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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 computationThu, 10 Dec 2009 04:41:58 -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/10/t1260445403erdy3xwpqho7u5z.htm/, Retrieved Fri, 19 Apr 2024 09:26:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65291, Retrieved Fri, 19 Apr 2024 09:26:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact177

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [paper - autocorre...] [2009-12-10 11:41:58] [a931a0a30926b49d162330b43e89b999] [Current]
-    D    [(Partial) Autocorrelation Function] [paper autocorrela...] [2009-12-10 17:03:48] [03c44f58d7d4de05d4cfabfda8c46d2c]
-   PD      [(Partial) Autocorrelation Function] [autocorrelatie fu...] [2009-12-21 15:56:52] [12f02da0296cb21dc23d82ae014a8b71]
- R  D      [(Partial) Autocorrelation Function] [acf graan paper b...] [2009-12-24 16:31:41] [757146c69eaf0537be37c7b0c18216d8]
-         [(Partial) Autocorrelation Function] [autocorrelatie fu...] [2009-12-21 14:58:45] [03c44f58d7d4de05d4cfabfda8c46d2c]
-   P     [(Partial) Autocorrelation Function] [autocorrelatie fu...] [2009-12-21 15:21:40] [12f02da0296cb21dc23d82ae014a8b71]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
108.5
112.3
116.6
115.5
120.1
132.9
128.1
129.3
132.5
131
124.9
120.8
122
122.1
127.4
135.2
137.3
135
136
138.4
134.7
138.4
133.9
133.6
141.2
151.8
155.4
156.6
161.6
160.7
156
159.5
168.7
169.9
169.9
185.9
190.8
195.8
211.9
227.1
251.3
256.7
251.9
251.2
270.3
267.2
243
229.9
187.2
178.2
175.2
192.4
187
184
194.1
212.7
217.5
200.5
205.9
196.5
206.3

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=65291&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=65291&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65291&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
10.9508747.42660
20.8882716.93760
30.8168886.38010
40.7456245.82350
50.6667075.20711e-06
60.5950884.64789e-06
70.5329154.16225e-05
80.4814033.75990.000192
90.4492433.50870.000426
100.4193033.27490.000873
110.3964493.09640.001479
120.3627052.83280.003122
130.328892.56870.006335
140.2866012.23840.014427
150.2423711.8930.031554
160.1922951.50190.069145
170.1350671.05490.147813
180.0833150.65070.258839
190.0330180.25790.398683
20-0.020752-0.16210.435889
21-0.079544-0.62130.268372
22-0.125959-0.98380.164556
23-0.165542-1.29290.100456
24-0.201953-1.57730.059949
25-0.231498-1.80810.037764
26-0.254352-1.98660.025735
27-0.274616-2.14480.01798
28-0.295268-2.30610.012259
29-0.313611-2.44940.008599
30-0.328787-2.56790.006349
31-0.349075-2.72640.004174
32-0.369217-2.88370.002712
33-0.382745-2.98930.002013
34-0.391214-3.05550.001665
35-0.396997-3.10060.001461
36-0.397524-3.10480.001444

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.950874 & 7.4266 & 0 \tabularnewline
2 & 0.888271 & 6.9376 & 0 \tabularnewline
3 & 0.816888 & 6.3801 & 0 \tabularnewline
