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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 computationSat, 19 Dec 2009 08:26:00 -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/19/t12612364037fdv5xjdviict69.htm/, Retrieved Fri, 03 May 2024 18:35:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69637, Retrieved Fri, 03 May 2024 18:35:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116
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]
-    D        [(Partial) Autocorrelation Function] [Model 1 (d = 0, D...] [2009-11-24 17:27:24] [ee7c2e7343f5b1451e62c5c16ec521f1]
- R PD            [(Partial) Autocorrelation Function] [] [2009-12-19 15:26:00] [d5175f34d1f80375edd7cbd8232724fe] [Current]
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Dataseries X:
1920
2218
3032
2375
2446
2916
2434
2540
2349
2310
2189
2660
2194
2419
2742
2137
2710
2173
2363
2126
1905
2121
1983
1734
2074
2049
2406
2558
2251
2059
2397
1747
1707
2319
1631
1627
1791
2034
1997
2169
2028
2253
2218
1855
2187
1852
1570
1851
1954
1828
2251
2277
2085
2282
2266
1878
2267
2069
1746
2299
2360
2214
2825
2355
2333
3016
2155
2172
2150
2533
2058
2160
2260
2498
2695
2799
2947
2930
2318
2540
2570
2669
2450
2842
3440
2678
2981
2260
2844
2546
2456
2295
2379
2479
2057
2280
2351
2276
2548
2311
2201
2725
2408
2139
1898
2537
2069
2063
2526
2440
2191
2797
2074
2628
2287
2146
2430
2141
1827
2082
1788




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69637&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]2 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=69637&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69637&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.4167074.58386e-06
20.4245654.67024e-06
30.4779625.25760
40.2411192.65230.004533
50.1948642.14350.017037
60.2072492.27970.012187
70.1387231.5260.064816
80.2374752.61220.005068
90.3183683.50210.000324
100.2323012.55530.005924
110.3136373.450.000386
120.3890214.27921.9e-05
130.2031782.2350.013628
140.2092392.30160.011533
150.1808461.98930.024462
160.0076590.08420.4665
170.0226040.24860.402028
18-0.080799-0.88880.187941
19-0.035392-0.38930.348864
20-0.029646-0.32610.372453
210.0654460.71990.236485
220.0238980.26290.396548
230.1146921.26160.104757
240.1069621.17660.120836
250.0484460.53290.297539
26-0.04764-0.5240.300604
27-0.123518-1.35870.088384
28-0.159106-1.75020.041312
29-0.246494-2.71140.003837
30-0.285344-3.13880.001066
31-0.26617-2.92790.002039
32-0.170985-1.88080.031199
33-0.194905-2.1440.017019
34-0.19687-2.16560.016153
35-0.151113-1.66220.049526
36-0.104358-1.14790.126628

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.416707 & 4.5838 & 6e-06 \tabularnewline
2 & 0.424565 & 4.6702 & 4e-06 \tabularnewline
3 & 0.477962 & 5.2576 & 0 \tabularnewline
4 & 0.241119 & 2.6523 & 0.004533 \tabularnewline
5 & 0.194864 & 2.1435 & 0.017037 \tabularnewline
