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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 computationTue, 24 Nov 2009 09:55:29 -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/24/t12590817752q9683gwils8skt.htm/, Retrieved Sun, 03 Dec 2023 07:03:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59165, Retrieved Sun, 03 Dec 2023 07:03:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151
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]
- R  D        [(Partial) Autocorrelation Function] [] [2009-11-24 16:19:12] [b7349fb284cae6f1172638396d27b11f]
- R P             [(Partial) Autocorrelation Function] [] [2009-11-24 16:55:29] [6dfcce621b31349cab7f0d189e6f8a9d] [Current]
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Dataseries X:
116222
110924
103753
99983
93302
91496
119321
139261
133739
123913
113438
109416
109406
105645
101328
97686
93093
91382
122257
139183
139887
131822
116805
113706
113012
110452
107005
102841
98173
98181
137277
147579
146571
138920
130340
128140
127059
122860
117702
113537
108366
111078
150739
159129
157928
147768
137507
136919
136151
133001
125554
119647
114158
116193
152803
161761
160942
149470
139208
134588
130322
126611
122401
117352
112135
112879
148729
157230
157221
146681
136524
132111




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=59165&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=59165&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59165&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
1-0.055239-0.42430.336445
2-0.1434-1.10150.137582
3-0.167081-1.28340.10219
40.0735190.56470.287206
50.1504951.1560.126176
60.1049260.8060.211753
70.1514321.16320.124721
8-0.100172-0.76940.222352
90.140351.07810.142699
100.0096670.07430.470531
11-0.172619-1.32590.09499
120.0138390.10630.457853
130.0053470.04110.48369
140.2714172.08480.020712
15-0.005054-0.03880.484582
160.0274710.2110.416804
17-0.071378-0.54830.29279
18-0.077294-0.59370.277489
19-0.015783-0.12120.451959
20-0.035551-0.27310.392876
210.1291330.99190.162651
220.0334750.25710.398988
230.0317230.24370.404167
24-0.114735-0.88130.190867
25-0.206075-1.58290.059396
26-0.054129-0.41580.339543
270.012650.09720.461461
280.171181.31490.096823
290.0045860.03520.486008
30-0.1657-1.27280.104047
31-0.145386-1.11670.134319
320.0390940.30030.382507
33-0.010139-0.07790.469093
34-0.030159-0.23170.408803
350.041190.31640.376413
36-0.063998-0.49160.312422

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.055239 & -0.4243 & 0.336445 \tabularnewline
2 & -0.1434 & -1.1015 & 0.137582 \tabularnewline
3 & -0.167081 & -1.2834 & 0.10219 \tabularnewline
4 & 0.073519 & 0.5647 & 0.287206 \tabularnewline
5 & 0.150495 & 1.156 & 0.126176 \tabularnewline
6 & 0.104926 & 0.806 & 0.211753 \tabularnewline
7 & 0.151432 & 1.1632 & 0.124721 \tabularnewline
