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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 computationFri, 27 Nov 2009 06:00:53 -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/27/t12593268855osf4o8gdpmn9bj.htm/, Retrieved Sun, 28 Apr 2024 20:47:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60694, Retrieved Sun, 28 Apr 2024 20:47:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132
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] [WS8] [2009-11-27 13:00:53] [40cfc51151e9382b81a5fb0c269b074d] [Current]
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Dataseries X:
286602
283042
276687
277915
277128
277103
275037
270150
267140
264993
287259
291186
292300
288186
281477
282656
280190
280408
276836
275216
274352
271311
289802
290726
292300
278506
269826
265861
269034
264176
255198
253353
246057
235372
258556
260993
254663
250643
243422
247105
248541
245039
237080
237085
225554
226839
247934
248333
246969
245098
246263
255765
264319
268347
273046
273963
267430
271993
292710
295881
293299




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=60694&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=60694&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60694&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
10.103440.71670.238531
20.3186052.20740.016051
30.3274972.2690.013902
40.230631.59790.058319
50.0844640.58520.280583
60.1736621.20320.117406
70.0635320.44020.330897
80.1525871.05720.147867
90.0990240.68610.247988
10-0.096562-0.6690.253349
110.3457882.39570.010268
12-0.176776-1.22470.113325
130.0124680.08640.465761
140.0627170.43450.332931
150.0561230.38880.34956
16-0.080881-0.56040.288921
170.1077880.74680.229421
18-0.156803-1.08640.141372
19-0.03024-0.20950.417468
20-0.129684-0.89850.186708
21-0.239753-1.66110.05161
22-0.073525-0.50940.306405
23-0.224034-1.55220.063597
24-0.166663-1.15470.12697
25-0.152244-1.05480.148404
26-0.077771-0.53880.296252
27-0.225167-1.560.062664
28-0.106699-0.73920.231683
29-0.174659-1.21010.116088
30-0.077373-0.53610.297198
31-0.072434-0.50180.309039
32-0.109096-0.75580.226719
33-0.00818-0.05670.477522
34-0.041988-0.29090.38619
35-0.0086-0.05960.476368
36-0.052607-0.36450.358553

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.10344 & 0.7167 & 0.238531 \tabularnewline
2 & 0.318605 & 2.2074 & 0.016051 \tabularnewline
3 & 0.327497 & 2.269 & 0.013902 \tabularnewline
4 & 0.23063 & 1.5979 & 0.058319 \tabularnewline
5 & 0.084464 & 0.5852 & 0.280583 \tabularnewline
6 & 0.173662 & 1.2032 & 0.117406 \tabularnewline
7 & 0.063532 & 0.4402 & 0.330897 \tabularnewline
8 & 0.152587 & 1.0572 & 0.147867 \tabularnewline
9 & 0.099024 & 0.6861 & 0.247988 \tabularnewline
10 & -0.096562 & -0.669 & 0.253349 \tabularnewline
11 & 0.345788 & 2.3957 & 0.010268 \tabularnewline