6 & 0.207249 & 2.2797 & 0.012187 \tabularnewline
7 & 0.138723 & 1.526 & 0.064816 \tabularnewline
8 & 0.237475 & 2.6122 & 0.005068 \tabularnewline
9 & 0.318368 & 3.5021 & 0.000324 \tabularnewline
10 & 0.232301 & 2.5553 & 0.005924 \tabularnewline
11 & 0.313637 & 3.45 & 0.000386 \tabularnewline
12 & 0.389021 & 4.2792 & 1.9e-05 \tabularnewline
13 & 0.203178 & 2.235 & 0.013628 \tabularnewline
14 & 0.209239 & 2.3016 & 0.011533 \tabularnewline
15 & 0.180846 & 1.9893 & 0.024462 \tabularnewline
16 & 0.007659 & 0.0842 & 0.4665 \tabularnewline
17 & 0.022604 & 0.2486 & 0.402028 \tabularnewline
18 & -0.080799 & -0.8888 & 0.187941 \tabularnewline
19 & -0.035392 & -0.3893 & 0.348864 \tabularnewline
20 & -0.029646 & -0.3261 & 0.372453 \tabularnewline
21 & 0.065446 & 0.7199 & 0.236485 \tabularnewline
22 & 0.023898 & 0.2629 & 0.396548 \tabularnewline
23 & 0.114692 & 1.2616 & 0.104757 \tabularnewline
24 & 0.106962 & 1.1766 & 0.120836 \tabularnewline
25 & 0.048446 & 0.5329 & 0.297539 \tabularnewline
26 & -0.04764 & -0.524 & 0.300604 \tabularnewline
27 & -0.123518 & -1.3587 & 0.088384 \tabularnewline
28 & -0.159106 & -1.7502 & 0.041312 \tabularnewline
29 & -0.246494 & -2.7114 & 0.003837 \tabularnewline
30 & -0.285344 & -3.1388 & 0.001066 \tabularnewline
31 & -0.26617 & -2.9279 & 0.002039 \tabularnewline
32 & -0.170985 & -1.8808 & 0.031199 \tabularnewline
33 & -0.194905 & -2.144 & 0.017019 \tabularnewline
34 & -0.19687 & -2.1656 & 0.016153 \tabularnewline
35 & -0.151113 & -1.6622 & 0.049526 \tabularnewline
36 & -0.104358 & -1.1479 & 0.126628 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69637&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]0.416707[/C][C]4.5838[/C][C]6e-06[/C][/ROW]
[ROW][C]2[/C][C]0.424565[/C][C]4.6702[/C][C]4e-06[/C][/ROW]
[ROW][C]3[/C][C]0.477962[/C][C]5.2576[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.241119[/C][C]2.6523[/C][C]0.004533[/C][/ROW]
[ROW][C]5[/C][C]0.194864[/C][C]2.1435[/C][C]0.017037[/C][/ROW]
[ROW][C]6[/C][C]0.207249[/C][C]2.2797[/C][C]0.012187[/C][/ROW]
[ROW][C]7[/C][C]0.138723[/C][C]1.526[/C][C]0.064816[/C][/ROW]
[ROW][C]8[/C][C]0.237475[/C][C]2.6122[/C][C]0.005068[/C][/ROW]
[ROW][C]9[/C][C]0.318368[/C][C]3.5021[/C][C]0.000324[/C][/ROW]
[ROW][C]10[/C][C]0.232301[/C][C]2.5553[/C][C]0.005924[/C][/ROW]
[ROW][C]11[/C][C]0.313637[/C][C]3.45[/C][C]0.000386[/C][/ROW]
[ROW][C]12[/C][C]0.389021[/C][C]4.2792[/C][C]1.9e-05[/C][/ROW]
[ROW][C]13[/C][C]0.203178[/C][C]2.235[/C][C]0.013628[/C][/ROW]
[ROW][C]14[/C][C]0.209239[/C][C]2.3016[/C][C]0.011533[/C][/ROW]
[ROW][C]15[/C][C]0.180846[/C][C]1.9893[/C][C]0.024462[/C][/ROW]
[ROW][C]16[/C][C]0.007659[/C][C]0.0842[/C][C]0.4665[/C][/ROW]
[ROW][C]17[/C][C]0.022604[/C][C]0.2486[/C][C]0.402028[/C][/ROW]
[ROW][C]18[/C][C]-0.080799[/C][C]-0.8888[/C][C]0.187941[/C][/ROW]
[ROW][C]19[/C][C]-0.035392[/C][C]-0.3893[/C][C]0.348864[/C][/ROW]
