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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 computationFri, 05 Dec 2008 06:28:10 -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/05/t1228483796vjxqcxfzri9fuhi.htm/, Retrieved Fri, 29 Mar 2024 10:48:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29245, Retrieved Fri, 29 Mar 2024 10:48:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact259
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMP   [(Partial) Autocorrelation Function] [Taak 10 Stap 2 AC...] [2008-12-03 15:12:42] [6fea0e9a9b3b29a63badf2c274e82506]
-    D    [(Partial) Autocorrelation Function] [Taak 10 Stap 2 AC...] [2008-12-04 18:21:05] [819b576fab25b35cfda70f80599828ec]
-   P       [(Partial) Autocorrelation Function] [Taak 10 deel 2 st...] [2008-12-05 13:18:35] [6fea0e9a9b3b29a63badf2c274e82506]
-   P         [(Partial) Autocorrelation Function] [Taak 10 deel 2 st...] [2008-12-05 13:24:16] [6fea0e9a9b3b29a63badf2c274e82506]
-   P             [(Partial) Autocorrelation Function] [Taak 10 deel 2 st...] [2008-12-05 13:28:10] [286e96bd53289970f8e5f25a93fb50b3] [Current]
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Dataseries X:
58.972
59.249
63.955
53.785
52.760
44.795
37.348
32.370
32.717
40.974
33.591
21.124
58.608
46.865
51.378
46.235
47.206
45.382
41.227
33.795
31.295
42.625
33.625
21.538
56.421
53.152
53.536
52.408
41.454
38.271
35.306
26.414
31.917
38.030
27.534
18.387
50.556
43.901
48.572
43.899
37.532
40.357
35.489
29.027
34.485
42.598
30.306
26.451
47.460
50.104
61.465
53.726
39.477
43.895
31.481
29.896
33.842
39.120
33.702
25.094




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29245&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29245&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29245&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.312204-2.14040.018773
20.01190.08160.467664
3-0.034294-0.23510.407573
4-0.164135-1.12530.133097
5-0.037966-0.26030.397891
60.1655731.13510.131042
7-0.146665-1.00550.159906
80.0615820.42220.337408
90.2183541.4970.070545
10-0.187325-1.28420.102677
110.0628970.43120.334146
12-0.207989-1.42590.080253
13-0.073037-0.50070.309454
14-0.070005-0.47990.316752
150.2992932.05190.022889
16-0.179449-1.23020.112365
170.0945010.64790.260111
180.0748850.51340.305042
19-0.211253-1.44830.077089
200.2207141.51310.06847
21-0.176674-1.21120.115934
22-0.079764-0.54680.293539
230.0909470.62350.267985
240.1510271.03540.152893
25-0.065451-0.44870.327852
260.2251561.54360.064697
27-0.251663-1.72530.04552
280.0827780.56750.286538
29-0.015706-0.10770.457355
30-0.067683-0.4640.322392
31-0.002626-0.0180.492856
320.0328790.22540.411319
330.0657530.45080.32711
34-0.056127-0.38480.351065
350.1085920.74450.23015
36-0.150503-1.03180.153724

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.312204 & -2.1404 & 0.018773 \tabularnewline
2 & 0.0119 & 0.0816 & 0.467664 \tabularnewline
