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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 computationTue, 24 Nov 2009 09:15:49 -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/24/t1259079443nzgwwqjvnnrm517.htm/, Retrieved Mon, 15 Apr 2024 15:02:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59145, Retrieved Mon, 15 Apr 2024 15:02:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsws8ma1.2
Estimated Impact136
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]
-   PD          [(Partial) Autocorrelation Function] [] [2009-11-24 16:15:49] [9ea4b07b6662a0f40f92decdf1e3b5d5] [Current]
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Dataseries X:
2756.76
2849.27
2921.44
2981.85
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3801.06
3570.12
3701.61
3862.27
3970.1
4138.52
4199.75
4290.89
4443.91
4502.64
4356.98
4591.27
4696.96
4621.4
4562.84
4202.52
4296.49
4435.23
4105.18
4116.68
3844.49
3720.98
3674.4
3857.62
3801.06
3504.37
3032.6
3047.03
2962.34
2197.82
2014.45
1862.83
1905.41
1810.99
1670.07
1864.44
2052.02
2029.6
2070.83
2293.41
2443.27




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=59145&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=59145&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59145&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
10.2893652.22270.015042
20.0773040.59380.277464
30.2278041.74980.042676
40.2360641.81320.037441
50.24681.89570.03145
6-0.030815-0.23670.406858
7-0.030108-0.23130.408954
80.152511.17140.123064
90.0313750.2410.405198
10-0.149441-1.14790.127826
110.1325071.01780.156463
120.0245290.18840.4256
13-0.039008-0.29960.382759
140.0664620.51050.305803
15-0.026186-0.20110.420642
160.048380.37160.355755
17-0.134068-1.02980.153654
18-0.196045-1.50580.068721
190.0168850.12970.448623
20-0.078289-0.60130.274956
21-0.151189-1.16130.125098
22-0.173273-1.33090.094165
23-0.137716-1.05780.147226
24-0.123509-0.94870.173325
25-0.059353-0.45590.325069
26-0.095164-0.7310.233846
27-0.036772-0.28250.389292
280.0561660.43140.333868
29-0.025977-0.19950.421267
30-0.044455-0.34150.366984
31-0.075777-0.58210.281374
32-0.042673-0.32780.37212
33-0.059676-0.45840.324181
34-0.078998-0.60680.273158
35-0.119823-0.92040.180562
36-0.064781-0.49760.310311

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.289365 & 2.2227 & 0.015042 \tabularnewline
2 & 0.077304 & 0.5938 & 0.277464 \tabularnewline
3 & 0.227804 & 1.7498 & 0.042676 \tabularnewline
4 & 0.236064 & 1.8132 & 0.037441 \tabularnewline
5 & 0.2468 & 1.8957 & 0.03145 \tabularnewline
6 & -0.030815 & -0.2367 & 0.406858 \tabularnewline
7 & -0.030108 & -0.2313 & 0.408954 \tabularnewline
8 & 0.15251 & 1.1714 & 0.123064 \tabularnewline
9 & 0.031375 & 0.241 & 0.405198 \tabularnewline
10 & -0.149441 & -1.1479 & 0.127826 \tabularnewline