8 & -0.100172 & -0.7694 & 0.222352 \tabularnewline
9 & 0.14035 & 1.0781 & 0.142699 \tabularnewline
10 & 0.009667 & 0.0743 & 0.470531 \tabularnewline
11 & -0.172619 & -1.3259 & 0.09499 \tabularnewline
12 & 0.013839 & 0.1063 & 0.457853 \tabularnewline
13 & 0.005347 & 0.0411 & 0.48369 \tabularnewline
14 & 0.271417 & 2.0848 & 0.020712 \tabularnewline
15 & -0.005054 & -0.0388 & 0.484582 \tabularnewline
16 & 0.027471 & 0.211 & 0.416804 \tabularnewline
17 & -0.071378 & -0.5483 & 0.29279 \tabularnewline
18 & -0.077294 & -0.5937 & 0.277489 \tabularnewline
19 & -0.015783 & -0.1212 & 0.451959 \tabularnewline
20 & -0.035551 & -0.2731 & 0.392876 \tabularnewline
21 & 0.129133 & 0.9919 & 0.162651 \tabularnewline
22 & 0.033475 & 0.2571 & 0.398988 \tabularnewline
23 & 0.031723 & 0.2437 & 0.404167 \tabularnewline
24 & -0.114735 & -0.8813 & 0.190867 \tabularnewline
25 & -0.206075 & -1.5829 & 0.059396 \tabularnewline
26 & -0.054129 & -0.4158 & 0.339543 \tabularnewline
27 & 0.01265 & 0.0972 & 0.461461 \tabularnewline
28 & 0.17118 & 1.3149 & 0.096823 \tabularnewline
29 & 0.004586 & 0.0352 & 0.486008 \tabularnewline
30 & -0.1657 & -1.2728 & 0.104047 \tabularnewline
31 & -0.145386 & -1.1167 & 0.134319 \tabularnewline
32 & 0.039094 & 0.3003 & 0.382507 \tabularnewline
33 & -0.010139 & -0.0779 & 0.469093 \tabularnewline
34 & -0.030159 & -0.2317 & 0.408803 \tabularnewline
35 & 0.04119 & 0.3164 & 0.376413 \tabularnewline
36 & -0.063998 & -0.4916 & 0.312422 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59165&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]-0.055239[/C][C]-0.4243[/C][C]0.336445[/C][/ROW]
[ROW][C]2[/C][C]-0.1434[/C][C]-1.1015[/C][C]0.137582[/C][/ROW]
[ROW][C]3[/C][C]-0.167081[/C][C]-1.2834[/C][C]0.10219[/C][/ROW]
[ROW][C]4[/C][C]0.073519[/C][C]0.5647[/C][C]0.287206[/C][/ROW]
[ROW][C]5[/C][C]0.150495[/C][C]1.156[/C][C]0.126176[/C][/ROW]
[ROW][C]6[/C][C]0.104926[/C][C]0.806[/C][C]0.211753[/C][/ROW]
[ROW][C]7[/C][C]0.151432[/C][C]1.1632[/C][C]0.124721[/C][/ROW]
[ROW][C]8[/C][C]-0.100172[/C][C]-0.7694[/C][C]0.222352[/C][/ROW]
[ROW][C]9[/C][C]0.14035[/C][C]1.0781[/C][C]0.142699[/C][/ROW]
[ROW][C]10[/C][C]0.009667[/C][C]0.0743[/C][C]0.470531[/C][/ROW]
[ROW][C]11[/C][C]-0.172619[/C][C]-1.3259[/C][C]0.09499[/C][/ROW]
[ROW][C]12[/C][C]0.013839[/C][C]0.1063[/C][C]0.457853[/C][/ROW]
[ROW][C]13[/C][C]0.005347[/C][C]0.0411[/C][C]0.48369[/C][/ROW]
[ROW][C]14[/C][C]0.271417[/C][C]2.0848[/C][C]0.020712[/C][/ROW]
[ROW][C]15[/C][C]-0.005054[/C][C]-0.0388[/C][C]0.484582[/C][/ROW]
[ROW][C]16[/C][C]0.027471[/C][C]0.211[/C][C]0.416804[/C][/ROW]
[ROW][C]17[/C][C]-0.071378[/C][C]-0.5483[/C][C]0.29279[/C][/ROW]
[ROW][C]18[/C][C]-0.077294[/C][C]-0.5937[/C][C]0.277489[/C][/ROW]
[ROW][C]19[/C][C]-0.015783[/C][C]-0.1212[/C][C]0.451959[/C][/ROW]
[ROW][C]20[/C][C]-0.035551[/C][C]-0.2731[/C][C]0.392876[/C][/ROW]
