Free Statistics

of Irreproducible Research!

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, 26 Nov 2009 11:32:39 -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/Nov/26/t125926045819p70e2ydp20nss.htm/, Retrieved Mon, 29 Apr 2024 07:13:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60246, Retrieved Mon, 29 Apr 2024 07:13:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147
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] [WS 8 ACF (0;0;1)] [2009-11-26 18:32:39] [eba9f01697e64705b70041e6f338cb22] [Current]
Feedback Forum

Post a new message
Dataseries X:
108,01
101,21
119,93
94,76
95,26
117,96
115,86
111,44
108,16
108,77
109,45
124,83
115,31
109,49
124,24
92,85
98,42
120,88
111,72
116,1
109,37
111,65
114,29
133,68
114,27
126,49
131
104
108,88
128,48
132,44
128,04
116,35
120,93
118,59
133,1
121,05
127,62
135,44
114,88
114,34
128,85
138,9
129,44
114,96
127,98
127,03
128,75
137,91
128,37
135,9
122,19
113,08
136,2
138
115,24
110,95
99,23
102,39
112,67




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=60246&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=60246&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60246&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.4093773.1710.001197
20.1435641.1120.135277
30.2876452.22810.014817
40.1953741.51340.067719
50.2771262.14660.017938
60.3303142.55860.006525
70.210411.62980.054189
80.1224720.94870.173299
90.0749610.58060.281827
10-0.094364-0.73090.233831
110.123320.95520.171646
120.4852833.7590.000194
130.1087990.84280.201357
14-0.081158-0.62860.265982
150.0267070.20690.418405
160.024040.18620.426452
170.0547970.42450.336375
180.0868510.67270.251845
190.0323910.25090.401374
20-0.087099-0.67470.251239
21-0.123706-0.95820.170898
22-0.24864-1.9260.029426
23-0.081721-0.6330.264566
240.1363491.05620.147566
25-0.068231-0.52850.299545
26-0.267843-2.07470.021156
27-0.204182-1.58160.059501
28-0.12856-0.99580.161668
29-0.146435-1.13430.130594
30-0.114049-0.88340.190267
31-0.07856-0.60850.272568
32-0.22477-1.74110.043399
33-0.231777-1.79530.038818
34-0.261414-2.02490.023667
35-0.206061-1.59610.057855
36-0.015893-0.12310.451216

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.409377 & 3.171 & 0.001197 \tabularnewline
2 & 0.143564 & 1.112 & 0.135277 \tabularnewline
3 & 0.287645 & 2.2281 & 0.014817 \tabularnewline
4 & 0.195374 & 1.5134 & 0.067719 \tabularnewline
5 & 0.277126 & 2.1466 & 0.017938 \tabularnewline
6 & 0.330314 & 2.5586 & 0.006525 \tabularnewline
7 & 0.21041 & 1.6298 & 0.054189 \tabularnewline
8 & 0.122472 & 0.9487 & 0.173299 \tabularnewline
9 & 0.074961 & 0.5806 & 0.281827 \tabularnewline
10 & -0.094364 & -0.7309 & 0.233831 \tabularnewline
11 & 0.12332 & 0.9552 & 0.171646 \tabularnewline
12 & 0.485283 & 3.759 & 0.000194 \tabularnewline
