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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 computationWed, 03 Dec 2008 05:35:52 -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/2008/Dec/03/t1228307810px1i0jienl0p76n.htm/, Retrieved Sat, 18 May 2024 03:45:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28658, Retrieved Sat, 18 May 2024 03:45:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordstotale werklsh d=1, D=1
Estimated Impact209

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Law of Averages] [Random Walk Simul...] [2008-11-25 18:31:28] [b98453cac15ba1066b407e146608df68]
F RM D  [(Partial) Autocorrelation Function] [non stationary ti...] [2008-12-02 20:37:52] [47f64d63202c1921bd27f3073f07a153]
F    D    [(Partial) Autocorrelation Function] [non stationary ti...] [2008-12-02 20:40:11] [47f64d63202c1921bd27f3073f07a153]
-           [(Partial) Autocorrelation Function] [non stationary ti...] [2008-12-02 20:41:59] [47f64d63202c1921bd27f3073f07a153]
-   P           [(Partial) Autocorrelation Function] [non stat time ser...] [2008-12-03 12:35:52] [3bdbbe597ac6c61989658933956ee6ac] [Current]
F   P             [(Partial) Autocorrelation Function] [non stat time ser...] [2008-12-03 12:56:47] [c96f3dce3a823a83b6ede18389e1cfd4]
-   P               [(Partial) Autocorrelation Function] [non stat time ser...] [2008-12-03 13:00:59] [c96f3dce3a823a83b6ede18389e1cfd4]
F                     [(Partial) Autocorrelation Function] [ARMA processing Q...] [2008-12-09 09:11:43] [c96f3dce3a823a83b6ede18389e1cfd4]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
8.4
8.4
8.4
8.6
8.9
8.8
8.3
7.5
7.2
7.5
8.8
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.6
8.2
8.1
8
8.6
8.7
8.8
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8.1
8.2
8.1
8.1
7.9
7.9
7.9
8
8
7.9
8
7.7
7.2
7.5
7.3
7
7
7
7.2
7.3
7.1
6.8
6.6
6.2
6.2
6.8
6.9
6.8

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=28658&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=28658&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28658&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
10.4673613.2380.001093
2-0.022637-0.15680.438016
3-0.364251-2.52360.00749
4-0.539759-3.73960.000246
5-0.246962-1.7110.046768
60.0314880.21820.414118
70.1590371.10180.138013
80.2274841.57610.060791
90.0432870.29990.382773
10-0.033279-0.23060.409318
110.0376830.26110.397575
12-0.005502-0.03810.484877
130.0464840.3220.374408
14-0.002189-0.01520.493982
15-0.110592-0.76620.223653
16-0.10885-0.75410.227226
17-0.113224-0.78440.218318
180.0067230.04660.48152
190.0677970.46970.320345
200.1313850.91030.183616
210.1023190.70890.240913
22-0.003799-0.02630.489556
23-0.041725-0.28910.386883
24-0.085767-0.59420.27758
25-0.014577-0.1010.459989
260.0737040.51060.305972
27-0.040644-0.28160.389735
28-0.102634-0.71110.240241
29-0.132329-0.91680.181914
30-0.095949-0.66480.254695
310.1694111.17370.12315
320.2308851.59960.058123
330.1640361.13650.1307
