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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 computationMon, 28 Dec 2009 11:55:49 -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/Dec/28/t1262026588k1t290959ydjzir.htm/, Retrieved Sat, 04 May 2024 21:47:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71032, Retrieved Sat, 04 May 2024 21:47:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87
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] [tijdreeksanalyse] [2009-12-28 18:55:49] [f47dffd5f5a8c03c3681db4cc9472742] [Current]
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Dataseries X:
286.445
288.576
293.299
295.881
292.710
271.993
267.430
273.963
273.046
268.347
264.319
255.765
246.263
245.098
246.969
248.333
247.934
226.839
225.554
237.085
237.080
245.039
248.541
247.105
243.422
250.643
254.663
260.993
258.556
235.372
246.057
253.353
255.198
264.176
269.034
265.861
269.826
278.506
292.300
290.726
289.802
271.311
274.352
275.216
276.836
280.408
280.190
282.656
281.477
288.186
292.300
291.186
287.259
264.993
267.140
270.150
275.037
277.103
277.128




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=71032&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=71032&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71032&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
10.8952976.87690
20.7645395.87250
30.6608255.07592e-06
40.5878974.51571.5e-05
50.5474844.20534.5e-05
60.5052383.88080.000133
70.4107953.15540.001262
80.2870432.20480.015689
90.1919791.47460.072816
100.1372461.05420.148043
110.1325831.01840.156325
120.1137380.87360.19293
13-0.011991-0.09210.463465
14-0.133566-1.02590.154554
15-0.22131-1.69990.047207
16-0.273062-2.09740.020125
17-0.289837-2.22630.014914
18-0.299688-2.30190.012443
19-0.345014-2.65010.005156
20-0.409769-3.14750.001291
21-0.439343-3.37470.000656
22-0.429951-3.30250.000815
23-0.384087-2.95020.002274
24-0.348874-2.67980.004767
25-0.390513-2.99960.001978
26-0.423137-3.25020.000954
27-0.425105-3.26530.000912
28-0.403481-3.09920.001486
29-0.354223-2.72080.004272
30-0.288337-2.21480.015325
31-0.263562-2.02450.023729
32-0.251037-1.92820.02932
33-0.210844-1.61950.055334
34-0.153664-1.18030.121307
35-0.081163-0.62340.267703
36-0.026232-0.20150.420505

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.895297 & 6.8769 & 0 \tabularnewline
2 & 0.764539 & 5.8725 & 0 \tabularnewline
3 & 0.660825 & 5.0759 & 2e-06 \tabularnewline
4 & 0.587897 & 4.5157 & 1.5e-05 \tabularnewline
5 & 0.547484 & 4.2053 & 4.5e-05 \tabularnewline
6 & 0.505238 & 3.8808 & 0.000133 \tabularnewline
7 & 0.410795 & 3.1554 & 0.001262 \tabularnewline
8 & 0.287043 & 2.2048 & 0.015689 \tabularnewline
9 & 0.191979 & 1.4746 & 0.072816 \tabularnewline
10 & 0.137246 & 1.0542 & 0.148043 \tabularnewline
11 & 0.132583 & 1.0184 & 0.156325 \tabularnewline
