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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, 14 Dec 2008 08:37:18 -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/2008/Dec/14/t1229269145izqefwwfsnb5ti2.htm/, Retrieved Wed, 15 May 2024 12:52:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33426, Retrieved Wed, 15 May 2024 12:52:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact190

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] [(P)ACF Totale omzet] [2007-12-20 14:02:48] [74be16979710d4c4e7c6647856088456]
- R PD    [(Partial) Autocorrelation Function] [invoer] [2008-12-14 15:37:18] [5925747fb2a6bb4cfcd8015825ee5e92] [Current]
- RM D      [Spectral Analysis] [werkloosheid] [2008-12-14 17:09:07] [5e74953d94072114d25d7276793b561e]
- RM D        [Kendall tau Correlation Matrix] [kendall tau] [2008-12-14 19:40:10] [5e74953d94072114d25d7276793b561e]
- RM D      [ARIMA Backward Selection] [invoer] [2008-12-14 17:17:09] [5e74953d94072114d25d7276793b561e]
- RM D      [ARIMA Backward Selection] [werkloosheid] [2008-12-14 17:43:32] [5e74953d94072114d25d7276793b561e]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
11554.5
13182.1
14800.1
12150.7
14478.2
13253.9
12036.8
12653.2
14035.4
14571.4
15400.9
14283.2
14485.3
14196.3
15559.1
13767.4
14634
14381.1
12509.9
12122.3
13122.3
13908.7
13456.5
12441.6
12953
13057.2
14350.1
13830.2
13755.5
13574.4
12802.6
11737.3
13850.2
15081.8
13653.3
14019.1
13962
13768.7
14747.1
13858.1
13188
13693.1
12970
11392.8
13985.2
14994.7
13584.7
14257.8
13553.4
14007.3
16535.8
14721.4
13664.6
16805.9
13829.4
13735.6
15870.5
15962.4
15744.1
16083.7
14863.9
15533.1
17473.1
15925.5
15573.7
17495
14155.8
14913.9
17250.4
15879.8
17647.8
17749.9
17111.8
16934.8
20280
16238.2
17896.1
18089.3
15660
16162.4
17850.1
18520.4
18524.7
16843.7

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=33426&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=33426&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33426&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
1-0.525468-4.42771.7e-05
20.0936960.78950.216225
30.1805861.52160.06627
4-0.134892-1.13660.129759
5-0.036704-0.30930.379011
60.1951211.64410.052286
7-0.196878-1.65890.050771
80.0765920.64540.260382
90.1028410.86660.194553
10-0.132449-1.1160.134085
110.0328840.27710.391258
120.0148190.12490.450491
13-0.188517-1.58850.058312
140.0720770.60730.272785
150.114880.9680.168166
16-0.262908-2.21530.014974
170.1410581.18860.119284
180.1641381.38310.085491
19-0.231493-1.95060.027527
200.0871850.73460.23249
210.1654411.3940.083828
22-0.301266-2.53850.006663
230.3368112.8380.002957
24-0.150654-1.26940.104216
25-0.082891-0.69850.243588
260.2473092.08390.020386
27-0.205022-1.72750.044209
280.0699280.58920.27879
290.0731560.61640.269793
30-0.154545-1.30220.098525
31-0.003316-0.02790.488895
320.1039550.87590.192007
33-0.137889-1.16190.12459
34-0.063328-0.53360.297639
350.1223321.03080.153069
36-0.096535-0.81340.209349