13 & 0.108799 & 0.8428 & 0.201357 \tabularnewline
14 & -0.081158 & -0.6286 & 0.265982 \tabularnewline
15 & 0.026707 & 0.2069 & 0.418405 \tabularnewline
16 & 0.02404 & 0.1862 & 0.426452 \tabularnewline
17 & 0.054797 & 0.4245 & 0.336375 \tabularnewline
18 & 0.086851 & 0.6727 & 0.251845 \tabularnewline
19 & 0.032391 & 0.2509 & 0.401374 \tabularnewline
20 & -0.087099 & -0.6747 & 0.251239 \tabularnewline
21 & -0.123706 & -0.9582 & 0.170898 \tabularnewline
22 & -0.24864 & -1.926 & 0.029426 \tabularnewline
23 & -0.081721 & -0.633 & 0.264566 \tabularnewline
24 & 0.136349 & 1.0562 & 0.147566 \tabularnewline
25 & -0.068231 & -0.5285 & 0.299545 \tabularnewline
26 & -0.267843 & -2.0747 & 0.021156 \tabularnewline
27 & -0.204182 & -1.5816 & 0.059501 \tabularnewline
28 & -0.12856 & -0.9958 & 0.161668 \tabularnewline
29 & -0.146435 & -1.1343 & 0.130594 \tabularnewline
30 & -0.114049 & -0.8834 & 0.190267 \tabularnewline
31 & -0.07856 & -0.6085 & 0.272568 \tabularnewline
32 & -0.22477 & -1.7411 & 0.043399 \tabularnewline
33 & -0.231777 & -1.7953 & 0.038818 \tabularnewline
34 & -0.261414 & -2.0249 & 0.023667 \tabularnewline
35 & -0.206061 & -1.5961 & 0.057855 \tabularnewline
36 & -0.015893 & -0.1231 & 0.451216 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60246&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]0.409377[/C][C]3.171[/C][C]0.001197[/C][/ROW]
[ROW][C]2[/C][C]0.143564[/C][C]1.112[/C][C]0.135277[/C][/ROW]
[ROW][C]3[/C][C]0.287645[/C][C]2.2281[/C][C]0.014817[/C][/ROW]
[ROW][C]4[/C][C]0.195374[/C][C]1.5134[/C][C]0.067719[/C][/ROW]
[ROW][C]5[/C][C]0.277126[/C][C]2.1466[/C][C]0.017938[/C][/ROW]
[ROW][C]6[/C][C]0.330314[/C][C]2.5586[/C][C]0.006525[/C][/ROW]
[ROW][C]7[/C][C]0.21041[/C][C]1.6298[/C][C]0.054189[/C][/ROW]
[ROW][C]8[/C][C]0.122472[/C][C]0.9487[/C][C]0.173299[/C][/ROW]
[ROW][C]9[/C][C]0.074961[/C][C]0.5806[/C][C]0.281827[/C][/ROW]
[ROW][C]10[/C][C]-0.094364[/C][C]-0.7309[/C][C]0.233831[/C][/ROW]
[ROW][C]11[/C][C]0.12332[/C][C]0.9552[/C][C]0.171646[/C][/ROW]
[ROW][C]12[/C][C]0.485283[/C][C]3.759[/C][C]0.000194[/C][/ROW]
[ROW][C]13[/C][C]0.108799[/C][C]0.8428[/C][C]0.201357[/C][/ROW]
[ROW][C]14[/C][C]-0.081158[/C][C]-0.6286[/C][C]0.265982[/C][/ROW]
[ROW][C]15[/C][C]0.026707[/C][C]0.2069[/C][C]0.418405[/C][/ROW]
[ROW][C]16[/C][C]0.02404[/C][C]0.1862[/C][C]0.426452[/C][/ROW]
[ROW][C]17[/C][C]0.054797[/C][C]0.4245[/C][C]0.336375[/C][/ROW]
[ROW][C]18[/C][C]0.086851[/C][C]0.6727[/C][C]0.251845[/C][/ROW]
[ROW][C]19[/C][C]0.032391[/C][C]0.2509[/C][C]0.401374[/C][/ROW]
[ROW][C]20[/C][C]-0.087099[/C][C]-0.6747[/C][C]0.251239[/C][/ROW]
[ROW][C]21[/C][C]-0.123706[/C][C]-0.9582[/C][C]0.170898[/C][/ROW]
[ROW][C]22[/C][C]-0.24864[/C][C]-1.926[/C][C]0.029426[/C][/ROW]
[ROW][C]23[/C][C]-0.081721[/C][C]-0.633[/C][C]0.264566[/C][/ROW]