12 & 0.113738 & 0.8736 & 0.19293 \tabularnewline
13 & -0.011991 & -0.0921 & 0.463465 \tabularnewline
14 & -0.133566 & -1.0259 & 0.154554 \tabularnewline
15 & -0.22131 & -1.6999 & 0.047207 \tabularnewline
16 & -0.273062 & -2.0974 & 0.020125 \tabularnewline
17 & -0.289837 & -2.2263 & 0.014914 \tabularnewline
18 & -0.299688 & -2.3019 & 0.012443 \tabularnewline
19 & -0.345014 & -2.6501 & 0.005156 \tabularnewline
20 & -0.409769 & -3.1475 & 0.001291 \tabularnewline
21 & -0.439343 & -3.3747 & 0.000656 \tabularnewline
22 & -0.429951 & -3.3025 & 0.000815 \tabularnewline
23 & -0.384087 & -2.9502 & 0.002274 \tabularnewline
24 & -0.348874 & -2.6798 & 0.004767 \tabularnewline
25 & -0.390513 & -2.9996 & 0.001978 \tabularnewline
26 & -0.423137 & -3.2502 & 0.000954 \tabularnewline
27 & -0.425105 & -3.2653 & 0.000912 \tabularnewline
28 & -0.403481 & -3.0992 & 0.001486 \tabularnewline
29 & -0.354223 & -2.7208 & 0.004272 \tabularnewline
30 & -0.288337 & -2.2148 & 0.015325 \tabularnewline
31 & -0.263562 & -2.0245 & 0.023729 \tabularnewline
32 & -0.251037 & -1.9282 & 0.02932 \tabularnewline
33 & -0.210844 & -1.6195 & 0.055334 \tabularnewline
34 & -0.153664 & -1.1803 & 0.121307 \tabularnewline
35 & -0.081163 & -0.6234 & 0.267703 \tabularnewline
36 & -0.026232 & -0.2015 & 0.420505 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71032&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]0.895297[/C][C]6.8769[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.764539[/C][C]5.8725[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.660825[/C][C]5.0759[/C][C]2e-06[/C][/ROW]
[ROW][C]4[/C][C]0.587897[/C][C]4.5157[/C][C]1.5e-05[/C][/ROW]
[ROW][C]5[/C][C]0.547484[/C][C]4.2053[/C][C]4.5e-05[/C][/ROW]
[ROW][C]6[/C][C]0.505238[/C][C]3.8808[/C][C]0.000133[/C][/ROW]
[ROW][C]7[/C][C]0.410795[/C][C]3.1554[/C][C]0.001262[/C][/ROW]
[ROW][C]8[/C][C]0.287043[/C][C]2.2048[/C][C]0.015689[/C][/ROW]
[ROW][C]9[/C][C]0.191979[/C][C]1.4746[/C][C]0.072816[/C][/ROW]
[ROW][C]10[/C][C]0.137246[/C][C]1.0542[/C][C]0.148043[/C][/ROW]
[ROW][C]11[/C][C]0.132583[/C][C]1.0184[/C][C]0.156325[/C][/ROW]
[ROW][C]12[/C][C]0.113738[/C][C]0.8736[/C][C]0.19293[/C][/ROW]
[ROW][C]13[/C][C]-0.011991[/C][C]-0.0921[/C][C]0.463465[/C][/ROW]
[ROW][C]14[/C][C]-0.133566[/C][C]-1.0259[/C][C]0.154554[/C][/ROW]
[ROW][C]15[/C][C]-0.22131[/C][C]-1.6999[/C][C]0.047207[/C][/ROW]
[ROW][C]16[/C][C]-0.273062[/C][C]-2.0974[/C][C]0.020125[/C][/ROW]
[ROW][C]17[/C][C]-0.289837[/C][C]-2.2263[/C][C]0.014914[/C][/ROW]
[ROW][C]18[/C][C]-0.299688[/C][C]-2.3019[/C][C]0.012443[/C][/ROW]
[ROW][C]19[/C][C]-0.345014[/C][C]-2.6501[/C][C]0.005156[/C][/ROW]
[ROW][C]20[/C][C]-0.409769[/C][C]-3.1475[/C][C]0.001291[/C][/ROW]
[ROW][C]21[/C][C]-0.439343[/C][C]-3.3747[/C][C]0.000656[/C][/ROW]
[ROW][C]22[/C][C]-0.429951[/C][C]-3.3025[/C][C]0.000815[/C][/ROW]
