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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, 04 Dec 2009 10:50:40 -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/t1259949142tnx8wd0sjsa2qji.htm/, Retrieved Sun, 28 Apr 2024 06:11:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63976, Retrieved Sun, 28 Apr 2024 06:11:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [] [2009-11-27 14:46:03] [b98453cac15ba1066b407e146608df68]
- R PD    [(Partial) Autocorrelation Function] [Partiele autocorr...] [2009-12-03 17:25:34] [863a41223bd4bb97f4e5094488ffff34]
-   P       [(Partial) Autocorrelation Function] [Partial correlati...] [2009-12-03 17:57:16] [863a41223bd4bb97f4e5094488ffff34]
-   P           [(Partial) Autocorrelation Function] [Autocorrelation e...] [2009-12-04 17:50:40] [b1ac221d009d6e5c29a4ef1869874933] [Current]
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Dataseries X:
89.6
92.8
107.6
104.6
103
106.9
56.3
93.4
109.1
113.8
97.4
72.5
82.7
88.9
105.9
100.8
94
105
58.5
87.6
113.1
112.5
89.6
74.5
82.7
90.1
109.4
96
89.2
109.1
49.1
92.9
107.7
103.5
91.1
79.8
71.9
82.9
90.1
100.7
90.7
108.8
44.1
93.6
107.4
96.5
93.6
76.5
76.7
84
103.3
88.5
99
105.9
44.7
94
107.1
104.8
102.5
77.7
85.2
91.3
106.5
92.4
97.5
107
51.1
98.6
102.2
114.3
99.4
72.5
92.3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63976&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]0 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=63976&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63976&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.082019-0.64060.262095
20.1777551.38830.085046
30.1412551.10320.137129
40.1194190.93270.177328
50.1222720.9550.171679
60.2498721.95160.027793
7-0.067954-0.53070.298764
80.1872211.46220.074404
90.1875941.46520.074007
10-0.024809-0.19380.423501
110.1717621.34150.092365
12-0.129591-1.01210.157735
130.0070290.05490.478198
140.0031680.02470.490169
150.1377981.07620.143029
16-0.108743-0.84930.199516
170.1575831.23080.111569
18-0.089705-0.70060.243102
190.0254270.19860.421621
20-0.109739-0.85710.197376
210.0358460.280.390226
22-0.109247-0.85320.198431
230.0472760.36920.356615
24-0.083567-0.65270.258207
25-0.108994-0.85130.198975
260.1313761.02610.154453
27-0.117457-0.91740.181282
28-0.133763-1.04470.150136
29-0.009587-0.07490.470278
30-0.057731-0.45090.326834
31-0.143122-1.11780.134014
320.0887120.69290.245514
33-0.099407-0.77640.220257
34-0.062416-0.48750.313832
350.0159320.12440.45069
36-0.153122-1.19590.118178

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.082019 & -0.6406 & 0.262095 \tabularnewline
2 & 0.177755 & 1.3883 & 0.085046 \tabularnewline
3 & 0.141255 & 1.1032 & 0.137129 \tabularnewline
4 & 0.119419 & 0.9327 & 0.177328 \tabularnewline
5 & 0.122272 & 0.955 & 0.171679 \tabularnewline
6 & 0.249872 & 1.9516 & 0.027793 \tabularnewline
