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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 19:26:32 -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/05/t1259980071lxacfzud24ty1qd.htm/, Retrieved Tue, 30 Apr 2024 01:41:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64220, Retrieved Tue, 30 Apr 2024 01:41:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact164

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 12:19:56] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [WS 8: Methode 1 A...] [2009-11-27 13:04:03] [8cf9233b7464ea02e32be3b30fdac052]
-   P             [(Partial) Autocorrelation Function] [] [2009-12-05 02:26:32] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
114
116
153
162
161
149
139
135
130
127
122
117
112
113
149
157
157
147
137
132
125
123
117
114
111
112
144
150
149
134
123
116
117
111
105
102
95
93
124
130
124
115
106
105
105
101
95
93
84
87
116
120
117
109
105
107
109
109
108
107

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=64220&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=64220&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64220&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
10.3074512.36160.010759
2-0.10049-0.77190.221633
3-0.295609-2.27060.013418
4-0.255795-1.96480.027076
5-0.06566-0.50430.307948
6-0.012914-0.09920.46066
7-0.07929-0.6090.272419
8-0.251317-1.93040.029184
9-0.261057-2.00520.024767
10-0.097931-0.75220.227454
110.266932.05030.022392
120.7780785.97650
130.2234191.71610.045694
14-0.080594-0.61910.269132
15-0.236881-1.81950.036954
16-0.193001-1.48250.071769
17-0.036335-0.27910.390574
18-0.010243-0.07870.468777
19-0.077937-0.59860.27585
20-0.202357-1.55430.062727
21-0.195807-1.5040.068956
22-0.058891-0.45240.326338
230.197191.51460.067601
240.566234.34932.7e-05
250.1551161.19150.11912
26-0.075246-0.5780.282741
27-0.195283-1.50.069474
28-0.126153-0.9690.168251
29-0.009143-0.07020.472125
300.0032250.02480.490161
31-0.061101-0.46930.320285
32-0.137525-1.05640.147557
33-0.1274-0.97860.165891
34-0.060713-0.46630.321344
350.1211930.93090.177849
360.3629072.78750.003568

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.307451 & 2.3616 & 0.010759 \tabularnewline
2 & -0.10049 & -0.7719 & 0.221633 \tabularnewline
3 & -0.295609 & -2.2706 & 0.013418 \tabularnewline
4 & -0.255795 & -1.9648 & 0.027076 \tabularnewline
5 & -0.06566 & -0.5043 & 0.307948 \tabularnewline
6 & -0.012914 & -0.0992 & 0.46066 \tabularnewline
7 & -0.07929 & -0.609 & 0.272419 \tabularnewline
8 & -0.251317 & -1.9304 & 0.029184 \tabularnewline
9 & -0.261057 & -2.0052 & 0.024767 \tabularnewline
10 & -0.097931 & -0.7522 & 0.227454 \tabularnewline
11 & 0.26693 & 2.0503 & 0.022392 \tabularnewline
12 & 0.778078 & 5.9765 & 0 \tabularnewline
13 & 0.223419 & 1.7161 & 0.045694 \tabularnewline