[ROW][C]23[/C][C]-0.384087[/C][C]-2.9502[/C][C]0.002274[/C][/ROW]
[ROW][C]24[/C][C]-0.348874[/C][C]-2.6798[/C][C]0.004767[/C][/ROW]
[ROW][C]25[/C][C]-0.390513[/C][C]-2.9996[/C][C]0.001978[/C][/ROW]
[ROW][C]26[/C][C]-0.423137[/C][C]-3.2502[/C][C]0.000954[/C][/ROW]
[ROW][C]27[/C][C]-0.425105[/C][C]-3.2653[/C][C]0.000912[/C][/ROW]
[ROW][C]28[/C][C]-0.403481[/C][C]-3.0992[/C][C]0.001486[/C][/ROW]
[ROW][C]29[/C][C]-0.354223[/C][C]-2.7208[/C][C]0.004272[/C][/ROW]
[ROW][C]30[/C][C]-0.288337[/C][C]-2.2148[/C][C]0.015325[/C][/ROW]
[ROW][C]31[/C][C]-0.263562[/C][C]-2.0245[/C][C]0.023729[/C][/ROW]
[ROW][C]32[/C][C]-0.251037[/C][C]-1.9282[/C][C]0.02932[/C][/ROW]
[ROW][C]33[/C][C]-0.210844[/C][C]-1.6195[/C][C]0.055334[/C][/ROW]
[ROW][C]34[/C][C]-0.153664[/C][C]-1.1803[/C][C]0.121307[/C][/ROW]
[ROW][C]35[/C][C]-0.081163[/C][C]-0.6234[/C][C]0.267703[/C][/ROW]
[ROW][C]36[/C][C]-0.026232[/C][C]-0.2015[/C][C]0.420505[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71032&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71032&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
10.8952976.87690
20.7645395.87250
30.6608255.07592e-06
40.5878974.51571.5e-05
50.5474844.20534.5e-05
60.5052383.88080.000133
70.4107953.15540.001262
80.2870432.20480.015689
90.1919791.47460.072816
100.1372461.05420.148043
110.1325831.01840.156325
120.1137380.87360.19293
13-0.011991-0.09210.463465
14-0.133566-1.02590.154554
15-0.22131-1.69990.047207
16-0.273062-2.09740.020125
17-0.289837-2.22630.014914
18-0.299688-2.30190.012443
19-0.345014-2.65010.005156
20-0.409769-3.14750.001291
21-0.439343-3.37470.000656
22-0.429951-3.30250.000815
23-0.384087-2.95020.002274
24-0.348874-2.67980.004767
25-0.390513-2.99960.001978
26-0.423137-3.25020.000954
27-0.425105-3.26530.000912
28-0.403481-3.09920.001486
29-0.354223-2.72080.004272
30-0.288337-2.21480.015325
31-0.263562-2.02450.023729
32-0.251037-1.92820.02932
33-0.210844-1.61950.055334
34-0.153664-1.18030.121307
35-0.081163-0.62340.267703
36-0.026232-0.20150.420505







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8952976.87690
2-0.186539-1.43280.078592
30.0817570.6280.266217
40.0611940.470.320029
50.1037270.79670.214398
6-0.049479-0.38010.352635
7-0.255072-1.95920.027407
8-0.136158-1.04590.149948
90.0653110.50170.308885
100.0507410.38980.349062
110.1391811.06910.144696
12-0.139482-1.07140.14418
13-0.512443-3.93610.000111
140.1447281.11170.135393
150.0588250.45180.326518
16-0.030465-0.2340.407894
17-0.113426-0.87120.193577
18-0.076035-0.5840.280712
190.0703140.54010.295584
200.0307490.23620.407052
210.0012020.00920.496333
22-0.073746-0.56650.286616
23-0.074917-0.57540.283589
240.0554190.42570.335945
25-0.144376-1.1090.13597
260.0143590.11030.456275
270.0073050.05610.477721
28-0.074762-0.57430.283989
290.0169870.13050.448316
300.0950810.73030.234038
