FreeStatistics.org

Free Statistics

of Irreproducible Research!

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, 11 Dec 2009 08:41:35 -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/11/t126054620529w9podnsn79s35.htm/, Retrieved Tue, 10 Feb 2026 09:38:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=66397, Retrieved Tue, 10 Feb 2026 09:38:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact354

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [Shwws9_v1] [2009-12-09 17:40:43] [5f89c040fdf1f8599c99d7f78a662321]
-   PD    [(Partial) Autocorrelation Function] [Shwws9_v1] [2009-12-11 15:41:35] [93b66894f6318f3da4fcda772f2ffa6f] [Current]
-   PD      [(Partial) Autocorrelation Function] [Paper] [2009-12-16 02:50:18] [5f89c040fdf1f8599c99d7f78a662321]
-   PD      [(Partial) Autocorrelation Function] [Paper] [2009-12-16 02:57:09] [5f89c040fdf1f8599c99d7f78a662321]
-   PD        [(Partial) Autocorrelation Function] [Paper] [2009-12-16 03:20:14] [5f89c040fdf1f8599c99d7f78a662321]
-   PD        [(Partial) Autocorrelation Function] [Paper] [2009-12-16 03:22:45] [5f89c040fdf1f8599c99d7f78a662321]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
102.1
102.86
102.99
103.73
105.02
104.43
104.63
104.93
105.87
105.66
106.76
106
107.22
107.33
107.11
108.86
107.72
107.88
108.38
107.72
108.41
109.9
111.45
112.18
113.34
113.46
114.06
115.54
116.39
115.94
116.97
115.94
115.91
116.43
116.26
116.35
117.9
117.7
117.53
117.86
117.65
116.51
115.93
115.31
115

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=66397&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=66397&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66397&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
1-0.060604-0.4020.344814
20.1423240.94410.175145
30.2854721.89360.032432
4-0.151165-1.00270.160741
5-0.054911-0.36420.358713
60.165091.09510.139719
7-0.096678-0.64130.26233
8-0.083369-0.5530.291529
90.1364270.9050.185209
10-0.100963-0.66970.253269
11-0.050238-0.33320.370267
120.1788511.18640.120922
13-0.071804-0.47630.31811
14-0.026201-0.17380.43141
150.0562680.37320.355382
16-0.200462-1.32970.095233
17-0.171741-1.13920.130392
180.087010.57720.283387
19-0.211533-1.40320.083795
20-0.072986-0.48410.315346
21-0.028901-0.19170.424428
22-0.083222-0.5520.29186
23-0.002312-0.01530.493916
240.1495310.99190.16334
25-0.02824-0.18730.426135
260.0900580.59740.276659
27-0.001606-0.01070.495774
28-0.042-0.27860.390929
29-0.001004-0.00670.497358
30-0.015617-0.10360.458983
31-0.089136-0.59130.278685
320.0723770.48010.31677
33-0.011332-0.07520.470211
34-0.059271-0.39320.34805
350.0295250.19580.422815
360.0117450.07790.469128