4 & 0.745624 & 5.8235 & 0 \tabularnewline
5 & 0.666707 & 5.2071 & 1e-06 \tabularnewline
6 & 0.595088 & 4.6478 & 9e-06 \tabularnewline
7 & 0.532915 & 4.1622 & 5e-05 \tabularnewline
8 & 0.481403 & 3.7599 & 0.000192 \tabularnewline
9 & 0.449243 & 3.5087 & 0.000426 \tabularnewline
10 & 0.419303 & 3.2749 & 0.000873 \tabularnewline
11 & 0.396449 & 3.0964 & 0.001479 \tabularnewline
12 & 0.362705 & 2.8328 & 0.003122 \tabularnewline
13 & 0.32889 & 2.5687 & 0.006335 \tabularnewline
14 & 0.286601 & 2.2384 & 0.014427 \tabularnewline
15 & 0.242371 & 1.893 & 0.031554 \tabularnewline
16 & 0.192295 & 1.5019 & 0.069145 \tabularnewline
17 & 0.135067 & 1.0549 & 0.147813 \tabularnewline
18 & 0.083315 & 0.6507 & 0.258839 \tabularnewline
19 & 0.033018 & 0.2579 & 0.398683 \tabularnewline
20 & -0.020752 & -0.1621 & 0.435889 \tabularnewline
21 & -0.079544 & -0.6213 & 0.268372 \tabularnewline
22 & -0.125959 & -0.9838 & 0.164556 \tabularnewline
23 & -0.165542 & -1.2929 & 0.100456 \tabularnewline
24 & -0.201953 & -1.5773 & 0.059949 \tabularnewline
25 & -0.231498 & -1.8081 & 0.037764 \tabularnewline
26 & -0.254352 & -1.9866 & 0.025735 \tabularnewline
27 & -0.274616 & -2.1448 & 0.01798 \tabularnewline
28 & -0.295268 & -2.3061 & 0.012259 \tabularnewline
29 & -0.313611 & -2.4494 & 0.008599 \tabularnewline
30 & -0.328787 & -2.5679 & 0.006349 \tabularnewline
31 & -0.349075 & -2.7264 & 0.004174 \tabularnewline
32 & -0.369217 & -2.8837 & 0.002712 \tabularnewline
33 & -0.382745 & -2.9893 & 0.002013 \tabularnewline
34 & -0.391214 & -3.0555 & 0.001665 \tabularnewline
35 & -0.396997 & -3.1006 & 0.001461 \tabularnewline
36 & -0.397524 & -3.1048 & 0.001444 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65291&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]0.950874[/C][C]7.4266[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.888271[/C][C]6.9376[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.816888[/C][C]6.3801[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.745624[/C][C]5.8235[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.666707[/C][C]5.2071[/C][C]1e-06[/C][/ROW]
[ROW][C]6[/C][C]0.595088[/C][C]4.6478[/C][C]9e-06[/C][/ROW]
[ROW][C]7[/C][C]0.532915[/C][C]4.1622[/C][C]5e-05[/C][/ROW]
[ROW][C]8[/C][C]0.481403[/C][C]3.7599[/C][C]0.000192[/C][/ROW]
[ROW][C]9[/C][C]0.449243[/C][C]3.5087[/C][C]0.000426[/C][/ROW]
[ROW][C]10[/C][C]0.419303[/C][C]3.2749[/C][C]0.000873[/C][/ROW]
[ROW][C]11[/C][C]0.396449[/C][C]3.0964[/C][C]0.001479[/C][/ROW]
[ROW][C]12[/C][C]0.362705[/C][C]2.8328[/C][C]0.003122[/C][/ROW]
[ROW][C]13[/C][C]0.32889[/C][C]2.5687[/C][C]0.006335[/C][/ROW]
[ROW][C]14[/C][C]0.286601[/C][C]2.2384[/C][C]0.014427[/C][/ROW]
[ROW][C]15[/C][C]0.242371[/C][C]1.893[/C][C]0.031554[/C][/ROW]
[ROW][C]16[/C][C]0.192295[/C][C]1.5019[/C][C]0.069145[/C][/ROW]
[ROW][C]17[/C][C]0.135067[/C][C]1.0549[/C][C]0.147813[/C][/ROW]
[ROW][C]18[/C][C]0.083315[/C][C]0.6507[/C][C]0.258839[/C][/ROW]