340.0830690.57550.283814
35-0.14394-0.99720.161823
36-0.256573-1.77760.040903

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.467361 & 3.238 & 0.001093 \tabularnewline
2 & -0.022637 & -0.1568 & 0.438016 \tabularnewline
3 & -0.364251 & -2.5236 & 0.00749 \tabularnewline
4 & -0.539759 & -3.7396 & 0.000246 \tabularnewline
5 & -0.246962 & -1.711 & 0.046768 \tabularnewline
6 & 0.031488 & 0.2182 & 0.414118 \tabularnewline
7 & 0.159037 & 1.1018 & 0.138013 \tabularnewline
8 & 0.227484 & 1.5761 & 0.060791 \tabularnewline
9 & 0.043287 & 0.2999 & 0.382773 \tabularnewline
10 & -0.033279 & -0.2306 & 0.409318 \tabularnewline
11 & 0.037683 & 0.2611 & 0.397575 \tabularnewline
12 & -0.005502 & -0.0381 & 0.484877 \tabularnewline
13 & 0.046484 & 0.322 & 0.374408 \tabularnewline
14 & -0.002189 & -0.0152 & 0.493982 \tabularnewline
15 & -0.110592 & -0.7662 & 0.223653 \tabularnewline
16 & -0.10885 & -0.7541 & 0.227226 \tabularnewline
17 & -0.113224 & -0.7844 & 0.218318 \tabularnewline
18 & 0.006723 & 0.0466 & 0.48152 \tabularnewline
19 & 0.067797 & 0.4697 & 0.320345 \tabularnewline
20 & 0.131385 & 0.9103 & 0.183616 \tabularnewline
21 & 0.102319 & 0.7089 & 0.240913 \tabularnewline
22 & -0.003799 & -0.0263 & 0.489556 \tabularnewline
23 & -0.041725 & -0.2891 & 0.386883 \tabularnewline
24 & -0.085767 & -0.5942 & 0.27758 \tabularnewline
25 & -0.014577 & -0.101 & 0.459989 \tabularnewline
26 & 0.073704 & 0.5106 & 0.305972 \tabularnewline
27 & -0.040644 & -0.2816 & 0.389735 \tabularnewline
28 & -0.102634 & -0.7111 & 0.240241 \tabularnewline
29 & -0.132329 & -0.9168 & 0.181914 \tabularnewline
30 & -0.095949 & -0.6648 & 0.254695 \tabularnewline
31 & 0.169411 & 1.1737 & 0.12315 \tabularnewline
32 & 0.230885 & 1.5996 & 0.058123 \tabularnewline
33 & 0.164036 & 1.1365 & 0.1307 \tabularnewline
34 & 0.083069 & 0.5755 & 0.283814 \tabularnewline
35 & -0.14394 & -0.9972 & 0.161823 \tabularnewline
36 & -0.256573 & -1.7776 & 0.040903 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28658&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]0.467361[/C][C]3.238[/C][C]0.001093[/C][/ROW]
[ROW][C]2[/C][C]-0.022637[/C][C]-0.1568[/C][C]0.438016[/C][/ROW]
[ROW][C]3[/C][C]-0.364251[/C][C]-2.5236[/C][C]0.00749[/C][/ROW]
[ROW][C]4[/C][C]-0.539759[/C][C]-3.7396[/C][C]0.000246[/C][/ROW]
[ROW][C]5[/C][C]-0.246962[/C][C]-1.711[/C][C]0.046768[/C][/ROW]
[ROW][C]6[/C][C]0.031488[/C][C]0.2182[/C][C]0.414118[/C][/ROW]
[ROW][C]7[/C][C]0.159037[/C][C]1.1018[/C][C]0.138013[/C][/ROW]
[ROW][C]8[/C][C]0.227484[/C][C]1.5761[/C][C]0.060791[/C][/ROW]
[ROW][C]9[/C][C]0.043287[/C][C]0.2999[/C][C]0.382773[/C][/ROW]
[ROW][C]10[/C][C]-0.033279[/C][C]-0.2306[/C][C]0.409318[/C][/ROW]
[ROW][C]11[/C][C]0.037683[/C][C]0.2611[/C][C]0.397575[/C][/ROW]
[ROW][C]12[/C][C]-0.005502[/C][C]-0.0381[/C][C]0.484877[/C][/ROW]
[ROW][C]13[/C][C]0.046484[/C][C]0.322[/C][C]0.374408[/C][/ROW]
[ROW][C]14[/C][C]-0.002189[/C][C]-0.0152[/C][C]0.493982[/C][/ROW]