3 & -0.034294 & -0.2351 & 0.407573 \tabularnewline
4 & -0.164135 & -1.1253 & 0.133097 \tabularnewline
5 & -0.037966 & -0.2603 & 0.397891 \tabularnewline
6 & 0.165573 & 1.1351 & 0.131042 \tabularnewline
7 & -0.146665 & -1.0055 & 0.159906 \tabularnewline
8 & 0.061582 & 0.4222 & 0.337408 \tabularnewline
9 & 0.218354 & 1.497 & 0.070545 \tabularnewline
10 & -0.187325 & -1.2842 & 0.102677 \tabularnewline
11 & 0.062897 & 0.4312 & 0.334146 \tabularnewline
12 & -0.207989 & -1.4259 & 0.080253 \tabularnewline
13 & -0.073037 & -0.5007 & 0.309454 \tabularnewline
14 & -0.070005 & -0.4799 & 0.316752 \tabularnewline
15 & 0.299293 & 2.0519 & 0.022889 \tabularnewline
16 & -0.179449 & -1.2302 & 0.112365 \tabularnewline
17 & 0.094501 & 0.6479 & 0.260111 \tabularnewline
18 & 0.074885 & 0.5134 & 0.305042 \tabularnewline
19 & -0.211253 & -1.4483 & 0.077089 \tabularnewline
20 & 0.220714 & 1.5131 & 0.06847 \tabularnewline
21 & -0.176674 & -1.2112 & 0.115934 \tabularnewline
22 & -0.079764 & -0.5468 & 0.293539 \tabularnewline
23 & 0.090947 & 0.6235 & 0.267985 \tabularnewline
24 & 0.151027 & 1.0354 & 0.152893 \tabularnewline
25 & -0.065451 & -0.4487 & 0.327852 \tabularnewline
26 & 0.225156 & 1.5436 & 0.064697 \tabularnewline
27 & -0.251663 & -1.7253 & 0.04552 \tabularnewline
28 & 0.082778 & 0.5675 & 0.286538 \tabularnewline
29 & -0.015706 & -0.1077 & 0.457355 \tabularnewline
30 & -0.067683 & -0.464 & 0.322392 \tabularnewline
31 & -0.002626 & -0.018 & 0.492856 \tabularnewline
32 & 0.032879 & 0.2254 & 0.411319 \tabularnewline
33 & 0.065753 & 0.4508 & 0.32711 \tabularnewline
34 & -0.056127 & -0.3848 & 0.351065 \tabularnewline
35 & 0.108592 & 0.7445 & 0.23015 \tabularnewline
36 & -0.150503 & -1.0318 & 0.153724 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29245&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]-0.312204[/C][C]-2.1404[/C][C]0.018773[/C][/ROW]
[ROW][C]2[/C][C]0.0119[/C][C]0.0816[/C][C]0.467664[/C][/ROW]
[ROW][C]3[/C][C]-0.034294[/C][C]-0.2351[/C][C]0.407573[/C][/ROW]
[ROW][C]4[/C][C]-0.164135[/C][C]-1.1253[/C][C]0.133097[/C][/ROW]
[ROW][C]5[/C][C]-0.037966[/C][C]-0.2603[/C][C]0.397891[/C][/ROW]
[ROW][C]6[/C][C]0.165573[/C][C]1.1351[/C][C]0.131042[/C][/ROW]
[ROW][C]7[/C][C]-0.146665[/C][C]-1.0055[/C][C]0.159906[/C][/ROW]
[ROW][C]8[/C][C]0.061582[/C][C]0.4222[/C][C]0.337408[/C][/ROW]
[ROW][C]9[/C][C]0.218354[/C][C]1.497[/C][C]0.070545[/C][/ROW]
[ROW][C]10[/C][C]-0.187325[/C][C]-1.2842[/C][C]0.102677[/C][/ROW]
[ROW][C]11[/C][C]0.062897[/C][C]0.4312[/C][C]0.334146[/C][/ROW]
[ROW][C]12[/C][C]-0.207989[/C][C]-1.4259[/C][C]0.080253[/C][/ROW]
[ROW][C]13[/C][C]-0.073037[/C][C]-0.5007[/C][C]0.309454[/C][/ROW]
[ROW][C]14[/C][C]-0.070005[/C][C]-0.4799[/C][C]0.316752[/C][/ROW]
[ROW][C]15[/C][C]0.299293[/C][C]2.0519[/C][C]0.022889[/C][/ROW]
[ROW][C]16[/C][C]-0.179449[/C][C]-1.2302[/C][C]0.112365[/C][/ROW]
[ROW][C]17[/C][C]0.094501[/C][C]0.6479[/C][C]0.260111[/C][/ROW]
