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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 05:56:37 -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/t1228309086md2iqoi842l1c42.htm/, Retrieved Sat, 18 May 2024 07:50:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28677, Retrieved Sat, 18 May 2024 07:50:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsnon stationary time series totaal Q8 ACF
Estimated Impact220

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 stationary ti...] [2008-12-03 12:46:33] [47f64d63202c1921bd27f3073f07a153]
F   P             [(Partial) Autocorrelation Function] [non stationary ti...] [2008-12-03 12:56:37] [74c7506a1ea162af3aa8be25bcd05d28] [Current]
Feedback Forum
2008-12-08 17:37:30 [6066575aa30c0611e452e930b1dff53d] [reply] 
Het is inderdaad zo dat de lange termijn trend weggewerkt is, maar dat er nog steeds sprake is van seizoenaliteit.

Post a new message

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=28677&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=28677&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28677&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
1-0.027941-0.21460.415402
2-0.177012-1.35970.089557
3-0.402208-3.08940.001529
4-0.254403-1.95410.027717
50.070640.54260.294726
60.3649662.80340.003417
70.1544841.18660.120068
8-0.039996-0.30720.379881
9-0.231948-1.78160.039978
10-0.150586-1.15670.126034
11-0.057262-0.43980.330829
120.4727773.63150.000296
13-0.095812-0.73590.232341
14-0.019934-0.15310.439415
15-0.178597-1.37180.087656
16-0.036049-0.27690.391412
17-0.015963-0.12260.451415
180.1718361.31990.095984
190.0785790.60360.274219
20-0.051894-0.39860.34581
21-0.097349-0.74780.228789
22-0.0493-0.37870.353143
23-0.042687-0.32790.372079
240.2091181.60630.056778
25-0.047947-0.36830.356989
26-0.006668-0.05120.479663
27-0.101301-0.77810.219807
280.0172550.13250.447505
29-1.1e-05-1e-040.499966
300.0612420.47040.3199
310.1012340.77760.219958
32-0.083812-0.64380.261109
33-0.058602-0.45010.327132
34-0.03064-0.23530.407377
35-0.050681-0.38930.349231
360.1997921.53460.06511

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.027941 & -0.2146 & 0.415402 \tabularnewline
2 & -0.177012 & -1.3597 & 0.089557 \tabularnewline
3 & -0.402208 & -3.0894 & 0.001529 \tabularnewline
4 & -0.254403 & -1.9541 & 0.027717 \tabularnewline
5 & 0.07064 & 0.5426 & 0.294726 \tabularnewline
6 & 0.364966 & 2.8034 & 0.003417 \tabularnewline
7 & 0.154484 & 1.1866 & 0.120068 \tabularnewline
8 & -0.039996 & -0.3072 & 0.379881 \tabularnewline
9 & -0.231948 & -1.7816 & 0.039978 \tabularnewline
10 & -0.150586 & -1.1567 & 0.126034 \tabularnewline
11 & -0.057262 & -0.4398 & 0.330829 \tabularnewline
12 & 0.472777 & 3.6315 & 0.000296 \tabularnewline
