & 0.176665 & 1.3684 & 0.088138 \tabularnewline
26 & 0.153183 & 1.1866 & 0.12004 \tabularnewline
27 & 0.118391 & 0.9171 & 0.181393 \tabularnewline
28 & 0.046907 & 0.3633 & 0.358814 \tabularnewline
29 & -0.021435 & -0.166 & 0.434344 \tabularnewline
30 & -0.105568 & -0.8177 & 0.208374 \tabularnewline
31 & -0.165812 & -1.2844 & 0.101974 \tabularnewline
32 & -0.201615 & -1.5617 & 0.061809 \tabularnewline
33 & -0.200354 & -1.5519 & 0.062968 \tabularnewline
34 & -0.185375 & -1.4359 & 0.078111 \tabularnewline
35 & -0.176862 & -1.37 & 0.087901 \tabularnewline
36 & -0.189636 & -1.4689 & 0.073539 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60921&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]0.863793[/C][C]6.6909[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.682049[/C][C]5.2831[/C][C]1e-06[/C][/ROW]
[ROW][C]3[/C][C]0.429836[/C][C]3.3295[/C][C]0.000746[/C][/ROW]
[ROW][C]4[/C][C]0.300333[/C][C]2.3264[/C][C]0.011697[/C][/ROW]
[ROW][C]5[/C][C]0.21257[/C][C]1.6466[/C][C]0.052438[/C][/ROW]
[ROW][C]6[/C][C]0.183261[/C][C]1.4195[/C][C]0.08046[/C][/ROW]
[ROW][C]7[/C][C]0.118483[/C][C]0.9178[/C][C]0.181207[/C][/ROW]
[ROW][C]8[/C][C]0.028691[/C][C]0.2222[/C][C]0.412441[/C][/ROW]
[ROW][C]9[/C][C]-0.115036[/C][C]-0.8911[/C][C]0.188227[/C][/ROW]
[ROW][C]10[/C][C]-0.272688[/C][C]-2.1122[/C][C]0.019419[/C][/ROW]
[ROW][C]11[/C][C]-0.412092[/C][C]-3.1921[/C][C]0.001125[/C][/ROW]
[ROW][C]12[/C][C]-0.483303[/C][C]-3.7437[/C][C]0.000204[/C][/ROW]
[ROW][C]13[/C][C]-0.48033[/C][C]-3.7206[/C][C]0.00022[/C][/ROW]
[ROW][C]14[/C][C]-0.408538[/C][C]-3.1645[/C][C]0.00122[/C][/ROW]
[ROW][C]15[/C][C]-0.317849[/C][C]-2.462[/C][C]0.008352[/C][/ROW]
[ROW][C]16[/C][C]-0.230294[/C][C]-1.7839[/C][C]0.039753[/C][/ROW]
[ROW][C]17[/C][C]-0.174139[/C][C]-1.3489[/C][C]0.091223[/C][/ROW]
[ROW][C]18[/C][C]-0.13225[/C][C]-1.0244[/C][C]0.154878[/C][/ROW]
[ROW][C]19[/C][C]-0.085663[/C][C]-0.6635[/C][C]0.254763[/C][/ROW]
[ROW][C]20[/C][C]-0.037086[/C][C]-0.2873[/C][C]0.387449[/C][/ROW]
[ROW][C]21[/C][C]0.028074[/C][C]0.2175[/C][C]0.414293[/C][/ROW]
[ROW][C]22[/C][C]0.066465[/C][C]0.5148[/C][C]0.30428[/C][/ROW]
[ROW][C]23[/C][C]0.123454[/C][C]0.9563[/C][C]0.171386[/C][/ROW]
[ROW][C]24[/C][C]0.144625[/C][C]1.1203[/C][C]0.133533[/C][/ROW]
[ROW][C]25[/C][C]0.176665[/C][C]1.3684[/C][C]0.088138[/C][/ROW]
[ROW][C]26[/C][C]0.153183[/C][C]1.1866[/C][C]0.12004[/C][/ROW]
[ROW][C]27[/C][C]0.118391[/C][C]0.9171[/C][C]0.181393[/C][/ROW]
[ROW][C]28[/C][C]0.046907[/C][C]0.3633[/C][C]0.358814[/C][/ROW]
[ROW][C]29[/C][C]-0.021435[/C][C]-0.166[/C][C]0.434344[/C][/ROW]
[ROW][C]30[/C][C]-0.105568[/C][C]-0.8177[/C][C]0.208374[/C][/ROW]