[ROW][C]18[/C][C]0.074885[/C][C]0.5134[/C][C]0.305042[/C][/ROW]
[ROW][C]19[/C][C]-0.211253[/C][C]-1.4483[/C][C]0.077089[/C][/ROW]
[ROW][C]20[/C][C]0.220714[/C][C]1.5131[/C][C]0.06847[/C][/ROW]
[ROW][C]21[/C][C]-0.176674[/C][C]-1.2112[/C][C]0.115934[/C][/ROW]
[ROW][C]22[/C][C]-0.079764[/C][C]-0.5468[/C][C]0.293539[/C][/ROW]
[ROW][C]23[/C][C]0.090947[/C][C]0.6235[/C][C]0.267985[/C][/ROW]
[ROW][C]24[/C][C]0.151027[/C][C]1.0354[/C][C]0.152893[/C][/ROW]
[ROW][C]25[/C][C]-0.065451[/C][C]-0.4487[/C][C]0.327852[/C][/ROW]
[ROW][C]26[/C][C]0.225156[/C][C]1.5436[/C][C]0.064697[/C][/ROW]
[ROW][C]27[/C][C]-0.251663[/C][C]-1.7253[/C][C]0.04552[/C][/ROW]
[ROW][C]28[/C][C]0.082778[/C][C]0.5675[/C][C]0.286538[/C][/ROW]
[ROW][C]29[/C][C]-0.015706[/C][C]-0.1077[/C][C]0.457355[/C][/ROW]
[ROW][C]30[/C][C]-0.067683[/C][C]-0.464[/C][C]0.322392[/C][/ROW]
[ROW][C]31[/C][C]-0.002626[/C][C]-0.018[/C][C]0.492856[/C][/ROW]
[ROW][C]32[/C][C]0.032879[/C][C]0.2254[/C][C]0.411319[/C][/ROW]
[ROW][C]33[/C][C]0.065753[/C][C]0.4508[/C][C]0.32711[/C][/ROW]
[ROW][C]34[/C][C]-0.056127[/C][C]-0.3848[/C][C]0.351065[/C][/ROW]
[ROW][C]35[/C][C]0.108592[/C][C]0.7445[/C][C]0.23015[/C][/ROW]
[ROW][C]36[/C][C]-0.150503[/C][C]-1.0318[/C][C]0.153724[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29245&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29245&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
1-0.312204-2.14040.018773
20.01190.08160.467664
3-0.034294-0.23510.407573
4-0.164135-1.12530.133097
5-0.037966-0.26030.397891
60.1655731.13510.131042
7-0.146665-1.00550.159906
80.0615820.42220.337408
90.2183541.4970.070545
10-0.187325-1.28420.102677
110.0628970.43120.334146
12-0.207989-1.42590.080253
13-0.073037-0.50070.309454
14-0.070005-0.47990.316752
150.2992932.05190.022889
16-0.179449-1.23020.112365
170.0945010.64790.260111
180.0748850.51340.305042
19-0.211253-1.44830.077089
200.2207141.51310.06847
21-0.176674-1.21120.115934
22-0.079764-0.54680.293539
230.0909470.62350.267985
240.1510271.03540.152893
25-0.065451-0.44870.327852
260.2251561.54360.064697
27-0.251663-1.72530.04552
280.0827780.56750.286538
29-0.015706-0.10770.457355
30-0.067683-0.4640.322392
31-0.002626-0.0180.492856
320.0328790.22540.411319
330.0657530.45080.32711
34-0.056127-0.38480.351065
350.1085920.74450.23015
36-0.150503-1.03180.153724







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.312204-2.14040.018773
2-0.094813-0.650.259426
3-0.06689-0.45860.324326
4-0.219626-1.50570.069421
5-0.199778-1.36960.088658
60.0701520.48090.316395
7-0.122674-0.8410.2023
8-0.085014-0.58280.281399
90.2296141.57420.06108
10-0.01397-0.09580.462054
11-0.009452-0.06480.474303
12-0.230776-1.58210.060165
13-0.16079-1.10230.137968
14-0.28496-1.95360.028358
150.0845050.57930.282565
16-0.131608-0.90230.18576
17-0.154609-1.05990.147293
180.0533820.3660.358016
19-0.167531-1.14850.12828
200.147371.01030.158758
21-0.130585-0.89520.187608