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.525468 & -4.4277 & 1.7e-05 \tabularnewline
2 & 0.093696 & 0.7895 & 0.216225 \tabularnewline
3 & 0.180586 & 1.5216 & 0.06627 \tabularnewline
4 & -0.134892 & -1.1366 & 0.129759 \tabularnewline
5 & -0.036704 & -0.3093 & 0.379011 \tabularnewline
6 & 0.195121 & 1.6441 & 0.052286 \tabularnewline
7 & -0.196878 & -1.6589 & 0.050771 \tabularnewline
8 & 0.076592 & 0.6454 & 0.260382 \tabularnewline
9 & 0.102841 & 0.8666 & 0.194553 \tabularnewline
10 & -0.132449 & -1.116 & 0.134085 \tabularnewline
11 & 0.032884 & 0.2771 & 0.391258 \tabularnewline
12 & 0.014819 & 0.1249 & 0.450491 \tabularnewline
13 & -0.188517 & -1.5885 & 0.058312 \tabularnewline
14 & 0.072077 & 0.6073 & 0.272785 \tabularnewline
15 & 0.11488 & 0.968 & 0.168166 \tabularnewline
16 & -0.262908 & -2.2153 & 0.014974 \tabularnewline
17 & 0.141058 & 1.1886 & 0.119284 \tabularnewline
18 & 0.164138 & 1.3831 & 0.085491 \tabularnewline
19 & -0.231493 & -1.9506 & 0.027527 \tabularnewline
20 & 0.087185 & 0.7346 & 0.23249 \tabularnewline
21 & 0.165441 & 1.394 & 0.083828 \tabularnewline
22 & -0.301266 & -2.5385 & 0.006663 \tabularnewline
23 & 0.336811 & 2.838 & 0.002957 \tabularnewline
24 & -0.150654 & -1.2694 & 0.104216 \tabularnewline
25 & -0.082891 & -0.6985 & 0.243588 \tabularnewline
26 & 0.247309 & 2.0839 & 0.020386 \tabularnewline
27 & -0.205022 & -1.7275 & 0.044209 \tabularnewline
28 & 0.069928 & 0.5892 & 0.27879 \tabularnewline
29 & 0.073156 & 0.6164 & 0.269793 \tabularnewline
30 & -0.154545 & -1.3022 & 0.098525 \tabularnewline
31 & -0.003316 & -0.0279 & 0.488895 \tabularnewline
32 & 0.103955 & 0.8759 & 0.192007 \tabularnewline
33 & -0.137889 & -1.1619 & 0.12459 \tabularnewline
34 & -0.063328 & -0.5336 & 0.297639 \tabularnewline
35 & 0.122332 & 1.0308 & 0.153069 \tabularnewline
36 & -0.096535 & -0.8134 & 0.209349 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33426&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]-0.525468[/C][C]-4.4277[/C][C]1.7e-05[/C][/ROW]
[ROW][C]2[/C][C]0.093696[/C][C]0.7895[/C][C]0.216225[/C][/ROW]
[ROW][C]3[/C][C]0.180586[/C][C]1.5216[/C][C]0.06627[/C][/ROW]
[ROW][C]4[/C][C]-0.134892[/C][C]-1.1366[/C][C]0.129759[/C][/ROW]
[ROW][C]5[/C][C]-0.036704[/C][C]-0.3093[/C][C]0.379011[/C][/ROW]
[ROW][C]6[/C][C]0.195121[/C][C]1.6441[/C][C]0.052286[/C][/ROW]
[ROW][C]7[/C][C]-0.196878[/C][C]-1.6589[/C][C]0.050771[/C][/ROW]
[ROW][C]8[/C][C]0.076592[/C][C]0.6454[/C][C]0.260382[/C][/ROW]
[ROW][C]9[/C][C]0.102841[/C][C]0.8666[/C][C]0.194553[/C][/ROW]
[ROW][C]10[/C][C]-0.132449[/C][C]-1.116[/C][C]0.134085[/C][/ROW]
[ROW][C]11[/C][C]0.032884[/C][C]0.2771[/C][C]0.391258[/C][/ROW]
[ROW][C]12[/C][C]0.014819[/C][C]0.1249[/C][C]0.450491[/C][/ROW]
[ROW][C]13[/C][C]-0.188517[/C][C]-1.5885[/C][C]0.058312[/C][/ROW]
[ROW][C]14[/C][C]0.072077[/C][C]0.6073[/C][C]0.272785[/C][/ROW]
[ROW][C]15[/C][C]0.11488[/C][C]0.968[/C][C]0.168166[/C][/ROW]
[ROW][C]16[/C][C]-0.262908[/C][C]-2.2153[/C][C]0.014974[/C][/ROW]