14 & -0.080594 & -0.6191 & 0.269132 \tabularnewline
15 & -0.236881 & -1.8195 & 0.036954 \tabularnewline
16 & -0.193001 & -1.4825 & 0.071769 \tabularnewline
17 & -0.036335 & -0.2791 & 0.390574 \tabularnewline
18 & -0.010243 & -0.0787 & 0.468777 \tabularnewline
19 & -0.077937 & -0.5986 & 0.27585 \tabularnewline
20 & -0.202357 & -1.5543 & 0.062727 \tabularnewline
21 & -0.195807 & -1.504 & 0.068956 \tabularnewline
22 & -0.058891 & -0.4524 & 0.326338 \tabularnewline
23 & 0.19719 & 1.5146 & 0.067601 \tabularnewline
24 & 0.56623 & 4.3493 & 2.7e-05 \tabularnewline
25 & 0.155116 & 1.1915 & 0.11912 \tabularnewline
26 & -0.075246 & -0.578 & 0.282741 \tabularnewline
27 & -0.195283 & -1.5 & 0.069474 \tabularnewline
28 & -0.126153 & -0.969 & 0.168251 \tabularnewline
29 & -0.009143 & -0.0702 & 0.472125 \tabularnewline
30 & 0.003225 & 0.0248 & 0.490161 \tabularnewline
31 & -0.061101 & -0.4693 & 0.320285 \tabularnewline
32 & -0.137525 & -1.0564 & 0.147557 \tabularnewline
33 & -0.1274 & -0.9786 & 0.165891 \tabularnewline
34 & -0.060713 & -0.4663 & 0.321344 \tabularnewline
35 & 0.121193 & 0.9309 & 0.177849 \tabularnewline
36 & 0.362907 & 2.7875 & 0.003568 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64220&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]0.307451[/C][C]2.3616[/C][C]0.010759[/C][/ROW]
[ROW][C]2[/C][C]-0.10049[/C][C]-0.7719[/C][C]0.221633[/C][/ROW]
[ROW][C]3[/C][C]-0.295609[/C][C]-2.2706[/C][C]0.013418[/C][/ROW]
[ROW][C]4[/C][C]-0.255795[/C][C]-1.9648[/C][C]0.027076[/C][/ROW]
[ROW][C]5[/C][C]-0.06566[/C][C]-0.5043[/C][C]0.307948[/C][/ROW]
[ROW][C]6[/C][C]-0.012914[/C][C]-0.0992[/C][C]0.46066[/C][/ROW]
[ROW][C]7[/C][C]-0.07929[/C][C]-0.609[/C][C]0.272419[/C][/ROW]
[ROW][C]8[/C][C]-0.251317[/C][C]-1.9304[/C][C]0.029184[/C][/ROW]
[ROW][C]9[/C][C]-0.261057[/C][C]-2.0052[/C][C]0.024767[/C][/ROW]
[ROW][C]10[/C][C]-0.097931[/C][C]-0.7522[/C][C]0.227454[/C][/ROW]
[ROW][C]11[/C][C]0.26693[/C][C]2.0503[/C][C]0.022392[/C][/ROW]
[ROW][C]12[/C][C]0.778078[/C][C]5.9765[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.223419[/C][C]1.7161[/C][C]0.045694[/C][/ROW]
[ROW][C]14[/C][C]-0.080594[/C][C]-0.6191[/C][C]0.269132[/C][/ROW]
[ROW][C]15[/C][C]-0.236881[/C][C]-1.8195[/C][C]0.036954[/C][/ROW]
[ROW][C]16[/C][C]-0.193001[/C][C]-1.4825[/C][C]0.071769[/C][/ROW]
[ROW][C]17[/C][C]-0.036335[/C][C]-0.2791[/C][C]0.390574[/C][/ROW]
[ROW][C]18[/C][C]-0.010243[/C][C]-0.0787[/C][C]0.468777[/C][/ROW]
[ROW][C]19[/C][C]-0.077937[/C][C]-0.5986[/C][C]0.27585[/C][/ROW]
[ROW][C]20[/C][C]-0.202357[/C][C]-1.5543[/C][C]0.062727[/C][/ROW]
[ROW][C]21[/C][C]-0.195807[/C][C]-1.504[/C][C]0.068956[/C][/ROW]
[ROW][C]22[/C][C]-0.058891[/C][C]-0.4524[/C][C]0.326338[/C][/ROW]
[ROW][C]23[/C][C]0.19719[/C][C]1.5146[/C][C]0.067601[/C][/ROW]
[ROW][C]24[/C][C]0.56623[/C][C]4.3493[/C][C]2.7e-05[/C][/ROW]