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.060604 & -0.402 & 0.344814 \tabularnewline
2 & 0.142324 & 0.9441 & 0.175145 \tabularnewline
3 & 0.285472 & 1.8936 & 0.032432 \tabularnewline
4 & -0.151165 & -1.0027 & 0.160741 \tabularnewline
5 & -0.054911 & -0.3642 & 0.358713 \tabularnewline
6 & 0.16509 & 1.0951 & 0.139719 \tabularnewline
7 & -0.096678 & -0.6413 & 0.26233 \tabularnewline
8 & -0.083369 & -0.553 & 0.291529 \tabularnewline
9 & 0.136427 & 0.905 & 0.185209 \tabularnewline
10 & -0.100963 & -0.6697 & 0.253269 \tabularnewline
11 & -0.050238 & -0.3332 & 0.370267 \tabularnewline
12 & 0.178851 & 1.1864 & 0.120922 \tabularnewline
13 & -0.071804 & -0.4763 & 0.31811 \tabularnewline
14 & -0.026201 & -0.1738 & 0.43141 \tabularnewline
15 & 0.056268 & 0.3732 & 0.355382 \tabularnewline
16 & -0.200462 & -1.3297 & 0.095233 \tabularnewline
17 & -0.171741 & -1.1392 & 0.130392 \tabularnewline
18 & 0.08701 & 0.5772 & 0.283387 \tabularnewline
19 & -0.211533 & -1.4032 & 0.083795 \tabularnewline
20 & -0.072986 & -0.4841 & 0.315346 \tabularnewline
21 & -0.028901 & -0.1917 & 0.424428 \tabularnewline
22 & -0.083222 & -0.552 & 0.29186 \tabularnewline
23 & -0.002312 & -0.0153 & 0.493916 \tabularnewline
24 & 0.149531 & 0.9919 & 0.16334 \tabularnewline
25 & -0.02824 & -0.1873 & 0.426135 \tabularnewline
26 & 0.090058 & 0.5974 & 0.276659 \tabularnewline
27 & -0.001606 & -0.0107 & 0.495774 \tabularnewline
28 & -0.042 & -0.2786 & 0.390929 \tabularnewline
29 & -0.001004 & -0.0067 & 0.497358 \tabularnewline
30 & -0.015617 & -0.1036 & 0.458983 \tabularnewline
31 & -0.089136 & -0.5913 & 0.278685 \tabularnewline
32 & 0.072377 & 0.4801 & 0.31677 \tabularnewline
33 & -0.011332 & -0.0752 & 0.470211 \tabularnewline
34 & -0.059271 & -0.3932 & 0.34805 \tabularnewline
35 & 0.029525 & 0.1958 & 0.422815 \tabularnewline
36 & 0.011745 & 0.0779 & 0.469128 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66397&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]-0.060604[/C][C]-0.402[/C][C]0.344814[/C][/ROW]
[ROW][C]2[/C][C]0.142324[/C][C]0.9441[/C][C]0.175145[/C][/ROW]
[ROW][C]3[/C][C]0.285472[/C][C]1.8936[/C][C]0.032432[/C][/ROW]
[ROW][C]4[/C][C]-0.151165[/C][C]-1.0027[/C][C]0.160741[/C][/ROW]
[ROW][C]5[/C][C]-0.054911[/C][C]-0.3642[/C][C]0.358713[/C][/ROW]
[ROW][C]6[/C][C]0.16509[/C][C]1.0951[/C][C]0.139719[/C][/ROW]
[ROW][C]7[/C][C]-0.096678[/C][C]-0.6413[/C][C]0.26233[/C][/ROW]
[ROW][C]8[/C][C]-0.083369[/C][C]-0.553[/C][C]0.291529[/C][/ROW]
[ROW][C]9[/C][C]0.136427[/C][C]0.905[/C][C]0.185209[/C][/ROW]
[ROW][C]10[/C][C]-0.100963[/C][C]-0.6697[/C][C]0.253269[/C][/ROW]
[ROW][C]11[/C][C]-0.050238[/C][C]-0.3332[/C][C]0.370267[/C][/ROW]
