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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 13:15:25 -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/t1259266633dzp9e254tza4xut.htm/, Retrieved Sun, 28 Apr 2024 20:22:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60361, Retrieved Sun, 28 Apr 2024 20:22:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact196
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 12:26:39] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [workshop 8] [2009-11-26 20:15:25] [6c94b261890ba36343a04d1029691995] [Current]
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Dataseries X:
283.042
276.687
277.915
277.128
277.103
275.037
270.150
267.140
264.993
287.259
291.186
292.300
288.186
281.477
282.656
280.190
280.408
276.836
275.216
274.352
271.311
289.802
290.726
292.300
278.506
269.826
265.861
269.034
264.176
255.198
253.353
246.057
235.372
258.556
260.993
254.663
250.643
243.422
247.105
248.541
245.039
237.080
237.085
225.554
226.839
247.934
248.333
246.969
245.098
246.263
255.765
264.319
268.347
273.046
273.963
267.430
271.993
292.710
295.881
293.299




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=60361&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=60361&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60361&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
10.1020810.69980.24374
20.3179942.18010.017148
30.3248862.22730.015377
40.2301651.57790.060644
50.0817360.56040.28895
60.1767711.21190.115807
70.0654620.44880.327824
80.1512071.03660.152607
90.09420.64580.260774
10-0.100779-0.69090.246511
110.3465772.3760.010814
12-0.18905-1.29610.100641
130.009630.0660.473821
140.0560010.38390.351384
150.0621490.42610.335999
16-0.087583-0.60040.275549
170.1007290.69060.246618
18-0.158204-1.08460.141817
19-0.038922-0.26680.395381
20-0.140163-0.96090.170759
21-0.235847-1.61690.056298
22-0.072899-0.49980.309783
23-0.234966-1.61080.056955
24-0.156217-1.0710.144826
25-0.151777-1.04050.151708
26-0.069699-0.47780.317492
27-0.228373-1.56560.06207
28-0.10626-0.72850.234966
29-0.174912-1.19910.118243
30-0.076484-0.52430.30125
31-0.078993-0.54150.295344
32-0.09649-0.66150.255761
33-0.011926-0.08180.467592
34-0.045955-0.3150.377059
35-0.004224-0.0290.48851
36-0.051857-0.35550.361897

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.102081 & 0.6998 & 0.24374 \tabularnewline
2 & 0.317994 & 2.1801 & 0.017148 \tabularnewline
3 & 0.324886 & 2.2273 & 0.015377 \tabularnewline
4 & 0.230165 & 1.5779 & 0.060644 \tabularnewline
5 & 0.081736 & 0.5604 & 0.28895 \tabularnewline
6 & 0.176771 & 1.2119 & 0.115807 \tabularnewline
7 & 0.065462 & 0.4488 & 0.327824 \tabularnewline
8 & 0.151207 & 1.0366 & 0.152607 \tabularnewline
9 & 0.0942 & 0.6458 & 0.260774 \tabularnewline