11 & 0.132507 & 1.0178 & 0.156463 \tabularnewline
12 & 0.024529 & 0.1884 & 0.4256 \tabularnewline
13 & -0.039008 & -0.2996 & 0.382759 \tabularnewline
14 & 0.066462 & 0.5105 & 0.305803 \tabularnewline
15 & -0.026186 & -0.2011 & 0.420642 \tabularnewline
16 & 0.04838 & 0.3716 & 0.355755 \tabularnewline
17 & -0.134068 & -1.0298 & 0.153654 \tabularnewline
18 & -0.196045 & -1.5058 & 0.068721 \tabularnewline
19 & 0.016885 & 0.1297 & 0.448623 \tabularnewline
20 & -0.078289 & -0.6013 & 0.274956 \tabularnewline
21 & -0.151189 & -1.1613 & 0.125098 \tabularnewline
22 & -0.173273 & -1.3309 & 0.094165 \tabularnewline
23 & -0.137716 & -1.0578 & 0.147226 \tabularnewline
24 & -0.123509 & -0.9487 & 0.173325 \tabularnewline
25 & -0.059353 & -0.4559 & 0.325069 \tabularnewline
26 & -0.095164 & -0.731 & 0.233846 \tabularnewline
27 & -0.036772 & -0.2825 & 0.389292 \tabularnewline
28 & 0.056166 & 0.4314 & 0.333868 \tabularnewline
29 & -0.025977 & -0.1995 & 0.421267 \tabularnewline
30 & -0.044455 & -0.3415 & 0.366984 \tabularnewline
31 & -0.075777 & -0.5821 & 0.281374 \tabularnewline
32 & -0.042673 & -0.3278 & 0.37212 \tabularnewline
33 & -0.059676 & -0.4584 & 0.324181 \tabularnewline
34 & -0.078998 & -0.6068 & 0.273158 \tabularnewline
35 & -0.119823 & -0.9204 & 0.180562 \tabularnewline
36 & -0.064781 & -0.4976 & 0.310311 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59145&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]0.289365[/C][C]2.2227[/C][C]0.015042[/C][/ROW]
[ROW][C]2[/C][C]0.077304[/C][C]0.5938[/C][C]0.277464[/C][/ROW]
[ROW][C]3[/C][C]0.227804[/C][C]1.7498[/C][C]0.042676[/C][/ROW]
[ROW][C]4[/C][C]0.236064[/C][C]1.8132[/C][C]0.037441[/C][/ROW]
[ROW][C]5[/C][C]0.2468[/C][C]1.8957[/C][C]0.03145[/C][/ROW]
[ROW][C]6[/C][C]-0.030815[/C][C]-0.2367[/C][C]0.406858[/C][/ROW]
[ROW][C]7[/C][C]-0.030108[/C][C]-0.2313[/C][C]0.408954[/C][/ROW]
[ROW][C]8[/C][C]0.15251[/C][C]1.1714[/C][C]0.123064[/C][/ROW]
[ROW][C]9[/C][C]0.031375[/C][C]0.241[/C][C]0.405198[/C][/ROW]
[ROW][C]10[/C][C]-0.149441[/C][C]-1.1479[/C][C]0.127826[/C][/ROW]
[ROW][C]11[/C][C]0.132507[/C][C]1.0178[/C][C]0.156463[/C][/ROW]
[ROW][C]12[/C][C]0.024529[/C][C]0.1884[/C][C]0.4256[/C][/ROW]
[ROW][C]13[/C][C]-0.039008[/C][C]-0.2996[/C][C]0.382759[/C][/ROW]
[ROW][C]14[/C][C]0.066462[/C][C]0.5105[/C][C]0.305803[/C][/ROW]
[ROW][C]15[/C][C]-0.026186[/C][C]-0.2011[/C][C]0.420642[/C][/ROW]
[ROW][C]16[/C][C]0.04838[/C][C]0.3716[/C][C]0.355755[/C][/ROW]
[ROW][C]17[/C][C]-0.134068[/C][C]-1.0298[/C][C]0.153654[/C][/ROW]
[ROW][C]18[/C][C]-0.196045[/C][C]-1.5058[/C][C]0.068721[/C][/ROW]
[ROW][C]19[/C][C]0.016885[/C][C]0.1297[/C][C]0.448623[/C][/ROW]
[ROW][C]20[/C][C]-0.078289[/C][C]-0.6013[/C][C]0.274956[/C][/ROW]
[ROW][C]21[/C][C]-0.151189[/C][C]-1.1613[/C][C]0.125098[/C][/ROW]
[ROW][C]22[/C][C]-0.173273[/C][C]-1.3309[/C][C]0.094165[/C][/ROW]