[ROW][C]15[/C][C]-0.110592[/C][C]-0.7662[/C][C]0.223653[/C][/ROW]
[ROW][C]16[/C][C]-0.10885[/C][C]-0.7541[/C][C]0.227226[/C][/ROW]
[ROW][C]17[/C][C]-0.113224[/C][C]-0.7844[/C][C]0.218318[/C][/ROW]
[ROW][C]18[/C][C]0.006723[/C][C]0.0466[/C][C]0.48152[/C][/ROW]
[ROW][C]19[/C][C]0.067797[/C][C]0.4697[/C][C]0.320345[/C][/ROW]
[ROW][C]20[/C][C]0.131385[/C][C]0.9103[/C][C]0.183616[/C][/ROW]
[ROW][C]21[/C][C]0.102319[/C][C]0.7089[/C][C]0.240913[/C][/ROW]
[ROW][C]22[/C][C]-0.003799[/C][C]-0.0263[/C][C]0.489556[/C][/ROW]
[ROW][C]23[/C][C]-0.041725[/C][C]-0.2891[/C][C]0.386883[/C][/ROW]
[ROW][C]24[/C][C]-0.085767[/C][C]-0.5942[/C][C]0.27758[/C][/ROW]
[ROW][C]25[/C][C]-0.014577[/C][C]-0.101[/C][C]0.459989[/C][/ROW]
[ROW][C]26[/C][C]0.073704[/C][C]0.5106[/C][C]0.305972[/C][/ROW]
[ROW][C]27[/C][C]-0.040644[/C][C]-0.2816[/C][C]0.389735[/C][/ROW]
[ROW][C]28[/C][C]-0.102634[/C][C]-0.7111[/C][C]0.240241[/C][/ROW]
[ROW][C]29[/C][C]-0.132329[/C][C]-0.9168[/C][C]0.181914[/C][/ROW]
[ROW][C]30[/C][C]-0.095949[/C][C]-0.6648[/C][C]0.254695[/C][/ROW]
[ROW][C]31[/C][C]0.169411[/C][C]1.1737[/C][C]0.12315[/C][/ROW]
[ROW][C]32[/C][C]0.230885[/C][C]1.5996[/C][C]0.058123[/C][/ROW]
[ROW][C]33[/C][C]0.164036[/C][C]1.1365[/C][C]0.1307[/C][/ROW]
[ROW][C]34[/C][C]0.083069[/C][C]0.5755[/C][C]0.283814[/C][/ROW]
[ROW][C]35[/C][C]-0.14394[/C][C]-0.9972[/C][C]0.161823[/C][/ROW]
[ROW][C]36[/C][C]-0.256573[/C][C]-1.7776[/C][C]0.040903[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28658&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28658&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
10.4673613.2380.001093
2-0.022637-0.15680.438016
3-0.364251-2.52360.00749
4-0.539759-3.73960.000246
5-0.246962-1.7110.046768
60.0314880.21820.414118
70.1590371.10180.138013
80.2274841.57610.060791
90.0432870.29990.382773
10-0.033279-0.23060.409318
110.0376830.26110.397575
12-0.005502-0.03810.484877
130.0464840.3220.374408
14-0.002189-0.01520.493982
15-0.110592-0.76620.223653
16-0.10885-0.75410.227226
17-0.113224-0.78440.218318
180.0067230.04660.48152
190.0677970.46970.320345
200.1313850.91030.183616
210.1023190.70890.240913
22-0.003799-0.02630.489556
23-0.041725-0.28910.386883
24-0.085767-0.59420.27758
25-0.014577-0.1010.459989
260.0737040.51060.305972
27-0.040644-0.28160.389735
28-0.102634-0.71110.240241
29-0.132329-0.91680.181914
30-0.095949-0.66480.254695
310.1694111.17370.12315
320.2308851.59960.058123
330.1640361.13650.1307
340.0830690.57550.283814
35-0.14394-0.99720.161823
36-0.256573-1.77760.040903






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4673613.2380.001093
2-0.308434-2.13690.018865
3-0.291645-2.02060.024461
4-0.334467-2.31730.012401
50.1258640.8720.193771
6-0.073335-0.50810.306863
7-0.11562-0.8010.213529
80.0070020.04850.480755
9-0.125058-0.86640.195283
100.0659110.45660.324994
110.1370670.94960.17353
12-0.053138-0.36820.35719
130.0441740.3060.380447
14-0.023859-0.16530.4347
15-0.011276-0.07810.469027
16-0.0515-0.35680.361401
17-0.055977-0.38780.349932