22-0.122624-0.84070.202395
23-0.093833-0.64330.261583
24-0.037777-0.2590.398387
250.0120130.08240.467356
260.02030.13920.444955
27-0.051852-0.35550.361909
280.0915110.62740.266726
29-0.011081-0.0760.469883
30-0.035828-0.24560.403522
31-0.053891-0.36950.356723
32-0.01404-0.09630.461865
33-0.007285-0.04990.480189
34-0.076727-0.5260.300675
35-0.067821-0.4650.322055
360.0593160.40670.343055

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.312204 & -2.1404 & 0.018773 \tabularnewline
2 & -0.094813 & -0.65 & 0.259426 \tabularnewline
3 & -0.06689 & -0.4586 & 0.324326 \tabularnewline
4 & -0.219626 & -1.5057 & 0.069421 \tabularnewline
5 & -0.199778 & -1.3696 & 0.088658 \tabularnewline
6 & 0.070152 & 0.4809 & 0.316395 \tabularnewline
7 & -0.122674 & -0.841 & 0.2023 \tabularnewline
8 & -0.085014 & -0.5828 & 0.281399 \tabularnewline
9 & 0.229614 & 1.5742 & 0.06108 \tabularnewline
10 & -0.01397 & -0.0958 & 0.462054 \tabularnewline
11 & -0.009452 & -0.0648 & 0.474303 \tabularnewline
12 & -0.230776 & -1.5821 & 0.060165 \tabularnewline
13 & -0.16079 & -1.1023 & 0.137968 \tabularnewline
14 & -0.28496 & -1.9536 & 0.028358 \tabularnewline
15 & 0.084505 & 0.5793 & 0.282565 \tabularnewline
16 & -0.131608 & -0.9023 & 0.18576 \tabularnewline
17 & -0.154609 & -1.0599 & 0.147293 \tabularnewline
18 & 0.053382 & 0.366 & 0.358016 \tabularnewline
19 & -0.167531 & -1.1485 & 0.12828 \tabularnewline
20 & 0.14737 & 1.0103 & 0.158758 \tabularnewline
21 & -0.130585 & -0.8952 & 0.187608 \tabularnewline
22 & -0.122624 & -0.8407 & 0.202395 \tabularnewline
23 & -0.093833 & -0.6433 & 0.261583 \tabularnewline
24 & -0.037777 & -0.259 & 0.398387 \tabularnewline
25 & 0.012013 & 0.0824 & 0.467356 \tabularnewline
26 & 0.0203 & 0.1392 & 0.444955 \tabularnewline
27 & -0.051852 & -0.3555 & 0.361909 \tabularnewline
28 & 0.091511 & 0.6274 & 0.266726 \tabularnewline
29 & -0.011081 & -0.076 & 0.469883 \tabularnewline
30 & -0.035828 & -0.2456 & 0.403522 \tabularnewline
31 & -0.053891 & -0.3695 & 0.356723 \tabularnewline
32 & -0.01404 & -0.0963 & 0.461865 \tabularnewline
33 & -0.007285 & -0.0499 & 0.480189 \tabularnewline
34 & -0.076727 & -0.526 & 0.300675 \tabularnewline
35 & -0.067821 & -0.465 & 0.322055 \tabularnewline
36 & 0.059316 & 0.4067 & 0.343055 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29245&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]-0.312204[/C][C]-2.1404[/C][C]0.018773[/C][/ROW]
[ROW][C]2[/C][C]-0.094813[/C][C]-0.65[/C][C]0.259426[/C][/ROW]
[ROW][C]3[/C][C]-0.06689[/C][C]-0.4586[/C][C]0.324326[/C][/ROW]
[ROW][C]4[/C][C]-0.219626[/C][C]-1.5057[/C][C]0.069421[/C][/ROW]
[ROW][C]5[/C][C]-0.199778[/C][C]-1.3696[/C][C]0.088658[/C][/ROW]
[ROW][C]6[/C][C]0.070152[/C][C]0.4809[/C][C]0.316395[/C][/ROW]
[ROW][C]7[/C][C]-0.122674[/C][C]-0.841[/C][C]0.2023[/C][/ROW]
[ROW][C]8[/C][C]-0.085014[/C][C]-0.5828[/C][C]0.281399[/C][/ROW]
[ROW][C]9[/C][C]0.229614[/C][C]1.5742[/C][C]0.06108[/C][/ROW]