[ROW][C]21[/C][C]0.129133[/C][C]0.9919[/C][C]0.162651[/C][/ROW]
[ROW][C]22[/C][C]0.033475[/C][C]0.2571[/C][C]0.398988[/C][/ROW]
[ROW][C]23[/C][C]0.031723[/C][C]0.2437[/C][C]0.404167[/C][/ROW]
[ROW][C]24[/C][C]-0.114735[/C][C]-0.8813[/C][C]0.190867[/C][/ROW]
[ROW][C]25[/C][C]-0.206075[/C][C]-1.5829[/C][C]0.059396[/C][/ROW]
[ROW][C]26[/C][C]-0.054129[/C][C]-0.4158[/C][C]0.339543[/C][/ROW]
[ROW][C]27[/C][C]0.01265[/C][C]0.0972[/C][C]0.461461[/C][/ROW]
[ROW][C]28[/C][C]0.17118[/C][C]1.3149[/C][C]0.096823[/C][/ROW]
[ROW][C]29[/C][C]0.004586[/C][C]0.0352[/C][C]0.486008[/C][/ROW]
[ROW][C]30[/C][C]-0.1657[/C][C]-1.2728[/C][C]0.104047[/C][/ROW]
[ROW][C]31[/C][C]-0.145386[/C][C]-1.1167[/C][C]0.134319[/C][/ROW]
[ROW][C]32[/C][C]0.039094[/C][C]0.3003[/C][C]0.382507[/C][/ROW]
[ROW][C]33[/C][C]-0.010139[/C][C]-0.0779[/C][C]0.469093[/C][/ROW]
[ROW][C]34[/C][C]-0.030159[/C][C]-0.2317[/C][C]0.408803[/C][/ROW]
[ROW][C]35[/C][C]0.04119[/C][C]0.3164[/C][C]0.376413[/C][/ROW]
[ROW][C]36[/C][C]-0.063998[/C][C]-0.4916[/C][C]0.312422[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59165&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59165&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
1-0.055239-0.42430.336445
2-0.1434-1.10150.137582
3-0.167081-1.28340.10219
40.0735190.56470.287206
50.1504951.1560.126176
60.1049260.8060.211753
70.1514321.16320.124721
8-0.100172-0.76940.222352
90.140351.07810.142699
100.0096670.07430.470531
11-0.172619-1.32590.09499
120.0138390.10630.457853
130.0053470.04110.48369
140.2714172.08480.020712
15-0.005054-0.03880.484582
160.0274710.2110.416804
17-0.071378-0.54830.29279
18-0.077294-0.59370.277489
19-0.015783-0.12120.451959
20-0.035551-0.27310.392876
210.1291330.99190.162651
220.0334750.25710.398988
230.0317230.24370.404167
24-0.114735-0.88130.190867
25-0.206075-1.58290.059396
26-0.054129-0.41580.339543
270.012650.09720.461461
280.171181.31490.096823
290.0045860.03520.486008
30-0.1657-1.27280.104047
31-0.145386-1.11670.134319
320.0390940.30030.382507
33-0.010139-0.07790.469093
34-0.030159-0.23170.408803
350.041190.31640.376413
36-0.063998-0.49160.312422







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.055239-0.42430.336445
2-0.146899-1.12840.131869
3-0.188921-1.45110.07602
40.0266620.20480.419218
50.112470.86390.195571
60.1199570.92140.180295
70.2481041.90570.030781
80.0188650.14490.44264
90.240861.85010.034656
100.0819660.62960.265697
11-0.22016-1.69110.048049
12-0.050463-0.38760.349848
13-0.173427-1.33210.093973
140.1161850.89240.187892
150.033090.25420.400125
160.0997950.76650.223206
170.1557491.19630.118177
18-0.006826-0.05240.479182
19-0.110043-0.84530.20069
20-0.144616-1.11080.135577
21-0.121254-0.93140.177729
22-0.049496-0.38020.352585
23-0.019713-0.15140.440081
24-0.025195-0.19350.423606
25-0.067481-0.51830.303082
26-0.101225-0.77750.219978