[ROW][C]25[/C][C]0.155116[/C][C]1.1915[/C][C]0.11912[/C][/ROW]
[ROW][C]26[/C][C]-0.075246[/C][C]-0.578[/C][C]0.282741[/C][/ROW]
[ROW][C]27[/C][C]-0.195283[/C][C]-1.5[/C][C]0.069474[/C][/ROW]
[ROW][C]28[/C][C]-0.126153[/C][C]-0.969[/C][C]0.168251[/C][/ROW]
[ROW][C]29[/C][C]-0.009143[/C][C]-0.0702[/C][C]0.472125[/C][/ROW]
[ROW][C]30[/C][C]0.003225[/C][C]0.0248[/C][C]0.490161[/C][/ROW]
[ROW][C]31[/C][C]-0.061101[/C][C]-0.4693[/C][C]0.320285[/C][/ROW]
[ROW][C]32[/C][C]-0.137525[/C][C]-1.0564[/C][C]0.147557[/C][/ROW]
[ROW][C]33[/C][C]-0.1274[/C][C]-0.9786[/C][C]0.165891[/C][/ROW]
[ROW][C]34[/C][C]-0.060713[/C][C]-0.4663[/C][C]0.321344[/C][/ROW]
[ROW][C]35[/C][C]0.121193[/C][C]0.9309[/C][C]0.177849[/C][/ROW]
[ROW][C]36[/C][C]0.362907[/C][C]2.7875[/C][C]0.003568[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64220&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64220&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
10.3074512.36160.010759
2-0.10049-0.77190.221633
3-0.295609-2.27060.013418
4-0.255795-1.96480.027076
5-0.06566-0.50430.307948
6-0.012914-0.09920.46066
7-0.07929-0.6090.272419
8-0.251317-1.93040.029184
9-0.261057-2.00520.024767
10-0.097931-0.75220.227454
110.266932.05030.022392
120.7780785.97650
130.2234191.71610.045694
14-0.080594-0.61910.269132
15-0.236881-1.81950.036954
16-0.193001-1.48250.071769
17-0.036335-0.27910.390574
18-0.010243-0.07870.468777
19-0.077937-0.59860.27585
20-0.202357-1.55430.062727
21-0.195807-1.5040.068956
22-0.058891-0.45240.326338
230.197191.51460.067601
240.566234.34932.7e-05
250.1551161.19150.11912
26-0.075246-0.5780.282741
27-0.195283-1.50.069474
28-0.126153-0.9690.168251
29-0.009143-0.07020.472125
300.0032250.02480.490161
31-0.061101-0.46930.320285
32-0.137525-1.05640.147557
33-0.1274-0.97860.165891
34-0.060713-0.46630.321344
350.1211930.93090.177849
360.3629072.78750.003568






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3074512.36160.010759
2-0.215375-1.65430.051686
3-0.222175-1.70660.046582
4-0.127274-0.97760.166129
5-0.015707-0.12060.452189
6-0.116432-0.89430.187389
7-0.178916-1.37430.087277
8-0.320104-2.45880.008447
9-0.298385-2.29190.012747
10-0.283831-2.18020.016624
11-0.025799-0.19820.421798
120.6238984.79236e-06
13-0.291426-2.23850.014488
140.054960.42220.337224
150.0638880.49070.312717
16-0.008441-0.06480.47426
17-0.035056-0.26930.394331
18-0.016383-0.12580.450143
190.0003310.00250.498991
200.0582590.44750.328078
210.0183970.14130.444052
220.0544030.41790.338778
23-0.116376-0.89390.187504
24-0.026119-0.20060.42084
250.0260750.20030.420973
26-0.086739-0.66630.253923
27-0.052027-0.39960.345437
280.0435540.33450.369577
29-0.044068-0.33850.368097
300.0059130.04540.481965
31-0.00561-0.04310.482888
320.0435850.33480.369488
33-0.005815-0.04470.482261