[ROW][C]31[/C][C]-0.165812[/C][C]-1.2844[/C][C]0.101974[/C][/ROW]
[ROW][C]32[/C][C]-0.201615[/C][C]-1.5617[/C][C]0.061809[/C][/ROW]
[ROW][C]33[/C][C]-0.200354[/C][C]-1.5519[/C][C]0.062968[/C][/ROW]
[ROW][C]34[/C][C]-0.185375[/C][C]-1.4359[/C][C]0.078111[/C][/ROW]
[ROW][C]35[/C][C]-0.176862[/C][C]-1.37[/C][C]0.087901[/C][/ROW]
[ROW][C]36[/C][C]-0.189636[/C][C]-1.4689[/C][C]0.073539[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60921&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60921&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
10.8637936.69090
20.6820495.28311e-06
30.4298363.32950.000746
40.3003332.32640.011697
50.212571.64660.052438
60.1832611.41950.08046
70.1184830.91780.181207
80.0286910.22220.412441
9-0.115036-0.89110.188227
10-0.272688-2.11220.019419
11-0.412092-3.19210.001125
12-0.483303-3.74370.000204
13-0.48033-3.72060.00022
14-0.408538-3.16450.00122
15-0.317849-2.4620.008352
16-0.230294-1.78390.039753
17-0.174139-1.34890.091223
18-0.13225-1.02440.154878
19-0.085663-0.66350.254763
20-0.037086-0.28730.387449
210.0280740.21750.414293
220.0664650.51480.30428
230.1234540.95630.171386
240.1446251.12030.133533
250.1766651.36840.088138
260.1531831.18660.12004
270.1183910.91710.181393
280.0469070.36330.358814
29-0.021435-0.1660.434344
30-0.105568-0.81770.208374
31-0.165812-1.28440.101974
32-0.201615-1.56170.061809
33-0.200354-1.55190.062968
34-0.185375-1.43590.078111
35-0.176862-1.370.087901
36-0.189636-1.46890.073539






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8637936.69090
2-0.252458-1.95550.027591
3-0.378563-2.93230.002378
40.4726563.66120.000266
5-0.032357-0.25060.401477
6-0.269341-2.08630.020605
7-0.028711-0.22240.412382
8-0.069919-0.54160.295052
9-0.267378-2.07110.021329
10-0.213916-1.6570.051372
110.0311330.24120.405128
120.0494540.38310.351512
13-0.05777-0.44750.328068
140.1033230.80030.213337
150.0918360.71140.23981
160.0094930.07350.470815
170.0080460.06230.475256
180.0409960.31760.375963
190.0854170.66160.255368
20-0.196895-1.52510.066239
21-0.049078-0.38020.352585
22-0.091953-0.71230.23953
230.096640.74860.228522
24-0.090003-0.69720.244199
25-0.04085-0.31640.376391
260.0089980.06970.472332
27-0.06421-0.49740.310375
28-0.021601-0.16730.433841
29-0.10485-0.81220.209953
30-0.147443-1.14210.128977
310.0624360.48360.315206
320.0918320.71130.239819
33-0.105297-0.81560.208971
34-0.021445-0.16610.434314
350.0633420.49060.312734
36-0.046702-0.36180.359404

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.863793 & 6.6909 & 0 \tabularnewline
2 & -0.252458 & -1.9555 & 0.027591 \tabularnewline
3 & -0.378563 & -2.9323 & 0.002378 \tabularnewline