[ROW][C]12[/C][C]0.178851[/C][C]1.1864[/C][C]0.120922[/C][/ROW]
[ROW][C]13[/C][C]-0.071804[/C][C]-0.4763[/C][C]0.31811[/C][/ROW]
[ROW][C]14[/C][C]-0.026201[/C][C]-0.1738[/C][C]0.43141[/C][/ROW]
[ROW][C]15[/C][C]0.056268[/C][C]0.3732[/C][C]0.355382[/C][/ROW]
[ROW][C]16[/C][C]-0.200462[/C][C]-1.3297[/C][C]0.095233[/C][/ROW]
[ROW][C]17[/C][C]-0.171741[/C][C]-1.1392[/C][C]0.130392[/C][/ROW]
[ROW][C]18[/C][C]0.08701[/C][C]0.5772[/C][C]0.283387[/C][/ROW]
[ROW][C]19[/C][C]-0.211533[/C][C]-1.4032[/C][C]0.083795[/C][/ROW]
[ROW][C]20[/C][C]-0.072986[/C][C]-0.4841[/C][C]0.315346[/C][/ROW]
[ROW][C]21[/C][C]-0.028901[/C][C]-0.1917[/C][C]0.424428[/C][/ROW]
[ROW][C]22[/C][C]-0.083222[/C][C]-0.552[/C][C]0.29186[/C][/ROW]
[ROW][C]23[/C][C]-0.002312[/C][C]-0.0153[/C][C]0.493916[/C][/ROW]
[ROW][C]24[/C][C]0.149531[/C][C]0.9919[/C][C]0.16334[/C][/ROW]
[ROW][C]25[/C][C]-0.02824[/C][C]-0.1873[/C][C]0.426135[/C][/ROW]
[ROW][C]26[/C][C]0.090058[/C][C]0.5974[/C][C]0.276659[/C][/ROW]
[ROW][C]27[/C][C]-0.001606[/C][C]-0.0107[/C][C]0.495774[/C][/ROW]
[ROW][C]28[/C][C]-0.042[/C][C]-0.2786[/C][C]0.390929[/C][/ROW]
[ROW][C]29[/C][C]-0.001004[/C][C]-0.0067[/C][C]0.497358[/C][/ROW]
[ROW][C]30[/C][C]-0.015617[/C][C]-0.1036[/C][C]0.458983[/C][/ROW]
[ROW][C]31[/C][C]-0.089136[/C][C]-0.5913[/C][C]0.278685[/C][/ROW]
[ROW][C]32[/C][C]0.072377[/C][C]0.4801[/C][C]0.31677[/C][/ROW]
[ROW][C]33[/C][C]-0.011332[/C][C]-0.0752[/C][C]0.470211[/C][/ROW]
[ROW][C]34[/C][C]-0.059271[/C][C]-0.3932[/C][C]0.34805[/C][/ROW]
[ROW][C]35[/C][C]0.029525[/C][C]0.1958[/C][C]0.422815[/C][/ROW]
[ROW][C]36[/C][C]0.011745[/C][C]0.0779[/C][C]0.469128[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66397&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66397&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
1-0.060604-0.4020.344814
20.1423240.94410.175145
30.2854721.89360.032432
4-0.151165-1.00270.160741
5-0.054911-0.36420.358713
60.165091.09510.139719
7-0.096678-0.64130.26233
8-0.083369-0.5530.291529
90.1364270.9050.185209
10-0.100963-0.66970.253269
11-0.050238-0.33320.370267
120.1788511.18640.120922
13-0.071804-0.47630.31811
14-0.026201-0.17380.43141
150.0562680.37320.355382
16-0.200462-1.32970.095233
17-0.171741-1.13920.130392
180.087010.57720.283387
19-0.211533-1.40320.083795
20-0.072986-0.48410.315346
21-0.028901-0.19170.424428
22-0.083222-0.5520.29186
23-0.002312-0.01530.493916
240.1495310.99190.16334
25-0.02824-0.18730.426135
260.0900580.59740.276659
27-0.001606-0.01070.495774
28-0.042-0.27860.390929
29-0.001004-0.00670.497358
30-0.015617-0.10360.458983
31-0.089136-0.59130.278685
320.0723770.48010.31677
33-0.011332-0.07520.470211
34-0.059271-0.39320.34805
350.0295250.19580.422815
360.0117450.07790.469128