10 & -0.100779 & -0.6909 & 0.246511 \tabularnewline
11 & 0.346577 & 2.376 & 0.010814 \tabularnewline
12 & -0.18905 & -1.2961 & 0.100641 \tabularnewline
13 & 0.00963 & 0.066 & 0.473821 \tabularnewline
14 & 0.056001 & 0.3839 & 0.351384 \tabularnewline
15 & 0.062149 & 0.4261 & 0.335999 \tabularnewline
16 & -0.087583 & -0.6004 & 0.275549 \tabularnewline
17 & 0.100729 & 0.6906 & 0.246618 \tabularnewline
18 & -0.158204 & -1.0846 & 0.141817 \tabularnewline
19 & -0.038922 & -0.2668 & 0.395381 \tabularnewline
20 & -0.140163 & -0.9609 & 0.170759 \tabularnewline
21 & -0.235847 & -1.6169 & 0.056298 \tabularnewline
22 & -0.072899 & -0.4998 & 0.309783 \tabularnewline
23 & -0.234966 & -1.6108 & 0.056955 \tabularnewline
24 & -0.156217 & -1.071 & 0.144826 \tabularnewline
25 & -0.151777 & -1.0405 & 0.151708 \tabularnewline
26 & -0.069699 & -0.4778 & 0.317492 \tabularnewline
27 & -0.228373 & -1.5656 & 0.06207 \tabularnewline
28 & -0.10626 & -0.7285 & 0.234966 \tabularnewline
29 & -0.174912 & -1.1991 & 0.118243 \tabularnewline
30 & -0.076484 & -0.5243 & 0.30125 \tabularnewline
31 & -0.078993 & -0.5415 & 0.295344 \tabularnewline
32 & -0.09649 & -0.6615 & 0.255761 \tabularnewline
33 & -0.011926 & -0.0818 & 0.467592 \tabularnewline
34 & -0.045955 & -0.315 & 0.377059 \tabularnewline
35 & -0.004224 & -0.029 & 0.48851 \tabularnewline
36 & -0.051857 & -0.3555 & 0.361897 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60361&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]0.102081[/C][C]0.6998[/C][C]0.24374[/C][/ROW]
[ROW][C]2[/C][C]0.317994[/C][C]2.1801[/C][C]0.017148[/C][/ROW]
[ROW][C]3[/C][C]0.324886[/C][C]2.2273[/C][C]0.015377[/C][/ROW]
[ROW][C]4[/C][C]0.230165[/C][C]1.5779[/C][C]0.060644[/C][/ROW]
[ROW][C]5[/C][C]0.081736[/C][C]0.5604[/C][C]0.28895[/C][/ROW]
[ROW][C]6[/C][C]0.176771[/C][C]1.2119[/C][C]0.115807[/C][/ROW]
[ROW][C]7[/C][C]0.065462[/C][C]0.4488[/C][C]0.327824[/C][/ROW]
[ROW][C]8[/C][C]0.151207[/C][C]1.0366[/C][C]0.152607[/C][/ROW]
[ROW][C]9[/C][C]0.0942[/C][C]0.6458[/C][C]0.260774[/C][/ROW]
[ROW][C]10[/C][C]-0.100779[/C][C]-0.6909[/C][C]0.246511[/C][/ROW]
[ROW][C]11[/C][C]0.346577[/C][C]2.376[/C][C]0.010814[/C][/ROW]
[ROW][C]12[/C][C]-0.18905[/C][C]-1.2961[/C][C]0.100641[/C][/ROW]
[ROW][C]13[/C][C]0.00963[/C][C]0.066[/C][C]0.473821[/C][/ROW]
[ROW][C]14[/C][C]0.056001[/C][C]0.3839[/C][C]0.351384[/C][/ROW]
[ROW][C]15[/C][C]0.062149[/C][C]0.4261[/C][C]0.335999[/C][/ROW]
[ROW][C]16[/C][C]-0.087583[/C][C]-0.6004[/C][C]0.275549[/C][/ROW]
[ROW][C]17[/C][C]0.100729[/C][C]0.6906[/C][C]0.246618[/C][/ROW]
[ROW][C]18[/C][C]-0.158204[/C][C]-1.0846[/C][C]0.141817[/C][/ROW]
[ROW][C]19[/C][C]-0.038922[/C][C]-0.2668[/C][C]0.395381[/C][/ROW]
[ROW][C]20[/C][C]-0.140163[/C][C]-0.9609[/C][C]0.170759[/C][/ROW]
[ROW][C]21[/C][C]-0.235847[/C][C]-1.6169[/C][C]0.056298[/C][/ROW]