[ROW][C]23[/C][C]-0.137716[/C][C]-1.0578[/C][C]0.147226[/C][/ROW]
[ROW][C]24[/C][C]-0.123509[/C][C]-0.9487[/C][C]0.173325[/C][/ROW]
[ROW][C]25[/C][C]-0.059353[/C][C]-0.4559[/C][C]0.325069[/C][/ROW]
[ROW][C]26[/C][C]-0.095164[/C][C]-0.731[/C][C]0.233846[/C][/ROW]
[ROW][C]27[/C][C]-0.036772[/C][C]-0.2825[/C][C]0.389292[/C][/ROW]
[ROW][C]28[/C][C]0.056166[/C][C]0.4314[/C][C]0.333868[/C][/ROW]
[ROW][C]29[/C][C]-0.025977[/C][C]-0.1995[/C][C]0.421267[/C][/ROW]
[ROW][C]30[/C][C]-0.044455[/C][C]-0.3415[/C][C]0.366984[/C][/ROW]
[ROW][C]31[/C][C]-0.075777[/C][C]-0.5821[/C][C]0.281374[/C][/ROW]
[ROW][C]32[/C][C]-0.042673[/C][C]-0.3278[/C][C]0.37212[/C][/ROW]
[ROW][C]33[/C][C]-0.059676[/C][C]-0.4584[/C][C]0.324181[/C][/ROW]
[ROW][C]34[/C][C]-0.078998[/C][C]-0.6068[/C][C]0.273158[/C][/ROW]
[ROW][C]35[/C][C]-0.119823[/C][C]-0.9204[/C][C]0.180562[/C][/ROW]
[ROW][C]36[/C][C]-0.064781[/C][C]-0.4976[/C][C]0.310311[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59145&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59145&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
10.2893652.22270.015042
20.0773040.59380.277464
30.2278041.74980.042676
40.2360641.81320.037441
50.24681.89570.03145
6-0.030815-0.23670.406858
7-0.030108-0.23130.408954
80.152511.17140.123064
90.0313750.2410.405198
10-0.149441-1.14790.127826
110.1325071.01780.156463
120.0245290.18840.4256
13-0.039008-0.29960.382759
140.0664620.51050.305803
15-0.026186-0.20110.420642
160.048380.37160.355755
17-0.134068-1.02980.153654
18-0.196045-1.50580.068721
190.0168850.12970.448623
20-0.078289-0.60130.274956
21-0.151189-1.16130.125098
22-0.173273-1.33090.094165
23-0.137716-1.05780.147226
24-0.123509-0.94870.173325
25-0.059353-0.45590.325069
26-0.095164-0.7310.233846
27-0.036772-0.28250.389292
280.0561660.43140.333868
29-0.025977-0.19950.421267
30-0.044455-0.34150.366984
31-0.075777-0.58210.281374
32-0.042673-0.32780.37212
33-0.059676-0.45840.324181
34-0.078998-0.60680.273158
35-0.119823-0.92040.180562
36-0.064781-0.49760.310311







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2893652.22270.015042
2-0.007015-0.05390.478604
30.2262641.7380.043717
40.1259470.96740.168642
50.1727661.3270.094804
6-0.204566-1.57130.06073
7-0.03841-0.2950.384502
80.0729870.56060.288587
9-0.053387-0.41010.341618
10-0.16041-1.23210.111394
110.2961912.27510.013275
12-0.141161-1.08430.141325
13-0.007511-0.05770.477093
140.123470.94840.1734
15-0.045248-0.34760.364706
16-0.09452-0.7260.235348
17-0.131346-1.00890.158574
18-0.080911-0.62150.268336
190.0002770.00210.499155
20-0.063882-0.49070.312735
210.0895930.68820.24702
22-0.171315-1.31590.096649
23-0.011518-0.08850.464902
24-0.077689-0.59670.276482
250.0742420.57030.285331
26-4.2e-05-3e-040.499872
270.0386690.2970.383746
280.1125690.86470.195363
