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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, 27 Nov 2009 08:09:59 -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/27/t1259334718wlq7a37evwl0t7x.htm/, Retrieved Sun, 28 Apr 2024 23:10:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60885, Retrieved Sun, 28 Apr 2024 23:10:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact138

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]
-   PD        [(Partial) Autocorrelation Function] [] [2009-11-27 14:56:22] [539cd8be0bf6326526ff2d448281a204]
-   P             [(Partial) Autocorrelation Function] [] [2009-11-27 15:09:59] [f90b018c65398c2fee7b197f24b65ddd] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
902.2
891.9
874
930.9
944.2
935.9
937.1
885.1
892.4
987.3
946.3
799.6
875.4
846.2
880.6
885.7
868.9
882.5
789.6
773.3
804.3
817.8
836.7
721.8
760.8
841.4
1045.6
949.2
850.1
957.4
851.8
913.9
888
973.8
927.6
833
879.5
797.3
834.5
735.1
835
892.8
697.2
821.1
732.7
797.6
866.3
826.3
778.6
779.2
951
692.3
841.4
857.3
760.7
841.2
810.3
1007.4
931.3
931.2

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=60885&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=60885&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60885&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
1-0.213292-1.46230.075163
2-0.281962-1.9330.029634
30.1721021.17990.121995
40.0237990.16320.435546
5-0.112307-0.76990.222595
6-0.00109-0.00750.497035
70.2760041.89220.032317
8-0.331918-2.27550.013739
9-0.02436-0.1670.434041
100.2495091.71050.046879
11-0.060055-0.41170.34121
12-0.309632-2.12270.019536
13-0.133586-0.91580.182218
140.3020762.07090.021941
15-0.135302-0.92760.179182
16-0.029452-0.20190.420429
170.1884961.29230.101291
18-0.156011-1.06960.145141
19-0.106894-0.73280.233652
200.0470090.32230.374335
210.2601571.78350.040478
22-0.24316-1.6670.051081
230.0662240.4540.325955
240.1711741.17350.123252
25-0.135035-0.92580.179652
260.0411670.28220.389504
270.0166840.11440.454712
280.0175530.12030.452365
29-0.111348-0.76340.22453
300.0733990.50320.308587
310.0594670.40770.342679
32-0.049787-0.34130.36719
33-0.006219-0.04260.483086
34-0.00303-0.02080.491758
350.0237960.16310.435556
36-0.045895-0.31460.377214

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.213292 & -1.4623 & 0.075163 \tabularnewline
2 & -0.281962 & -1.933 & 0.029634 \tabularnewline
3 & 0.172102 & 1.1799 & 0.121995 \tabularnewline
4 & 0.023799 & 0.1632 & 0.435546 \tabularnewline
5 & -0.112307 & -0.7699 & 0.222595 \tabularnewline
6 & -0.00109 & -0.0075 & 0.497035 \tabularnewline
7 & 0.276004 & 1.8922 & 0.032317 \tabularnewline
8 & -0.331918 & -2.2755 & 0.013739 \tabularnewline
9 & -0.02436 & -0.167 & 0.434041 \tabularnewline
10 & 0.249509 & 1.7105 & 0.046879 \tabularnewline