[ROW][C]22[/C][C]-0.072899[/C][C]-0.4998[/C][C]0.309783[/C][/ROW]
[ROW][C]23[/C][C]-0.234966[/C][C]-1.6108[/C][C]0.056955[/C][/ROW]
[ROW][C]24[/C][C]-0.156217[/C][C]-1.071[/C][C]0.144826[/C][/ROW]
[ROW][C]25[/C][C]-0.151777[/C][C]-1.0405[/C][C]0.151708[/C][/ROW]
[ROW][C]26[/C][C]-0.069699[/C][C]-0.4778[/C][C]0.317492[/C][/ROW]
[ROW][C]27[/C][C]-0.228373[/C][C]-1.5656[/C][C]0.06207[/C][/ROW]
[ROW][C]28[/C][C]-0.10626[/C][C]-0.7285[/C][C]0.234966[/C][/ROW]
[ROW][C]29[/C][C]-0.174912[/C][C]-1.1991[/C][C]0.118243[/C][/ROW]
[ROW][C]30[/C][C]-0.076484[/C][C]-0.5243[/C][C]0.30125[/C][/ROW]
[ROW][C]31[/C][C]-0.078993[/C][C]-0.5415[/C][C]0.295344[/C][/ROW]
[ROW][C]32[/C][C]-0.09649[/C][C]-0.6615[/C][C]0.255761[/C][/ROW]
[ROW][C]33[/C][C]-0.011926[/C][C]-0.0818[/C][C]0.467592[/C][/ROW]
[ROW][C]34[/C][C]-0.045955[/C][C]-0.315[/C][C]0.377059[/C][/ROW]
[ROW][C]35[/C][C]-0.004224[/C][C]-0.029[/C][C]0.48851[/C][/ROW]
[ROW][C]36[/C][C]-0.051857[/C][C]-0.3555[/C][C]0.361897[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60361&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60361&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
10.1020810.69980.24374
20.3179942.18010.017148
30.3248862.22730.015377
40.2301651.57790.060644
50.0817360.56040.28895
60.1767711.21190.115807
70.0654620.44880.327824
80.1512071.03660.152607
90.09420.64580.260774
10-0.100779-0.69090.246511
110.3465772.3760.010814
12-0.18905-1.29610.100641
130.009630.0660.473821
140.0560010.38390.351384
150.0621490.42610.335999
16-0.087583-0.60040.275549
170.1007290.69060.246618
18-0.158204-1.08460.141817
19-0.038922-0.26680.395381
20-0.140163-0.96090.170759
21-0.235847-1.61690.056298
22-0.072899-0.49980.309783
23-0.234966-1.61080.056955
24-0.156217-1.0710.144826
25-0.151777-1.04050.151708
26-0.069699-0.47780.317492
27-0.228373-1.56560.06207
28-0.10626-0.72850.234966
29-0.174912-1.19910.118243
30-0.076484-0.52430.30125
31-0.078993-0.54150.295344
32-0.09649-0.66150.255761
33-0.011926-0.08180.467592
34-0.045955-0.3150.377059
35-0.004224-0.0290.48851
36-0.051857-0.35550.361897







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1020810.69980.24374
20.3108132.13080.019183
30.3028982.07660.021667
40.1415270.97030.168442
5-0.120025-0.82280.207375
6-0.0309-0.21180.416573
7-0.042043-0.28820.387218
80.1150460.78870.21712
90.081020.55540.290613
10-0.237319-1.6270.055214
110.311662.13660.018932
12-0.263378-1.80560.038692
13-0.07291-0.49980.309759
140.048380.33170.370804
150.1124750.77110.222256
160.0440090.30170.382103
17-0.044781-0.3070.380098
18-0.224735-1.54070.065048
19-0.147008-1.00780.159348
20-0.110158-0.75520.226948
21-0.002984-0.02050.491883
22-0.083922-0.57530.283902
230.0506380.34720.365012
240.0083380.05720.47733
25-0.107137-0.73450.233147
260.0352610.24170.405017
27-0.030693-0.21040.417125
28-0.12708-0.87120.194033