[ROW][C]24[/C][C]0.136349[/C][C]1.0562[/C][C]0.147566[/C][/ROW]
[ROW][C]25[/C][C]-0.068231[/C][C]-0.5285[/C][C]0.299545[/C][/ROW]
[ROW][C]26[/C][C]-0.267843[/C][C]-2.0747[/C][C]0.021156[/C][/ROW]
[ROW][C]27[/C][C]-0.204182[/C][C]-1.5816[/C][C]0.059501[/C][/ROW]
[ROW][C]28[/C][C]-0.12856[/C][C]-0.9958[/C][C]0.161668[/C][/ROW]
[ROW][C]29[/C][C]-0.146435[/C][C]-1.1343[/C][C]0.130594[/C][/ROW]
[ROW][C]30[/C][C]-0.114049[/C][C]-0.8834[/C][C]0.190267[/C][/ROW]
[ROW][C]31[/C][C]-0.07856[/C][C]-0.6085[/C][C]0.272568[/C][/ROW]
[ROW][C]32[/C][C]-0.22477[/C][C]-1.7411[/C][C]0.043399[/C][/ROW]
[ROW][C]33[/C][C]-0.231777[/C][C]-1.7953[/C][C]0.038818[/C][/ROW]
[ROW][C]34[/C][C]-0.261414[/C][C]-2.0249[/C][C]0.023667[/C][/ROW]
[ROW][C]35[/C][C]-0.206061[/C][C]-1.5961[/C][C]0.057855[/C][/ROW]
[ROW][C]36[/C][C]-0.015893[/C][C]-0.1231[/C][C]0.451216[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60246&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60246&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
10.4093773.1710.001197
20.1435641.1120.135277
30.2876452.22810.014817
40.1953741.51340.067719
50.2771262.14660.017938
60.3303142.55860.006525
70.210411.62980.054189
80.1224720.94870.173299
90.0749610.58060.281827
10-0.094364-0.73090.233831
110.123320.95520.171646
120.4852833.7590.000194
130.1087990.84280.201357
14-0.081158-0.62860.265982
150.0267070.20690.418405
160.024040.18620.426452
170.0547970.42450.336375
180.0868510.67270.251845
190.0323910.25090.401374
20-0.087099-0.67470.251239
21-0.123706-0.95820.170898
22-0.24864-1.9260.029426
23-0.081721-0.6330.264566
240.1363491.05620.147566
25-0.068231-0.52850.299545
26-0.267843-2.07470.021156
27-0.204182-1.58160.059501
28-0.12856-0.99580.161668
29-0.146435-1.13430.130594
30-0.114049-0.88340.190267
31-0.07856-0.60850.272568
32-0.22477-1.74110.043399
33-0.231777-1.79530.038818
34-0.261414-2.02490.023667
35-0.206061-1.59610.057855
36-0.015893-0.12310.451216







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4093773.1710.001197
2-0.028862-0.22360.411928
30.2873482.22580.014898
4-0.03182-0.24650.403077
50.2698892.09060.020407
60.0919040.71190.239647
70.0543930.42130.337511
8-0.070285-0.54440.294084
9-0.065634-0.50840.306519
10-0.281817-2.18290.016482
110.2335381.8090.037732
120.4202613.25530.000932
13-0.23819-1.8450.034986
14-0.129342-1.00190.160212
15-0.070924-0.54940.292392
160.136371.05630.14753
17-0.132607-1.02720.154233
18-0.051716-0.40060.345072
19-0.036496-0.28270.389191
20-0.122239-0.94690.173754
210.0157560.1220.451634
22-0.06059-0.46930.320268
230.0311480.24130.405085
24-0.128268-0.99360.162213
250.132091.02320.15517
26-0.177784-1.37710.086798
27-0.004459-0.03450.486281
28-0.056905-0.44080.330476
29-0.007781-0.06030.47607
30-0.09601-0.74370.229984