11 & -0.060055 & -0.4117 & 0.34121 \tabularnewline
12 & -0.309632 & -2.1227 & 0.019536 \tabularnewline
13 & -0.133586 & -0.9158 & 0.182218 \tabularnewline
14 & 0.302076 & 2.0709 & 0.021941 \tabularnewline
15 & -0.135302 & -0.9276 & 0.179182 \tabularnewline
16 & -0.029452 & -0.2019 & 0.420429 \tabularnewline
17 & 0.188496 & 1.2923 & 0.101291 \tabularnewline
18 & -0.156011 & -1.0696 & 0.145141 \tabularnewline
19 & -0.106894 & -0.7328 & 0.233652 \tabularnewline
20 & 0.047009 & 0.3223 & 0.374335 \tabularnewline
21 & 0.260157 & 1.7835 & 0.040478 \tabularnewline
22 & -0.24316 & -1.667 & 0.051081 \tabularnewline
23 & 0.066224 & 0.454 & 0.325955 \tabularnewline
24 & 0.171174 & 1.1735 & 0.123252 \tabularnewline
25 & -0.135035 & -0.9258 & 0.179652 \tabularnewline
26 & 0.041167 & 0.2822 & 0.389504 \tabularnewline
27 & 0.016684 & 0.1144 & 0.454712 \tabularnewline
28 & 0.017553 & 0.1203 & 0.452365 \tabularnewline
29 & -0.111348 & -0.7634 & 0.22453 \tabularnewline
30 & 0.073399 & 0.5032 & 0.308587 \tabularnewline
31 & 0.059467 & 0.4077 & 0.342679 \tabularnewline
32 & -0.049787 & -0.3413 & 0.36719 \tabularnewline
33 & -0.006219 & -0.0426 & 0.483086 \tabularnewline
34 & -0.00303 & -0.0208 & 0.491758 \tabularnewline
35 & 0.023796 & 0.1631 & 0.435556 \tabularnewline
36 & -0.045895 & -0.3146 & 0.377214 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60885&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]-0.213292[/C][C]-1.4623[/C][C]0.075163[/C][/ROW]
[ROW][C]2[/C][C]-0.281962[/C][C]-1.933[/C][C]0.029634[/C][/ROW]
[ROW][C]3[/C][C]0.172102[/C][C]1.1799[/C][C]0.121995[/C][/ROW]
[ROW][C]4[/C][C]0.023799[/C][C]0.1632[/C][C]0.435546[/C][/ROW]
[ROW][C]5[/C][C]-0.112307[/C][C]-0.7699[/C][C]0.222595[/C][/ROW]
[ROW][C]6[/C][C]-0.00109[/C][C]-0.0075[/C][C]0.497035[/C][/ROW]
[ROW][C]7[/C][C]0.276004[/C][C]1.8922[/C][C]0.032317[/C][/ROW]
[ROW][C]8[/C][C]-0.331918[/C][C]-2.2755[/C][C]0.013739[/C][/ROW]
[ROW][C]9[/C][C]-0.02436[/C][C]-0.167[/C][C]0.434041[/C][/ROW]
[ROW][C]10[/C][C]0.249509[/C][C]1.7105[/C][C]0.046879[/C][/ROW]
[ROW][C]11[/C][C]-0.060055[/C][C]-0.4117[/C][C]0.34121[/C][/ROW]
[ROW][C]12[/C][C]-0.309632[/C][C]-2.1227[/C][C]0.019536[/C][/ROW]
[ROW][C]13[/C][C]-0.133586[/C][C]-0.9158[/C][C]0.182218[/C][/ROW]
[ROW][C]14[/C][C]0.302076[/C][C]2.0709[/C][C]0.021941[/C][/ROW]
[ROW][C]15[/C][C]-0.135302[/C][C]-0.9276[/C][C]0.179182[/C][/ROW]
[ROW][C]16[/C][C]-0.029452[/C][C]-0.2019[/C][C]0.420429[/C][/ROW]
[ROW][C]17[/C][C]0.188496[/C][C]1.2923[/C][C]0.101291[/C][/ROW]
[ROW][C]18[/C][C]-0.156011[/C][C]-1.0696[/C][C]0.145141[/C][/ROW]
[ROW][C]19[/C][C]-0.106894[/C][C]-0.7328[/C][C]0.233652[/C][/ROW]
[ROW][C]20[/C][C]0.047009[/C][C]0.3223[/C][C]0.374335[/C][/ROW]
[ROW][C]21[/C][C]0.260157[/C][C]1.7835[/C][C]0.040478[/C][/ROW]
[ROW][C]22[/C][C]-0.24316[/C][C]-1.667[/C][C]0.051081[/C][/ROW]
