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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 computationThu, 26 Nov 2009 11:27:11 -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/26/t1259260101snfoapme25ngmy8.htm/, Retrieved Mon, 29 Apr 2024 01:46:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60239, Retrieved Mon, 29 Apr 2024 01:46:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsd=0 D=1 tijdreeks: aantal bouwvergunningen
Estimated Impact110
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]
- R  D          [(Partial) Autocorrelation Function] [autocorr. functie] [2009-11-26 18:27:11] [03368d751914a6c247d86aff8eac7cbf] [Current]
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Dataseries X:
2465
1932
1993
2243
1758
1806
2063
1823
2137
2428
2139
2265
2615
2070
2794
2190
2434
2520
2063
2068
2537
1898
2139
2408
2725
2201
2311
2548
2276
2351
2280
2057
2479
2379
2295
2456
2546
2844
2260
2981
2678
3440
2842
2450
2669
2570
2540
2318
2930
2946
2799
2695
2498
2260
2160
2058
2533
2150
2172
2155
3016




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=60239&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=60239&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60239&T=0

As an alternative you can also use a 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
10.3399622.37970.010631
20.3977682.78440.003801
30.2468161.72770.045169
40.2049011.43430.078919
50.0509140.35640.361536
60.0954920.66840.253493
70.0056260.03940.484372
80.0119840.08390.466745
9-0.092176-0.64520.260893
10-0.116741-0.81720.208889
11-0.152624-1.06840.145295
12-0.416136-2.9130.00269
13-0.202958-1.42070.080868
14-0.240483-1.68340.049331
15-0.197077-1.37950.086996
16-0.232178-1.62520.055263
17-0.060083-0.42060.337949
18-0.123254-0.86280.196231
19-0.061195-0.42840.335131
20-0.134874-0.94410.17487
210.0178670.12510.45049
22-0.02856-0.19990.421185
230.1291620.90410.185175
240.0525460.36780.357296
250.1960441.37230.088109
260.1038040.72660.235456
270.1734111.21390.115307
280.1072330.75060.228233
290.0770240.53920.296107
300.0604440.42310.337033
310.0654380.45810.324465
320.142570.9980.161594
330.0394720.27630.391739
340.0118910.08320.467
35-0.054887-0.38420.351243
36-0.036122-0.25290.400719

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.339962 & 2.3797 & 0.010631 \tabularnewline
2 & 0.397768 & 2.7844 & 0.003801 \tabularnewline
3 & 0.246816 & 1.7277 & 0.045169 \tabularnewline
4 & 0.204901 & 1.4343 & 0.078919 \tabularnewline
5 & 0.050914 & 0.3564 & 0.361536 \tabularnewline
6 & 0.095492 & 0.6684 & 0.253493 \tabularnewline
7 & 0.005626 & 0.0394 & 0.484372 \tabularnewline
8 & 0.011984 & 0.0839 & 0.466745 \tabularnewline
9 & -0.092176 & -0.6452 & 0.260893 \tabularnewline
10 & -0.116741 & -0.8172 & 0.208889 \tabularnewline