7 & -0.067954 & -0.5307 & 0.298764 \tabularnewline
8 & 0.187221 & 1.4622 & 0.074404 \tabularnewline
9 & 0.187594 & 1.4652 & 0.074007 \tabularnewline
10 & -0.024809 & -0.1938 & 0.423501 \tabularnewline
11 & 0.171762 & 1.3415 & 0.092365 \tabularnewline
12 & -0.129591 & -1.0121 & 0.157735 \tabularnewline
13 & 0.007029 & 0.0549 & 0.478198 \tabularnewline
14 & 0.003168 & 0.0247 & 0.490169 \tabularnewline
15 & 0.137798 & 1.0762 & 0.143029 \tabularnewline
16 & -0.108743 & -0.8493 & 0.199516 \tabularnewline
17 & 0.157583 & 1.2308 & 0.111569 \tabularnewline
18 & -0.089705 & -0.7006 & 0.243102 \tabularnewline
19 & 0.025427 & 0.1986 & 0.421621 \tabularnewline
20 & -0.109739 & -0.8571 & 0.197376 \tabularnewline
21 & 0.035846 & 0.28 & 0.390226 \tabularnewline
22 & -0.109247 & -0.8532 & 0.198431 \tabularnewline
23 & 0.047276 & 0.3692 & 0.356615 \tabularnewline
24 & -0.083567 & -0.6527 & 0.258207 \tabularnewline
25 & -0.108994 & -0.8513 & 0.198975 \tabularnewline
26 & 0.131376 & 1.0261 & 0.154453 \tabularnewline
27 & -0.117457 & -0.9174 & 0.181282 \tabularnewline
28 & -0.133763 & -1.0447 & 0.150136 \tabularnewline
29 & -0.009587 & -0.0749 & 0.470278 \tabularnewline
30 & -0.057731 & -0.4509 & 0.326834 \tabularnewline
31 & -0.143122 & -1.1178 & 0.134014 \tabularnewline
32 & 0.088712 & 0.6929 & 0.245514 \tabularnewline
33 & -0.099407 & -0.7764 & 0.220257 \tabularnewline
34 & -0.062416 & -0.4875 & 0.313832 \tabularnewline
35 & 0.015932 & 0.1244 & 0.45069 \tabularnewline
36 & -0.153122 & -1.1959 & 0.118178 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63976&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]-0.082019[/C][C]-0.6406[/C][C]0.262095[/C][/ROW]
[ROW][C]2[/C][C]0.177755[/C][C]1.3883[/C][C]0.085046[/C][/ROW]
[ROW][C]3[/C][C]0.141255[/C][C]1.1032[/C][C]0.137129[/C][/ROW]
[ROW][C]4[/C][C]0.119419[/C][C]0.9327[/C][C]0.177328[/C][/ROW]
[ROW][C]5[/C][C]0.122272[/C][C]0.955[/C][C]0.171679[/C][/ROW]
[ROW][C]6[/C][C]0.249872[/C][C]1.9516[/C][C]0.027793[/C][/ROW]
[ROW][C]7[/C][C]-0.067954[/C][C]-0.5307[/C][C]0.298764[/C][/ROW]
[ROW][C]8[/C][C]0.187221[/C][C]1.4622[/C][C]0.074404[/C][/ROW]
[ROW][C]9[/C][C]0.187594[/C][C]1.4652[/C][C]0.074007[/C][/ROW]
[ROW][C]10[/C][C]-0.024809[/C][C]-0.1938[/C][C]0.423501[/C][/ROW]
[ROW][C]11[/C][C]0.171762[/C][C]1.3415[/C][C]0.092365[/C][/ROW]
[ROW][C]12[/C][C]-0.129591[/C][C]-1.0121[/C][C]0.157735[/C][/ROW]
[ROW][C]13[/C][C]0.007029[/C][C]0.0549[/C][C]0.478198[/C][/ROW]
[ROW][C]14[/C][C]0.003168[/C][C]0.0247[/C][C]0.490169[/C][/ROW]
[ROW][C]15[/C][C]0.137798[/C][C]1.0762[/C][C]0.143029[/C][/ROW]
[ROW][C]16[/C][C]-0.108743[/C][C]-0.8493[/C][C]0.199516[/C][/ROW]
[ROW][C]17[/C][C]0.157583[/C][C]1.2308[/C][C]0.111569[/C][/ROW]
[ROW][C]18[/C][C]-0.089705[/C][C]-0.7006[/C][C]0.243102[/C][/ROW]
[ROW][C]19[/C][C]0.025427[/C][C]0.1986[/C][C]0.421621[/C][/ROW]