[ROW][C]23[/C][C]0.066224[/C][C]0.454[/C][C]0.325955[/C][/ROW]
[ROW][C]24[/C][C]0.171174[/C][C]1.1735[/C][C]0.123252[/C][/ROW]
[ROW][C]25[/C][C]-0.135035[/C][C]-0.9258[/C][C]0.179652[/C][/ROW]
[ROW][C]26[/C][C]0.041167[/C][C]0.2822[/C][C]0.389504[/C][/ROW]
[ROW][C]27[/C][C]0.016684[/C][C]0.1144[/C][C]0.454712[/C][/ROW]
[ROW][C]28[/C][C]0.017553[/C][C]0.1203[/C][C]0.452365[/C][/ROW]
[ROW][C]29[/C][C]-0.111348[/C][C]-0.7634[/C][C]0.22453[/C][/ROW]
[ROW][C]30[/C][C]0.073399[/C][C]0.5032[/C][C]0.308587[/C][/ROW]
[ROW][C]31[/C][C]0.059467[/C][C]0.4077[/C][C]0.342679[/C][/ROW]
[ROW][C]32[/C][C]-0.049787[/C][C]-0.3413[/C][C]0.36719[/C][/ROW]
[ROW][C]33[/C][C]-0.006219[/C][C]-0.0426[/C][C]0.483086[/C][/ROW]
[ROW][C]34[/C][C]-0.00303[/C][C]-0.0208[/C][C]0.491758[/C][/ROW]
[ROW][C]35[/C][C]0.023796[/C][C]0.1631[/C][C]0.435556[/C][/ROW]
[ROW][C]36[/C][C]-0.045895[/C][C]-0.3146[/C][C]0.377214[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60885&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60885&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
1-0.213292-1.46230.075163
2-0.281962-1.9330.029634
30.1721021.17990.121995
40.0237990.16320.435546
5-0.112307-0.76990.222595
6-0.00109-0.00750.497035
70.2760041.89220.032317
8-0.331918-2.27550.013739
9-0.02436-0.1670.434041
100.2495091.71050.046879
11-0.060055-0.41170.34121
12-0.309632-2.12270.019536
13-0.133586-0.91580.182218
140.3020762.07090.021941
15-0.135302-0.92760.179182
16-0.029452-0.20190.420429
170.1884961.29230.101291
18-0.156011-1.06960.145141
19-0.106894-0.73280.233652
200.0470090.32230.374335
210.2601571.78350.040478
22-0.24316-1.6670.051081
230.0662240.4540.325955
240.1711741.17350.123252
25-0.135035-0.92580.179652
260.0411670.28220.389504
270.0166840.11440.454712
280.0175530.12030.452365
29-0.111348-0.76340.22453
300.0733990.50320.308587
310.0594670.40770.342679
32-0.049787-0.34130.36719
33-0.006219-0.04260.483086
34-0.00303-0.02080.491758
350.0237960.16310.435556
36-0.045895-0.31460.377214






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.213292-1.46230.075163
2-0.343063-2.35190.011459
30.021560.14780.441563
4-0.022053-0.15120.440238
5-0.055599-0.38120.352398
6-0.055012-0.37710.353882
70.2570431.76220.042269
8-0.254615-1.74550.043712
9-0.001176-0.00810.496799
100.044660.30620.380413
110.0622840.4270.335666
12-0.308824-2.11720.019782
13-0.395647-2.71240.004651
14-0.031355-0.2150.415365
15-0.021556-0.14780.441574
16-0.059644-0.40890.342235
170.0301670.20680.418525
18-0.04157-0.2850.388451
19-0.004674-0.0320.487287
20-0.213395-1.4630.075066
210.0714130.48960.313352
22-0.051653-0.35410.362419
230.1648651.13030.132052
24-0.167337-1.14720.128551
25-0.144433-0.99020.163577
26-0.043596-0.29890.383175
270.0471820.32350.373891
28-0.123152-0.84430.201393
290.0666780.45710.324845
30-0.061505-0.42170.337599
31-0.080735-0.55350.291275