310.0564850.43750.33165
32-0.104376-0.80850.211002
330.0238830.1850.426927
340.0132650.10280.459251
35-0.105134-0.81440.209328
360.019410.15040.440495

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.409377 & 3.171 & 0.001197 \tabularnewline
2 & -0.028862 & -0.2236 & 0.411928 \tabularnewline
3 & 0.287348 & 2.2258 & 0.014898 \tabularnewline
4 & -0.03182 & -0.2465 & 0.403077 \tabularnewline
5 & 0.269889 & 2.0906 & 0.020407 \tabularnewline
6 & 0.091904 & 0.7119 & 0.239647 \tabularnewline
7 & 0.054393 & 0.4213 & 0.337511 \tabularnewline
8 & -0.070285 & -0.5444 & 0.294084 \tabularnewline
9 & -0.065634 & -0.5084 & 0.306519 \tabularnewline
10 & -0.281817 & -2.1829 & 0.016482 \tabularnewline
11 & 0.233538 & 1.809 & 0.037732 \tabularnewline
12 & 0.420261 & 3.2553 & 0.000932 \tabularnewline
13 & -0.23819 & -1.845 & 0.034986 \tabularnewline
14 & -0.129342 & -1.0019 & 0.160212 \tabularnewline
15 & -0.070924 & -0.5494 & 0.292392 \tabularnewline
16 & 0.13637 & 1.0563 & 0.14753 \tabularnewline
17 & -0.132607 & -1.0272 & 0.154233 \tabularnewline
18 & -0.051716 & -0.4006 & 0.345072 \tabularnewline
19 & -0.036496 & -0.2827 & 0.389191 \tabularnewline
20 & -0.122239 & -0.9469 & 0.173754 \tabularnewline
21 & 0.015756 & 0.122 & 0.451634 \tabularnewline
22 & -0.06059 & -0.4693 & 0.320268 \tabularnewline
23 & 0.031148 & 0.2413 & 0.405085 \tabularnewline
24 & -0.128268 & -0.9936 & 0.162213 \tabularnewline
25 & 0.13209 & 1.0232 & 0.15517 \tabularnewline
26 & -0.177784 & -1.3771 & 0.086798 \tabularnewline
27 & -0.004459 & -0.0345 & 0.486281 \tabularnewline
28 & -0.056905 & -0.4408 & 0.330476 \tabularnewline
29 & -0.007781 & -0.0603 & 0.47607 \tabularnewline
30 & -0.09601 & -0.7437 & 0.229984 \tabularnewline
31 & 0.056485 & 0.4375 & 0.33165 \tabularnewline
32 & -0.104376 & -0.8085 & 0.211002 \tabularnewline
33 & 0.023883 & 0.185 & 0.426927 \tabularnewline
34 & 0.013265 & 0.1028 & 0.459251 \tabularnewline
35 & -0.105134 & -0.8144 & 0.209328 \tabularnewline
36 & 0.01941 & 0.1504 & 0.440495 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60246&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]0.409377[/C][C]3.171[/C][C]0.001197[/C][/ROW]
[ROW][C]2[/C][C]-0.028862[/C][C]-0.2236[/C][C]0.411928[/C][/ROW]
[ROW][C]3[/C][C]0.287348[/C][C]2.2258[/C][C]0.014898[/C][/ROW]
[ROW][C]4[/C][C]-0.03182[/C][C]-0.2465[/C][C]0.403077[/C][/ROW]
[ROW][C]5[/C][C]0.269889[/C][C]2.0906[/C][C]0.020407[/C][/ROW]
[ROW][C]6[/C][C]0.091904[/C][C]0.7119[/C][C]0.239647[/C][/ROW]
[ROW][C]7[/C][C]0.054393[/C][C]0.4213[/C][C]0.337511[/C][/ROW]
[ROW][C]8[/C][C]-0.070285[/C][C]-0.5444[/C][C]0.294084[/C][/ROW]
[ROW][C]9[/C][C]-0.065634[/C][C]-0.5084[/C][C]0.306519[/C][/ROW]
[ROW][C]10[/C][C]-0.281817[/C][C]-2.1829[/C][C]0.016482[/C][/ROW]
[ROW][C]11[/C][C]0.233538[/C][C]1.809[/C][C]0.037732[/C][/ROW]