34-0.108472-0.83320.204049
350.0063390.04870.480666
36-0.145708-1.11920.133794

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.307451 & 2.3616 & 0.010759 \tabularnewline
2 & -0.215375 & -1.6543 & 0.051686 \tabularnewline
3 & -0.222175 & -1.7066 & 0.046582 \tabularnewline
4 & -0.127274 & -0.9776 & 0.166129 \tabularnewline
5 & -0.015707 & -0.1206 & 0.452189 \tabularnewline
6 & -0.116432 & -0.8943 & 0.187389 \tabularnewline
7 & -0.178916 & -1.3743 & 0.087277 \tabularnewline
8 & -0.320104 & -2.4588 & 0.008447 \tabularnewline
9 & -0.298385 & -2.2919 & 0.012747 \tabularnewline
10 & -0.283831 & -2.1802 & 0.016624 \tabularnewline
11 & -0.025799 & -0.1982 & 0.421798 \tabularnewline
12 & 0.623898 & 4.7923 & 6e-06 \tabularnewline
13 & -0.291426 & -2.2385 & 0.014488 \tabularnewline
14 & 0.05496 & 0.4222 & 0.337224 \tabularnewline
15 & 0.063888 & 0.4907 & 0.312717 \tabularnewline
16 & -0.008441 & -0.0648 & 0.47426 \tabularnewline
17 & -0.035056 & -0.2693 & 0.394331 \tabularnewline
18 & -0.016383 & -0.1258 & 0.450143 \tabularnewline
19 & 0.000331 & 0.0025 & 0.498991 \tabularnewline
20 & 0.058259 & 0.4475 & 0.328078 \tabularnewline
21 & 0.018397 & 0.1413 & 0.444052 \tabularnewline
22 & 0.054403 & 0.4179 & 0.338778 \tabularnewline
23 & -0.116376 & -0.8939 & 0.187504 \tabularnewline
24 & -0.026119 & -0.2006 & 0.42084 \tabularnewline
25 & 0.026075 & 0.2003 & 0.420973 \tabularnewline
26 & -0.086739 & -0.6663 & 0.253923 \tabularnewline
27 & -0.052027 & -0.3996 & 0.345437 \tabularnewline
28 & 0.043554 & 0.3345 & 0.369577 \tabularnewline
29 & -0.044068 & -0.3385 & 0.368097 \tabularnewline
30 & 0.005913 & 0.0454 & 0.481965 \tabularnewline
31 & -0.00561 & -0.0431 & 0.482888 \tabularnewline
32 & 0.043585 & 0.3348 & 0.369488 \tabularnewline
33 & -0.005815 & -0.0447 & 0.482261 \tabularnewline
34 & -0.108472 & -0.8332 & 0.204049 \tabularnewline
35 & 0.006339 & 0.0487 & 0.480666 \tabularnewline
36 & -0.145708 & -1.1192 & 0.133794 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64220&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]0.307451[/C][C]2.3616[/C][C]0.010759[/C][/ROW]
[ROW][C]2[/C][C]-0.215375[/C][C]-1.6543[/C][C]0.051686[/C][/ROW]
[ROW][C]3[/C][C]-0.222175[/C][C]-1.7066[/C][C]0.046582[/C][/ROW]
[ROW][C]4[/C][C]-0.127274[/C][C]-0.9776[/C][C]0.166129[/C][/ROW]
[ROW][C]5[/C][C]-0.015707[/C][C]-0.1206[/C][C]0.452189[/C][/ROW]
[ROW][C]6[/C][C]-0.116432[/C][C]-0.8943[/C][C]0.187389[/C][/ROW]
[ROW][C]7[/C][C]-0.178916[/C][C]-1.3743[/C][C]0.087277[/C][/ROW]
[ROW][C]8[/C][C]-0.320104[/C][C]-2.4588[/C][C]0.008447[/C][/ROW]
[ROW][C]9[/C][C]-0.298385[/C][C]-2.2919[/C][C]0.012747[/C][/ROW]
[ROW][C]10[/C][C]-0.283831[/C][C]-2.1802[/C][C]0.016624[/C][/ROW]
[ROW][C]11[/C][C]-0.025799[/C][C]-0.1982[/C][C]0.421798[/C][/ROW]