290.0219040.16820.433483
30-0.184844-1.41980.080462
310.0199490.15320.439369
32-0.074494-0.57220.28468
33-0.092949-0.7140.239036
34-0.00566-0.04350.482736
35-0.014589-0.11210.455579
360.0005460.00420.498333

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.289365 & 2.2227 & 0.015042 \tabularnewline
2 & -0.007015 & -0.0539 & 0.478604 \tabularnewline
3 & 0.226264 & 1.738 & 0.043717 \tabularnewline
4 & 0.125947 & 0.9674 & 0.168642 \tabularnewline
5 & 0.172766 & 1.327 & 0.094804 \tabularnewline
6 & -0.204566 & -1.5713 & 0.06073 \tabularnewline
7 & -0.03841 & -0.295 & 0.384502 \tabularnewline
8 & 0.072987 & 0.5606 & 0.288587 \tabularnewline
9 & -0.053387 & -0.4101 & 0.341618 \tabularnewline
10 & -0.16041 & -1.2321 & 0.111394 \tabularnewline
11 & 0.296191 & 2.2751 & 0.013275 \tabularnewline
12 & -0.141161 & -1.0843 & 0.141325 \tabularnewline
13 & -0.007511 & -0.0577 & 0.477093 \tabularnewline
14 & 0.12347 & 0.9484 & 0.1734 \tabularnewline
15 & -0.045248 & -0.3476 & 0.364706 \tabularnewline
16 & -0.09452 & -0.726 & 0.235348 \tabularnewline
17 & -0.131346 & -1.0089 & 0.158574 \tabularnewline
18 & -0.080911 & -0.6215 & 0.268336 \tabularnewline
19 & 0.000277 & 0.0021 & 0.499155 \tabularnewline
20 & -0.063882 & -0.4907 & 0.312735 \tabularnewline
21 & 0.089593 & 0.6882 & 0.24702 \tabularnewline
22 & -0.171315 & -1.3159 & 0.096649 \tabularnewline
23 & -0.011518 & -0.0885 & 0.464902 \tabularnewline
24 & -0.077689 & -0.5967 & 0.276482 \tabularnewline
25 & 0.074242 & 0.5703 & 0.285331 \tabularnewline
26 & -4.2e-05 & -3e-04 & 0.499872 \tabularnewline
27 & 0.038669 & 0.297 & 0.383746 \tabularnewline
28 & 0.112569 & 0.8647 & 0.195363 \tabularnewline
29 & 0.021904 & 0.1682 & 0.433483 \tabularnewline
30 & -0.184844 & -1.4198 & 0.080462 \tabularnewline
31 & 0.019949 & 0.1532 & 0.439369 \tabularnewline
32 & -0.074494 & -0.5722 & 0.28468 \tabularnewline
33 & -0.092949 & -0.714 & 0.239036 \tabularnewline
34 & -0.00566 & -0.0435 & 0.482736 \tabularnewline
35 & -0.014589 & -0.1121 & 0.455579 \tabularnewline
36 & 0.000546 & 0.0042 & 0.498333 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59145&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]0.289365[/C][C]2.2227[/C][C]0.015042[/C][/ROW]
[ROW][C]2[/C][C]-0.007015[/C][C]-0.0539[/C][C]0.478604[/C][/ROW]
[ROW][C]3[/C][C]0.226264[/C][C]1.738[/C][C]0.043717[/C][/ROW]
[ROW][C]4[/C][C]0.125947[/C][C]0.9674[/C][C]0.168642[/C][/ROW]
[ROW][C]5[/C][C]0.172766[/C][C]1.327[/C][C]0.094804[/C][/ROW]
[ROW][C]6[/C][C]-0.204566[/C][C]-1.5713[/C][C]0.06073[/C][/ROW]
[ROW][C]7[/C][C]-0.03841[/C][C]-0.295[/C][C]0.384502[/C][/ROW]
[ROW][C]8[/C][C]0.072987[/C][C]0.5606[/C][C]0.288587[/C][/ROW]
[ROW][C]9[/C][C]-0.053387[/C][C]-0.4101[/C][C]0.341618[/C][/ROW]
[ROW][C]10[/C][C]-0.16041[/C][C]-1.2321[/C][C]0.111394[/C][/ROW]