12 & -0.176776 & -1.2247 & 0.113325 \tabularnewline
13 & 0.012468 & 0.0864 & 0.465761 \tabularnewline
14 & 0.062717 & 0.4345 & 0.332931 \tabularnewline
15 & 0.056123 & 0.3888 & 0.34956 \tabularnewline
16 & -0.080881 & -0.5604 & 0.288921 \tabularnewline
17 & 0.107788 & 0.7468 & 0.229421 \tabularnewline
18 & -0.156803 & -1.0864 & 0.141372 \tabularnewline
19 & -0.03024 & -0.2095 & 0.417468 \tabularnewline
20 & -0.129684 & -0.8985 & 0.186708 \tabularnewline
21 & -0.239753 & -1.6611 & 0.05161 \tabularnewline
22 & -0.073525 & -0.5094 & 0.306405 \tabularnewline
23 & -0.224034 & -1.5522 & 0.063597 \tabularnewline
24 & -0.166663 & -1.1547 & 0.12697 \tabularnewline
25 & -0.152244 & -1.0548 & 0.148404 \tabularnewline
26 & -0.077771 & -0.5388 & 0.296252 \tabularnewline
27 & -0.225167 & -1.56 & 0.062664 \tabularnewline
28 & -0.106699 & -0.7392 & 0.231683 \tabularnewline
29 & -0.174659 & -1.2101 & 0.116088 \tabularnewline
30 & -0.077373 & -0.5361 & 0.297198 \tabularnewline
31 & -0.072434 & -0.5018 & 0.309039 \tabularnewline
32 & -0.109096 & -0.7558 & 0.226719 \tabularnewline
33 & -0.00818 & -0.0567 & 0.477522 \tabularnewline
34 & -0.041988 & -0.2909 & 0.38619 \tabularnewline
35 & -0.0086 & -0.0596 & 0.476368 \tabularnewline
36 & -0.052607 & -0.3645 & 0.358553 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60694&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]0.10344[/C][C]0.7167[/C][C]0.238531[/C][/ROW]
[ROW][C]2[/C][C]0.318605[/C][C]2.2074[/C][C]0.016051[/C][/ROW]
[ROW][C]3[/C][C]0.327497[/C][C]2.269[/C][C]0.013902[/C][/ROW]
[ROW][C]4[/C][C]0.23063[/C][C]1.5979[/C][C]0.058319[/C][/ROW]
[ROW][C]5[/C][C]0.084464[/C][C]0.5852[/C][C]0.280583[/C][/ROW]
[ROW][C]6[/C][C]0.173662[/C][C]1.2032[/C][C]0.117406[/C][/ROW]
[ROW][C]7[/C][C]0.063532[/C][C]0.4402[/C][C]0.330897[/C][/ROW]
[ROW][C]8[/C][C]0.152587[/C][C]1.0572[/C][C]0.147867[/C][/ROW]
[ROW][C]9[/C][C]0.099024[/C][C]0.6861[/C][C]0.247988[/C][/ROW]
[ROW][C]10[/C][C]-0.096562[/C][C]-0.669[/C][C]0.253349[/C][/ROW]
[ROW][C]11[/C][C]0.345788[/C][C]2.3957[/C][C]0.010268[/C][/ROW]
[ROW][C]12[/C][C]-0.176776[/C][C]-1.2247[/C][C]0.113325[/C][/ROW]
[ROW][C]13[/C][C]0.012468[/C][C]0.0864[/C][C]0.465761[/C][/ROW]
[ROW][C]14[/C][C]0.062717[/C][C]0.4345[/C][C]0.332931[/C][/ROW]
[ROW][C]15[/C][C]0.056123[/C][C]0.3888[/C][C]0.34956[/C][/ROW]
[ROW][C]16[/C][C]-0.080881[/C][C]-0.5604[/C][C]0.288921[/C][/ROW]
[ROW][C]17[/C][C]0.107788[/C][C]0.7468[/C][C]0.229421[/C][/ROW]
[ROW][C]18[/C][C]-0.156803[/C][C]-1.0864[/C][C]0.141372[/C][/ROW]
[ROW][C]19[/C][C]-0.03024[/C][C]-0.2095[/C][C]0.417468[/C][/ROW]
[ROW][C]20[/C][C]-0.129684[/C][C]-0.8985[/C][C]0.186708[/C][/ROW]
[ROW][C]21[/C][C]-0.239753[/C][C]-1.6611[/C][C]0.05161[/C][/ROW]
[ROW][C]22[/C][C]-0.073525[/C][C]-0.5094[/C][C]0.306405[/C][/ROW]
