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Description of Statistical Computation

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, 04 Dec 2009 10:19:28 -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/04/t1259947220g9eqw94ursse2q9.htm/, Retrieved Sun, 28 Apr 2024 05:32:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63928, Retrieved Sun, 28 Apr 2024 05:32:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact83

Tree of Dependent Computations

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] [WS8] [2009-11-25 21:02:46] [cd6314e7e707a6546bd4604c9d1f2b69]
-                 [(Partial) Autocorrelation Function] [Paper - ACF (1)] [2009-12-04 17:19:28] [ea241b681aafed79da4b5b99fad98471] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
216234
213587
209465
204045
200237
203666
241476
260307
243324
244460
233575
237217
235243
230354
227184
221678
217142
219452
256446
265845
248624
241114
229245
231805
219277
219313
212610
214771
211142
211457
240048
240636
230580
208795
197922
194596
194581
185686
178106
172608
167302
168053
202300
202388
182516
173476
166444
171297
169701
164182
161914
159612
151001
158114
186530
187069
174330
169362
166827
178037
186412
189226
191563
188906
186005
195309
223532
226899
214126

Tables (Output of Computation)





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=63928&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=63928&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63928&T=0

As an alternative you can also use a QR Code:  
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
10.9040427.50950
20.7619446.32920
30.6714785.57770
40.6365385.28751e-06
50.6277535.21451e-06
60.6050175.02562e-06
70.5621474.66957e-06
80.5013064.16424.4e-05
90.4694093.89920.000111
100.4753093.94829.4e-05
110.5300914.40331.9e-05
120.5348564.44281.6e-05
130.4016123.3360.000686
140.2405051.99780.024842
150.1310511.08860.14006
160.0761980.6330.264429
170.0471670.39180.348208
180.0132870.11040.456219
19-0.034992-0.29070.38609
20-0.092027-0.76440.223608
21-0.126019-1.04680.149425
22-0.127254-1.0570.147088
23-0.08834-0.73380.232776
24-0.091712-0.76180.224384
25-0.19457-1.61620.055305
26-0.311694-2.58910.005863
27-0.376144-3.12450.001302
28-0.392674-3.26180.000861
29-0.385864-3.20520.001023
30-0.38545-3.20180.001033
31-0.399626-3.31950.000721
32-0.415052-3.44770.000484
33-0.40994-3.40520.000553
34-0.372179-3.09150.001436
35-0.307249-2.55220.006461
36-0.277145-2.30210.012175

