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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 computationWed, 25 Nov 2009 06:05:26 -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/25/t1259154400oyrlxoe3xey54n9.htm/, Retrieved Tue, 07 May 2024 12:54:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59365, Retrieved Tue, 07 May 2024 12:54:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsSHW WS 8 Methode 1:ACF van Y[t] (d=0, D=1,Lambda=1)
Estimated Impact157

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 12:19:56] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [WS 8 Methode 1:AC...] [2009-11-25 13:05:26] [a45cc820faa25ce30779915639528ec2] [Current]
-    D            [(Partial) Autocorrelation Function] [Paper: (Partial) ...] [2009-12-17 13:16:42] [b103a1dc147def8132c7f643ad8c8f84]
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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 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=59365&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=59365&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59365&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
10.7102685.54740
20.6498145.07522e-06
30.5313084.14975.2e-05
40.293962.29590.012566
50.2020421.5780.059869
60.0520310.40640.342944
7-0.142715-1.11460.134688
8-0.170533-1.33190.093924
9-0.244143-1.90680.030628
10-0.277093-2.16420.017188
11-0.236104-1.8440.035018
12-0.275443-2.15130.017712
13-0.248124-1.93790.028633
14-0.2015-1.57380.060357
15-0.167877-1.31120.097358
16-0.178345-1.39290.08435
17-0.100679-0.78630.21736
18-0.097824-0.7640.223898
19-0.069241-0.54080.29531
20-0.013287-0.10380.458844
21-0.003637-0.02840.488716
220.0157580.12310.451227
230.0916010.71540.238537
240.05940.46390.322175
250.1351951.05590.147588
260.1287151.00530.159363
270.0973950.76070.224889
280.0974510.76110.224759
290.0836560.65340.257985
300.0286780.2240.411759
310.0177990.1390.444949
32-0.013986-0.10920.456688
33-0.007854-0.06130.475643
34-0.023992-0.18740.42599
35-0.037005-0.2890.386775
36-0.050072-0.39110.348553

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.710268 & 5.5474 & 0 \tabularnewline
2 & 0.649814 & 5.0752 & 2e-06 \tabularnewline
3 & 0.531308 & 4.1497 & 5.2e-05 \tabularnewline
4 & 0.29396 & 2.2959 & 0.012566 \tabularnewline
5 & 0.202042 & 1.578 & 0.059869 \tabularnewline
6 & 0.052031 & 0.4064 & 0.342944 \tabularnewline
7 & -0.142715 & -1.1146 & 0.134688 \tabularnewline
8 & -0.170533 & -1.3319 & 0.093924 \tabularnewline
9 & -0.244143 & -1.9068 & 0.030628 \tabularnewline
10 & -0.277093 & -2.1642 & 0.017188 \tabularnewline
11 & -0.236104 & -1.844 & 0.035018 \tabularnewline
12 & -0.275443 & -2.1513 & 0.017712 \tabularnewline
13 & -0.248124 & -1.9379 & 0.028633 \tabularnewline