[ROW][C]23[/C][C]-0.224034[/C][C]-1.5522[/C][C]0.063597[/C][/ROW]
[ROW][C]24[/C][C]-0.166663[/C][C]-1.1547[/C][C]0.12697[/C][/ROW]
[ROW][C]25[/C][C]-0.152244[/C][C]-1.0548[/C][C]0.148404[/C][/ROW]
[ROW][C]26[/C][C]-0.077771[/C][C]-0.5388[/C][C]0.296252[/C][/ROW]
[ROW][C]27[/C][C]-0.225167[/C][C]-1.56[/C][C]0.062664[/C][/ROW]
[ROW][C]28[/C][C]-0.106699[/C][C]-0.7392[/C][C]0.231683[/C][/ROW]
[ROW][C]29[/C][C]-0.174659[/C][C]-1.2101[/C][C]0.116088[/C][/ROW]
[ROW][C]30[/C][C]-0.077373[/C][C]-0.5361[/C][C]0.297198[/C][/ROW]
[ROW][C]31[/C][C]-0.072434[/C][C]-0.5018[/C][C]0.309039[/C][/ROW]
[ROW][C]32[/C][C]-0.109096[/C][C]-0.7558[/C][C]0.226719[/C][/ROW]
[ROW][C]33[/C][C]-0.00818[/C][C]-0.0567[/C][C]0.477522[/C][/ROW]
[ROW][C]34[/C][C]-0.041988[/C][C]-0.2909[/C][C]0.38619[/C][/ROW]
[ROW][C]35[/C][C]-0.0086[/C][C]-0.0596[/C][C]0.476368[/C][/ROW]
[ROW][C]36[/C][C]-0.052607[/C][C]-0.3645[/C][C]0.358553[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60694&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60694&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
10.103440.71670.238531
20.3186052.20740.016051
30.3274972.2690.013902
40.230631.59790.058319
50.0844640.58520.280583
60.1736621.20320.117406
70.0635320.44020.330897
80.1525871.05720.147867
90.0990240.68610.247988
10-0.096562-0.6690.253349
110.3457882.39570.010268
12-0.176776-1.22470.113325
130.0124680.08640.465761
140.0627170.43450.332931
150.0561230.38880.34956
16-0.080881-0.56040.288921
170.1077880.74680.229421
18-0.156803-1.08640.141372
19-0.03024-0.20950.417468
20-0.129684-0.89850.186708
21-0.239753-1.66110.05161
22-0.073525-0.50940.306405
23-0.224034-1.55220.063597
24-0.166663-1.15470.12697
25-0.152244-1.05480.148404
26-0.077771-0.53880.296252
27-0.225167-1.560.062664
28-0.106699-0.73920.231683
29-0.174659-1.21010.116088
30-0.077373-0.53610.297198
31-0.072434-0.50180.309039
32-0.109096-0.75580.226719
33-0.00818-0.05670.477522
34-0.041988-0.29090.38619
35-0.0086-0.05960.476368
36-0.052607-0.36450.358553







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.103440.71670.238531
20.3112362.15630.01805
30.3051072.11380.019875
40.1414310.97990.166033
5-0.118907-0.82380.207061
6-0.036815-0.25510.399883
7-0.047613-0.32990.371467
80.1179870.81740.20886
90.0926930.64220.261902
10-0.228358-1.58210.060096
110.3038532.10520.020268
12-0.254751-1.7650.041966
13-0.077081-0.5340.297893
140.0504820.34980.364028
150.0981990.68030.249778
160.0445450.30860.379474
17-0.021207-0.14690.441903
18-0.225422-1.56180.062456
19-0.142473-0.98710.164277
20-0.116454-0.80680.211876
21-0.021543-0.14930.440989
22-0.077057-0.53390.297948
230.0599880.41560.339775
240.0036810.02550.489881
25-0.116775-0.8090.211241
260.0249090.17260.431856
27-0.029479-0.20420.419516
28-0.126719-0.87790.192177
290.1187430.82270.20738