11 & -0.152624 & -1.0684 & 0.145295 \tabularnewline
12 & -0.416136 & -2.913 & 0.00269 \tabularnewline
13 & -0.202958 & -1.4207 & 0.080868 \tabularnewline
14 & -0.240483 & -1.6834 & 0.049331 \tabularnewline
15 & -0.197077 & -1.3795 & 0.086996 \tabularnewline
16 & -0.232178 & -1.6252 & 0.055263 \tabularnewline
17 & -0.060083 & -0.4206 & 0.337949 \tabularnewline
18 & -0.123254 & -0.8628 & 0.196231 \tabularnewline
19 & -0.061195 & -0.4284 & 0.335131 \tabularnewline
20 & -0.134874 & -0.9441 & 0.17487 \tabularnewline
21 & 0.017867 & 0.1251 & 0.45049 \tabularnewline
22 & -0.02856 & -0.1999 & 0.421185 \tabularnewline
23 & 0.129162 & 0.9041 & 0.185175 \tabularnewline
24 & 0.052546 & 0.3678 & 0.357296 \tabularnewline
25 & 0.196044 & 1.3723 & 0.088109 \tabularnewline
26 & 0.103804 & 0.7266 & 0.235456 \tabularnewline
27 & 0.173411 & 1.2139 & 0.115307 \tabularnewline
28 & 0.107233 & 0.7506 & 0.228233 \tabularnewline
29 & 0.077024 & 0.5392 & 0.296107 \tabularnewline
30 & 0.060444 & 0.4231 & 0.337033 \tabularnewline
31 & 0.065438 & 0.4581 & 0.324465 \tabularnewline
32 & 0.14257 & 0.998 & 0.161594 \tabularnewline
33 & 0.039472 & 0.2763 & 0.391739 \tabularnewline
34 & 0.011891 & 0.0832 & 0.467 \tabularnewline
35 & -0.054887 & -0.3842 & 0.351243 \tabularnewline
36 & -0.036122 & -0.2529 & 0.400719 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60239&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]0.339962[/C][C]2.3797[/C][C]0.010631[/C][/ROW]
[ROW][C]2[/C][C]0.397768[/C][C]2.7844[/C][C]0.003801[/C][/ROW]
[ROW][C]3[/C][C]0.246816[/C][C]1.7277[/C][C]0.045169[/C][/ROW]
[ROW][C]4[/C][C]0.204901[/C][C]1.4343[/C][C]0.078919[/C][/ROW]
[ROW][C]5[/C][C]0.050914[/C][C]0.3564[/C][C]0.361536[/C][/ROW]
[ROW][C]6[/C][C]0.095492[/C][C]0.6684[/C][C]0.253493[/C][/ROW]
[ROW][C]7[/C][C]0.005626[/C][C]0.0394[/C][C]0.484372[/C][/ROW]
[ROW][C]8[/C][C]0.011984[/C][C]0.0839[/C][C]0.466745[/C][/ROW]
[ROW][C]9[/C][C]-0.092176[/C][C]-0.6452[/C][C]0.260893[/C][/ROW]
[ROW][C]10[/C][C]-0.116741[/C][C]-0.8172[/C][C]0.208889[/C][/ROW]
[ROW][C]11[/C][C]-0.152624[/C][C]-1.0684[/C][C]0.145295[/C][/ROW]
[ROW][C]12[/C][C]-0.416136[/C][C]-2.913[/C][C]0.00269[/C][/ROW]
[ROW][C]13[/C][C]-0.202958[/C][C]-1.4207[/C][C]0.080868[/C][/ROW]
[ROW][C]14[/C][C]-0.240483[/C][C]-1.6834[/C][C]0.049331[/C][/ROW]
[ROW][C]15[/C][C]-0.197077[/C][C]-1.3795[/C][C]0.086996[/C][/ROW]
[ROW][C]16[/C][C]-0.232178[/C][C]-1.6252[/C][C]0.055263[/C][/ROW]
[ROW][C]17[/C][C]-0.060083[/C][C]-0.4206[/C][C]0.337949[/C][/ROW]
[ROW][C]18[/C][C]-0.123254[/C][C]-0.8628[/C][C]0.196231[/C][/ROW]
[ROW][C]19[/C][C]-0.061195[/C][C]-0.4284[/C][C]0.335131[/C][/ROW]
[ROW][C]20[/C][C]-0.134874[/C][C]-0.9441[/C][C]0.17487[/C][/ROW]
[ROW][C]21[/C][C]0.017867[/C][C]0.1251[/C][C]0.45049[/C][/ROW]
[ROW][C]22[/C][C]-0.02856[/C][C]-0.1999[/C][C]0.421185[/C][/ROW]