[ROW][C]20[/C][C]-0.029646[/C][C]-0.3261[/C][C]0.372453[/C][/ROW]
[ROW][C]21[/C][C]0.065446[/C][C]0.7199[/C][C]0.236485[/C][/ROW]
[ROW][C]22[/C][C]0.023898[/C][C]0.2629[/C][C]0.396548[/C][/ROW]
[ROW][C]23[/C][C]0.114692[/C][C]1.2616[/C][C]0.104757[/C][/ROW]
[ROW][C]24[/C][C]0.106962[/C][C]1.1766[/C][C]0.120836[/C][/ROW]
[ROW][C]25[/C][C]0.048446[/C][C]0.5329[/C][C]0.297539[/C][/ROW]
[ROW][C]26[/C][C]-0.04764[/C][C]-0.524[/C][C]0.300604[/C][/ROW]
[ROW][C]27[/C][C]-0.123518[/C][C]-1.3587[/C][C]0.088384[/C][/ROW]
[ROW][C]28[/C][C]-0.159106[/C][C]-1.7502[/C][C]0.041312[/C][/ROW]
[ROW][C]29[/C][C]-0.246494[/C][C]-2.7114[/C][C]0.003837[/C][/ROW]
[ROW][C]30[/C][C]-0.285344[/C][C]-3.1388[/C][C]0.001066[/C][/ROW]
[ROW][C]31[/C][C]-0.26617[/C][C]-2.9279[/C][C]0.002039[/C][/ROW]
[ROW][C]32[/C][C]-0.170985[/C][C]-1.8808[/C][C]0.031199[/C][/ROW]
[ROW][C]33[/C][C]-0.194905[/C][C]-2.144[/C][C]0.017019[/C][/ROW]
[ROW][C]34[/C][C]-0.19687[/C][C]-2.1656[/C][C]0.016153[/C][/ROW]
[ROW][C]35[/C][C]-0.151113[/C][C]-1.6622[/C][C]0.049526[/C][/ROW]
[ROW][C]36[/C][C]-0.104358[/C][C]-1.1479[/C][C]0.126628[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69637&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69637&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
10.4167074.58386e-06
20.4245654.67024e-06
30.4779625.25760
40.2411192.65230.004533
50.1948642.14350.017037
60.2072492.27970.012187
70.1387231.5260.064816
80.2374752.61220.005068
90.3183683.50210.000324
100.2323012.55530.005924
110.3136373.450.000386
120.3890214.27921.9e-05
130.2031782.2350.013628
140.2092392.30160.011533
150.1808461.98930.024462
160.0076590.08420.4665
170.0226040.24860.402028
18-0.080799-0.88880.187941
19-0.035392-0.38930.348864
20-0.029646-0.32610.372453
210.0654460.71990.236485
220.0238980.26290.396548
230.1146921.26160.104757
240.1069621.17660.120836
250.0484460.53290.297539
26-0.04764-0.5240.300604
27-0.123518-1.35870.088384
28-0.159106-1.75020.041312
29-0.246494-2.71140.003837
30-0.285344-3.13880.001066
31-0.26617-2.92790.002039
32-0.170985-1.88080.031199
33-0.194905-2.1440.017019
34-0.19687-2.16560.016153
35-0.151113-1.66220.049526
36-0.104358-1.14790.126628







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4167074.58386e-06
20.3036483.34010.000557
30.3042433.34670.000545
4-0.105232-1.15760.124663
5-0.101713-1.11880.132712
60.0140950.1550.438521
70.0548130.60290.273836
80.2109662.32060.010991
90.2381572.61970.004963
10-0.001449-0.01590.493653
110.003980.04380.482576
120.122551.34810.09008
13-0.0857-0.94270.173856
14-0.067642-0.74410.229142
15-0.051563-0.56720.285817
16-0.138948-1.52840.064508
17-0.076024-0.83630.202326
18-0.179074-1.96980.025572
190.0543560.59790.275505
20-0.037786-0.41560.339202
210.1375441.5130.066445
22-0.024917-0.27410.392244
230.0368750.40560.342868
24-0.033457-0.3680.356748
250.0191540.21070.416738
26-0.152614-1.67880.04789