300.0069050.04780.481023
310.108150.74930.228672
32-0.026955-0.18680.426322
33-0.005574-0.03860.484677
34-0.0332-0.230.409527
350.0861820.59710.276628
360.0527670.36560.358142

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.10344 & 0.7167 & 0.238531 \tabularnewline
2 & 0.311236 & 2.1563 & 0.01805 \tabularnewline
3 & 0.305107 & 2.1138 & 0.019875 \tabularnewline
4 & 0.141431 & 0.9799 & 0.166033 \tabularnewline
5 & -0.118907 & -0.8238 & 0.207061 \tabularnewline
6 & -0.036815 & -0.2551 & 0.399883 \tabularnewline
7 & -0.047613 & -0.3299 & 0.371467 \tabularnewline
8 & 0.117987 & 0.8174 & 0.20886 \tabularnewline
9 & 0.092693 & 0.6422 & 0.261902 \tabularnewline
10 & -0.228358 & -1.5821 & 0.060096 \tabularnewline
11 & 0.303853 & 2.1052 & 0.020268 \tabularnewline
12 & -0.254751 & -1.765 & 0.041966 \tabularnewline
13 & -0.077081 & -0.534 & 0.297893 \tabularnewline
14 & 0.050482 & 0.3498 & 0.364028 \tabularnewline
15 & 0.098199 & 0.6803 & 0.249778 \tabularnewline
16 & 0.044545 & 0.3086 & 0.379474 \tabularnewline
17 & -0.021207 & -0.1469 & 0.441903 \tabularnewline
18 & -0.225422 & -1.5618 & 0.062456 \tabularnewline
19 & -0.142473 & -0.9871 & 0.164277 \tabularnewline
20 & -0.116454 & -0.8068 & 0.211876 \tabularnewline
21 & -0.021543 & -0.1493 & 0.440989 \tabularnewline
22 & -0.077057 & -0.5339 & 0.297948 \tabularnewline
23 & 0.059988 & 0.4156 & 0.339775 \tabularnewline
24 & 0.003681 & 0.0255 & 0.489881 \tabularnewline
25 & -0.116775 & -0.809 & 0.211241 \tabularnewline
26 & 0.024909 & 0.1726 & 0.431856 \tabularnewline
27 & -0.029479 & -0.2042 & 0.419516 \tabularnewline
28 & -0.126719 & -0.8779 & 0.192177 \tabularnewline
29 & 0.118743 & 0.8227 & 0.20738 \tabularnewline
30 & 0.006905 & 0.0478 & 0.481023 \tabularnewline
31 & 0.10815 & 0.7493 & 0.228672 \tabularnewline
32 & -0.026955 & -0.1868 & 0.426322 \tabularnewline
33 & -0.005574 & -0.0386 & 0.484677 \tabularnewline
34 & -0.0332 & -0.23 & 0.409527 \tabularnewline
35 & 0.086182 & 0.5971 & 0.276628 \tabularnewline
36 & 0.052767 & 0.3656 & 0.358142 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60694&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]0.10344[/C][C]0.7167[/C][C]0.238531[/C][/ROW]
[ROW][C]2[/C][C]0.311236[/C][C]2.1563[/C][C]0.01805[/C][/ROW]
[ROW][C]3[/C][C]0.305107[/C][C]2.1138[/C][C]0.019875[/C][/ROW]
[ROW][C]4[/C][C]0.141431[/C][C]0.9799[/C][C]0.166033[/C][/ROW]
[ROW][C]5[/C][C]-0.118907[/C][C]-0.8238[/C][C]0.207061[/C][/ROW]
[ROW][C]6[/C][C]-0.036815[/C][C]-0.2551[/C][C]0.399883[/C][/ROW]
[ROW][C]7[/C][C]-0.047613[/C][C]-0.3299[/C][C]0.371467[/C][/ROW]
[ROW][C]8[/C][C]0.117987[/C][C]0.8174[/C][C]0.20886[/C][/ROW]
[ROW][C]9[/C][C]0.092693[/C][C]0.6422[/C][C]0.261902[/C][/ROW]
[ROW][C]10[/C][C]-0.228358[/C][C]-1.5821[/C][C]0.060096[/C][/ROW]
[ROW][C]11[/C][C]0.303853[/C][C]2.1052[/C][C]0.020268[/C][/ROW]