32-0.086891-0.59570.277119
330.0110620.07580.469936
340.1219950.83640.203594
350.0578740.39680.346668
36-0.002714-0.01860.492616

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.213292 & -1.4623 & 0.075163 \tabularnewline
2 & -0.343063 & -2.3519 & 0.011459 \tabularnewline
3 & 0.02156 & 0.1478 & 0.441563 \tabularnewline
4 & -0.022053 & -0.1512 & 0.440238 \tabularnewline
5 & -0.055599 & -0.3812 & 0.352398 \tabularnewline
6 & -0.055012 & -0.3771 & 0.353882 \tabularnewline
7 & 0.257043 & 1.7622 & 0.042269 \tabularnewline
8 & -0.254615 & -1.7455 & 0.043712 \tabularnewline
9 & -0.001176 & -0.0081 & 0.496799 \tabularnewline
10 & 0.04466 & 0.3062 & 0.380413 \tabularnewline
11 & 0.062284 & 0.427 & 0.335666 \tabularnewline
12 & -0.308824 & -2.1172 & 0.019782 \tabularnewline
13 & -0.395647 & -2.7124 & 0.004651 \tabularnewline
14 & -0.031355 & -0.215 & 0.415365 \tabularnewline
15 & -0.021556 & -0.1478 & 0.441574 \tabularnewline
16 & -0.059644 & -0.4089 & 0.342235 \tabularnewline
17 & 0.030167 & 0.2068 & 0.418525 \tabularnewline
18 & -0.04157 & -0.285 & 0.388451 \tabularnewline
19 & -0.004674 & -0.032 & 0.487287 \tabularnewline
20 & -0.213395 & -1.463 & 0.075066 \tabularnewline
21 & 0.071413 & 0.4896 & 0.313352 \tabularnewline
22 & -0.051653 & -0.3541 & 0.362419 \tabularnewline
23 & 0.164865 & 1.1303 & 0.132052 \tabularnewline
24 & -0.167337 & -1.1472 & 0.128551 \tabularnewline
25 & -0.144433 & -0.9902 & 0.163577 \tabularnewline
26 & -0.043596 & -0.2989 & 0.383175 \tabularnewline
27 & 0.047182 & 0.3235 & 0.373891 \tabularnewline
28 & -0.123152 & -0.8443 & 0.201393 \tabularnewline
29 & 0.066678 & 0.4571 & 0.324845 \tabularnewline
30 & -0.061505 & -0.4217 & 0.337599 \tabularnewline
31 & -0.080735 & -0.5535 & 0.291275 \tabularnewline
32 & -0.086891 & -0.5957 & 0.277119 \tabularnewline
33 & 0.011062 & 0.0758 & 0.469936 \tabularnewline
34 & 0.121995 & 0.8364 & 0.203594 \tabularnewline
35 & 0.057874 & 0.3968 & 0.346668 \tabularnewline
36 & -0.002714 & -0.0186 & 0.492616 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60885&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]-0.213292[/C][C]-1.4623[/C][C]0.075163[/C][/ROW]
[ROW][C]2[/C][C]-0.343063[/C][C]-2.3519[/C][C]0.011459[/C][/ROW]
[ROW][C]3[/C][C]0.02156[/C][C]0.1478[/C][C]0.441563[/C][/ROW]
[ROW][C]4[/C][C]-0.022053[/C][C]-0.1512[/C][C]0.440238[/C][/ROW]
[ROW][C]5[/C][C]-0.055599[/C][C]-0.3812[/C][C]0.352398[/C][/ROW]
[ROW][C]6[/C][C]-0.055012[/C][C]-0.3771[/C][C]0.353882[/C][/ROW]
[ROW][C]7[/C][C]0.257043[/C][C]1.7622[/C][C]0.042269[/C][/ROW]
[ROW][C]8[/C][C]-0.254615[/C][C]-1.7455[/C][C]0.043712[/C][/ROW]
[ROW][C]9[/C][C]-0.001176[/C][C]-0.0081[/C][C]0.496799[/C][/ROW]
[ROW][C]10[/C][C]0.04466[/C][C]0.3062[/C][C]0.380413[/C][/ROW]
[ROW][C]11[/C][C]0.062284[/C][C]0.427[/C][C]0.335666[/C][/ROW]