[ROW][C]17[/C][C]0.141058[/C][C]1.1886[/C][C]0.119284[/C][/ROW]
[ROW][C]18[/C][C]0.164138[/C][C]1.3831[/C][C]0.085491[/C][/ROW]
[ROW][C]19[/C][C]-0.231493[/C][C]-1.9506[/C][C]0.027527[/C][/ROW]
[ROW][C]20[/C][C]0.087185[/C][C]0.7346[/C][C]0.23249[/C][/ROW]
[ROW][C]21[/C][C]0.165441[/C][C]1.394[/C][C]0.083828[/C][/ROW]
[ROW][C]22[/C][C]-0.301266[/C][C]-2.5385[/C][C]0.006663[/C][/ROW]
[ROW][C]23[/C][C]0.336811[/C][C]2.838[/C][C]0.002957[/C][/ROW]
[ROW][C]24[/C][C]-0.150654[/C][C]-1.2694[/C][C]0.104216[/C][/ROW]
[ROW][C]25[/C][C]-0.082891[/C][C]-0.6985[/C][C]0.243588[/C][/ROW]
[ROW][C]26[/C][C]0.247309[/C][C]2.0839[/C][C]0.020386[/C][/ROW]
[ROW][C]27[/C][C]-0.205022[/C][C]-1.7275[/C][C]0.044209[/C][/ROW]
[ROW][C]28[/C][C]0.069928[/C][C]0.5892[/C][C]0.27879[/C][/ROW]
[ROW][C]29[/C][C]0.073156[/C][C]0.6164[/C][C]0.269793[/C][/ROW]
[ROW][C]30[/C][C]-0.154545[/C][C]-1.3022[/C][C]0.098525[/C][/ROW]
[ROW][C]31[/C][C]-0.003316[/C][C]-0.0279[/C][C]0.488895[/C][/ROW]
[ROW][C]32[/C][C]0.103955[/C][C]0.8759[/C][C]0.192007[/C][/ROW]
[ROW][C]33[/C][C]-0.137889[/C][C]-1.1619[/C][C]0.12459[/C][/ROW]
[ROW][C]34[/C][C]-0.063328[/C][C]-0.5336[/C][C]0.297639[/C][/ROW]
[ROW][C]35[/C][C]0.122332[/C][C]1.0308[/C][C]0.153069[/C][/ROW]
[ROW][C]36[/C][C]-0.096535[/C][C]-0.8134[/C][C]0.209349[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33426&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33426&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
1-0.525468-4.42771.7e-05
20.0936960.78950.216225
30.1805861.52160.06627
4-0.134892-1.13660.129759
5-0.036704-0.30930.379011
60.1951211.64410.052286
7-0.196878-1.65890.050771
80.0765920.64540.260382
90.1028410.86660.194553
10-0.132449-1.1160.134085
110.0328840.27710.391258
120.0148190.12490.450491
13-0.188517-1.58850.058312
140.0720770.60730.272785
150.114880.9680.168166
16-0.262908-2.21530.014974
170.1410581.18860.119284
180.1641381.38310.085491
19-0.231493-1.95060.027527
200.0871850.73460.23249
210.1654411.3940.083828
22-0.301266-2.53850.006663
230.3368112.8380.002957
24-0.150654-1.26940.104216
25-0.082891-0.69850.243588
260.2473092.08390.020386
27-0.205022-1.72750.044209
280.0699280.58920.27879
290.0731560.61640.269793
30-0.154545-1.30220.098525
31-0.003316-0.02790.488895
320.1039550.87590.192007
33-0.137889-1.16190.12459
34-0.063328-0.53360.297639
350.1223321.03080.153069
36-0.096535-0.81340.209349






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.525468-4.42771.7e-05
2-0.252003-2.12340.018603
30.161981.36490.088303
40.1140450.9610.169917
5-0.093636-0.7890.216371
60.0985510.83040.204547
7-0.017295-0.14570.442274
8-0.02633-0.22190.412529
90.0970020.81740.208231
100.0339110.28570.387955
11-0.052061-0.43870.331115
12-0.101913-0.85870.196689
13-0.250881-2.1140.019016
14-0.213376-1.79790.038219
150.1205351.01570.156622
16-0.042535-0.35840.36055
17-0.112188-0.94530.173854
180.240022.02240.023449
190.1831551.54330.063603
20-0.065477-0.55170.291438
210.1596511.34520.091414
220.0069240.05830.476819