13 & -0.095812 & -0.7359 & 0.232341 \tabularnewline
14 & -0.019934 & -0.1531 & 0.439415 \tabularnewline
15 & -0.178597 & -1.3718 & 0.087656 \tabularnewline
16 & -0.036049 & -0.2769 & 0.391412 \tabularnewline
17 & -0.015963 & -0.1226 & 0.451415 \tabularnewline
18 & 0.171836 & 1.3199 & 0.095984 \tabularnewline
19 & 0.078579 & 0.6036 & 0.274219 \tabularnewline
20 & -0.051894 & -0.3986 & 0.34581 \tabularnewline
21 & -0.097349 & -0.7478 & 0.228789 \tabularnewline
22 & -0.0493 & -0.3787 & 0.353143 \tabularnewline
23 & -0.042687 & -0.3279 & 0.372079 \tabularnewline
24 & 0.209118 & 1.6063 & 0.056778 \tabularnewline
25 & -0.047947 & -0.3683 & 0.356989 \tabularnewline
26 & -0.006668 & -0.0512 & 0.479663 \tabularnewline
27 & -0.101301 & -0.7781 & 0.219807 \tabularnewline
28 & 0.017255 & 0.1325 & 0.447505 \tabularnewline
29 & -1.1e-05 & -1e-04 & 0.499966 \tabularnewline
30 & 0.061242 & 0.4704 & 0.3199 \tabularnewline
31 & 0.101234 & 0.7776 & 0.219958 \tabularnewline
32 & -0.083812 & -0.6438 & 0.261109 \tabularnewline
33 & -0.058602 & -0.4501 & 0.327132 \tabularnewline
34 & -0.03064 & -0.2353 & 0.407377 \tabularnewline
35 & -0.050681 & -0.3893 & 0.349231 \tabularnewline
36 & 0.199792 & 1.5346 & 0.06511 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28677&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]-0.027941[/C][C]-0.2146[/C][C]0.415402[/C][/ROW]
[ROW][C]2[/C][C]-0.177012[/C][C]-1.3597[/C][C]0.089557[/C][/ROW]
[ROW][C]3[/C][C]-0.402208[/C][C]-3.0894[/C][C]0.001529[/C][/ROW]
[ROW][C]4[/C][C]-0.254403[/C][C]-1.9541[/C][C]0.027717[/C][/ROW]
[ROW][C]5[/C][C]0.07064[/C][C]0.5426[/C][C]0.294726[/C][/ROW]
[ROW][C]6[/C][C]0.364966[/C][C]2.8034[/C][C]0.003417[/C][/ROW]
[ROW][C]7[/C][C]0.154484[/C][C]1.1866[/C][C]0.120068[/C][/ROW]
[ROW][C]8[/C][C]-0.039996[/C][C]-0.3072[/C][C]0.379881[/C][/ROW]
[ROW][C]9[/C][C]-0.231948[/C][C]-1.7816[/C][C]0.039978[/C][/ROW]
[ROW][C]10[/C][C]-0.150586[/C][C]-1.1567[/C][C]0.126034[/C][/ROW]
[ROW][C]11[/C][C]-0.057262[/C][C]-0.4398[/C][C]0.330829[/C][/ROW]
[ROW][C]12[/C][C]0.472777[/C][C]3.6315[/C][C]0.000296[/C][/ROW]
[ROW][C]13[/C][C]-0.095812[/C][C]-0.7359[/C][C]0.232341[/C][/ROW]
[ROW][C]14[/C][C]-0.019934[/C][C]-0.1531[/C][C]0.439415[/C][/ROW]
[ROW][C]15[/C][C]-0.178597[/C][C]-1.3718[/C][C]0.087656[/C][/ROW]
[ROW][C]16[/C][C]-0.036049[/C][C]-0.2769[/C][C]0.391412[/C][/ROW]
[ROW][C]17[/C][C]-0.015963[/C][C]-0.1226[/C][C]0.451415[/C][/ROW]
[ROW][C]18[/C][C]0.171836[/C][C]1.3199[/C][C]0.095984[/C][/ROW]
[ROW][C]19[/C][C]0.078579[/C][C]0.6036[/C][C]0.274219[/C][/ROW]
[ROW][C]20[/C][C]-0.051894[/C][C]-0.3986[/C][C]0.34581[/C][/ROW]
[ROW][C]21[/C][C]-0.097349[/C][C]-0.7478[/C][C]0.228789[/C][/ROW]
[ROW][C]22[/C][C]-0.0493[/C][C]-0.3787[/C][C]0.353143[/C][/ROW]