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.060604-0.4020.344814
20.1391620.92310.180496
30.3084152.04580.023391
4-0.144129-0.9560.172137
5-0.18938-1.25620.107835
60.1350990.89610.187525
70.0675820.44830.328071
8-0.131878-0.87480.193222
90.0154530.10250.459411
100.0179320.11890.45293
11-0.018645-0.12370.451068
120.1003730.66580.254507
130.0053850.03570.485833
14-0.05603-0.37170.355964
15-0.073507-0.48760.314131
16-0.14893-0.98790.164305
17-0.161208-1.06930.145375
180.1054660.69960.243934
19-0.042015-0.27870.390892
20-0.094851-0.62920.266246
21-0.165755-1.09950.138767
220.0781380.51830.303419
230.1329230.88170.191362
240.1092750.72480.236191
25-0.071888-0.47690.317914
260.0330410.21920.413766
27-0.088966-0.59010.27906
280.0176850.11730.453575
290.0415120.27540.392164
30-0.020493-0.13590.446245
31-0.131995-0.87560.193012
320.0341220.22630.410993
330.0380010.25210.40108
34-0.016354-0.10850.457055
35-0.08459-0.56110.288785
36-0.068506-0.45440.325881

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.060604 & -0.402 & 0.344814 \tabularnewline
2 & 0.139162 & 0.9231 & 0.180496 \tabularnewline
3 & 0.308415 & 2.0458 & 0.023391 \tabularnewline
4 & -0.144129 & -0.956 & 0.172137 \tabularnewline
5 & -0.18938 & -1.2562 & 0.107835 \tabularnewline
6 & 0.135099 & 0.8961 & 0.187525 \tabularnewline
7 & 0.067582 & 0.4483 & 0.328071 \tabularnewline
8 & -0.131878 & -0.8748 & 0.193222 \tabularnewline
9 & 0.015453 & 0.1025 & 0.459411 \tabularnewline
10 & 0.017932 & 0.1189 & 0.45293 \tabularnewline
11 & -0.018645 & -0.1237 & 0.451068 \tabularnewline
12 & 0.100373 & 0.6658 & 0.254507 \tabularnewline
13 & 0.005385 & 0.0357 & 0.485833 \tabularnewline
14 & -0.05603 & -0.3717 & 0.355964 \tabularnewline
15 & -0.073507 & -0.4876 & 0.314131 \tabularnewline
16 & -0.14893 & -0.9879 & 0.164305 \tabularnewline
17 & -0.161208 & -1.0693 & 0.145375 \tabularnewline
18 & 0.105466 & 0.6996 & 0.243934 \tabularnewline
19 & -0.042015 & -0.2787 & 0.390892 \tabularnewline
20 & -0.094851 & -0.6292 & 0.266246 \tabularnewline
21 & -0.165755 & -1.0995 & 0.138767 \tabularnewline
22 & 0.078138 & 0.5183 & 0.303419 \tabularnewline
23 & 0.132923 & 0.8817 & 0.191362 \tabularnewline
24 & 0.109275 & 0.7248 & 0.236191 \tabularnewline
25 & -0.071888 & -0.4769 & 0.317914 \tabularnewline
26 & 0.033041 & 0.2192 & 0.413766 \tabularnewline
27 & -0.088966 & -0.5901 & 0.27906 \tabularnewline
28 & 0.017685 & 0.1173 & 0.453575 \tabularnewline
29 & 0.041512 & 0.2754 & 0.392164 \tabularnewline
30 & -0.020493 & -0.1359 & 0.446245 \tabularnewline
31 & -0.131995 & -0.8756 & 0.193012 \tabularnewline
32 & 0.034122 & 0.2263 & 0.410993 \tabularnewline
33 & 0.038001 & 0.2521 & 0.40108 \tabularnewline
34 & -0.016354 & -0.1085 & 0.457055 \tabularnewline
35 & -0.08459 & -0.5611 & 0.288785 \tabularnewline
36 & -0.068506 & -0.4544 & 0.325881 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66397&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]-0.060604[/C][C]-0.402[/C][C]0.344814[/C][/ROW]
[ROW][C]2[/C][C]0.139162[/C][C]0.9231[/C][C]0.180496[/C][/ROW]
[ROW][C]3[/C][C]0.308415[/C][C]2.0458[/C][C]0.023391[/C][/ROW]
[ROW][C]4[/C][C]-0.144129[/C][C]-0.956[/C][C]0.172137[/C][/ROW]
[ROW][C]5[/C][C]-0.18938[/C][C]-1.2562[/C][C]0.107835[/C][/ROW]