[ROW][C]12[/C][C]-0.254751[/C][C]-1.765[/C][C]0.041966[/C][/ROW]
[ROW][C]13[/C][C]-0.077081[/C][C]-0.534[/C][C]0.297893[/C][/ROW]
[ROW][C]14[/C][C]0.050482[/C][C]0.3498[/C][C]0.364028[/C][/ROW]
[ROW][C]15[/C][C]0.098199[/C][C]0.6803[/C][C]0.249778[/C][/ROW]
[ROW][C]16[/C][C]0.044545[/C][C]0.3086[/C][C]0.379474[/C][/ROW]
[ROW][C]17[/C][C]-0.021207[/C][C]-0.1469[/C][C]0.441903[/C][/ROW]
[ROW][C]18[/C][C]-0.225422[/C][C]-1.5618[/C][C]0.062456[/C][/ROW]
[ROW][C]19[/C][C]-0.142473[/C][C]-0.9871[/C][C]0.164277[/C][/ROW]
[ROW][C]20[/C][C]-0.116454[/C][C]-0.8068[/C][C]0.211876[/C][/ROW]
[ROW][C]21[/C][C]-0.021543[/C][C]-0.1493[/C][C]0.440989[/C][/ROW]
[ROW][C]22[/C][C]-0.077057[/C][C]-0.5339[/C][C]0.297948[/C][/ROW]
[ROW][C]23[/C][C]0.059988[/C][C]0.4156[/C][C]0.339775[/C][/ROW]
[ROW][C]24[/C][C]0.003681[/C][C]0.0255[/C][C]0.489881[/C][/ROW]
[ROW][C]25[/C][C]-0.116775[/C][C]-0.809[/C][C]0.211241[/C][/ROW]
[ROW][C]26[/C][C]0.024909[/C][C]0.1726[/C][C]0.431856[/C][/ROW]
[ROW][C]27[/C][C]-0.029479[/C][C]-0.2042[/C][C]0.419516[/C][/ROW]
[ROW][C]28[/C][C]-0.126719[/C][C]-0.8779[/C][C]0.192177[/C][/ROW]
[ROW][C]29[/C][C]0.118743[/C][C]0.8227[/C][C]0.20738[/C][/ROW]
[ROW][C]30[/C][C]0.006905[/C][C]0.0478[/C][C]0.481023[/C][/ROW]
[ROW][C]31[/C][C]0.10815[/C][C]0.7493[/C][C]0.228672[/C][/ROW]
[ROW][C]32[/C][C]-0.026955[/C][C]-0.1868[/C][C]0.426322[/C][/ROW]
[ROW][C]33[/C][C]-0.005574[/C][C]-0.0386[/C][C]0.484677[/C][/ROW]
[ROW][C]34[/C][C]-0.0332[/C][C]-0.23[/C][C]0.409527[/C][/ROW]
[ROW][C]35[/C][C]0.086182[/C][C]0.5971[/C][C]0.276628[/C][/ROW]
[ROW][C]36[/C][C]0.052767[/C][C]0.3656[/C][C]0.358142[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60694&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60694&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
10.103440.71670.238531
20.3112362.15630.01805
30.3051072.11380.019875
40.1414310.97990.166033
5-0.118907-0.82380.207061
6-0.036815-0.25510.399883
7-0.047613-0.32990.371467
80.1179870.81740.20886
90.0926930.64220.261902
10-0.228358-1.58210.060096
110.3038532.10520.020268
12-0.254751-1.7650.041966
13-0.077081-0.5340.297893
140.0504820.34980.364028
150.0981990.68030.249778
160.0445450.30860.379474
17-0.021207-0.14690.441903
18-0.225422-1.56180.062456
19-0.142473-0.98710.164277
20-0.116454-0.80680.211876
21-0.021543-0.14930.440989
22-0.077057-0.53390.297948
230.0599880.41560.339775
240.0036810.02550.489881
25-0.116775-0.8090.211241
260.0249090.17260.431856
27-0.029479-0.20420.419516
28-0.126719-0.87790.192177
290.1187430.82270.20738
300.0069050.04780.481023
310.108150.74930.228672
32-0.026955-0.18680.426322
33-0.005574-0.03860.484677
34-0.0332-0.230.409527
350.0861820.59710.276628
360.0527670.36560.358142



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')