[ROW][C]10[/C][C]-0.01397[/C][C]-0.0958[/C][C]0.462054[/C][/ROW]
[ROW][C]11[/C][C]-0.009452[/C][C]-0.0648[/C][C]0.474303[/C][/ROW]
[ROW][C]12[/C][C]-0.230776[/C][C]-1.5821[/C][C]0.060165[/C][/ROW]
[ROW][C]13[/C][C]-0.16079[/C][C]-1.1023[/C][C]0.137968[/C][/ROW]
[ROW][C]14[/C][C]-0.28496[/C][C]-1.9536[/C][C]0.028358[/C][/ROW]
[ROW][C]15[/C][C]0.084505[/C][C]0.5793[/C][C]0.282565[/C][/ROW]
[ROW][C]16[/C][C]-0.131608[/C][C]-0.9023[/C][C]0.18576[/C][/ROW]
[ROW][C]17[/C][C]-0.154609[/C][C]-1.0599[/C][C]0.147293[/C][/ROW]
[ROW][C]18[/C][C]0.053382[/C][C]0.366[/C][C]0.358016[/C][/ROW]
[ROW][C]19[/C][C]-0.167531[/C][C]-1.1485[/C][C]0.12828[/C][/ROW]
[ROW][C]20[/C][C]0.14737[/C][C]1.0103[/C][C]0.158758[/C][/ROW]
[ROW][C]21[/C][C]-0.130585[/C][C]-0.8952[/C][C]0.187608[/C][/ROW]
[ROW][C]22[/C][C]-0.122624[/C][C]-0.8407[/C][C]0.202395[/C][/ROW]
[ROW][C]23[/C][C]-0.093833[/C][C]-0.6433[/C][C]0.261583[/C][/ROW]
[ROW][C]24[/C][C]-0.037777[/C][C]-0.259[/C][C]0.398387[/C][/ROW]
[ROW][C]25[/C][C]0.012013[/C][C]0.0824[/C][C]0.467356[/C][/ROW]
[ROW][C]26[/C][C]0.0203[/C][C]0.1392[/C][C]0.444955[/C][/ROW]
[ROW][C]27[/C][C]-0.051852[/C][C]-0.3555[/C][C]0.361909[/C][/ROW]
[ROW][C]28[/C][C]0.091511[/C][C]0.6274[/C][C]0.266726[/C][/ROW]
[ROW][C]29[/C][C]-0.011081[/C][C]-0.076[/C][C]0.469883[/C][/ROW]
[ROW][C]30[/C][C]-0.035828[/C][C]-0.2456[/C][C]0.403522[/C][/ROW]
[ROW][C]31[/C][C]-0.053891[/C][C]-0.3695[/C][C]0.356723[/C][/ROW]
[ROW][C]32[/C][C]-0.01404[/C][C]-0.0963[/C][C]0.461865[/C][/ROW]
[ROW][C]33[/C][C]-0.007285[/C][C]-0.0499[/C][C]0.480189[/C][/ROW]
[ROW][C]34[/C][C]-0.076727[/C][C]-0.526[/C][C]0.300675[/C][/ROW]
[ROW][C]35[/C][C]-0.067821[/C][C]-0.465[/C][C]0.322055[/C][/ROW]
[ROW][C]36[/C][C]0.059316[/C][C]0.4067[/C][C]0.343055[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29245&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29245&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
1-0.312204-2.14040.018773
2-0.094813-0.650.259426
3-0.06689-0.45860.324326
4-0.219626-1.50570.069421
5-0.199778-1.36960.088658
60.0701520.48090.316395
7-0.122674-0.8410.2023
8-0.085014-0.58280.281399
90.2296141.57420.06108
10-0.01397-0.09580.462054
11-0.009452-0.06480.474303
12-0.230776-1.58210.060165
13-0.16079-1.10230.137968
14-0.28496-1.95360.028358
150.0845050.57930.282565
16-0.131608-0.90230.18576
17-0.154609-1.05990.147293
180.0533820.3660.358016
19-0.167531-1.14850.12828
200.147371.01030.158758
21-0.130585-0.89520.187608
22-0.122624-0.84070.202395
23-0.093833-0.64330.261583
24-0.037777-0.2590.398387
250.0120130.08240.467356
260.02030.13920.444955
27-0.051852-0.35550.361909
280.0915110.62740.266726
29-0.011081-0.0760.469883
30-0.035828-0.24560.403522
31-0.053891-0.36950.356723
32-0.01404-0.09630.461865
33-0.007285-0.04990.480189
34-0.076727-0.5260.300675
35-0.067821-0.4650.322055
360.0593160.40670.343055



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')