290.1024110.70210.243041
30-0.00566-0.03880.484606
310.1090960.74790.229115
32-0.025446-0.17450.43113
330.0013190.0090.496411
34-0.019188-0.13150.447953
350.0698210.47870.317197
360.0530910.3640.358756

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.102081 & 0.6998 & 0.24374 \tabularnewline
2 & 0.310813 & 2.1308 & 0.019183 \tabularnewline
3 & 0.302898 & 2.0766 & 0.021667 \tabularnewline
4 & 0.141527 & 0.9703 & 0.168442 \tabularnewline
5 & -0.120025 & -0.8228 & 0.207375 \tabularnewline
6 & -0.0309 & -0.2118 & 0.416573 \tabularnewline
7 & -0.042043 & -0.2882 & 0.387218 \tabularnewline
8 & 0.115046 & 0.7887 & 0.21712 \tabularnewline
9 & 0.08102 & 0.5554 & 0.290613 \tabularnewline
10 & -0.237319 & -1.627 & 0.055214 \tabularnewline
11 & 0.31166 & 2.1366 & 0.018932 \tabularnewline
12 & -0.263378 & -1.8056 & 0.038692 \tabularnewline
13 & -0.07291 & -0.4998 & 0.309759 \tabularnewline
14 & 0.04838 & 0.3317 & 0.370804 \tabularnewline
15 & 0.112475 & 0.7711 & 0.222256 \tabularnewline
16 & 0.044009 & 0.3017 & 0.382103 \tabularnewline
17 & -0.044781 & -0.307 & 0.380098 \tabularnewline
18 & -0.224735 & -1.5407 & 0.065048 \tabularnewline
19 & -0.147008 & -1.0078 & 0.159348 \tabularnewline
20 & -0.110158 & -0.7552 & 0.226948 \tabularnewline
21 & -0.002984 & -0.0205 & 0.491883 \tabularnewline
22 & -0.083922 & -0.5753 & 0.283902 \tabularnewline
23 & 0.050638 & 0.3472 & 0.365012 \tabularnewline
24 & 0.008338 & 0.0572 & 0.47733 \tabularnewline
25 & -0.107137 & -0.7345 & 0.233147 \tabularnewline
26 & 0.035261 & 0.2417 & 0.405017 \tabularnewline
27 & -0.030693 & -0.2104 & 0.417125 \tabularnewline
28 & -0.12708 & -0.8712 & 0.194033 \tabularnewline
29 & 0.102411 & 0.7021 & 0.243041 \tabularnewline
30 & -0.00566 & -0.0388 & 0.484606 \tabularnewline
31 & 0.109096 & 0.7479 & 0.229115 \tabularnewline
32 & -0.025446 & -0.1745 & 0.43113 \tabularnewline
33 & 0.001319 & 0.009 & 0.496411 \tabularnewline
34 & -0.019188 & -0.1315 & 0.447953 \tabularnewline
35 & 0.069821 & 0.4787 & 0.317197 \tabularnewline
36 & 0.053091 & 0.364 & 0.358756 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60361&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]0.102081[/C][C]0.6998[/C][C]0.24374[/C][/ROW]
[ROW][C]2[/C][C]0.310813[/C][C]2.1308[/C][C]0.019183[/C][/ROW]
[ROW][C]3[/C][C]0.302898[/C][C]2.0766[/C][C]0.021667[/C][/ROW]
[ROW][C]4[/C][C]0.141527[/C][C]0.9703[/C][C]0.168442[/C][/ROW]
[ROW][C]5[/C][C]-0.120025[/C][C]-0.8228[/C][C]0.207375[/C][/ROW]
[ROW][C]6[/C][C]-0.0309[/C][C]-0.2118[/C][C]0.416573[/C][/ROW]
[ROW][C]7[/C][C]-0.042043[/C][C]-0.2882[/C][C]0.387218[/C][/ROW]
[ROW][C]8[/C][C]0.115046[/C][C]0.7887[/C][C]0.21712[/C][/ROW]
[ROW][C]9[/C][C]0.08102[/C][C]0.5554[/C][C]0.290613[/C][/ROW]
[ROW][C]10[/C][C]-0.237319[/C][C]-1.627[/C][C]0.055214[/C][/ROW]