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.904042 & 7.5095 & 0 \tabularnewline
2 & 0.761944 & 6.3292 & 0 \tabularnewline
3 & 0.671478 & 5.5777 & 0 \tabularnewline
4 & 0.636538 & 5.2875 & 1e-06 \tabularnewline
5 & 0.627753 & 5.2145 & 1e-06 \tabularnewline
6 & 0.605017 & 5.0256 & 2e-06 \tabularnewline
7 & 0.562147 & 4.6695 & 7e-06 \tabularnewline
8 & 0.501306 & 4.1642 & 4.4e-05 \tabularnewline
9 & 0.469409 & 3.8992 & 0.000111 \tabularnewline
10 & 0.475309 & 3.9482 & 9.4e-05 \tabularnewline
11 & 0.530091 & 4.4033 & 1.9e-05 \tabularnewline
12 & 0.534856 & 4.4428 & 1.6e-05 \tabularnewline
13 & 0.401612 & 3.336 & 0.000686 \tabularnewline
14 & 0.240505 & 1.9978 & 0.024842 \tabularnewline
15 & 0.131051 & 1.0886 & 0.14006 \tabularnewline
16 & 0.076198 & 0.633 & 0.264429 \tabularnewline
17 & 0.047167 & 0.3918 & 0.348208 \tabularnewline
18 & 0.013287 & 0.1104 & 0.456219 \tabularnewline
19 & -0.034992 & -0.2907 & 0.38609 \tabularnewline
20 & -0.092027 & -0.7644 & 0.223608 \tabularnewline
21 & -0.126019 & -1.0468 & 0.149425 \tabularnewline
22 & -0.127254 & -1.057 & 0.147088 \tabularnewline
23 & -0.08834 & -0.7338 & 0.232776 \tabularnewline
24 & -0.091712 & -0.7618 & 0.224384 \tabularnewline
25 & -0.19457 & -1.6162 & 0.055305 \tabularnewline
26 & -0.311694 & -2.5891 & 0.005863 \tabularnewline
27 & -0.376144 & -3.1245 & 0.001302 \tabularnewline
28 & -0.392674 & -3.2618 & 0.000861 \tabularnewline
29 & -0.385864 & -3.2052 & 0.001023 \tabularnewline
30 & -0.38545 & -3.2018 & 0.001033 \tabularnewline
31 & -0.399626 & -3.3195 & 0.000721 \tabularnewline
32 & -0.415052 & -3.4477 & 0.000484 \tabularnewline
33 & -0.40994 & -3.4052 & 0.000553 \tabularnewline
34 & -0.372179 & -3.0915 & 0.001436 \tabularnewline
35 & -0.307249 & -2.5522 & 0.006461 \tabularnewline
36 & -0.277145 & -2.3021 & 0.012175 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63928&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]0.904042[/C][C]7.5095[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.761944[/C][C]6.3292[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.671478[/C][C]5.5777[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.636538[/C][C]5.2875[/C][C]1e-06[/C][/ROW]
[ROW][C]5[/C][C]0.627753[/C][C]5.2145[/C][C]1e-06[/C][/ROW]
[ROW][C]6[/C][C]0.605017[/C][C]5.0256[/C][C]2e-06[/C][/ROW]
[ROW][C]7[/C][C]0.562147[/C][C]4.6695[/C][C]7e-06[/C][/ROW]
[ROW][C]8[/C][C]0.501306[/C][C]4.1642[/C][C]4.4e-05[/C][/ROW]
[ROW][C]9[/C][C]0.469409[/C][C]3.8992[/C][C]0.000111[/C][/ROW]
[ROW][C]10[/C][C]0.475309[/C][C]3.9482[/C][C]9.4e-05[/C][/ROW]
[ROW][C]11[/C][C]0.530091[/C][C]4.4033[/C][C]1.9e-05[/C][/ROW]