4 & 0.472656 & 3.6612 & 0.000266 \tabularnewline
5 & -0.032357 & -0.2506 & 0.401477 \tabularnewline
6 & -0.269341 & -2.0863 & 0.020605 \tabularnewline
7 & -0.028711 & -0.2224 & 0.412382 \tabularnewline
8 & -0.069919 & -0.5416 & 0.295052 \tabularnewline
9 & -0.267378 & -2.0711 & 0.021329 \tabularnewline
10 & -0.213916 & -1.657 & 0.051372 \tabularnewline
11 & 0.031133 & 0.2412 & 0.405128 \tabularnewline
12 & 0.049454 & 0.3831 & 0.351512 \tabularnewline
13 & -0.05777 & -0.4475 & 0.328068 \tabularnewline
14 & 0.103323 & 0.8003 & 0.213337 \tabularnewline
15 & 0.091836 & 0.7114 & 0.23981 \tabularnewline
16 & 0.009493 & 0.0735 & 0.470815 \tabularnewline
17 & 0.008046 & 0.0623 & 0.475256 \tabularnewline
18 & 0.040996 & 0.3176 & 0.375963 \tabularnewline
19 & 0.085417 & 0.6616 & 0.255368 \tabularnewline
20 & -0.196895 & -1.5251 & 0.066239 \tabularnewline
21 & -0.049078 & -0.3802 & 0.352585 \tabularnewline
22 & -0.091953 & -0.7123 & 0.23953 \tabularnewline
23 & 0.09664 & 0.7486 & 0.228522 \tabularnewline
24 & -0.090003 & -0.6972 & 0.244199 \tabularnewline
25 & -0.04085 & -0.3164 & 0.376391 \tabularnewline
26 & 0.008998 & 0.0697 & 0.472332 \tabularnewline
27 & -0.06421 & -0.4974 & 0.310375 \tabularnewline
28 & -0.021601 & -0.1673 & 0.433841 \tabularnewline
29 & -0.10485 & -0.8122 & 0.209953 \tabularnewline
30 & -0.147443 & -1.1421 & 0.128977 \tabularnewline
31 & 0.062436 & 0.4836 & 0.315206 \tabularnewline
32 & 0.091832 & 0.7113 & 0.239819 \tabularnewline
33 & -0.105297 & -0.8156 & 0.208971 \tabularnewline
34 & -0.021445 & -0.1661 & 0.434314 \tabularnewline
35 & 0.063342 & 0.4906 & 0.312734 \tabularnewline
36 & -0.046702 & -0.3618 & 0.359404 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60921&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]0.863793[/C][C]6.6909[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.252458[/C][C]-1.9555[/C][C]0.027591[/C][/ROW]
[ROW][C]3[/C][C]-0.378563[/C][C]-2.9323[/C][C]0.002378[/C][/ROW]
[ROW][C]4[/C][C]0.472656[/C][C]3.6612[/C][C]0.000266[/C][/ROW]
[ROW][C]5[/C][C]-0.032357[/C][C]-0.2506[/C][C]0.401477[/C][/ROW]
[ROW][C]6[/C][C]-0.269341[/C][C]-2.0863[/C][C]0.020605[/C][/ROW]
[ROW][C]7[/C][C]-0.028711[/C][C]-0.2224[/C][C]0.412382[/C][/ROW]
[ROW][C]8[/C][C]-0.069919[/C][C]-0.5416[/C][C]0.295052[/C][/ROW]
[ROW][C]9[/C][C]-0.267378[/C][C]-2.0711[/C][C]0.021329[/C][/ROW]
[ROW][C]10[/C][C]-0.213916[/C][C]-1.657[/C][C]0.051372[/C][/ROW]
[ROW][C]11[/C][C]0.031133[/C][C]0.2412[/C][C]0.405128[/C][/ROW]
[ROW][C]12[/C][C]0.049454[/C][C]0.3831[/C][C]0.351512[/C][/ROW]
[ROW][C]13[/C][C]-0.05777[/C][C]-0.4475[/C][C]0.328068[/C][/ROW]
[ROW][C]14[/C][C]0.103323[/C][C]0.8003[/C][C]0.213337[/C][/ROW]