[ROW][C]20[/C][C]-0.109739[/C][C]-0.8571[/C][C]0.197376[/C][/ROW]
[ROW][C]21[/C][C]0.035846[/C][C]0.28[/C][C]0.390226[/C][/ROW]
[ROW][C]22[/C][C]-0.109247[/C][C]-0.8532[/C][C]0.198431[/C][/ROW]
[ROW][C]23[/C][C]0.047276[/C][C]0.3692[/C][C]0.356615[/C][/ROW]
[ROW][C]24[/C][C]-0.083567[/C][C]-0.6527[/C][C]0.258207[/C][/ROW]
[ROW][C]25[/C][C]-0.108994[/C][C]-0.8513[/C][C]0.198975[/C][/ROW]
[ROW][C]26[/C][C]0.131376[/C][C]1.0261[/C][C]0.154453[/C][/ROW]
[ROW][C]27[/C][C]-0.117457[/C][C]-0.9174[/C][C]0.181282[/C][/ROW]
[ROW][C]28[/C][C]-0.133763[/C][C]-1.0447[/C][C]0.150136[/C][/ROW]
[ROW][C]29[/C][C]-0.009587[/C][C]-0.0749[/C][C]0.470278[/C][/ROW]
[ROW][C]30[/C][C]-0.057731[/C][C]-0.4509[/C][C]0.326834[/C][/ROW]
[ROW][C]31[/C][C]-0.143122[/C][C]-1.1178[/C][C]0.134014[/C][/ROW]
[ROW][C]32[/C][C]0.088712[/C][C]0.6929[/C][C]0.245514[/C][/ROW]
[ROW][C]33[/C][C]-0.099407[/C][C]-0.7764[/C][C]0.220257[/C][/ROW]
[ROW][C]34[/C][C]-0.062416[/C][C]-0.4875[/C][C]0.313832[/C][/ROW]
[ROW][C]35[/C][C]0.015932[/C][C]0.1244[/C][C]0.45069[/C][/ROW]
[ROW][C]36[/C][C]-0.153122[/C][C]-1.1959[/C][C]0.118178[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63976&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63976&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
1-0.082019-0.64060.262095
20.1777551.38830.085046
30.1412551.10320.137129
40.1194190.93270.177328
50.1222720.9550.171679
60.2498721.95160.027793
7-0.067954-0.53070.298764
80.1872211.46220.074404
90.1875941.46520.074007
10-0.024809-0.19380.423501
110.1717621.34150.092365
12-0.129591-1.01210.157735
130.0070290.05490.478198
140.0031680.02470.490169
150.1377981.07620.143029
16-0.108743-0.84930.199516
170.1575831.23080.111569
18-0.089705-0.70060.243102
190.0254270.19860.421621
20-0.109739-0.85710.197376
210.0358460.280.390226
22-0.109247-0.85320.198431
230.0472760.36920.356615
24-0.083567-0.65270.258207
25-0.108994-0.85130.198975
260.1313761.02610.154453
27-0.117457-0.91740.181282
28-0.133763-1.04470.150136
29-0.009587-0.07490.470278
30-0.057731-0.45090.326834
31-0.143122-1.11780.134014
320.0887120.69290.245514
33-0.099407-0.77640.220257
34-0.062416-0.48750.313832
350.0159320.12440.45069
36-0.153122-1.19590.118178







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.082019-0.64060.262095
20.1721861.34480.091831
30.1737311.35690.089909
40.1227950.95910.170657
50.0985820.76990.222151
60.229261.79060.039162
7-0.089497-0.6990.243606
80.0599080.46790.320762
90.172861.35010.090989
10-0.070944-0.55410.290771
110.0538440.42050.337787
12-0.223373-1.74460.043045
13-0.102422-0.79990.213425
14-0.106303-0.83030.204816
150.1293361.01010.158208
16-0.023903-0.18670.426263
170.0919860.71840.237615
180.0223570.17460.43098
19-0.040277-0.31460.37708
20-0.147246-1.150.127311
210.0470960.36780.357137
22-0.037873-0.29580.384195
230.0275890.21550.415057
24-0.068521-0.53520.29724
25-0.146266-1.14240.128881