[ROW][C]12[/C][C]0.420261[/C][C]3.2553[/C][C]0.000932[/C][/ROW]
[ROW][C]13[/C][C]-0.23819[/C][C]-1.845[/C][C]0.034986[/C][/ROW]
[ROW][C]14[/C][C]-0.129342[/C][C]-1.0019[/C][C]0.160212[/C][/ROW]
[ROW][C]15[/C][C]-0.070924[/C][C]-0.5494[/C][C]0.292392[/C][/ROW]
[ROW][C]16[/C][C]0.13637[/C][C]1.0563[/C][C]0.14753[/C][/ROW]
[ROW][C]17[/C][C]-0.132607[/C][C]-1.0272[/C][C]0.154233[/C][/ROW]
[ROW][C]18[/C][C]-0.051716[/C][C]-0.4006[/C][C]0.345072[/C][/ROW]
[ROW][C]19[/C][C]-0.036496[/C][C]-0.2827[/C][C]0.389191[/C][/ROW]
[ROW][C]20[/C][C]-0.122239[/C][C]-0.9469[/C][C]0.173754[/C][/ROW]
[ROW][C]21[/C][C]0.015756[/C][C]0.122[/C][C]0.451634[/C][/ROW]
[ROW][C]22[/C][C]-0.06059[/C][C]-0.4693[/C][C]0.320268[/C][/ROW]
[ROW][C]23[/C][C]0.031148[/C][C]0.2413[/C][C]0.405085[/C][/ROW]
[ROW][C]24[/C][C]-0.128268[/C][C]-0.9936[/C][C]0.162213[/C][/ROW]
[ROW][C]25[/C][C]0.13209[/C][C]1.0232[/C][C]0.15517[/C][/ROW]
[ROW][C]26[/C][C]-0.177784[/C][C]-1.3771[/C][C]0.086798[/C][/ROW]
[ROW][C]27[/C][C]-0.004459[/C][C]-0.0345[/C][C]0.486281[/C][/ROW]
[ROW][C]28[/C][C]-0.056905[/C][C]-0.4408[/C][C]0.330476[/C][/ROW]
[ROW][C]29[/C][C]-0.007781[/C][C]-0.0603[/C][C]0.47607[/C][/ROW]
[ROW][C]30[/C][C]-0.09601[/C][C]-0.7437[/C][C]0.229984[/C][/ROW]
[ROW][C]31[/C][C]0.056485[/C][C]0.4375[/C][C]0.33165[/C][/ROW]
[ROW][C]32[/C][C]-0.104376[/C][C]-0.8085[/C][C]0.211002[/C][/ROW]
[ROW][C]33[/C][C]0.023883[/C][C]0.185[/C][C]0.426927[/C][/ROW]
[ROW][C]34[/C][C]0.013265[/C][C]0.1028[/C][C]0.459251[/C][/ROW]
[ROW][C]35[/C][C]-0.105134[/C][C]-0.8144[/C][C]0.209328[/C][/ROW]
[ROW][C]36[/C][C]0.01941[/C][C]0.1504[/C][C]0.440495[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60246&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60246&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
10.4093773.1710.001197
2-0.028862-0.22360.411928
30.2873482.22580.014898
4-0.03182-0.24650.403077
50.2698892.09060.020407
60.0919040.71190.239647
70.0543930.42130.337511
8-0.070285-0.54440.294084
9-0.065634-0.50840.306519
10-0.281817-2.18290.016482
110.2335381.8090.037732
120.4202613.25530.000932
13-0.23819-1.8450.034986
14-0.129342-1.00190.160212
15-0.070924-0.54940.292392
160.136371.05630.14753
17-0.132607-1.02720.154233
18-0.051716-0.40060.345072
19-0.036496-0.28270.389191
20-0.122239-0.94690.173754
210.0157560.1220.451634
22-0.06059-0.46930.320268
230.0311480.24130.405085
24-0.128268-0.99360.162213
250.132091.02320.15517
26-0.177784-1.37710.086798
27-0.004459-0.03450.486281
28-0.056905-0.44080.330476
29-0.007781-0.06030.47607
30-0.09601-0.74370.229984
310.0564850.43750.33165
32-0.104376-0.80850.211002
330.0238830.1850.426927
340.0132650.10280.459251
35-0.105134-0.81440.209328
360.019410.15040.440495



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')