[ROW][C]23[/C][C]0.129162[/C][C]0.9041[/C][C]0.185175[/C][/ROW]
[ROW][C]24[/C][C]0.052546[/C][C]0.3678[/C][C]0.357296[/C][/ROW]
[ROW][C]25[/C][C]0.196044[/C][C]1.3723[/C][C]0.088109[/C][/ROW]
[ROW][C]26[/C][C]0.103804[/C][C]0.7266[/C][C]0.235456[/C][/ROW]
[ROW][C]27[/C][C]0.173411[/C][C]1.2139[/C][C]0.115307[/C][/ROW]
[ROW][C]28[/C][C]0.107233[/C][C]0.7506[/C][C]0.228233[/C][/ROW]
[ROW][C]29[/C][C]0.077024[/C][C]0.5392[/C][C]0.296107[/C][/ROW]
[ROW][C]30[/C][C]0.060444[/C][C]0.4231[/C][C]0.337033[/C][/ROW]
[ROW][C]31[/C][C]0.065438[/C][C]0.4581[/C][C]0.324465[/C][/ROW]
[ROW][C]32[/C][C]0.14257[/C][C]0.998[/C][C]0.161594[/C][/ROW]
[ROW][C]33[/C][C]0.039472[/C][C]0.2763[/C][C]0.391739[/C][/ROW]
[ROW][C]34[/C][C]0.011891[/C][C]0.0832[/C][C]0.467[/C][/ROW]
[ROW][C]35[/C][C]-0.054887[/C][C]-0.3842[/C][C]0.351243[/C][/ROW]
[ROW][C]36[/C][C]-0.036122[/C][C]-0.2529[/C][C]0.400719[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60239&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60239&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3399622.37970.010631
20.3977682.78440.003801
30.2468161.72770.045169
40.2049011.43430.078919
50.0509140.35640.361536
60.0954920.66840.253493
70.0056260.03940.484372
80.0119840.08390.466745
9-0.092176-0.64520.260893
10-0.116741-0.81720.208889
11-0.152624-1.06840.145295
12-0.416136-2.9130.00269
13-0.202958-1.42070.080868
14-0.240483-1.68340.049331
15-0.197077-1.37950.086996
16-0.232178-1.62520.055263
17-0.060083-0.42060.337949
18-0.123254-0.86280.196231
19-0.061195-0.42840.335131
20-0.134874-0.94410.17487
210.0178670.12510.45049
22-0.02856-0.19990.421185
230.1291620.90410.185175
240.0525460.36780.357296
250.1960441.37230.088109
260.1038040.72660.235456
270.1734111.21390.115307
280.1072330.75060.228233
290.0770240.53920.296107
300.0604440.42310.337033
310.0654380.45810.324465
320.142570.9980.161594
330.0394720.27630.391739
340.0118910.08320.467
35-0.054887-0.38420.351243
36-0.036122-0.25290.400719







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3399622.37970.010631
20.3190692.23350.015057
30.058240.40770.342643
40.0138940.09730.46146
5-0.118293-0.8280.205829
60.0304830.21340.415957
7-0.021585-0.15110.44026
8-0.008636-0.06040.476022
9-0.103931-0.72750.235186
10-0.103433-0.7240.236244
11-0.052789-0.36950.356666
12-0.37597-2.63180.005663
130.0692670.48490.314964
140.057640.40350.344176
15-0.006506-0.04550.481929
16-0.092078-0.64450.261113
170.0624720.43730.331907
180.0256530.17960.429116
19-0.038303-0.26810.394865
20-0.098943-0.69260.245914
210.0495410.34680.365117
220.0216740.15170.440015
230.1285840.90010.186238
24-0.19067-1.33470.094073
250.131450.92010.181001
260.0109410.07660.469631
270.016350.11450.454674
28-0.091008-0.63710.263527
29-0.016272-0.11390.454889