180.0457180.31670.376405
19-0.132208-0.9160.182132
200.1375940.95330.172613
21-0.076034-0.52680.300387
22-0.025721-0.17820.429658
230.0537960.37270.355502
24-0.051448-0.35640.361537
250.1376580.95370.172501
260.016570.11480.454542
27-0.172592-1.19570.118834
28-0.059754-0.4140.340362
29-0.067886-0.47030.320127
300.0482170.33410.369895
310.1177080.81550.209406
32-0.044937-0.31130.378447
33-0.011488-0.07960.468445
340.0586870.40660.343057
350.0790690.54780.293181
36-0.170367-1.18030.121841

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.467361 & 3.238 & 0.001093 \tabularnewline
2 & -0.308434 & -2.1369 & 0.018865 \tabularnewline
3 & -0.291645 & -2.0206 & 0.024461 \tabularnewline
4 & -0.334467 & -2.3173 & 0.012401 \tabularnewline
5 & 0.125864 & 0.872 & 0.193771 \tabularnewline
6 & -0.073335 & -0.5081 & 0.306863 \tabularnewline
7 & -0.11562 & -0.801 & 0.213529 \tabularnewline
8 & 0.007002 & 0.0485 & 0.480755 \tabularnewline
9 & -0.125058 & -0.8664 & 0.195283 \tabularnewline
10 & 0.065911 & 0.4566 & 0.324994 \tabularnewline
11 & 0.137067 & 0.9496 & 0.17353 \tabularnewline
12 & -0.053138 & -0.3682 & 0.35719 \tabularnewline
13 & 0.044174 & 0.306 & 0.380447 \tabularnewline
14 & -0.023859 & -0.1653 & 0.4347 \tabularnewline
15 & -0.011276 & -0.0781 & 0.469027 \tabularnewline
16 & -0.0515 & -0.3568 & 0.361401 \tabularnewline
17 & -0.055977 & -0.3878 & 0.349932 \tabularnewline
18 & 0.045718 & 0.3167 & 0.376405 \tabularnewline
19 & -0.132208 & -0.916 & 0.182132 \tabularnewline
20 & 0.137594 & 0.9533 & 0.172613 \tabularnewline
21 & -0.076034 & -0.5268 & 0.300387 \tabularnewline
22 & -0.025721 & -0.1782 & 0.429658 \tabularnewline
23 & 0.053796 & 0.3727 & 0.355502 \tabularnewline
24 & -0.051448 & -0.3564 & 0.361537 \tabularnewline
25 & 0.137658 & 0.9537 & 0.172501 \tabularnewline
26 & 0.01657 & 0.1148 & 0.454542 \tabularnewline
27 & -0.172592 & -1.1957 & 0.118834 \tabularnewline
28 & -0.059754 & -0.414 & 0.340362 \tabularnewline
29 & -0.067886 & -0.4703 & 0.320127 \tabularnewline
30 & 0.048217 & 0.3341 & 0.369895 \tabularnewline
31 & 0.117708 & 0.8155 & 0.209406 \tabularnewline
32 & -0.044937 & -0.3113 & 0.378447 \tabularnewline
33 & -0.011488 & -0.0796 & 0.468445 \tabularnewline
34 & 0.058687 & 0.4066 & 0.343057 \tabularnewline
35 & 0.079069 & 0.5478 & 0.293181 \tabularnewline
36 & -0.170367 & -1.1803 & 0.121841 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28658&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]0.467361[/C][C]3.238[/C][C]0.001093[/C][/ROW]
[ROW][C]2[/C][C]-0.308434[/C][C]-2.1369[/C][C]0.018865[/C][/ROW]
[ROW][C]3[/C][C]-0.291645[/C][C]-2.0206[/C][C]0.024461[/C][/ROW]
[ROW][C]4[/C][C]-0.334467[/C][C]-2.3173[/C][C]0.012401[/C][/ROW]
[ROW][C]5[/C][C]0.125864[/C][C]0.872[/C][C]0.193771[/C][/ROW]
[ROW][C]6[/C][C]-0.073335[/C][C]-0.5081[/C][C]0.306863[/C][/ROW]
[ROW][C]7[/C][C]-0.11562[/C][C]-0.801[/C][C]0.213529[/C][/ROW]
[ROW][C]8[/C][C]0.007002[/C][C]0.0485[/C][C]0.480755[/C][/ROW]