[ROW][C]12[/C][C]0.534856[/C][C]4.4428[/C][C]1.6e-05[/C][/ROW]
[ROW][C]13[/C][C]0.401612[/C][C]3.336[/C][C]0.000686[/C][/ROW]
[ROW][C]14[/C][C]0.240505[/C][C]1.9978[/C][C]0.024842[/C][/ROW]
[ROW][C]15[/C][C]0.131051[/C][C]1.0886[/C][C]0.14006[/C][/ROW]
[ROW][C]16[/C][C]0.076198[/C][C]0.633[/C][C]0.264429[/C][/ROW]
[ROW][C]17[/C][C]0.047167[/C][C]0.3918[/C][C]0.348208[/C][/ROW]
[ROW][C]18[/C][C]0.013287[/C][C]0.1104[/C][C]0.456219[/C][/ROW]
[ROW][C]19[/C][C]-0.034992[/C][C]-0.2907[/C][C]0.38609[/C][/ROW]
[ROW][C]20[/C][C]-0.092027[/C][C]-0.7644[/C][C]0.223608[/C][/ROW]
[ROW][C]21[/C][C]-0.126019[/C][C]-1.0468[/C][C]0.149425[/C][/ROW]
[ROW][C]22[/C][C]-0.127254[/C][C]-1.057[/C][C]0.147088[/C][/ROW]
[ROW][C]23[/C][C]-0.08834[/C][C]-0.7338[/C][C]0.232776[/C][/ROW]
[ROW][C]24[/C][C]-0.091712[/C][C]-0.7618[/C][C]0.224384[/C][/ROW]
[ROW][C]25[/C][C]-0.19457[/C][C]-1.6162[/C][C]0.055305[/C][/ROW]
[ROW][C]26[/C][C]-0.311694[/C][C]-2.5891[/C][C]0.005863[/C][/ROW]
[ROW][C]27[/C][C]-0.376144[/C][C]-3.1245[/C][C]0.001302[/C][/ROW]
[ROW][C]28[/C][C]-0.392674[/C][C]-3.2618[/C][C]0.000861[/C][/ROW]
[ROW][C]29[/C][C]-0.385864[/C][C]-3.2052[/C][C]0.001023[/C][/ROW]
[ROW][C]30[/C][C]-0.38545[/C][C]-3.2018[/C][C]0.001033[/C][/ROW]
[ROW][C]31[/C][C]-0.399626[/C][C]-3.3195[/C][C]0.000721[/C][/ROW]
[ROW][C]32[/C][C]-0.415052[/C][C]-3.4477[/C][C]0.000484[/C][/ROW]
[ROW][C]33[/C][C]-0.40994[/C][C]-3.4052[/C][C]0.000553[/C][/ROW]
[ROW][C]34[/C][C]-0.372179[/C][C]-3.0915[/C][C]0.001436[/C][/ROW]
[ROW][C]35[/C][C]-0.307249[/C][C]-2.5522[/C][C]0.006461[/C][/ROW]
[ROW][C]36[/C][C]-0.277145[/C][C]-2.3021[/C][C]0.012175[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63928&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63928&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9040427.50950
20.7619446.32920
30.6714785.57770
40.6365385.28751e-06
50.6277535.21451e-06
60.6050175.02562e-06
70.5621474.66957e-06
80.5013064.16424.4e-05
90.4694093.89920.000111
100.4753093.94829.4e-05
110.5300914.40331.9e-05
120.5348564.44281.6e-05
130.4016123.3360.000686
140.2405051.99780.024842
150.1310511.08860.14006
160.0761980.6330.264429
170.0471670.39180.348208
180.0132870.11040.456219
19-0.034992-0.29070.38609
20-0.092027-0.76440.223608
21-0.126019-1.04680.149425
22-0.127254-1.0570.147088
23-0.08834-0.73380.232776
24-0.091712-0.76180.224384
25-0.19457-1.61620.055305
26-0.311694-2.58910.005863
27-0.376144-3.12450.001302
28-0.392674-3.26180.000861
29-0.385864-3.20520.001023
30-0.38545-3.20180.001033
31-0.399626-3.31950.000721
32-0.415052-3.44770.000484
33-0.40994-3.40520.000553
34-0.372179-3.09150.001436
35-0.307249-2.55220.006461
36-0.277145-2.30210.012175