14 & -0.2015 & -1.5738 & 0.060357 \tabularnewline
15 & -0.167877 & -1.3112 & 0.097358 \tabularnewline
16 & -0.178345 & -1.3929 & 0.08435 \tabularnewline
17 & -0.100679 & -0.7863 & 0.21736 \tabularnewline
18 & -0.097824 & -0.764 & 0.223898 \tabularnewline
19 & -0.069241 & -0.5408 & 0.29531 \tabularnewline
20 & -0.013287 & -0.1038 & 0.458844 \tabularnewline
21 & -0.003637 & -0.0284 & 0.488716 \tabularnewline
22 & 0.015758 & 0.1231 & 0.451227 \tabularnewline
23 & 0.091601 & 0.7154 & 0.238537 \tabularnewline
24 & 0.0594 & 0.4639 & 0.322175 \tabularnewline
25 & 0.135195 & 1.0559 & 0.147588 \tabularnewline
26 & 0.128715 & 1.0053 & 0.159363 \tabularnewline
27 & 0.097395 & 0.7607 & 0.224889 \tabularnewline
28 & 0.097451 & 0.7611 & 0.224759 \tabularnewline
29 & 0.083656 & 0.6534 & 0.257985 \tabularnewline
30 & 0.028678 & 0.224 & 0.411759 \tabularnewline
31 & 0.017799 & 0.139 & 0.444949 \tabularnewline
32 & -0.013986 & -0.1092 & 0.456688 \tabularnewline
33 & -0.007854 & -0.0613 & 0.475643 \tabularnewline
34 & -0.023992 & -0.1874 & 0.42599 \tabularnewline
35 & -0.037005 & -0.289 & 0.386775 \tabularnewline
36 & -0.050072 & -0.3911 & 0.348553 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59365&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]0.710268[/C][C]5.5474[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.649814[/C][C]5.0752[/C][C]2e-06[/C][/ROW]
[ROW][C]3[/C][C]0.531308[/C][C]4.1497[/C][C]5.2e-05[/C][/ROW]
[ROW][C]4[/C][C]0.29396[/C][C]2.2959[/C][C]0.012566[/C][/ROW]
[ROW][C]5[/C][C]0.202042[/C][C]1.578[/C][C]0.059869[/C][/ROW]
[ROW][C]6[/C][C]0.052031[/C][C]0.4064[/C][C]0.342944[/C][/ROW]
[ROW][C]7[/C][C]-0.142715[/C][C]-1.1146[/C][C]0.134688[/C][/ROW]
[ROW][C]8[/C][C]-0.170533[/C][C]-1.3319[/C][C]0.093924[/C][/ROW]
[ROW][C]9[/C][C]-0.244143[/C][C]-1.9068[/C][C]0.030628[/C][/ROW]
[ROW][C]10[/C][C]-0.277093[/C][C]-2.1642[/C][C]0.017188[/C][/ROW]
[ROW][C]11[/C][C]-0.236104[/C][C]-1.844[/C][C]0.035018[/C][/ROW]
[ROW][C]12[/C][C]-0.275443[/C][C]-2.1513[/C][C]0.017712[/C][/ROW]
[ROW][C]13[/C][C]-0.248124[/C][C]-1.9379[/C][C]0.028633[/C][/ROW]
[ROW][C]14[/C][C]-0.2015[/C][C]-1.5738[/C][C]0.060357[/C][/ROW]
[ROW][C]15[/C][C]-0.167877[/C][C]-1.3112[/C][C]0.097358[/C][/ROW]
[ROW][C]16[/C][C]-0.178345[/C][C]-1.3929[/C][C]0.08435[/C][/ROW]
[ROW][C]17[/C][C]-0.100679[/C][C]-0.7863[/C][C]0.21736[/C][/ROW]
[ROW][C]18[/C][C]-0.097824[/C][C]-0.764[/C][C]0.223898[/C][/ROW]
[ROW][C]19[/C][C]-0.069241[/C][C]-0.5408[/C][C]0.29531[/C][/ROW]
[ROW][C]20[/C][C]-0.013287[/C][C]-0.1038[/C][C]0.458844[/C][/ROW]
[ROW][C]21[/C][C]-0.003637[/C][C]-0.0284[/C][C]0.488716[/C][/ROW]
[ROW][C]22[/C][C]0.015758[/C][C]0.1231[/C][C]0.451227[/C][/ROW]
[ROW][C]23[/C][C]0.091601[/C][C]0.7154[/C][C]0.238537[/C][/ROW]
[ROW][C]24[/C][C]0.0594[/C][C]0.4639[/C][C]0.322175[/C][/ROW]