[ROW][C]15[/C][C]0.091836[/C][C]0.7114[/C][C]0.23981[/C][/ROW]
[ROW][C]16[/C][C]0.009493[/C][C]0.0735[/C][C]0.470815[/C][/ROW]
[ROW][C]17[/C][C]0.008046[/C][C]0.0623[/C][C]0.475256[/C][/ROW]
[ROW][C]18[/C][C]0.040996[/C][C]0.3176[/C][C]0.375963[/C][/ROW]
[ROW][C]19[/C][C]0.085417[/C][C]0.6616[/C][C]0.255368[/C][/ROW]
[ROW][C]20[/C][C]-0.196895[/C][C]-1.5251[/C][C]0.066239[/C][/ROW]
[ROW][C]21[/C][C]-0.049078[/C][C]-0.3802[/C][C]0.352585[/C][/ROW]
[ROW][C]22[/C][C]-0.091953[/C][C]-0.7123[/C][C]0.23953[/C][/ROW]
[ROW][C]23[/C][C]0.09664[/C][C]0.7486[/C][C]0.228522[/C][/ROW]
[ROW][C]24[/C][C]-0.090003[/C][C]-0.6972[/C][C]0.244199[/C][/ROW]
[ROW][C]25[/C][C]-0.04085[/C][C]-0.3164[/C][C]0.376391[/C][/ROW]
[ROW][C]26[/C][C]0.008998[/C][C]0.0697[/C][C]0.472332[/C][/ROW]
[ROW][C]27[/C][C]-0.06421[/C][C]-0.4974[/C][C]0.310375[/C][/ROW]
[ROW][C]28[/C][C]-0.021601[/C][C]-0.1673[/C][C]0.433841[/C][/ROW]
[ROW][C]29[/C][C]-0.10485[/C][C]-0.8122[/C][C]0.209953[/C][/ROW]
[ROW][C]30[/C][C]-0.147443[/C][C]-1.1421[/C][C]0.128977[/C][/ROW]
[ROW][C]31[/C][C]0.062436[/C][C]0.4836[/C][C]0.315206[/C][/ROW]
[ROW][C]32[/C][C]0.091832[/C][C]0.7113[/C][C]0.239819[/C][/ROW]
[ROW][C]33[/C][C]-0.105297[/C][C]-0.8156[/C][C]0.208971[/C][/ROW]
[ROW][C]34[/C][C]-0.021445[/C][C]-0.1661[/C][C]0.434314[/C][/ROW]
[ROW][C]35[/C][C]0.063342[/C][C]0.4906[/C][C]0.312734[/C][/ROW]
[ROW][C]36[/C][C]-0.046702[/C][C]-0.3618[/C][C]0.359404[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60921&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60921&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
10.8637936.69090
2-0.252458-1.95550.027591
3-0.378563-2.93230.002378
40.4726563.66120.000266
5-0.032357-0.25060.401477
6-0.269341-2.08630.020605
7-0.028711-0.22240.412382
8-0.069919-0.54160.295052
9-0.267378-2.07110.021329
10-0.213916-1.6570.051372
110.0311330.24120.405128
120.0494540.38310.351512
13-0.05777-0.44750.328068
140.1033230.80030.213337
150.0918360.71140.23981
160.0094930.07350.470815
170.0080460.06230.475256
180.0409960.31760.375963
190.0854170.66160.255368
20-0.196895-1.52510.066239
21-0.049078-0.38020.352585
22-0.091953-0.71230.23953
230.096640.74860.228522
24-0.090003-0.69720.244199
25-0.04085-0.31640.376391
260.0089980.06970.472332
27-0.06421-0.49740.310375
28-0.021601-0.16730.433841
29-0.10485-0.81220.209953
30-0.147443-1.14210.128977
310.0624360.48360.315206
320.0918320.71130.239819
33-0.105297-0.81560.208971
34-0.021445-0.16610.434314
350.0633420.49060.312734
36-0.046702-0.36180.359404


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
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')