[ROW][C]19[/C][C]0.033018[/C][C]0.2579[/C][C]0.398683[/C][/ROW]
[ROW][C]20[/C][C]-0.020752[/C][C]-0.1621[/C][C]0.435889[/C][/ROW]
[ROW][C]21[/C][C]-0.079544[/C][C]-0.6213[/C][C]0.268372[/C][/ROW]
[ROW][C]22[/C][C]-0.125959[/C][C]-0.9838[/C][C]0.164556[/C][/ROW]
[ROW][C]23[/C][C]-0.165542[/C][C]-1.2929[/C][C]0.100456[/C][/ROW]
[ROW][C]24[/C][C]-0.201953[/C][C]-1.5773[/C][C]0.059949[/C][/ROW]
[ROW][C]25[/C][C]-0.231498[/C][C]-1.8081[/C][C]0.037764[/C][/ROW]
[ROW][C]26[/C][C]-0.254352[/C][C]-1.9866[/C][C]0.025735[/C][/ROW]
[ROW][C]27[/C][C]-0.274616[/C][C]-2.1448[/C][C]0.01798[/C][/ROW]
[ROW][C]28[/C][C]-0.295268[/C][C]-2.3061[/C][C]0.012259[/C][/ROW]
[ROW][C]29[/C][C]-0.313611[/C][C]-2.4494[/C][C]0.008599[/C][/ROW]
[ROW][C]30[/C][C]-0.328787[/C][C]-2.5679[/C][C]0.006349[/C][/ROW]
[ROW][C]31[/C][C]-0.349075[/C][C]-2.7264[/C][C]0.004174[/C][/ROW]
[ROW][C]32[/C][C]-0.369217[/C][C]-2.8837[/C][C]0.002712[/C][/ROW]
[ROW][C]33[/C][C]-0.382745[/C][C]-2.9893[/C][C]0.002013[/C][/ROW]
[ROW][C]34[/C][C]-0.391214[/C][C]-3.0555[/C][C]0.001665[/C][/ROW]
[ROW][C]35[/C][C]-0.396997[/C][C]-3.1006[/C][C]0.001461[/C][/ROW]
[ROW][C]36[/C][C]-0.397524[/C][C]-3.1048[/C][C]0.001444[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65291&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65291&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
10.9508747.42660
20.8882716.93760
30.8168886.38010
40.7456245.82350
50.6667075.20711e-06
60.5950884.64789e-06
70.5329154.16225e-05
80.4814033.75990.000192
90.4492433.50870.000426
100.4193033.27490.000873
110.3964493.09640.001479
120.3627052.83280.003122
130.328892.56870.006335
140.2866012.23840.014427
150.2423711.8930.031554
160.1922951.50190.069145
170.1350671.05490.147813
180.0833150.65070.258839
190.0330180.25790.398683
20-0.020752-0.16210.435889
21-0.079544-0.62130.268372
22-0.125959-0.98380.164556
23-0.165542-1.29290.100456
24-0.201953-1.57730.059949
25-0.231498-1.80810.037764
26-0.254352-1.98660.025735
27-0.274616-2.14480.01798
28-0.295268-2.30610.012259
29-0.313611-2.44940.008599
30-0.328787-2.56790.006349
31-0.349075-2.72640.004174
32-0.369217-2.88370.002712
33-0.382745-2.98930.002013
34-0.391214-3.05550.001665
35-0.396997-3.10060.001461
36-0.397524-3.10480.001444






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9508747.42660
2-0.165802-1.2950.100107
3-0.108692-0.84890.199625
4-0.017337-0.13540.446367
5-0.120556-0.94160.175063
60.0492950.3850.350785
70.0500060.39060.348742
80.0370520.28940.386635
90.1504891.17540.12221
10-0.07393-0.57740.282893
110.0205550.16050.436492
12-0.157828-1.23270.111214
13-0.028575-0.22320.412072
14-0.066498-0.51940.302693
15-0.024414-0.19070.424706
16-0.028493-0.22250.412318
17-0.092594-0.72320.236167
180.0408370.31890.375428
19-0.043736-0.34160.366918
20-0.149184-1.16520.124244
21-0.085834-0.67040.25257
220.0350050.27340.392737
230.0190860.14910.440997
24-0.048636-0.37990.352684