[ROW][C]25[/C][C]0.135195[/C][C]1.0559[/C][C]0.147588[/C][/ROW]
[ROW][C]26[/C][C]0.128715[/C][C]1.0053[/C][C]0.159363[/C][/ROW]
[ROW][C]27[/C][C]0.097395[/C][C]0.7607[/C][C]0.224889[/C][/ROW]
[ROW][C]28[/C][C]0.097451[/C][C]0.7611[/C][C]0.224759[/C][/ROW]
[ROW][C]29[/C][C]0.083656[/C][C]0.6534[/C][C]0.257985[/C][/ROW]
[ROW][C]30[/C][C]0.028678[/C][C]0.224[/C][C]0.411759[/C][/ROW]
[ROW][C]31[/C][C]0.017799[/C][C]0.139[/C][C]0.444949[/C][/ROW]
[ROW][C]32[/C][C]-0.013986[/C][C]-0.1092[/C][C]0.456688[/C][/ROW]
[ROW][C]33[/C][C]-0.007854[/C][C]-0.0613[/C][C]0.475643[/C][/ROW]
[ROW][C]34[/C][C]-0.023992[/C][C]-0.1874[/C][C]0.42599[/C][/ROW]
[ROW][C]35[/C][C]-0.037005[/C][C]-0.289[/C][C]0.386775[/C][/ROW]
[ROW][C]36[/C][C]-0.050072[/C][C]-0.3911[/C][C]0.348553[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59365&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59365&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
10.7102685.54740
20.6498145.07522e-06
30.5313084.14975.2e-05
40.293962.29590.012566
50.2020421.5780.059869
60.0520310.40640.342944
7-0.142715-1.11460.134688
8-0.170533-1.33190.093924
9-0.244143-1.90680.030628
10-0.277093-2.16420.017188
11-0.236104-1.8440.035018
12-0.275443-2.15130.017712
13-0.248124-1.93790.028633
14-0.2015-1.57380.060357
15-0.167877-1.31120.097358
16-0.178345-1.39290.08435
17-0.100679-0.78630.21736
18-0.097824-0.7640.223898
19-0.069241-0.54080.29531
20-0.013287-0.10380.458844
21-0.003637-0.02840.488716
220.0157580.12310.451227
230.0916010.71540.238537
240.05940.46390.322175
250.1351951.05590.147588
260.1287151.00530.159363
270.0973950.76070.224889
280.0974510.76110.224759
290.0836560.65340.257985
300.0286780.2240.411759
310.0177990.1390.444949
32-0.013986-0.10920.456688
33-0.007854-0.06130.475643
34-0.023992-0.18740.42599
35-0.037005-0.2890.386775
36-0.050072-0.39110.348553






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7102685.54740
20.2932942.29070.012725
3-0.00703-0.05490.478196
4-0.357084-2.78890.003522
5-0.045945-0.35880.360475
6-0.047545-0.37130.355837
7-0.230902-1.80340.038132
80.0421430.32910.371587
90.0750330.5860.28001
100.0095350.07450.470439
11-0.012017-0.09390.462766
12-0.109491-0.85520.197907
13-0.055052-0.430.334366
14-0.019218-0.15010.440591
150.0651420.50880.306372
16-0.1748-1.36520.088597
170.0762230.59530.276915
180.0331620.2590.398252
19-0.039378-0.30760.379734
20-0.019687-0.15380.439152
210.0322180.25160.401086
22-0.01534-0.11980.452515
230.0795230.62110.268426
24-0.06424-0.50170.308831
250.101330.79140.215885
26-0.058831-0.45950.32376
27-0.026259-0.20510.419093
28-0.107433-0.83910.202351
290.0863840.67470.251214
30-0.031049-0.24250.404602
31-0.025467-0.19890.4215
320.016040.12530.450359
330.1600631.25010.108014