[ROW][C]23[/C][C]-0.042687[/C][C]-0.3279[/C][C]0.372079[/C][/ROW]
[ROW][C]24[/C][C]0.209118[/C][C]1.6063[/C][C]0.056778[/C][/ROW]
[ROW][C]25[/C][C]-0.047947[/C][C]-0.3683[/C][C]0.356989[/C][/ROW]
[ROW][C]26[/C][C]-0.006668[/C][C]-0.0512[/C][C]0.479663[/C][/ROW]
[ROW][C]27[/C][C]-0.101301[/C][C]-0.7781[/C][C]0.219807[/C][/ROW]
[ROW][C]28[/C][C]0.017255[/C][C]0.1325[/C][C]0.447505[/C][/ROW]
[ROW][C]29[/C][C]-1.1e-05[/C][C]-1e-04[/C][C]0.499966[/C][/ROW]
[ROW][C]30[/C][C]0.061242[/C][C]0.4704[/C][C]0.3199[/C][/ROW]
[ROW][C]31[/C][C]0.101234[/C][C]0.7776[/C][C]0.219958[/C][/ROW]
[ROW][C]32[/C][C]-0.083812[/C][C]-0.6438[/C][C]0.261109[/C][/ROW]
[ROW][C]33[/C][C]-0.058602[/C][C]-0.4501[/C][C]0.327132[/C][/ROW]
[ROW][C]34[/C][C]-0.03064[/C][C]-0.2353[/C][C]0.407377[/C][/ROW]
[ROW][C]35[/C][C]-0.050681[/C][C]-0.3893[/C][C]0.349231[/C][/ROW]
[ROW][C]36[/C][C]0.199792[/C][C]1.5346[/C][C]0.06511[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28677&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28677&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
1-0.027941-0.21460.415402
2-0.177012-1.35970.089557
3-0.402208-3.08940.001529
4-0.254403-1.95410.027717
50.070640.54260.294726
60.3649662.80340.003417
70.1544841.18660.120068
8-0.039996-0.30720.379881
9-0.231948-1.78160.039978
10-0.150586-1.15670.126034
11-0.057262-0.43980.330829
120.4727773.63150.000296
13-0.095812-0.73590.232341
14-0.019934-0.15310.439415
15-0.178597-1.37180.087656
16-0.036049-0.27690.391412
17-0.015963-0.12260.451415
180.1718361.31990.095984
190.0785790.60360.274219
20-0.051894-0.39860.34581
21-0.097349-0.74780.228789
22-0.0493-0.37870.353143
23-0.042687-0.32790.372079
240.2091181.60630.056778
25-0.047947-0.36830.356989
26-0.006668-0.05120.479663
27-0.101301-0.77810.219807
280.0172550.13250.447505
29-1.1e-05-1e-040.499966
300.0612420.47040.3199
310.1012340.77760.219958
32-0.083812-0.64380.261109
33-0.058602-0.45010.327132
34-0.03064-0.23530.407377
35-0.050681-0.38930.349231
360.1997921.53460.06511






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.027941-0.21460.415402
2-0.177931-1.36670.08845
3-0.426842-3.27860.000876
4-0.434852-3.34020.000728
5-0.329073-2.52770.007091
6-0.077598-0.5960.276714
7-0.161266-1.23870.11018
8-0.180675-1.38780.08521
9-0.221488-1.70130.047078
10-0.202225-1.55330.062848
11-0.382796-2.94030.002338
120.1994731.53220.065411
13-0.28777-2.21040.015484
14-0.183936-1.41280.081478
15-0.14939-1.14750.127907
160.0356430.27380.392607
17-0.176255-1.35380.090476
18-0.159657-1.22630.11247
190.0037490.02880.488562
20-0.100914-0.77510.220678
21-0.060572-0.46530.321727
22-0.013721-0.10540.458209
230.0046150.03540.485922
24-0.068633-0.52720.300024
250.0925240.71070.240038
260.0113110.08690.465531
27-0.049246-0.37830.353296