230.1711241.44190.076861
24-0.039893-0.33610.368876
25-0.223684-1.88480.031776
260.0063040.05310.478894
27-0.161734-1.36280.088627
28-0.035641-0.30030.382405
29-0.039967-0.33680.368644
30-0.055222-0.46530.321569
31-0.001649-0.01390.494475
32-0.049604-0.4180.338616
330.0103810.08750.465273
34-0.021145-0.17820.429547
350.0035750.03010.488025
36-0.004551-0.03830.484759

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.525468 & -4.4277 & 1.7e-05 \tabularnewline
2 & -0.252003 & -2.1234 & 0.018603 \tabularnewline
3 & 0.16198 & 1.3649 & 0.088303 \tabularnewline
4 & 0.114045 & 0.961 & 0.169917 \tabularnewline
5 & -0.093636 & -0.789 & 0.216371 \tabularnewline
6 & 0.098551 & 0.8304 & 0.204547 \tabularnewline
7 & -0.017295 & -0.1457 & 0.442274 \tabularnewline
8 & -0.02633 & -0.2219 & 0.412529 \tabularnewline
9 & 0.097002 & 0.8174 & 0.208231 \tabularnewline
10 & 0.033911 & 0.2857 & 0.387955 \tabularnewline
11 & -0.052061 & -0.4387 & 0.331115 \tabularnewline
12 & -0.101913 & -0.8587 & 0.196689 \tabularnewline
13 & -0.250881 & -2.114 & 0.019016 \tabularnewline
14 & -0.213376 & -1.7979 & 0.038219 \tabularnewline
15 & 0.120535 & 1.0157 & 0.156622 \tabularnewline
16 & -0.042535 & -0.3584 & 0.36055 \tabularnewline
17 & -0.112188 & -0.9453 & 0.173854 \tabularnewline
18 & 0.24002 & 2.0224 & 0.023449 \tabularnewline
19 & 0.183155 & 1.5433 & 0.063603 \tabularnewline
20 & -0.065477 & -0.5517 & 0.291438 \tabularnewline
21 & 0.159651 & 1.3452 & 0.091414 \tabularnewline
22 & 0.006924 & 0.0583 & 0.476819 \tabularnewline
23 & 0.171124 & 1.4419 & 0.076861 \tabularnewline
24 & -0.039893 & -0.3361 & 0.368876 \tabularnewline
25 & -0.223684 & -1.8848 & 0.031776 \tabularnewline
26 & 0.006304 & 0.0531 & 0.478894 \tabularnewline
27 & -0.161734 & -1.3628 & 0.088627 \tabularnewline
28 & -0.035641 & -0.3003 & 0.382405 \tabularnewline
29 & -0.039967 & -0.3368 & 0.368644 \tabularnewline
30 & -0.055222 & -0.4653 & 0.321569 \tabularnewline
31 & -0.001649 & -0.0139 & 0.494475 \tabularnewline
32 & -0.049604 & -0.418 & 0.338616 \tabularnewline
33 & 0.010381 & 0.0875 & 0.465273 \tabularnewline
34 & -0.021145 & -0.1782 & 0.429547 \tabularnewline
35 & 0.003575 & 0.0301 & 0.488025 \tabularnewline
36 & -0.004551 & -0.0383 & 0.484759 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33426&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]-0.525468[/C][C]-4.4277[/C][C]1.7e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.252003[/C][C]-2.1234[/C][C]0.018603[/C][/ROW]
[ROW][C]3[/C][C]0.16198[/C][C]1.3649[/C][C]0.088303[/C][/ROW]
[ROW][C]4[/C][C]0.114045[/C][C]0.961[/C][C]0.169917[/C][/ROW]
[ROW][C]5[/C][C]-0.093636[/C][C]-0.789[/C][C]0.216371[/C][/ROW]
[ROW][C]6[/C][C]0.098551[/C][C]0.8304[/C][C]0.204547[/C][/ROW]
[ROW][C]7[/C][C]-0.017295[/C][C]-0.1457[/C][C]0.442274[/C][/ROW]
[ROW][C]8[/C][C]-0.02633[/C][C]-0.2219[/C][C]0.412529[/C][/ROW]
[ROW][C]9[/C][C]0.097002[/C][C]0.8174[/C][C]0.208231[/C][/ROW]
[ROW][C]10[/C][C]0.033911[/C][C]0.2857[/C][C]0.387955[/C][/ROW]