31-0.051803-0.39790.346069
320.0785280.60320.274349
33-0.039854-0.30610.380293
34-0.05501-0.42250.337085
35-0.018882-0.1450.442589
36-0.021987-0.16890.433233

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.895297 & 6.8769 & 0 \tabularnewline
2 & -0.186539 & -1.4328 & 0.078592 \tabularnewline
3 & 0.081757 & 0.628 & 0.266217 \tabularnewline
4 & 0.061194 & 0.47 & 0.320029 \tabularnewline
5 & 0.103727 & 0.7967 & 0.214398 \tabularnewline
6 & -0.049479 & -0.3801 & 0.352635 \tabularnewline
7 & -0.255072 & -1.9592 & 0.027407 \tabularnewline
8 & -0.136158 & -1.0459 & 0.149948 \tabularnewline
9 & 0.065311 & 0.5017 & 0.308885 \tabularnewline
10 & 0.050741 & 0.3898 & 0.349062 \tabularnewline
11 & 0.139181 & 1.0691 & 0.144696 \tabularnewline
12 & -0.139482 & -1.0714 & 0.14418 \tabularnewline
13 & -0.512443 & -3.9361 & 0.000111 \tabularnewline
14 & 0.144728 & 1.1117 & 0.135393 \tabularnewline
15 & 0.058825 & 0.4518 & 0.326518 \tabularnewline
16 & -0.030465 & -0.234 & 0.407894 \tabularnewline
17 & -0.113426 & -0.8712 & 0.193577 \tabularnewline
18 & -0.076035 & -0.584 & 0.280712 \tabularnewline
19 & 0.070314 & 0.5401 & 0.295584 \tabularnewline
20 & 0.030749 & 0.2362 & 0.407052 \tabularnewline
21 & 0.001202 & 0.0092 & 0.496333 \tabularnewline
22 & -0.073746 & -0.5665 & 0.286616 \tabularnewline
23 & -0.074917 & -0.5754 & 0.283589 \tabularnewline
24 & 0.055419 & 0.4257 & 0.335945 \tabularnewline
25 & -0.144376 & -1.109 & 0.13597 \tabularnewline
26 & 0.014359 & 0.1103 & 0.456275 \tabularnewline
27 & 0.007305 & 0.0561 & 0.477721 \tabularnewline
28 & -0.074762 & -0.5743 & 0.283989 \tabularnewline
29 & 0.016987 & 0.1305 & 0.448316 \tabularnewline
30 & 0.095081 & 0.7303 & 0.234038 \tabularnewline
31 & -0.051803 & -0.3979 & 0.346069 \tabularnewline
32 & 0.078528 & 0.6032 & 0.274349 \tabularnewline
33 & -0.039854 & -0.3061 & 0.380293 \tabularnewline
34 & -0.05501 & -0.4225 & 0.337085 \tabularnewline
35 & -0.018882 & -0.145 & 0.442589 \tabularnewline
36 & -0.021987 & -0.1689 & 0.433233 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71032&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]0.895297[/C][C]6.8769[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.186539[/C][C]-1.4328[/C][C]0.078592[/C][/ROW]
[ROW][C]3[/C][C]0.081757[/C][C]0.628[/C][C]0.266217[/C][/ROW]
[ROW][C]4[/C][C]0.061194[/C][C]0.47[/C][C]0.320029[/C][/ROW]
[ROW][C]5[/C][C]0.103727[/C][C]0.7967[/C][C]0.214398[/C][/ROW]
[ROW][C]6[/C][C]-0.049479[/C][C]-0.3801[/C][C]0.352635[/C][/ROW]
[ROW][C]7[/C][C]-0.255072[/C][C]-1.9592[/C][C]0.027407[/C][/ROW]
[ROW][C]8[/C][C]-0.136158[/C][C]-1.0459[/C][C]0.149948[/C][/ROW]
[ROW][C]9[/C][C]0.065311[/C][C]0.5017[/C][C]0.308885[/C][/ROW]
[ROW][C]10[/C][C]0.050741[/C][C]0.3898[/C][C]0.349062[/C][/ROW]
[ROW][C]11[/C][C]0.139181[/C][C]1.0691[/C][C]0.144696[/C][/ROW]