300.0423550.29650.384057
31-0.032259-0.22580.411143
320.089340.62540.267311
33-0.018706-0.13090.448178
34-0.092996-0.6510.259053
350.0023030.01610.493602
36-0.110689-0.77480.221083

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.339962 & 2.3797 & 0.010631 \tabularnewline
2 & 0.319069 & 2.2335 & 0.015057 \tabularnewline
3 & 0.05824 & 0.4077 & 0.342643 \tabularnewline
4 & 0.013894 & 0.0973 & 0.46146 \tabularnewline
5 & -0.118293 & -0.828 & 0.205829 \tabularnewline
6 & 0.030483 & 0.2134 & 0.415957 \tabularnewline
7 & -0.021585 & -0.1511 & 0.44026 \tabularnewline
8 & -0.008636 & -0.0604 & 0.476022 \tabularnewline
9 & -0.103931 & -0.7275 & 0.235186 \tabularnewline
10 & -0.103433 & -0.724 & 0.236244 \tabularnewline
11 & -0.052789 & -0.3695 & 0.356666 \tabularnewline
12 & -0.37597 & -2.6318 & 0.005663 \tabularnewline
13 & 0.069267 & 0.4849 & 0.314964 \tabularnewline
14 & 0.05764 & 0.4035 & 0.344176 \tabularnewline
15 & -0.006506 & -0.0455 & 0.481929 \tabularnewline
16 & -0.092078 & -0.6445 & 0.261113 \tabularnewline
17 & 0.062472 & 0.4373 & 0.331907 \tabularnewline
18 & 0.025653 & 0.1796 & 0.429116 \tabularnewline
19 & -0.038303 & -0.2681 & 0.394865 \tabularnewline
20 & -0.098943 & -0.6926 & 0.245914 \tabularnewline
21 & 0.049541 & 0.3468 & 0.365117 \tabularnewline
22 & 0.021674 & 0.1517 & 0.440015 \tabularnewline
23 & 0.128584 & 0.9001 & 0.186238 \tabularnewline
24 & -0.19067 & -1.3347 & 0.094073 \tabularnewline
25 & 0.13145 & 0.9201 & 0.181001 \tabularnewline
26 & 0.010941 & 0.0766 & 0.469631 \tabularnewline
27 & 0.01635 & 0.1145 & 0.454674 \tabularnewline
28 & -0.091008 & -0.6371 & 0.263527 \tabularnewline
29 & -0.016272 & -0.1139 & 0.454889 \tabularnewline
30 & 0.042355 & 0.2965 & 0.384057 \tabularnewline
31 & -0.032259 & -0.2258 & 0.411143 \tabularnewline
32 & 0.08934 & 0.6254 & 0.267311 \tabularnewline
33 & -0.018706 & -0.1309 & 0.448178 \tabularnewline
34 & -0.092996 & -0.651 & 0.259053 \tabularnewline
35 & 0.002303 & 0.0161 & 0.493602 \tabularnewline
36 & -0.110689 & -0.7748 & 0.221083 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60239&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]0.339962[/C][C]2.3797[/C][C]0.010631[/C][/ROW]
[ROW][C]2[/C][C]0.319069[/C][C]2.2335[/C][C]0.015057[/C][/ROW]
[ROW][C]3[/C][C]0.05824[/C][C]0.4077[/C][C]0.342643[/C][/ROW]
[ROW][C]4[/C][C]0.013894[/C][C]0.0973[/C][C]0.46146[/C][/ROW]
[ROW][C]5[/C][C]-0.118293[/C][C]-0.828[/C][C]0.205829[/C][/ROW]
[ROW][C]6[/C][C]0.030483[/C][C]0.2134[/C][C]0.415957[/C][/ROW]
[ROW][C]7[/C][C]-0.021585[/C][C]-0.1511[/C][C]0.44026[/C][/ROW]
[ROW][C]8[/C][C]-0.008636[/C][C]-0.0604[/C][C]0.476022[/C][/ROW]
[ROW][C]9[/C][C]-0.103931[/C][C]-0.7275[/C][C]0.235186[/C][/ROW]
[ROW][C]10[/C][C]-0.103433[/C][C]-0.724[/C][C]0.236244[/C][/ROW]