27-0.063591-0.48850.313519
280.0391510.30070.38234
290.0523980.40250.344394
30-0.130894-1.00540.1594
31-0.10229-0.78570.217593
320.0903870.69430.245118
33-0.035374-0.27170.393394
340.062390.47920.316775
350.0945240.72610.235338
36-0.059178-0.45460.32555

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.055239 & -0.4243 & 0.336445 \tabularnewline
2 & -0.146899 & -1.1284 & 0.131869 \tabularnewline
3 & -0.188921 & -1.4511 & 0.07602 \tabularnewline
4 & 0.026662 & 0.2048 & 0.419218 \tabularnewline
5 & 0.11247 & 0.8639 & 0.195571 \tabularnewline
6 & 0.119957 & 0.9214 & 0.180295 \tabularnewline
7 & 0.248104 & 1.9057 & 0.030781 \tabularnewline
8 & 0.018865 & 0.1449 & 0.44264 \tabularnewline
9 & 0.24086 & 1.8501 & 0.034656 \tabularnewline
10 & 0.081966 & 0.6296 & 0.265697 \tabularnewline
11 & -0.22016 & -1.6911 & 0.048049 \tabularnewline
12 & -0.050463 & -0.3876 & 0.349848 \tabularnewline
13 & -0.173427 & -1.3321 & 0.093973 \tabularnewline
14 & 0.116185 & 0.8924 & 0.187892 \tabularnewline
15 & 0.03309 & 0.2542 & 0.400125 \tabularnewline
16 & 0.099795 & 0.7665 & 0.223206 \tabularnewline
17 & 0.155749 & 1.1963 & 0.118177 \tabularnewline
18 & -0.006826 & -0.0524 & 0.479182 \tabularnewline
19 & -0.110043 & -0.8453 & 0.20069 \tabularnewline
20 & -0.144616 & -1.1108 & 0.135577 \tabularnewline
21 & -0.121254 & -0.9314 & 0.177729 \tabularnewline
22 & -0.049496 & -0.3802 & 0.352585 \tabularnewline
23 & -0.019713 & -0.1514 & 0.440081 \tabularnewline
24 & -0.025195 & -0.1935 & 0.423606 \tabularnewline
25 & -0.067481 & -0.5183 & 0.303082 \tabularnewline
26 & -0.101225 & -0.7775 & 0.219978 \tabularnewline
27 & -0.063591 & -0.4885 & 0.313519 \tabularnewline
28 & 0.039151 & 0.3007 & 0.38234 \tabularnewline
29 & 0.052398 & 0.4025 & 0.344394 \tabularnewline
30 & -0.130894 & -1.0054 & 0.1594 \tabularnewline
31 & -0.10229 & -0.7857 & 0.217593 \tabularnewline
32 & 0.090387 & 0.6943 & 0.245118 \tabularnewline
33 & -0.035374 & -0.2717 & 0.393394 \tabularnewline
34 & 0.06239 & 0.4792 & 0.316775 \tabularnewline
35 & 0.094524 & 0.7261 & 0.235338 \tabularnewline
36 & -0.059178 & -0.4546 & 0.32555 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59165&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]-0.055239[/C][C]-0.4243[/C][C]0.336445[/C][/ROW]
[ROW][C]2[/C][C]-0.146899[/C][C]-1.1284[/C][C]0.131869[/C][/ROW]
[ROW][C]3[/C][C]-0.188921[/C][C]-1.4511[/C][C]0.07602[/C][/ROW]
[ROW][C]4[/C][C]0.026662[/C][C]0.2048[/C][C]0.419218[/C][/ROW]
[ROW][C]5[/C][C]0.11247[/C][C]0.8639[/C][C]0.195571[/C][/ROW]
[ROW][C]6[/C][C]0.119957[/C][C]0.9214[/C][C]0.180295[/C][/ROW]
[ROW][C]7[/C][C]0.248104[/C][C]1.9057[/C][C]0.030781[/C][/ROW]
[ROW][C]8[/C][C]0.018865[/C][C]0.1449[/C][C]0.44264[/C][/ROW]
[ROW][C]9[/C][C]0.24086[/C][C]1.8501[/C][C]0.034656[/C][/ROW]
[ROW][C]10[/C][C]0.081966[/C][C]0.6296[/C][C]0.265697[/C][/ROW]