34-0.097184-0.7590.225378
35-0.058003-0.4530.326072
36-0.066373-0.51840.303031

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.710268 & 5.5474 & 0 \tabularnewline
2 & 0.293294 & 2.2907 & 0.012725 \tabularnewline
3 & -0.00703 & -0.0549 & 0.478196 \tabularnewline
4 & -0.357084 & -2.7889 & 0.003522 \tabularnewline
5 & -0.045945 & -0.3588 & 0.360475 \tabularnewline
6 & -0.047545 & -0.3713 & 0.355837 \tabularnewline
7 & -0.230902 & -1.8034 & 0.038132 \tabularnewline
8 & 0.042143 & 0.3291 & 0.371587 \tabularnewline
9 & 0.075033 & 0.586 & 0.28001 \tabularnewline
10 & 0.009535 & 0.0745 & 0.470439 \tabularnewline
11 & -0.012017 & -0.0939 & 0.462766 \tabularnewline
12 & -0.109491 & -0.8552 & 0.197907 \tabularnewline
13 & -0.055052 & -0.43 & 0.334366 \tabularnewline
14 & -0.019218 & -0.1501 & 0.440591 \tabularnewline
15 & 0.065142 & 0.5088 & 0.306372 \tabularnewline
16 & -0.1748 & -1.3652 & 0.088597 \tabularnewline
17 & 0.076223 & 0.5953 & 0.276915 \tabularnewline
18 & 0.033162 & 0.259 & 0.398252 \tabularnewline
19 & -0.039378 & -0.3076 & 0.379734 \tabularnewline
20 & -0.019687 & -0.1538 & 0.439152 \tabularnewline
21 & 0.032218 & 0.2516 & 0.401086 \tabularnewline
22 & -0.01534 & -0.1198 & 0.452515 \tabularnewline
23 & 0.079523 & 0.6211 & 0.268426 \tabularnewline
24 & -0.06424 & -0.5017 & 0.308831 \tabularnewline
25 & 0.10133 & 0.7914 & 0.215885 \tabularnewline
26 & -0.058831 & -0.4595 & 0.32376 \tabularnewline
27 & -0.026259 & -0.2051 & 0.419093 \tabularnewline
28 & -0.107433 & -0.8391 & 0.202351 \tabularnewline
29 & 0.086384 & 0.6747 & 0.251214 \tabularnewline
30 & -0.031049 & -0.2425 & 0.404602 \tabularnewline
31 & -0.025467 & -0.1989 & 0.4215 \tabularnewline
32 & 0.01604 & 0.1253 & 0.450359 \tabularnewline
33 & 0.160063 & 1.2501 & 0.108014 \tabularnewline
34 & -0.097184 & -0.759 & 0.225378 \tabularnewline
35 & -0.058003 & -0.453 & 0.326072 \tabularnewline
36 & -0.066373 & -0.5184 & 0.303031 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59365&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]0.710268[/C][C]5.5474[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.293294[/C][C]2.2907[/C][C]0.012725[/C][/ROW]
[ROW][C]3[/C][C]-0.00703[/C][C]-0.0549[/C][C]0.478196[/C][/ROW]
[ROW][C]4[/C][C]-0.357084[/C][C]-2.7889[/C][C]0.003522[/C][/ROW]
[ROW][C]5[/C][C]-0.045945[/C][C]-0.3588[/C][C]0.360475[/C][/ROW]
[ROW][C]6[/C][C]-0.047545[/C][C]-0.3713[/C][C]0.355837[/C][/ROW]
[ROW][C]7[/C][C]-0.230902[/C][C]-1.8034[/C][C]0.038132[/C][/ROW]
[ROW][C]8[/C][C]0.042143[/C][C]0.3291[/C][C]0.371587[/C][/ROW]
[ROW][C]9[/C][C]0.075033[/C][C]0.586[/C][C]0.28001[/C][/ROW]
[ROW][C]10[/C][C]0.009535[/C][C]0.0745[/C][C]0.470439[/C][/ROW]
[ROW][C]11[/C][C]-0.012017[/C][C]-0.0939[/C][C]0.462766[/C][/ROW]
[ROW][C]12[/C][C]-0.109491[/C][C]-0.8552[/C][C]0.197907[/C][/ROW]