[ROW][C]11[/C][C]0.296191[/C][C]2.2751[/C][C]0.013275[/C][/ROW]
[ROW][C]12[/C][C]-0.141161[/C][C]-1.0843[/C][C]0.141325[/C][/ROW]
[ROW][C]13[/C][C]-0.007511[/C][C]-0.0577[/C][C]0.477093[/C][/ROW]
[ROW][C]14[/C][C]0.12347[/C][C]0.9484[/C][C]0.1734[/C][/ROW]
[ROW][C]15[/C][C]-0.045248[/C][C]-0.3476[/C][C]0.364706[/C][/ROW]
[ROW][C]16[/C][C]-0.09452[/C][C]-0.726[/C][C]0.235348[/C][/ROW]
[ROW][C]17[/C][C]-0.131346[/C][C]-1.0089[/C][C]0.158574[/C][/ROW]
[ROW][C]18[/C][C]-0.080911[/C][C]-0.6215[/C][C]0.268336[/C][/ROW]
[ROW][C]19[/C][C]0.000277[/C][C]0.0021[/C][C]0.499155[/C][/ROW]
[ROW][C]20[/C][C]-0.063882[/C][C]-0.4907[/C][C]0.312735[/C][/ROW]
[ROW][C]21[/C][C]0.089593[/C][C]0.6882[/C][C]0.24702[/C][/ROW]
[ROW][C]22[/C][C]-0.171315[/C][C]-1.3159[/C][C]0.096649[/C][/ROW]
[ROW][C]23[/C][C]-0.011518[/C][C]-0.0885[/C][C]0.464902[/C][/ROW]
[ROW][C]24[/C][C]-0.077689[/C][C]-0.5967[/C][C]0.276482[/C][/ROW]
[ROW][C]25[/C][C]0.074242[/C][C]0.5703[/C][C]0.285331[/C][/ROW]
[ROW][C]26[/C][C]-4.2e-05[/C][C]-3e-04[/C][C]0.499872[/C][/ROW]
[ROW][C]27[/C][C]0.038669[/C][C]0.297[/C][C]0.383746[/C][/ROW]
[ROW][C]28[/C][C]0.112569[/C][C]0.8647[/C][C]0.195363[/C][/ROW]
[ROW][C]29[/C][C]0.021904[/C][C]0.1682[/C][C]0.433483[/C][/ROW]
[ROW][C]30[/C][C]-0.184844[/C][C]-1.4198[/C][C]0.080462[/C][/ROW]
[ROW][C]31[/C][C]0.019949[/C][C]0.1532[/C][C]0.439369[/C][/ROW]
[ROW][C]32[/C][C]-0.074494[/C][C]-0.5722[/C][C]0.28468[/C][/ROW]
[ROW][C]33[/C][C]-0.092949[/C][C]-0.714[/C][C]0.239036[/C][/ROW]
[ROW][C]34[/C][C]-0.00566[/C][C]-0.0435[/C][C]0.482736[/C][/ROW]
[ROW][C]35[/C][C]-0.014589[/C][C]-0.1121[/C][C]0.455579[/C][/ROW]
[ROW][C]36[/C][C]0.000546[/C][C]0.0042[/C][C]0.498333[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59145&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59145&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
10.2893652.22270.015042
2-0.007015-0.05390.478604
30.2262641.7380.043717
40.1259470.96740.168642
50.1727661.3270.094804
6-0.204566-1.57130.06073
7-0.03841-0.2950.384502
80.0729870.56060.288587
9-0.053387-0.41010.341618
10-0.16041-1.23210.111394
110.2961912.27510.013275
12-0.141161-1.08430.141325
13-0.007511-0.05770.477093
140.123470.94840.1734
15-0.045248-0.34760.364706
16-0.09452-0.7260.235348
17-0.131346-1.00890.158574
18-0.080911-0.62150.268336
190.0002770.00210.499155
20-0.063882-0.49070.312735
210.0895930.68820.24702
22-0.171315-1.31590.096649
23-0.011518-0.08850.464902
24-0.077689-0.59670.276482
250.0742420.57030.285331
26-4.2e-05-3e-040.499872
270.0386690.2970.383746
280.1125690.86470.195363
290.0219040.16820.433483
30-0.184844-1.41980.080462
310.0199490.15320.439369
32-0.074494-0.57220.28468
33-0.092949-0.7140.239036
34-0.00566-0.04350.482736
35-0.014589-0.11210.455579
360.0005460.00420.498333



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')