[ROW][C]11[/C][C]-0.22016[/C][C]-1.6911[/C][C]0.048049[/C][/ROW]
[ROW][C]12[/C][C]-0.050463[/C][C]-0.3876[/C][C]0.349848[/C][/ROW]
[ROW][C]13[/C][C]-0.173427[/C][C]-1.3321[/C][C]0.093973[/C][/ROW]
[ROW][C]14[/C][C]0.116185[/C][C]0.8924[/C][C]0.187892[/C][/ROW]
[ROW][C]15[/C][C]0.03309[/C][C]0.2542[/C][C]0.400125[/C][/ROW]
[ROW][C]16[/C][C]0.099795[/C][C]0.7665[/C][C]0.223206[/C][/ROW]
[ROW][C]17[/C][C]0.155749[/C][C]1.1963[/C][C]0.118177[/C][/ROW]
[ROW][C]18[/C][C]-0.006826[/C][C]-0.0524[/C][C]0.479182[/C][/ROW]
[ROW][C]19[/C][C]-0.110043[/C][C]-0.8453[/C][C]0.20069[/C][/ROW]
[ROW][C]20[/C][C]-0.144616[/C][C]-1.1108[/C][C]0.135577[/C][/ROW]
[ROW][C]21[/C][C]-0.121254[/C][C]-0.9314[/C][C]0.177729[/C][/ROW]
[ROW][C]22[/C][C]-0.049496[/C][C]-0.3802[/C][C]0.352585[/C][/ROW]
[ROW][C]23[/C][C]-0.019713[/C][C]-0.1514[/C][C]0.440081[/C][/ROW]
[ROW][C]24[/C][C]-0.025195[/C][C]-0.1935[/C][C]0.423606[/C][/ROW]
[ROW][C]25[/C][C]-0.067481[/C][C]-0.5183[/C][C]0.303082[/C][/ROW]
[ROW][C]26[/C][C]-0.101225[/C][C]-0.7775[/C][C]0.219978[/C][/ROW]
[ROW][C]27[/C][C]-0.063591[/C][C]-0.4885[/C][C]0.313519[/C][/ROW]
[ROW][C]28[/C][C]0.039151[/C][C]0.3007[/C][C]0.38234[/C][/ROW]
[ROW][C]29[/C][C]0.052398[/C][C]0.4025[/C][C]0.344394[/C][/ROW]
[ROW][C]30[/C][C]-0.130894[/C][C]-1.0054[/C][C]0.1594[/C][/ROW]
[ROW][C]31[/C][C]-0.10229[/C][C]-0.7857[/C][C]0.217593[/C][/ROW]
[ROW][C]32[/C][C]0.090387[/C][C]0.6943[/C][C]0.245118[/C][/ROW]
[ROW][C]33[/C][C]-0.035374[/C][C]-0.2717[/C][C]0.393394[/C][/ROW]
[ROW][C]34[/C][C]0.06239[/C][C]0.4792[/C][C]0.316775[/C][/ROW]
[ROW][C]35[/C][C]0.094524[/C][C]0.7261[/C][C]0.235338[/C][/ROW]
[ROW][C]36[/C][C]-0.059178[/C][C]-0.4546[/C][C]0.32555[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59165&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59165&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
1-0.055239-0.42430.336445
2-0.146899-1.12840.131869
3-0.188921-1.45110.07602
40.0266620.20480.419218
50.112470.86390.195571
60.1199570.92140.180295
70.2481041.90570.030781
80.0188650.14490.44264
90.240861.85010.034656
100.0819660.62960.265697
11-0.22016-1.69110.048049
12-0.050463-0.38760.349848
13-0.173427-1.33210.093973
140.1161850.89240.187892
150.033090.25420.400125
160.0997950.76650.223206
170.1557491.19630.118177
18-0.006826-0.05240.479182
19-0.110043-0.84530.20069
20-0.144616-1.11080.135577
21-0.121254-0.93140.177729
22-0.049496-0.38020.352585
23-0.019713-0.15140.440081
24-0.025195-0.19350.423606
25-0.067481-0.51830.303082
26-0.101225-0.77750.219978
27-0.063591-0.48850.313519
280.0391510.30070.38234
290.0523980.40250.344394
30-0.130894-1.00540.1594
31-0.10229-0.78570.217593
320.0903870.69430.245118
33-0.035374-0.27170.393394
340.062390.47920.316775
350.0945240.72610.235338
36-0.059178-0.45460.32555



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