[ROW][C]12[/C][C]-0.139482[/C][C]-1.0714[/C][C]0.14418[/C][/ROW]
[ROW][C]13[/C][C]-0.512443[/C][C]-3.9361[/C][C]0.000111[/C][/ROW]
[ROW][C]14[/C][C]0.144728[/C][C]1.1117[/C][C]0.135393[/C][/ROW]
[ROW][C]15[/C][C]0.058825[/C][C]0.4518[/C][C]0.326518[/C][/ROW]
[ROW][C]16[/C][C]-0.030465[/C][C]-0.234[/C][C]0.407894[/C][/ROW]
[ROW][C]17[/C][C]-0.113426[/C][C]-0.8712[/C][C]0.193577[/C][/ROW]
[ROW][C]18[/C][C]-0.076035[/C][C]-0.584[/C][C]0.280712[/C][/ROW]
[ROW][C]19[/C][C]0.070314[/C][C]0.5401[/C][C]0.295584[/C][/ROW]
[ROW][C]20[/C][C]0.030749[/C][C]0.2362[/C][C]0.407052[/C][/ROW]
[ROW][C]21[/C][C]0.001202[/C][C]0.0092[/C][C]0.496333[/C][/ROW]
[ROW][C]22[/C][C]-0.073746[/C][C]-0.5665[/C][C]0.286616[/C][/ROW]
[ROW][C]23[/C][C]-0.074917[/C][C]-0.5754[/C][C]0.283589[/C][/ROW]
[ROW][C]24[/C][C]0.055419[/C][C]0.4257[/C][C]0.335945[/C][/ROW]
[ROW][C]25[/C][C]-0.144376[/C][C]-1.109[/C][C]0.13597[/C][/ROW]
[ROW][C]26[/C][C]0.014359[/C][C]0.1103[/C][C]0.456275[/C][/ROW]
[ROW][C]27[/C][C]0.007305[/C][C]0.0561[/C][C]0.477721[/C][/ROW]
[ROW][C]28[/C][C]-0.074762[/C][C]-0.5743[/C][C]0.283989[/C][/ROW]
[ROW][C]29[/C][C]0.016987[/C][C]0.1305[/C][C]0.448316[/C][/ROW]
[ROW][C]30[/C][C]0.095081[/C][C]0.7303[/C][C]0.234038[/C][/ROW]
[ROW][C]31[/C][C]-0.051803[/C][C]-0.3979[/C][C]0.346069[/C][/ROW]
[ROW][C]32[/C][C]0.078528[/C][C]0.6032[/C][C]0.274349[/C][/ROW]
[ROW][C]33[/C][C]-0.039854[/C][C]-0.3061[/C][C]0.380293[/C][/ROW]
[ROW][C]34[/C][C]-0.05501[/C][C]-0.4225[/C][C]0.337085[/C][/ROW]
[ROW][C]35[/C][C]-0.018882[/C][C]-0.145[/C][C]0.442589[/C][/ROW]
[ROW][C]36[/C][C]-0.021987[/C][C]-0.1689[/C][C]0.433233[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71032&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71032&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
10.8952976.87690
2-0.186539-1.43280.078592
30.0817570.6280.266217
40.0611940.470.320029
50.1037270.79670.214398
6-0.049479-0.38010.352635
7-0.255072-1.95920.027407
8-0.136158-1.04590.149948
90.0653110.50170.308885
100.0507410.38980.349062
110.1391811.06910.144696
12-0.139482-1.07140.14418
13-0.512443-3.93610.000111
140.1447281.11170.135393
150.0588250.45180.326518
16-0.030465-0.2340.407894
17-0.113426-0.87120.193577
18-0.076035-0.5840.280712
190.0703140.54010.295584
200.0307490.23620.407052
210.0012020.00920.496333
22-0.073746-0.56650.286616
23-0.074917-0.57540.283589
240.0554190.42570.335945
25-0.144376-1.1090.13597
260.0143590.11030.456275
270.0073050.05610.477721
28-0.074762-0.57430.283989
290.0169870.13050.448316
300.0950810.73030.234038
31-0.051803-0.39790.346069
320.0785280.60320.274349
33-0.039854-0.30610.380293
34-0.05501-0.42250.337085
35-0.018882-0.1450.442589
36-0.021987-0.16890.433233



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; 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')