[ROW][C]12[/C][C]0.623898[/C][C]4.7923[/C][C]6e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.291426[/C][C]-2.2385[/C][C]0.014488[/C][/ROW]
[ROW][C]14[/C][C]0.05496[/C][C]0.4222[/C][C]0.337224[/C][/ROW]
[ROW][C]15[/C][C]0.063888[/C][C]0.4907[/C][C]0.312717[/C][/ROW]
[ROW][C]16[/C][C]-0.008441[/C][C]-0.0648[/C][C]0.47426[/C][/ROW]
[ROW][C]17[/C][C]-0.035056[/C][C]-0.2693[/C][C]0.394331[/C][/ROW]
[ROW][C]18[/C][C]-0.016383[/C][C]-0.1258[/C][C]0.450143[/C][/ROW]
[ROW][C]19[/C][C]0.000331[/C][C]0.0025[/C][C]0.498991[/C][/ROW]
[ROW][C]20[/C][C]0.058259[/C][C]0.4475[/C][C]0.328078[/C][/ROW]
[ROW][C]21[/C][C]0.018397[/C][C]0.1413[/C][C]0.444052[/C][/ROW]
[ROW][C]22[/C][C]0.054403[/C][C]0.4179[/C][C]0.338778[/C][/ROW]
[ROW][C]23[/C][C]-0.116376[/C][C]-0.8939[/C][C]0.187504[/C][/ROW]
[ROW][C]24[/C][C]-0.026119[/C][C]-0.2006[/C][C]0.42084[/C][/ROW]
[ROW][C]25[/C][C]0.026075[/C][C]0.2003[/C][C]0.420973[/C][/ROW]
[ROW][C]26[/C][C]-0.086739[/C][C]-0.6663[/C][C]0.253923[/C][/ROW]
[ROW][C]27[/C][C]-0.052027[/C][C]-0.3996[/C][C]0.345437[/C][/ROW]
[ROW][C]28[/C][C]0.043554[/C][C]0.3345[/C][C]0.369577[/C][/ROW]
[ROW][C]29[/C][C]-0.044068[/C][C]-0.3385[/C][C]0.368097[/C][/ROW]
[ROW][C]30[/C][C]0.005913[/C][C]0.0454[/C][C]0.481965[/C][/ROW]
[ROW][C]31[/C][C]-0.00561[/C][C]-0.0431[/C][C]0.482888[/C][/ROW]
[ROW][C]32[/C][C]0.043585[/C][C]0.3348[/C][C]0.369488[/C][/ROW]
[ROW][C]33[/C][C]-0.005815[/C][C]-0.0447[/C][C]0.482261[/C][/ROW]
[ROW][C]34[/C][C]-0.108472[/C][C]-0.8332[/C][C]0.204049[/C][/ROW]
[ROW][C]35[/C][C]0.006339[/C][C]0.0487[/C][C]0.480666[/C][/ROW]
[ROW][C]36[/C][C]-0.145708[/C][C]-1.1192[/C][C]0.133794[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64220&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64220&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
10.3074512.36160.010759
2-0.215375-1.65430.051686
3-0.222175-1.70660.046582
4-0.127274-0.97760.166129
5-0.015707-0.12060.452189
6-0.116432-0.89430.187389
7-0.178916-1.37430.087277
8-0.320104-2.45880.008447
9-0.298385-2.29190.012747
10-0.283831-2.18020.016624
11-0.025799-0.19820.421798
120.6238984.79236e-06
13-0.291426-2.23850.014488
140.054960.42220.337224
150.0638880.49070.312717
16-0.008441-0.06480.47426
17-0.035056-0.26930.394331
18-0.016383-0.12580.450143
190.0003310.00250.498991
200.0582590.44750.328078
210.0183970.14130.444052
220.0544030.41790.338778
23-0.116376-0.89390.187504
24-0.026119-0.20060.42084
250.0260750.20030.420973
26-0.086739-0.66630.253923
27-0.052027-0.39960.345437
280.0435540.33450.369577
29-0.044068-0.33850.368097
300.0059130.04540.481965
31-0.00561-0.04310.482888
320.0435850.33480.369488
33-0.005815-0.04470.482261
34-0.108472-0.83320.204049
350.0063390.04870.480666
36-0.145708-1.11920.133794


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; 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')