27-0.144542-1.590.057226
28-0.0263-0.28930.386422
29-0.069912-0.7690.221686
30-0.065743-0.72320.235485
31-0.092031-1.01230.156698
320.0980391.07840.141494
33-0.057248-0.62970.265031
34-0.118874-1.30760.096741
35-0.091568-1.00730.157912
360.053290.58620.279421

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.416707 & 4.5838 & 6e-06 \tabularnewline
2 & 0.303648 & 3.3401 & 0.000557 \tabularnewline
3 & 0.304243 & 3.3467 & 0.000545 \tabularnewline
4 & -0.105232 & -1.1576 & 0.124663 \tabularnewline
5 & -0.101713 & -1.1188 & 0.132712 \tabularnewline
6 & 0.014095 & 0.155 & 0.438521 \tabularnewline
7 & 0.054813 & 0.6029 & 0.273836 \tabularnewline
8 & 0.210966 & 2.3206 & 0.010991 \tabularnewline
9 & 0.238157 & 2.6197 & 0.004963 \tabularnewline
10 & -0.001449 & -0.0159 & 0.493653 \tabularnewline
11 & 0.00398 & 0.0438 & 0.482576 \tabularnewline
12 & 0.12255 & 1.3481 & 0.09008 \tabularnewline
13 & -0.0857 & -0.9427 & 0.173856 \tabularnewline
14 & -0.067642 & -0.7441 & 0.229142 \tabularnewline
15 & -0.051563 & -0.5672 & 0.285817 \tabularnewline
16 & -0.138948 & -1.5284 & 0.064508 \tabularnewline
17 & -0.076024 & -0.8363 & 0.202326 \tabularnewline
18 & -0.179074 & -1.9698 & 0.025572 \tabularnewline
19 & 0.054356 & 0.5979 & 0.275505 \tabularnewline
20 & -0.037786 & -0.4156 & 0.339202 \tabularnewline
21 & 0.137544 & 1.513 & 0.066445 \tabularnewline
22 & -0.024917 & -0.2741 & 0.392244 \tabularnewline
23 & 0.036875 & 0.4056 & 0.342868 \tabularnewline
24 & -0.033457 & -0.368 & 0.356748 \tabularnewline
25 & 0.019154 & 0.2107 & 0.416738 \tabularnewline
26 & -0.152614 & -1.6788 & 0.04789 \tabularnewline
27 & -0.144542 & -1.59 & 0.057226 \tabularnewline
28 & -0.0263 & -0.2893 & 0.386422 \tabularnewline
29 & -0.069912 & -0.769 & 0.221686 \tabularnewline
30 & -0.065743 & -0.7232 & 0.235485 \tabularnewline
31 & -0.092031 & -1.0123 & 0.156698 \tabularnewline
32 & 0.098039 & 1.0784 & 0.141494 \tabularnewline
33 & -0.057248 & -0.6297 & 0.265031 \tabularnewline
34 & -0.118874 & -1.3076 & 0.096741 \tabularnewline
35 & -0.091568 & -1.0073 & 0.157912 \tabularnewline
36 & 0.05329 & 0.5862 & 0.279421 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69637&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]0.416707[/C][C]4.5838[/C][C]6e-06[/C][/ROW]
[ROW][C]2[/C][C]0.303648[/C][C]3.3401[/C][C]0.000557[/C][/ROW]
[ROW][C]3[/C][C]0.304243[/C][C]3.3467[/C][C]0.000545[/C][/ROW]
[ROW][C]4[/C][C]-0.105232[/C][C]-1.1576[/C][C]0.124663[/C][/ROW]
[ROW][C]5[/C][C]-0.101713[/C][C]-1.1188[/C][C]0.132712[/C][/ROW]
[ROW][C]6[/C][C]0.014095[/C][C]0.155[/C][C]0.438521[/C][/ROW]
[ROW][C]7[/C][C]0.054813[/C][C]0.6029[/C][C]0.273836[/C][/ROW]
[ROW][C]8[/C][C]0.210966[/C][C]2.3206[/C][C]0.010991[/C][/ROW]
[ROW][C]9[/C][C]0.238157[/C][C]2.6197[/C][C]0.004963[/C][/ROW]
[ROW][C]10[/C][C]-0.001449[/C][C]-0.0159[/C][C]0.493653[/C][/ROW]