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9040427.50950
2-0.302928-2.51630.007094
30.2883122.39490.009672
40.1044020.86720.194411
50.0965390.80190.212678
6-0.042213-0.35060.363461
70.0068050.05650.477542
8-0.093121-0.77350.220928
90.1835411.52460.065964
100.0473580.39340.347623
110.3259832.70780.004266
12-0.412527-3.42670.000517
13-0.561227-4.66197e-06
140.0439640.36520.358042
15-0.074531-0.61910.268944
16-0.142381-1.18270.120492
170.0594210.49360.311581
18-0.067071-0.55710.28962
190.0971770.80720.211158
20-0.022025-0.1830.427687
21-0.007064-0.05870.47669
220.0119060.09890.460751
23-0.013058-0.10850.45697
240.0035060.02910.488426
250.0031180.02590.489704
26-0.042366-0.35190.362985
270.0905420.75210.227276
28-0.093309-0.77510.22047
290.0598240.49690.310406
30-0.098164-0.81540.208822
31-0.007349-0.0610.475749
320.0283260.23530.407337
330.0199330.16560.434486
340.0431870.35870.360444
350.0127560.1060.457961
360.0215450.1790.429245

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.904042 & 7.5095 & 0 \tabularnewline
2 & -0.302928 & -2.5163 & 0.007094 \tabularnewline
3 & 0.288312 & 2.3949 & 0.009672 \tabularnewline
4 & 0.104402 & 0.8672 & 0.194411 \tabularnewline
5 & 0.096539 & 0.8019 & 0.212678 \tabularnewline
6 & -0.042213 & -0.3506 & 0.363461 \tabularnewline
7 & 0.006805 & 0.0565 & 0.477542 \tabularnewline
8 & -0.093121 & -0.7735 & 0.220928 \tabularnewline
9 & 0.183541 & 1.5246 & 0.065964 \tabularnewline
10 & 0.047358 & 0.3934 & 0.347623 \tabularnewline
11 & 0.325983 & 2.7078 & 0.004266 \tabularnewline
12 & -0.412527 & -3.4267 & 0.000517 \tabularnewline
13 & -0.561227 & -4.6619 & 7e-06 \tabularnewline
14 & 0.043964 & 0.3652 & 0.358042 \tabularnewline
15 & -0.074531 & -0.6191 & 0.268944 \tabularnewline
16 & -0.142381 & -1.1827 & 0.120492 \tabularnewline
17 & 0.059421 & 0.4936 & 0.311581 \tabularnewline
18 & -0.067071 & -0.5571 & 0.28962 \tabularnewline
19 & 0.097177 & 0.8072 & 0.211158 \tabularnewline
20 & -0.022025 & -0.183 & 0.427687 \tabularnewline
21 & -0.007064 & -0.0587 & 0.47669 \tabularnewline
22 & 0.011906 & 0.0989 & 0.460751 \tabularnewline
23 & -0.013058 & -0.1085 & 0.45697 \tabularnewline
24 & 0.003506 & 0.0291 & 0.488426 \tabularnewline
25 & 0.003118 & 0.0259 & 0.489704 \tabularnewline
26 & -0.042366 & -0.3519 & 0.362985 \tabularnewline
27 & 0.090542 & 0.7521 & 0.227276 \tabularnewline
28 & -0.093309 & -0.7751 & 0.22047 \tabularnewline
29 & 0.059824 & 0.4969 & 0.310406 \tabularnewline
30 & -0.098164 & -0.8154 & 0.208822 \tabularnewline
31 & -0.007349 & -0.061 & 0.475749 \tabularnewline
32 & 0.028326 & 0.2353 & 0.407337 \tabularnewline
33 & 0.019933 & 0.1656 & 0.434486 \tabularnewline
34 & 0.043187 & 0.3587 & 0.360444 \tabularnewline
35 & 0.012756 & 0.106 & 0.457961 \tabularnewline
36 & 0.021545 & 0.179 & 0.429245 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63928&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]0.904042[/C][C]7.5095[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.302928[/C][C]-2.5163[/C][C]0.007094[/C][/ROW]
[ROW][C]3[/C][C]0.288312[/C][C]2.3949[/C][C]0.009672[/C][/ROW]
[ROW][C]4[/C][C]0.104402[/C][C]0.8672[/C][C]0.194411[/C][/ROW]
[ROW][C]5[/C][C]0.096539[/C][C]0.8019[/C][C]0.212678[/C][/ROW]