[ROW][C]13[/C][C]-0.055052[/C][C]-0.43[/C][C]0.334366[/C][/ROW]
[ROW][C]14[/C][C]-0.019218[/C][C]-0.1501[/C][C]0.440591[/C][/ROW]
[ROW][C]15[/C][C]0.065142[/C][C]0.5088[/C][C]0.306372[/C][/ROW]
[ROW][C]16[/C][C]-0.1748[/C][C]-1.3652[/C][C]0.088597[/C][/ROW]
[ROW][C]17[/C][C]0.076223[/C][C]0.5953[/C][C]0.276915[/C][/ROW]
[ROW][C]18[/C][C]0.033162[/C][C]0.259[/C][C]0.398252[/C][/ROW]
[ROW][C]19[/C][C]-0.039378[/C][C]-0.3076[/C][C]0.379734[/C][/ROW]
[ROW][C]20[/C][C]-0.019687[/C][C]-0.1538[/C][C]0.439152[/C][/ROW]
[ROW][C]21[/C][C]0.032218[/C][C]0.2516[/C][C]0.401086[/C][/ROW]
[ROW][C]22[/C][C]-0.01534[/C][C]-0.1198[/C][C]0.452515[/C][/ROW]
[ROW][C]23[/C][C]0.079523[/C][C]0.6211[/C][C]0.268426[/C][/ROW]
[ROW][C]24[/C][C]-0.06424[/C][C]-0.5017[/C][C]0.308831[/C][/ROW]
[ROW][C]25[/C][C]0.10133[/C][C]0.7914[/C][C]0.215885[/C][/ROW]
[ROW][C]26[/C][C]-0.058831[/C][C]-0.4595[/C][C]0.32376[/C][/ROW]
[ROW][C]27[/C][C]-0.026259[/C][C]-0.2051[/C][C]0.419093[/C][/ROW]
[ROW][C]28[/C][C]-0.107433[/C][C]-0.8391[/C][C]0.202351[/C][/ROW]
[ROW][C]29[/C][C]0.086384[/C][C]0.6747[/C][C]0.251214[/C][/ROW]
[ROW][C]30[/C][C]-0.031049[/C][C]-0.2425[/C][C]0.404602[/C][/ROW]
[ROW][C]31[/C][C]-0.025467[/C][C]-0.1989[/C][C]0.4215[/C][/ROW]
[ROW][C]32[/C][C]0.01604[/C][C]0.1253[/C][C]0.450359[/C][/ROW]
[ROW][C]33[/C][C]0.160063[/C][C]1.2501[/C][C]0.108014[/C][/ROW]
[ROW][C]34[/C][C]-0.097184[/C][C]-0.759[/C][C]0.225378[/C][/ROW]
[ROW][C]35[/C][C]-0.058003[/C][C]-0.453[/C][C]0.326072[/C][/ROW]
[ROW][C]36[/C][C]-0.066373[/C][C]-0.5184[/C][C]0.303031[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59365&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59365&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
10.7102685.54740
20.2932942.29070.012725
3-0.00703-0.05490.478196
4-0.357084-2.78890.003522
5-0.045945-0.35880.360475
6-0.047545-0.37130.355837
7-0.230902-1.80340.038132
80.0421430.32910.371587
90.0750330.5860.28001
100.0095350.07450.470439
11-0.012017-0.09390.462766
12-0.109491-0.85520.197907
13-0.055052-0.430.334366
14-0.019218-0.15010.440591
150.0651420.50880.306372
16-0.1748-1.36520.088597
170.0762230.59530.276915
180.0331620.2590.398252
19-0.039378-0.30760.379734
20-0.019687-0.15380.439152
210.0322180.25160.401086
22-0.01534-0.11980.452515
230.0795230.62110.268426
24-0.06424-0.50170.308831
250.101330.79140.215885
26-0.058831-0.45950.32376
27-0.026259-0.20510.419093
28-0.107433-0.83910.202351
290.0863840.67470.251214
30-0.031049-0.24250.404602
31-0.025467-0.19890.4215
320.016040.12530.450359
330.1600631.25010.108014
34-0.097184-0.7590.225378
35-0.058003-0.4530.326072
36-0.066373-0.51840.303031


Figures (Output of Computation)

Input Parameters & R Code

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