260.1255780.98080.165284
270.0074020.05780.477043
28-0.126324-0.98660.163863
290.0577240.45080.326852
300.011940.09330.463003
31-0.085461-0.66750.253494
32-0.040702-0.31790.375825
330.1403671.09630.138628
34-0.077311-0.60380.274103
350.0268290.20950.417362
36-0.103011-0.80450.212105

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.082019 & -0.6406 & 0.262095 \tabularnewline
2 & 0.172186 & 1.3448 & 0.091831 \tabularnewline
3 & 0.173731 & 1.3569 & 0.089909 \tabularnewline
4 & 0.122795 & 0.9591 & 0.170657 \tabularnewline
5 & 0.098582 & 0.7699 & 0.222151 \tabularnewline
6 & 0.22926 & 1.7906 & 0.039162 \tabularnewline
7 & -0.089497 & -0.699 & 0.243606 \tabularnewline
8 & 0.059908 & 0.4679 & 0.320762 \tabularnewline
9 & 0.17286 & 1.3501 & 0.090989 \tabularnewline
10 & -0.070944 & -0.5541 & 0.290771 \tabularnewline
11 & 0.053844 & 0.4205 & 0.337787 \tabularnewline
12 & -0.223373 & -1.7446 & 0.043045 \tabularnewline
13 & -0.102422 & -0.7999 & 0.213425 \tabularnewline
14 & -0.106303 & -0.8303 & 0.204816 \tabularnewline
15 & 0.129336 & 1.0101 & 0.158208 \tabularnewline
16 & -0.023903 & -0.1867 & 0.426263 \tabularnewline
17 & 0.091986 & 0.7184 & 0.237615 \tabularnewline
18 & 0.022357 & 0.1746 & 0.43098 \tabularnewline
19 & -0.040277 & -0.3146 & 0.37708 \tabularnewline
20 & -0.147246 & -1.15 & 0.127311 \tabularnewline
21 & 0.047096 & 0.3678 & 0.357137 \tabularnewline
22 & -0.037873 & -0.2958 & 0.384195 \tabularnewline
23 & 0.027589 & 0.2155 & 0.415057 \tabularnewline
24 & -0.068521 & -0.5352 & 0.29724 \tabularnewline
25 & -0.146266 & -1.1424 & 0.128881 \tabularnewline
26 & 0.125578 & 0.9808 & 0.165284 \tabularnewline
27 & 0.007402 & 0.0578 & 0.477043 \tabularnewline
28 & -0.126324 & -0.9866 & 0.163863 \tabularnewline
29 & 0.057724 & 0.4508 & 0.326852 \tabularnewline
30 & 0.01194 & 0.0933 & 0.463003 \tabularnewline
31 & -0.085461 & -0.6675 & 0.253494 \tabularnewline
32 & -0.040702 & -0.3179 & 0.375825 \tabularnewline
33 & 0.140367 & 1.0963 & 0.138628 \tabularnewline
34 & -0.077311 & -0.6038 & 0.274103 \tabularnewline
35 & 0.026829 & 0.2095 & 0.417362 \tabularnewline
36 & -0.103011 & -0.8045 & 0.212105 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63976&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]-0.082019[/C][C]-0.6406[/C][C]0.262095[/C][/ROW]
[ROW][C]2[/C][C]0.172186[/C][C]1.3448[/C][C]0.091831[/C][/ROW]
[ROW][C]3[/C][C]0.173731[/C][C]1.3569[/C][C]0.089909[/C][/ROW]
[ROW][C]4[/C][C]0.122795[/C][C]0.9591[/C][C]0.170657[/C][/ROW]
[ROW][C]5[/C][C]0.098582[/C][C]0.7699[/C][C]0.222151[/C][/ROW]
[ROW][C]6[/C][C]0.22926[/C][C]1.7906[/C][C]0.039162[/C][/ROW]
[ROW][C]7[/C][C]-0.089497[/C][C]-0.699[/C][C]0.243606[/C][/ROW]
[ROW][C]8[/C][C]0.059908[/C][C]0.4679[/C][C]0.320762[/C][/ROW]
[ROW][C]9[/C][C]0.17286[/C][C]1.3501[/C][C]0.090989[/C][/ROW]
[ROW][C]10[/C][C]-0.070944[/C][C]-0.5541[/C][C]0.290771[/C][/ROW]