[ROW][C]11[/C][C]-0.052789[/C][C]-0.3695[/C][C]0.356666[/C][/ROW]
[ROW][C]12[/C][C]-0.37597[/C][C]-2.6318[/C][C]0.005663[/C][/ROW]
[ROW][C]13[/C][C]0.069267[/C][C]0.4849[/C][C]0.314964[/C][/ROW]
[ROW][C]14[/C][C]0.05764[/C][C]0.4035[/C][C]0.344176[/C][/ROW]
[ROW][C]15[/C][C]-0.006506[/C][C]-0.0455[/C][C]0.481929[/C][/ROW]
[ROW][C]16[/C][C]-0.092078[/C][C]-0.6445[/C][C]0.261113[/C][/ROW]
[ROW][C]17[/C][C]0.062472[/C][C]0.4373[/C][C]0.331907[/C][/ROW]
[ROW][C]18[/C][C]0.025653[/C][C]0.1796[/C][C]0.429116[/C][/ROW]
[ROW][C]19[/C][C]-0.038303[/C][C]-0.2681[/C][C]0.394865[/C][/ROW]
[ROW][C]20[/C][C]-0.098943[/C][C]-0.6926[/C][C]0.245914[/C][/ROW]
[ROW][C]21[/C][C]0.049541[/C][C]0.3468[/C][C]0.365117[/C][/ROW]
[ROW][C]22[/C][C]0.021674[/C][C]0.1517[/C][C]0.440015[/C][/ROW]
[ROW][C]23[/C][C]0.128584[/C][C]0.9001[/C][C]0.186238[/C][/ROW]
[ROW][C]24[/C][C]-0.19067[/C][C]-1.3347[/C][C]0.094073[/C][/ROW]
[ROW][C]25[/C][C]0.13145[/C][C]0.9201[/C][C]0.181001[/C][/ROW]
[ROW][C]26[/C][C]0.010941[/C][C]0.0766[/C][C]0.469631[/C][/ROW]
[ROW][C]27[/C][C]0.01635[/C][C]0.1145[/C][C]0.454674[/C][/ROW]
[ROW][C]28[/C][C]-0.091008[/C][C]-0.6371[/C][C]0.263527[/C][/ROW]
[ROW][C]29[/C][C]-0.016272[/C][C]-0.1139[/C][C]0.454889[/C][/ROW]
[ROW][C]30[/C][C]0.042355[/C][C]0.2965[/C][C]0.384057[/C][/ROW]
[ROW][C]31[/C][C]-0.032259[/C][C]-0.2258[/C][C]0.411143[/C][/ROW]
[ROW][C]32[/C][C]0.08934[/C][C]0.6254[/C][C]0.267311[/C][/ROW]
[ROW][C]33[/C][C]-0.018706[/C][C]-0.1309[/C][C]0.448178[/C][/ROW]
[ROW][C]34[/C][C]-0.092996[/C][C]-0.651[/C][C]0.259053[/C][/ROW]
[ROW][C]35[/C][C]0.002303[/C][C]0.0161[/C][C]0.493602[/C][/ROW]
[ROW][C]36[/C][C]-0.110689[/C][C]-0.7748[/C][C]0.221083[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60239&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60239&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3399622.37970.010631
20.3190692.23350.015057
30.058240.40770.342643
40.0138940.09730.46146
5-0.118293-0.8280.205829
60.0304830.21340.415957
7-0.021585-0.15110.44026
8-0.008636-0.06040.476022
9-0.103931-0.72750.235186
10-0.103433-0.7240.236244
11-0.052789-0.36950.356666
12-0.37597-2.63180.005663
130.0692670.48490.314964
140.057640.40350.344176
15-0.006506-0.04550.481929
16-0.092078-0.64450.261113
170.0624720.43730.331907
180.0256530.17960.429116
19-0.038303-0.26810.394865
20-0.098943-0.69260.245914
210.0495410.34680.365117
220.0216740.15170.440015
230.1285840.90010.186238
24-0.19067-1.33470.094073
250.131450.92010.181001
260.0109410.07660.469631
270.016350.11450.454674
28-0.091008-0.63710.263527
29-0.016272-0.11390.454889
300.0423550.29650.384057
31-0.032259-0.22580.411143
320.089340.62540.267311
33-0.018706-0.13090.448178
34-0.092996-0.6510.259053
350.0023030.01610.493602
36-0.110689-0.77480.221083



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')