[ROW][C]12[/C][C]-0.308824[/C][C]-2.1172[/C][C]0.019782[/C][/ROW]
[ROW][C]13[/C][C]-0.395647[/C][C]-2.7124[/C][C]0.004651[/C][/ROW]
[ROW][C]14[/C][C]-0.031355[/C][C]-0.215[/C][C]0.415365[/C][/ROW]
[ROW][C]15[/C][C]-0.021556[/C][C]-0.1478[/C][C]0.441574[/C][/ROW]
[ROW][C]16[/C][C]-0.059644[/C][C]-0.4089[/C][C]0.342235[/C][/ROW]
[ROW][C]17[/C][C]0.030167[/C][C]0.2068[/C][C]0.418525[/C][/ROW]
[ROW][C]18[/C][C]-0.04157[/C][C]-0.285[/C][C]0.388451[/C][/ROW]
[ROW][C]19[/C][C]-0.004674[/C][C]-0.032[/C][C]0.487287[/C][/ROW]
[ROW][C]20[/C][C]-0.213395[/C][C]-1.463[/C][C]0.075066[/C][/ROW]
[ROW][C]21[/C][C]0.071413[/C][C]0.4896[/C][C]0.313352[/C][/ROW]
[ROW][C]22[/C][C]-0.051653[/C][C]-0.3541[/C][C]0.362419[/C][/ROW]
[ROW][C]23[/C][C]0.164865[/C][C]1.1303[/C][C]0.132052[/C][/ROW]
[ROW][C]24[/C][C]-0.167337[/C][C]-1.1472[/C][C]0.128551[/C][/ROW]
[ROW][C]25[/C][C]-0.144433[/C][C]-0.9902[/C][C]0.163577[/C][/ROW]
[ROW][C]26[/C][C]-0.043596[/C][C]-0.2989[/C][C]0.383175[/C][/ROW]
[ROW][C]27[/C][C]0.047182[/C][C]0.3235[/C][C]0.373891[/C][/ROW]
[ROW][C]28[/C][C]-0.123152[/C][C]-0.8443[/C][C]0.201393[/C][/ROW]
[ROW][C]29[/C][C]0.066678[/C][C]0.4571[/C][C]0.324845[/C][/ROW]
[ROW][C]30[/C][C]-0.061505[/C][C]-0.4217[/C][C]0.337599[/C][/ROW]
[ROW][C]31[/C][C]-0.080735[/C][C]-0.5535[/C][C]0.291275[/C][/ROW]
[ROW][C]32[/C][C]-0.086891[/C][C]-0.5957[/C][C]0.277119[/C][/ROW]
[ROW][C]33[/C][C]0.011062[/C][C]0.0758[/C][C]0.469936[/C][/ROW]
[ROW][C]34[/C][C]0.121995[/C][C]0.8364[/C][C]0.203594[/C][/ROW]
[ROW][C]35[/C][C]0.057874[/C][C]0.3968[/C][C]0.346668[/C][/ROW]
[ROW][C]36[/C][C]-0.002714[/C][C]-0.0186[/C][C]0.492616[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60885&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60885&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
1-0.213292-1.46230.075163
2-0.343063-2.35190.011459
30.021560.14780.441563
4-0.022053-0.15120.440238
5-0.055599-0.38120.352398
6-0.055012-0.37710.353882
70.2570431.76220.042269
8-0.254615-1.74550.043712
9-0.001176-0.00810.496799
100.044660.30620.380413
110.0622840.4270.335666
12-0.308824-2.11720.019782
13-0.395647-2.71240.004651
14-0.031355-0.2150.415365
15-0.021556-0.14780.441574
16-0.059644-0.40890.342235
170.0301670.20680.418525
18-0.04157-0.2850.388451
19-0.004674-0.0320.487287
20-0.213395-1.4630.075066
210.0714130.48960.313352
22-0.051653-0.35410.362419
230.1648651.13030.132052
24-0.167337-1.14720.128551
25-0.144433-0.99020.163577
26-0.043596-0.29890.383175
270.0471820.32350.373891
28-0.123152-0.84430.201393
290.0666780.45710.324845
30-0.061505-0.42170.337599
31-0.080735-0.55350.291275
32-0.086891-0.59570.277119
330.0110620.07580.469936
340.1219950.83640.203594
350.0578740.39680.346668
36-0.002714-0.01860.492616


Figures (Output of Computation)

Input Parameters & R Code

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')