[ROW][C]11[/C][C]0.053844[/C][C]0.4205[/C][C]0.337787[/C][/ROW]
[ROW][C]12[/C][C]-0.223373[/C][C]-1.7446[/C][C]0.043045[/C][/ROW]
[ROW][C]13[/C][C]-0.102422[/C][C]-0.7999[/C][C]0.213425[/C][/ROW]
[ROW][C]14[/C][C]-0.106303[/C][C]-0.8303[/C][C]0.204816[/C][/ROW]
[ROW][C]15[/C][C]0.129336[/C][C]1.0101[/C][C]0.158208[/C][/ROW]
[ROW][C]16[/C][C]-0.023903[/C][C]-0.1867[/C][C]0.426263[/C][/ROW]
[ROW][C]17[/C][C]0.091986[/C][C]0.7184[/C][C]0.237615[/C][/ROW]
[ROW][C]18[/C][C]0.022357[/C][C]0.1746[/C][C]0.43098[/C][/ROW]
[ROW][C]19[/C][C]-0.040277[/C][C]-0.3146[/C][C]0.37708[/C][/ROW]
[ROW][C]20[/C][C]-0.147246[/C][C]-1.15[/C][C]0.127311[/C][/ROW]
[ROW][C]21[/C][C]0.047096[/C][C]0.3678[/C][C]0.357137[/C][/ROW]
[ROW][C]22[/C][C]-0.037873[/C][C]-0.2958[/C][C]0.384195[/C][/ROW]
[ROW][C]23[/C][C]0.027589[/C][C]0.2155[/C][C]0.415057[/C][/ROW]
[ROW][C]24[/C][C]-0.068521[/C][C]-0.5352[/C][C]0.29724[/C][/ROW]
[ROW][C]25[/C][C]-0.146266[/C][C]-1.1424[/C][C]0.128881[/C][/ROW]
[ROW][C]26[/C][C]0.125578[/C][C]0.9808[/C][C]0.165284[/C][/ROW]
[ROW][C]27[/C][C]0.007402[/C][C]0.0578[/C][C]0.477043[/C][/ROW]
[ROW][C]28[/C][C]-0.126324[/C][C]-0.9866[/C][C]0.163863[/C][/ROW]
[ROW][C]29[/C][C]0.057724[/C][C]0.4508[/C][C]0.326852[/C][/ROW]
[ROW][C]30[/C][C]0.01194[/C][C]0.0933[/C][C]0.463003[/C][/ROW]
[ROW][C]31[/C][C]-0.085461[/C][C]-0.6675[/C][C]0.253494[/C][/ROW]
[ROW][C]32[/C][C]-0.040702[/C][C]-0.3179[/C][C]0.375825[/C][/ROW]
[ROW][C]33[/C][C]0.140367[/C][C]1.0963[/C][C]0.138628[/C][/ROW]
[ROW][C]34[/C][C]-0.077311[/C][C]-0.6038[/C][C]0.274103[/C][/ROW]
[ROW][C]35[/C][C]0.026829[/C][C]0.2095[/C][C]0.417362[/C][/ROW]
[ROW][C]36[/C][C]-0.103011[/C][C]-0.8045[/C][C]0.212105[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63976&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63976&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
1-0.082019-0.64060.262095
20.1721861.34480.091831
30.1737311.35690.089909
40.1227950.95910.170657
50.0985820.76990.222151
60.229261.79060.039162
7-0.089497-0.6990.243606
80.0599080.46790.320762
90.172861.35010.090989
10-0.070944-0.55410.290771
110.0538440.42050.337787
12-0.223373-1.74460.043045
13-0.102422-0.79990.213425
14-0.106303-0.83030.204816
150.1293361.01010.158208
16-0.023903-0.18670.426263
170.0919860.71840.237615
180.0223570.17460.43098
19-0.040277-0.31460.37708
20-0.147246-1.150.127311
210.0470960.36780.357137
22-0.037873-0.29580.384195
230.0275890.21550.415057
24-0.068521-0.53520.29724
25-0.146266-1.14240.128881
260.1255780.98080.165284
270.0074020.05780.477043
28-0.126324-0.98660.163863
290.0577240.45080.326852
300.011940.09330.463003
31-0.085461-0.66750.253494
32-0.040702-0.31790.375825
330.1403671.09630.138628
34-0.077311-0.60380.274103
350.0268290.20950.417362
36-0.103011-0.80450.212105



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