[ROW][C]9[/C][C]-0.125058[/C][C]-0.8664[/C][C]0.195283[/C][/ROW]
[ROW][C]10[/C][C]0.065911[/C][C]0.4566[/C][C]0.324994[/C][/ROW]
[ROW][C]11[/C][C]0.137067[/C][C]0.9496[/C][C]0.17353[/C][/ROW]
[ROW][C]12[/C][C]-0.053138[/C][C]-0.3682[/C][C]0.35719[/C][/ROW]
[ROW][C]13[/C][C]0.044174[/C][C]0.306[/C][C]0.380447[/C][/ROW]
[ROW][C]14[/C][C]-0.023859[/C][C]-0.1653[/C][C]0.4347[/C][/ROW]
[ROW][C]15[/C][C]-0.011276[/C][C]-0.0781[/C][C]0.469027[/C][/ROW]
[ROW][C]16[/C][C]-0.0515[/C][C]-0.3568[/C][C]0.361401[/C][/ROW]
[ROW][C]17[/C][C]-0.055977[/C][C]-0.3878[/C][C]0.349932[/C][/ROW]
[ROW][C]18[/C][C]0.045718[/C][C]0.3167[/C][C]0.376405[/C][/ROW]
[ROW][C]19[/C][C]-0.132208[/C][C]-0.916[/C][C]0.182132[/C][/ROW]
[ROW][C]20[/C][C]0.137594[/C][C]0.9533[/C][C]0.172613[/C][/ROW]
[ROW][C]21[/C][C]-0.076034[/C][C]-0.5268[/C][C]0.300387[/C][/ROW]
[ROW][C]22[/C][C]-0.025721[/C][C]-0.1782[/C][C]0.429658[/C][/ROW]
[ROW][C]23[/C][C]0.053796[/C][C]0.3727[/C][C]0.355502[/C][/ROW]
[ROW][C]24[/C][C]-0.051448[/C][C]-0.3564[/C][C]0.361537[/C][/ROW]
[ROW][C]25[/C][C]0.137658[/C][C]0.9537[/C][C]0.172501[/C][/ROW]
[ROW][C]26[/C][C]0.01657[/C][C]0.1148[/C][C]0.454542[/C][/ROW]
[ROW][C]27[/C][C]-0.172592[/C][C]-1.1957[/C][C]0.118834[/C][/ROW]
[ROW][C]28[/C][C]-0.059754[/C][C]-0.414[/C][C]0.340362[/C][/ROW]
[ROW][C]29[/C][C]-0.067886[/C][C]-0.4703[/C][C]0.320127[/C][/ROW]
[ROW][C]30[/C][C]0.048217[/C][C]0.3341[/C][C]0.369895[/C][/ROW]
[ROW][C]31[/C][C]0.117708[/C][C]0.8155[/C][C]0.209406[/C][/ROW]
[ROW][C]32[/C][C]-0.044937[/C][C]-0.3113[/C][C]0.378447[/C][/ROW]
[ROW][C]33[/C][C]-0.011488[/C][C]-0.0796[/C][C]0.468445[/C][/ROW]
[ROW][C]34[/C][C]0.058687[/C][C]0.4066[/C][C]0.343057[/C][/ROW]
[ROW][C]35[/C][C]0.079069[/C][C]0.5478[/C][C]0.293181[/C][/ROW]
[ROW][C]36[/C][C]-0.170367[/C][C]-1.1803[/C][C]0.121841[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28658&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28658&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
10.4673613.2380.001093
2-0.308434-2.13690.018865
3-0.291645-2.02060.024461
4-0.334467-2.31730.012401
50.1258640.8720.193771
6-0.073335-0.50810.306863
7-0.11562-0.8010.213529
80.0070020.04850.480755
9-0.125058-0.86640.195283
100.0659110.45660.324994
110.1370670.94960.17353
12-0.053138-0.36820.35719
130.0441740.3060.380447
14-0.023859-0.16530.4347
15-0.011276-0.07810.469027
16-0.0515-0.35680.361401
17-0.055977-0.38780.349932
180.0457180.31670.376405
19-0.132208-0.9160.182132
200.1375940.95330.172613
21-0.076034-0.52680.300387
22-0.025721-0.17820.429658
230.0537960.37270.355502
24-0.051448-0.35640.361537
250.1376580.95370.172501
260.016570.11480.454542
27-0.172592-1.19570.118834
28-0.059754-0.4140.340362
29-0.067886-0.47030.320127
300.0482170.33410.369895
310.1177080.81550.209406
32-0.044937-0.31130.378447
33-0.011488-0.07960.468445
340.0586870.40660.343057
350.0790690.54780.293181
36-0.170367-1.18030.121841


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')