[ROW][C]6[/C][C]-0.042213[/C][C]-0.3506[/C][C]0.363461[/C][/ROW]
[ROW][C]7[/C][C]0.006805[/C][C]0.0565[/C][C]0.477542[/C][/ROW]
[ROW][C]8[/C][C]-0.093121[/C][C]-0.7735[/C][C]0.220928[/C][/ROW]
[ROW][C]9[/C][C]0.183541[/C][C]1.5246[/C][C]0.065964[/C][/ROW]
[ROW][C]10[/C][C]0.047358[/C][C]0.3934[/C][C]0.347623[/C][/ROW]
[ROW][C]11[/C][C]0.325983[/C][C]2.7078[/C][C]0.004266[/C][/ROW]
[ROW][C]12[/C][C]-0.412527[/C][C]-3.4267[/C][C]0.000517[/C][/ROW]
[ROW][C]13[/C][C]-0.561227[/C][C]-4.6619[/C][C]7e-06[/C][/ROW]
[ROW][C]14[/C][C]0.043964[/C][C]0.3652[/C][C]0.358042[/C][/ROW]
[ROW][C]15[/C][C]-0.074531[/C][C]-0.6191[/C][C]0.268944[/C][/ROW]
[ROW][C]16[/C][C]-0.142381[/C][C]-1.1827[/C][C]0.120492[/C][/ROW]
[ROW][C]17[/C][C]0.059421[/C][C]0.4936[/C][C]0.311581[/C][/ROW]
[ROW][C]18[/C][C]-0.067071[/C][C]-0.5571[/C][C]0.28962[/C][/ROW]
[ROW][C]19[/C][C]0.097177[/C][C]0.8072[/C][C]0.211158[/C][/ROW]
[ROW][C]20[/C][C]-0.022025[/C][C]-0.183[/C][C]0.427687[/C][/ROW]
[ROW][C]21[/C][C]-0.007064[/C][C]-0.0587[/C][C]0.47669[/C][/ROW]
[ROW][C]22[/C][C]0.011906[/C][C]0.0989[/C][C]0.460751[/C][/ROW]
[ROW][C]23[/C][C]-0.013058[/C][C]-0.1085[/C][C]0.45697[/C][/ROW]
[ROW][C]24[/C][C]0.003506[/C][C]0.0291[/C][C]0.488426[/C][/ROW]
[ROW][C]25[/C][C]0.003118[/C][C]0.0259[/C][C]0.489704[/C][/ROW]
[ROW][C]26[/C][C]-0.042366[/C][C]-0.3519[/C][C]0.362985[/C][/ROW]
[ROW][C]27[/C][C]0.090542[/C][C]0.7521[/C][C]0.227276[/C][/ROW]
[ROW][C]28[/C][C]-0.093309[/C][C]-0.7751[/C][C]0.22047[/C][/ROW]
[ROW][C]29[/C][C]0.059824[/C][C]0.4969[/C][C]0.310406[/C][/ROW]
[ROW][C]30[/C][C]-0.098164[/C][C]-0.8154[/C][C]0.208822[/C][/ROW]
[ROW][C]31[/C][C]-0.007349[/C][C]-0.061[/C][C]0.475749[/C][/ROW]
[ROW][C]32[/C][C]0.028326[/C][C]0.2353[/C][C]0.407337[/C][/ROW]
[ROW][C]33[/C][C]0.019933[/C][C]0.1656[/C][C]0.434486[/C][/ROW]
[ROW][C]34[/C][C]0.043187[/C][C]0.3587[/C][C]0.360444[/C][/ROW]
[ROW][C]35[/C][C]0.012756[/C][C]0.106[/C][C]0.457961[/C][/ROW]
[ROW][C]36[/C][C]0.021545[/C][C]0.179[/C][C]0.429245[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63928&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63928&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9040427.50950
2-0.302928-2.51630.007094
30.2883122.39490.009672
40.1044020.86720.194411
50.0965390.80190.212678
6-0.042213-0.35060.363461
70.0068050.05650.477542
8-0.093121-0.77350.220928
90.1835411.52460.065964
100.0473580.39340.347623
110.3259832.70780.004266
12-0.412527-3.42670.000517
13-0.561227-4.66197e-06
140.0439640.36520.358042
15-0.074531-0.61910.268944
16-0.142381-1.18270.120492
170.0594210.49360.311581
18-0.067071-0.55710.28962
190.0971770.80720.211158
20-0.022025-0.1830.427687
21-0.007064-0.05870.47669
220.0119060.09890.460751
23-0.013058-0.10850.45697
240.0035060.02910.488426
250.0031180.02590.489704
26-0.042366-0.35190.362985
270.0905420.75210.227276
28-0.093309-0.77510.22047
290.0598240.49690.310406
30-0.098164-0.81540.208822
31-0.007349-0.0610.475749
320.0283260.23530.407337
330.0199330.16560.434486
340.0431870.35870.360444
350.0127560.1060.457961
360.0215450.1790.429245


Figures (Output of Computation)

Input Parameters & R Code

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')