[ROW][C]11[/C][C]-0.052061[/C][C]-0.4387[/C][C]0.331115[/C][/ROW]
[ROW][C]12[/C][C]-0.101913[/C][C]-0.8587[/C][C]0.196689[/C][/ROW]
[ROW][C]13[/C][C]-0.250881[/C][C]-2.114[/C][C]0.019016[/C][/ROW]
[ROW][C]14[/C][C]-0.213376[/C][C]-1.7979[/C][C]0.038219[/C][/ROW]
[ROW][C]15[/C][C]0.120535[/C][C]1.0157[/C][C]0.156622[/C][/ROW]
[ROW][C]16[/C][C]-0.042535[/C][C]-0.3584[/C][C]0.36055[/C][/ROW]
[ROW][C]17[/C][C]-0.112188[/C][C]-0.9453[/C][C]0.173854[/C][/ROW]
[ROW][C]18[/C][C]0.24002[/C][C]2.0224[/C][C]0.023449[/C][/ROW]
[ROW][C]19[/C][C]0.183155[/C][C]1.5433[/C][C]0.063603[/C][/ROW]
[ROW][C]20[/C][C]-0.065477[/C][C]-0.5517[/C][C]0.291438[/C][/ROW]
[ROW][C]21[/C][C]0.159651[/C][C]1.3452[/C][C]0.091414[/C][/ROW]
[ROW][C]22[/C][C]0.006924[/C][C]0.0583[/C][C]0.476819[/C][/ROW]
[ROW][C]23[/C][C]0.171124[/C][C]1.4419[/C][C]0.076861[/C][/ROW]
[ROW][C]24[/C][C]-0.039893[/C][C]-0.3361[/C][C]0.368876[/C][/ROW]
[ROW][C]25[/C][C]-0.223684[/C][C]-1.8848[/C][C]0.031776[/C][/ROW]
[ROW][C]26[/C][C]0.006304[/C][C]0.0531[/C][C]0.478894[/C][/ROW]
[ROW][C]27[/C][C]-0.161734[/C][C]-1.3628[/C][C]0.088627[/C][/ROW]
[ROW][C]28[/C][C]-0.035641[/C][C]-0.3003[/C][C]0.382405[/C][/ROW]
[ROW][C]29[/C][C]-0.039967[/C][C]-0.3368[/C][C]0.368644[/C][/ROW]
[ROW][C]30[/C][C]-0.055222[/C][C]-0.4653[/C][C]0.321569[/C][/ROW]
[ROW][C]31[/C][C]-0.001649[/C][C]-0.0139[/C][C]0.494475[/C][/ROW]
[ROW][C]32[/C][C]-0.049604[/C][C]-0.418[/C][C]0.338616[/C][/ROW]
[ROW][C]33[/C][C]0.010381[/C][C]0.0875[/C][C]0.465273[/C][/ROW]
[ROW][C]34[/C][C]-0.021145[/C][C]-0.1782[/C][C]0.429547[/C][/ROW]
[ROW][C]35[/C][C]0.003575[/C][C]0.0301[/C][C]0.488025[/C][/ROW]
[ROW][C]36[/C][C]-0.004551[/C][C]-0.0383[/C][C]0.484759[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33426&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33426&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
1-0.525468-4.42771.7e-05
2-0.252003-2.12340.018603
30.161981.36490.088303
40.1140450.9610.169917
5-0.093636-0.7890.216371
60.0985510.83040.204547
7-0.017295-0.14570.442274
8-0.02633-0.22190.412529
90.0970020.81740.208231
100.0339110.28570.387955
11-0.052061-0.43870.331115
12-0.101913-0.85870.196689
13-0.250881-2.1140.019016
14-0.213376-1.79790.038219
150.1205351.01570.156622
16-0.042535-0.35840.36055
17-0.112188-0.94530.173854
180.240022.02240.023449
190.1831551.54330.063603
20-0.065477-0.55170.291438
210.1596511.34520.091414
220.0069240.05830.476819
230.1711241.44190.076861
24-0.039893-0.33610.368876
25-0.223684-1.88480.031776
260.0063040.05310.478894
27-0.161734-1.36280.088627
28-0.035641-0.30030.382405
29-0.039967-0.33680.368644
30-0.055222-0.46530.321569
31-0.001649-0.01390.494475
32-0.049604-0.4180.338616
330.0103810.08750.465273
34-0.021145-0.17820.429547
350.0035750.03010.488025
36-0.004551-0.03830.484759


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1.3 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 1.3 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')