[ROW][C]11[/C][C]0.00398[/C][C]0.0438[/C][C]0.482576[/C][/ROW]
[ROW][C]12[/C][C]0.12255[/C][C]1.3481[/C][C]0.09008[/C][/ROW]
[ROW][C]13[/C][C]-0.0857[/C][C]-0.9427[/C][C]0.173856[/C][/ROW]
[ROW][C]14[/C][C]-0.067642[/C][C]-0.7441[/C][C]0.229142[/C][/ROW]
[ROW][C]15[/C][C]-0.051563[/C][C]-0.5672[/C][C]0.285817[/C][/ROW]
[ROW][C]16[/C][C]-0.138948[/C][C]-1.5284[/C][C]0.064508[/C][/ROW]
[ROW][C]17[/C][C]-0.076024[/C][C]-0.8363[/C][C]0.202326[/C][/ROW]
[ROW][C]18[/C][C]-0.179074[/C][C]-1.9698[/C][C]0.025572[/C][/ROW]
[ROW][C]19[/C][C]0.054356[/C][C]0.5979[/C][C]0.275505[/C][/ROW]
[ROW][C]20[/C][C]-0.037786[/C][C]-0.4156[/C][C]0.339202[/C][/ROW]
[ROW][C]21[/C][C]0.137544[/C][C]1.513[/C][C]0.066445[/C][/ROW]
[ROW][C]22[/C][C]-0.024917[/C][C]-0.2741[/C][C]0.392244[/C][/ROW]
[ROW][C]23[/C][C]0.036875[/C][C]0.4056[/C][C]0.342868[/C][/ROW]
[ROW][C]24[/C][C]-0.033457[/C][C]-0.368[/C][C]0.356748[/C][/ROW]
[ROW][C]25[/C][C]0.019154[/C][C]0.2107[/C][C]0.416738[/C][/ROW]
[ROW][C]26[/C][C]-0.152614[/C][C]-1.6788[/C][C]0.04789[/C][/ROW]
[ROW][C]27[/C][C]-0.144542[/C][C]-1.59[/C][C]0.057226[/C][/ROW]
[ROW][C]28[/C][C]-0.0263[/C][C]-0.2893[/C][C]0.386422[/C][/ROW]
[ROW][C]29[/C][C]-0.069912[/C][C]-0.769[/C][C]0.221686[/C][/ROW]
[ROW][C]30[/C][C]-0.065743[/C][C]-0.7232[/C][C]0.235485[/C][/ROW]
[ROW][C]31[/C][C]-0.092031[/C][C]-1.0123[/C][C]0.156698[/C][/ROW]
[ROW][C]32[/C][C]0.098039[/C][C]1.0784[/C][C]0.141494[/C][/ROW]
[ROW][C]33[/C][C]-0.057248[/C][C]-0.6297[/C][C]0.265031[/C][/ROW]
[ROW][C]34[/C][C]-0.118874[/C][C]-1.3076[/C][C]0.096741[/C][/ROW]
[ROW][C]35[/C][C]-0.091568[/C][C]-1.0073[/C][C]0.157912[/C][/ROW]
[ROW][C]36[/C][C]0.05329[/C][C]0.5862[/C][C]0.279421[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69637&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69637&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
10.4167074.58386e-06
20.3036483.34010.000557
30.3042433.34670.000545
4-0.105232-1.15760.124663
5-0.101713-1.11880.132712
60.0140950.1550.438521
70.0548130.60290.273836
80.2109662.32060.010991
90.2381572.61970.004963
10-0.001449-0.01590.493653
110.003980.04380.482576
120.122551.34810.09008
13-0.0857-0.94270.173856
14-0.067642-0.74410.229142
15-0.051563-0.56720.285817
16-0.138948-1.52840.064508
17-0.076024-0.83630.202326
18-0.179074-1.96980.025572
190.0543560.59790.275505
20-0.037786-0.41560.339202
210.1375441.5130.066445
22-0.024917-0.27410.392244
230.0368750.40560.342868
24-0.033457-0.3680.356748
250.0191540.21070.416738
26-0.152614-1.67880.04789
27-0.144542-1.590.057226
28-0.0263-0.28930.386422
29-0.069912-0.7690.221686
30-0.065743-0.72320.235485
31-0.092031-1.01230.156698
320.0980391.07840.141494
33-0.057248-0.62970.265031
34-0.118874-1.30760.096741
35-0.091568-1.00730.157912
360.053290.58620.279421



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; 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')