[ROW][C]11[/C][C]0.31166[/C][C]2.1366[/C][C]0.018932[/C][/ROW]
[ROW][C]12[/C][C]-0.263378[/C][C]-1.8056[/C][C]0.038692[/C][/ROW]
[ROW][C]13[/C][C]-0.07291[/C][C]-0.4998[/C][C]0.309759[/C][/ROW]
[ROW][C]14[/C][C]0.04838[/C][C]0.3317[/C][C]0.370804[/C][/ROW]
[ROW][C]15[/C][C]0.112475[/C][C]0.7711[/C][C]0.222256[/C][/ROW]
[ROW][C]16[/C][C]0.044009[/C][C]0.3017[/C][C]0.382103[/C][/ROW]
[ROW][C]17[/C][C]-0.044781[/C][C]-0.307[/C][C]0.380098[/C][/ROW]
[ROW][C]18[/C][C]-0.224735[/C][C]-1.5407[/C][C]0.065048[/C][/ROW]
[ROW][C]19[/C][C]-0.147008[/C][C]-1.0078[/C][C]0.159348[/C][/ROW]
[ROW][C]20[/C][C]-0.110158[/C][C]-0.7552[/C][C]0.226948[/C][/ROW]
[ROW][C]21[/C][C]-0.002984[/C][C]-0.0205[/C][C]0.491883[/C][/ROW]
[ROW][C]22[/C][C]-0.083922[/C][C]-0.5753[/C][C]0.283902[/C][/ROW]
[ROW][C]23[/C][C]0.050638[/C][C]0.3472[/C][C]0.365012[/C][/ROW]
[ROW][C]24[/C][C]0.008338[/C][C]0.0572[/C][C]0.47733[/C][/ROW]
[ROW][C]25[/C][C]-0.107137[/C][C]-0.7345[/C][C]0.233147[/C][/ROW]
[ROW][C]26[/C][C]0.035261[/C][C]0.2417[/C][C]0.405017[/C][/ROW]
[ROW][C]27[/C][C]-0.030693[/C][C]-0.2104[/C][C]0.417125[/C][/ROW]
[ROW][C]28[/C][C]-0.12708[/C][C]-0.8712[/C][C]0.194033[/C][/ROW]
[ROW][C]29[/C][C]0.102411[/C][C]0.7021[/C][C]0.243041[/C][/ROW]
[ROW][C]30[/C][C]-0.00566[/C][C]-0.0388[/C][C]0.484606[/C][/ROW]
[ROW][C]31[/C][C]0.109096[/C][C]0.7479[/C][C]0.229115[/C][/ROW]
[ROW][C]32[/C][C]-0.025446[/C][C]-0.1745[/C][C]0.43113[/C][/ROW]
[ROW][C]33[/C][C]0.001319[/C][C]0.009[/C][C]0.496411[/C][/ROW]
[ROW][C]34[/C][C]-0.019188[/C][C]-0.1315[/C][C]0.447953[/C][/ROW]
[ROW][C]35[/C][C]0.069821[/C][C]0.4787[/C][C]0.317197[/C][/ROW]
[ROW][C]36[/C][C]0.053091[/C][C]0.364[/C][C]0.358756[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60361&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60361&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
10.1020810.69980.24374
20.3108132.13080.019183
30.3028982.07660.021667
40.1415270.97030.168442
5-0.120025-0.82280.207375
6-0.0309-0.21180.416573
7-0.042043-0.28820.387218
80.1150460.78870.21712
90.081020.55540.290613
10-0.237319-1.6270.055214
110.311662.13660.018932
12-0.263378-1.80560.038692
13-0.07291-0.49980.309759
140.048380.33170.370804
150.1124750.77110.222256
160.0440090.30170.382103
17-0.044781-0.3070.380098
18-0.224735-1.54070.065048
19-0.147008-1.00780.159348
20-0.110158-0.75520.226948
21-0.002984-0.02050.491883
22-0.083922-0.57530.283902
230.0506380.34720.365012
240.0083380.05720.47733
25-0.107137-0.73450.233147
260.0352610.24170.405017
27-0.030693-0.21040.417125
28-0.12708-0.87120.194033
290.1024110.70210.243041
30-0.00566-0.03880.484606
310.1090960.74790.229115
32-0.025446-0.17450.43113
330.0013190.0090.496411
34-0.019188-0.13150.447953
350.0698210.47870.317197
360.0530910.3640.358756



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