[ROW][C]6[/C][C]0.135099[/C][C]0.8961[/C][C]0.187525[/C][/ROW]
[ROW][C]7[/C][C]0.067582[/C][C]0.4483[/C][C]0.328071[/C][/ROW]
[ROW][C]8[/C][C]-0.131878[/C][C]-0.8748[/C][C]0.193222[/C][/ROW]
[ROW][C]9[/C][C]0.015453[/C][C]0.1025[/C][C]0.459411[/C][/ROW]
[ROW][C]10[/C][C]0.017932[/C][C]0.1189[/C][C]0.45293[/C][/ROW]
[ROW][C]11[/C][C]-0.018645[/C][C]-0.1237[/C][C]0.451068[/C][/ROW]
[ROW][C]12[/C][C]0.100373[/C][C]0.6658[/C][C]0.254507[/C][/ROW]
[ROW][C]13[/C][C]0.005385[/C][C]0.0357[/C][C]0.485833[/C][/ROW]
[ROW][C]14[/C][C]-0.05603[/C][C]-0.3717[/C][C]0.355964[/C][/ROW]
[ROW][C]15[/C][C]-0.073507[/C][C]-0.4876[/C][C]0.314131[/C][/ROW]
[ROW][C]16[/C][C]-0.14893[/C][C]-0.9879[/C][C]0.164305[/C][/ROW]
[ROW][C]17[/C][C]-0.161208[/C][C]-1.0693[/C][C]0.145375[/C][/ROW]
[ROW][C]18[/C][C]0.105466[/C][C]0.6996[/C][C]0.243934[/C][/ROW]
[ROW][C]19[/C][C]-0.042015[/C][C]-0.2787[/C][C]0.390892[/C][/ROW]
[ROW][C]20[/C][C]-0.094851[/C][C]-0.6292[/C][C]0.266246[/C][/ROW]
[ROW][C]21[/C][C]-0.165755[/C][C]-1.0995[/C][C]0.138767[/C][/ROW]
[ROW][C]22[/C][C]0.078138[/C][C]0.5183[/C][C]0.303419[/C][/ROW]
[ROW][C]23[/C][C]0.132923[/C][C]0.8817[/C][C]0.191362[/C][/ROW]
[ROW][C]24[/C][C]0.109275[/C][C]0.7248[/C][C]0.236191[/C][/ROW]
[ROW][C]25[/C][C]-0.071888[/C][C]-0.4769[/C][C]0.317914[/C][/ROW]
[ROW][C]26[/C][C]0.033041[/C][C]0.2192[/C][C]0.413766[/C][/ROW]
[ROW][C]27[/C][C]-0.088966[/C][C]-0.5901[/C][C]0.27906[/C][/ROW]
[ROW][C]28[/C][C]0.017685[/C][C]0.1173[/C][C]0.453575[/C][/ROW]
[ROW][C]29[/C][C]0.041512[/C][C]0.2754[/C][C]0.392164[/C][/ROW]
[ROW][C]30[/C][C]-0.020493[/C][C]-0.1359[/C][C]0.446245[/C][/ROW]
[ROW][C]31[/C][C]-0.131995[/C][C]-0.8756[/C][C]0.193012[/C][/ROW]
[ROW][C]32[/C][C]0.034122[/C][C]0.2263[/C][C]0.410993[/C][/ROW]
[ROW][C]33[/C][C]0.038001[/C][C]0.2521[/C][C]0.40108[/C][/ROW]
[ROW][C]34[/C][C]-0.016354[/C][C]-0.1085[/C][C]0.457055[/C][/ROW]
[ROW][C]35[/C][C]-0.08459[/C][C]-0.5611[/C][C]0.288785[/C][/ROW]
[ROW][C]36[/C][C]-0.068506[/C][C]-0.4544[/C][C]0.325881[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66397&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66397&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
1-0.060604-0.4020.344814
20.1391620.92310.180496
30.3084152.04580.023391
4-0.144129-0.9560.172137
5-0.18938-1.25620.107835
60.1350990.89610.187525
70.0675820.44830.328071
8-0.131878-0.87480.193222
90.0154530.10250.459411
100.0179320.11890.45293
11-0.018645-0.12370.451068
120.1003730.66580.254507
130.0053850.03570.485833
14-0.05603-0.37170.355964
15-0.073507-0.48760.314131
16-0.14893-0.98790.164305
17-0.161208-1.06930.145375
180.1054660.69960.243934
19-0.042015-0.27870.390892
20-0.094851-0.62920.266246
21-0.165755-1.09950.138767
220.0781380.51830.303419
230.1329230.88170.191362
240.1092750.72480.236191
25-0.071888-0.47690.317914
260.0330410.21920.413766
27-0.088966-0.59010.27906
280.0176850.11730.453575
290.0415120.27540.392164
30-0.020493-0.13590.446245
31-0.131995-0.87560.193012
320.0341220.22630.410993
330.0380010.25210.40108
34-0.016354-0.10850.457055
35-0.08459-0.56110.288785
36-0.068506-0.45440.325881


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; 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')