250.0301630.23560.407273
26-0.000252-0.0020.499219
27-0.053547-0.41820.338629
28-0.052782-0.41220.340803
29-0.04619-0.36080.359766
300.0363550.28390.388708
31-0.084919-0.66320.254839
320.013840.10810.457139
330.0592890.46310.322483
34-0.014518-0.11340.455047
35-0.00598-0.04670.481449
36-0.002805-0.02190.491295

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.950874 & 7.4266 & 0 \tabularnewline
2 & -0.165802 & -1.295 & 0.100107 \tabularnewline
3 & -0.108692 & -0.8489 & 0.199625 \tabularnewline
4 & -0.017337 & -0.1354 & 0.446367 \tabularnewline
5 & -0.120556 & -0.9416 & 0.175063 \tabularnewline
6 & 0.049295 & 0.385 & 0.350785 \tabularnewline
7 & 0.050006 & 0.3906 & 0.348742 \tabularnewline
8 & 0.037052 & 0.2894 & 0.386635 \tabularnewline
9 & 0.150489 & 1.1754 & 0.12221 \tabularnewline
10 & -0.07393 & -0.5774 & 0.282893 \tabularnewline
11 & 0.020555 & 0.1605 & 0.436492 \tabularnewline
12 & -0.157828 & -1.2327 & 0.111214 \tabularnewline
13 & -0.028575 & -0.2232 & 0.412072 \tabularnewline
14 & -0.066498 & -0.5194 & 0.302693 \tabularnewline
15 & -0.024414 & -0.1907 & 0.424706 \tabularnewline
16 & -0.028493 & -0.2225 & 0.412318 \tabularnewline
17 & -0.092594 & -0.7232 & 0.236167 \tabularnewline
18 & 0.040837 & 0.3189 & 0.375428 \tabularnewline
19 & -0.043736 & -0.3416 & 0.366918 \tabularnewline
20 & -0.149184 & -1.1652 & 0.124244 \tabularnewline
21 & -0.085834 & -0.6704 & 0.25257 \tabularnewline
22 & 0.035005 & 0.2734 & 0.392737 \tabularnewline
23 & 0.019086 & 0.1491 & 0.440997 \tabularnewline
24 & -0.048636 & -0.3799 & 0.352684 \tabularnewline
25 & 0.030163 & 0.2356 & 0.407273 \tabularnewline
26 & -0.000252 & -0.002 & 0.499219 \tabularnewline
27 & -0.053547 & -0.4182 & 0.338629 \tabularnewline
28 & -0.052782 & -0.4122 & 0.340803 \tabularnewline
29 & -0.04619 & -0.3608 & 0.359766 \tabularnewline
30 & 0.036355 & 0.2839 & 0.388708 \tabularnewline
31 & -0.084919 & -0.6632 & 0.254839 \tabularnewline
32 & 0.01384 & 0.1081 & 0.457139 \tabularnewline
33 & 0.059289 & 0.4631 & 0.322483 \tabularnewline
34 & -0.014518 & -0.1134 & 0.455047 \tabularnewline
35 & -0.00598 & -0.0467 & 0.481449 \tabularnewline
36 & -0.002805 & -0.0219 & 0.491295 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65291&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]0.950874[/C][C]7.4266[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.165802[/C][C]-1.295[/C][C]0.100107[/C][/ROW]
[ROW][C]3[/C][C]-0.108692[/C][C]-0.8489[/C][C]0.199625[/C][/ROW]
[ROW][C]4[/C][C]-0.017337[/C][C]-0.1354[/C][C]0.446367[/C][/ROW]
[ROW][C]5[/C][C]-0.120556[/C][C]-0.9416[/C][C]0.175063[/C][/ROW]
[ROW][C]6[/C][C]0.049295[/C][C]0.385[/C][C]0.350785[/C][/ROW]
[ROW][C]7[/C][C]0.050006[/C][C]0.3906[/C][C]0.348742[/C][/ROW]
[ROW][C]8[/C][C]0.037052[/C][C]0.2894[/C][C]0.386635[/C][/ROW]
[ROW][C]9[/C][C]0.150489[/C][C]1.1754[/C][C]0.12221[/C][/ROW]
[ROW][C]10[/C][C]-0.07393[/C][C]-0.5774[/C][C]0.282893[/C][/ROW]
[ROW][C]11[/C][C]0.020555[/C][C]0.1605[/C][C]0.436492[/C][/ROW]
[ROW][C]12[/C][C]-0.157828[/C][C]-1.2327[/C][C]0.111214[/C][/ROW]
[ROW][C]13[/C][C]-0.028575[/C][C]-0.2232[/C][C]0.412072[/C][/ROW]
[ROW][C]14[/C][C]-0.066498[/C][C]-0.5194[/C][C]0.302693[/C][/ROW]
[ROW][C]15[/C][C]-0.024414[/C][C]-0.1907[/C][C]0.424706[/C][/ROW]
[ROW][C]16[/C][C]-0.028493[/C][C]-0.2225[/C][C]0.412318[/C][/ROW]
[ROW][C]17[/C][C]-0.092594[/C][C]-0.7232[/C][C]0.236167[/C][/ROW]
[ROW][C]18[/C][C]0.040837[/C][C]0.3189[/C][C]0.375428[/C][/ROW]
[ROW][C]19[/C][C]-0.043736[/C][C]-0.3416[/C][C]0.366918[/C][/ROW]
[ROW][C]20[/C][C]-0.149184[/C][C]-1.1652[/C][C]0.124244[/C][/ROW]
[ROW][C]21[/C][C]-0.085834[/C][C]-0.6704[/C][C]0.25257[/C][/ROW]
[ROW][C]22[/C][C]0.035005[/C][C]0.2734[/C][C]0.392737[/C][/ROW]
[ROW][C]23[/C][C]0.019086[/C][C]0.1491[/C][C]0.440997[/C][/ROW]
[ROW][C]24[/C][C]-0.048636[/C][C]-0.3799[/C][C]0.352684[/C][/ROW]
[ROW][C]25[/C][C]0.030163[/C][C]0.2356[/C][C]0.407273[/C][/ROW]
[ROW][C]26[/C][C]-0.000252[/C][C]-0.002[/C][C]0.499219[/C][/ROW]
[ROW][C]27[/C][C]-0.053547[/C][C]-0.4182[/C][C]0.338629[/C][/ROW]
[ROW][C]28[/C][C]-0.052782[/C][C]-0.4122[/C][C]0.340803[/C][/ROW]
[ROW][C]29[/C][C]-0.04619[/C][C]-0.3608[/C][C]0.359766[/C][/ROW]
[ROW][C]30[/C][C]0.036355[/C][C]0.2839[/C][C]0.388708[/C][/ROW]
[ROW][C]31[/C][C]-0.084919[/C][C]-0.6632[/C][C]0.254839[/C][/ROW]
[ROW][C]32[/C][C]0.01384[/C][C]0.1081[/C][C]0.457139[/C][/ROW]
[ROW][C]33[/C][C]0.059289[/C][C]0.4631[/C][C]0.322483[/C][/ROW]
[ROW][C]34[/C][C]-0.014518[/C][C]-0.1134[/C][C]0.455047[/C][/ROW]
[ROW][C]35[/C][C]-0.00598[/C][C]-0.0467[/C][C]0.481449[/C][/ROW]
[ROW][C]36[/C][C]-0.002805[/C][C]-0.0219[/C][C]0.491295[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65291&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65291&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
10.9508747.42660
2-0.165802-1.2950.100107
3-0.108692-0.84890.199625
4-0.017337-0.13540.446367
5-0.120556-0.94160.175063
60.0492950.3850.350785
70.0500060.39060.348742
80.0370520.28940.386635
90.1504891.17540.12221
10-0.07393-0.57740.282893
110.0205550.16050.436492
12-0.157828-1.23270.111214
13-0.028575-0.22320.412072
14-0.066498-0.51940.302693
15-0.024414-0.19070.424706
16-0.028493-0.22250.412318
17-0.092594-0.72320.236167
180.0408370.31890.375428
19-0.043736-0.34160.366918
20-0.149184-1.16520.124244
21-0.085834-0.67040.25257
220.0350050.27340.392737
230.0190860.14910.440997
24-0.048636-0.37990.352684
250.0301630.23560.407273
26-0.000252-0.0020.499219
27-0.053547-0.41820.338629
28-0.052782-0.41220.340803
29-0.04619-0.36080.359766
300.0363550.28390.388708
31-0.084919-0.66320.254839
320.013840.10810.457139
330.0592890.46310.322483
34-0.014518-0.11340.455047
35-0.00598-0.04670.481449
36-0.002805-0.02190.491295


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; 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')