28-0.065704-0.50470.307832
290.0644540.49510.311191
30-0.161424-1.23990.109957
310.0103570.07960.468432
32-0.057428-0.44110.330372
33-0.047482-0.36470.358313
34-0.090112-0.69220.245775
35-0.118769-0.91230.182666
360.1289490.99050.162993

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.027941 & -0.2146 & 0.415402 \tabularnewline
2 & -0.177931 & -1.3667 & 0.08845 \tabularnewline
3 & -0.426842 & -3.2786 & 0.000876 \tabularnewline
4 & -0.434852 & -3.3402 & 0.000728 \tabularnewline
5 & -0.329073 & -2.5277 & 0.007091 \tabularnewline
6 & -0.077598 & -0.596 & 0.276714 \tabularnewline
7 & -0.161266 & -1.2387 & 0.11018 \tabularnewline
8 & -0.180675 & -1.3878 & 0.08521 \tabularnewline
9 & -0.221488 & -1.7013 & 0.047078 \tabularnewline
10 & -0.202225 & -1.5533 & 0.062848 \tabularnewline
11 & -0.382796 & -2.9403 & 0.002338 \tabularnewline
12 & 0.199473 & 1.5322 & 0.065411 \tabularnewline
13 & -0.28777 & -2.2104 & 0.015484 \tabularnewline
14 & -0.183936 & -1.4128 & 0.081478 \tabularnewline
15 & -0.14939 & -1.1475 & 0.127907 \tabularnewline
16 & 0.035643 & 0.2738 & 0.392607 \tabularnewline
17 & -0.176255 & -1.3538 & 0.090476 \tabularnewline
18 & -0.159657 & -1.2263 & 0.11247 \tabularnewline
19 & 0.003749 & 0.0288 & 0.488562 \tabularnewline
20 & -0.100914 & -0.7751 & 0.220678 \tabularnewline
21 & -0.060572 & -0.4653 & 0.321727 \tabularnewline
22 & -0.013721 & -0.1054 & 0.458209 \tabularnewline
23 & 0.004615 & 0.0354 & 0.485922 \tabularnewline
24 & -0.068633 & -0.5272 & 0.300024 \tabularnewline
25 & 0.092524 & 0.7107 & 0.240038 \tabularnewline
26 & 0.011311 & 0.0869 & 0.465531 \tabularnewline
27 & -0.049246 & -0.3783 & 0.353296 \tabularnewline
28 & -0.065704 & -0.5047 & 0.307832 \tabularnewline
29 & 0.064454 & 0.4951 & 0.311191 \tabularnewline
30 & -0.161424 & -1.2399 & 0.109957 \tabularnewline
31 & 0.010357 & 0.0796 & 0.468432 \tabularnewline
32 & -0.057428 & -0.4411 & 0.330372 \tabularnewline
33 & -0.047482 & -0.3647 & 0.358313 \tabularnewline
34 & -0.090112 & -0.6922 & 0.245775 \tabularnewline
35 & -0.118769 & -0.9123 & 0.182666 \tabularnewline
36 & 0.128949 & 0.9905 & 0.162993 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28677&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]-0.027941[/C][C]-0.2146[/C][C]0.415402[/C][/ROW]
[ROW][C]2[/C][C]-0.177931[/C][C]-1.3667[/C][C]0.08845[/C][/ROW]
[ROW][C]3[/C][C]-0.426842[/C][C]-3.2786[/C][C]0.000876[/C][/ROW]
[ROW][C]4[/C][C]-0.434852[/C][C]-3.3402[/C][C]0.000728[/C][/ROW]
[ROW][C]5[/C][C]-0.329073[/C][C]-2.5277[/C][C]0.007091[/C][/ROW]
[ROW][C]6[/C][C]-0.077598[/C][C]-0.596[/C][C]0.276714[/C][/ROW]
[ROW][C]7[/C][C]-0.161266[/C][C]-1.2387[/C][C]0.11018[/C][/ROW]
[ROW][C]8[/C][C]-0.180675[/C][C]-1.3878[/C][C]0.08521[/C][/ROW]
[ROW][C]9[/C][C]-0.221488[/C][C]-1.7013[/C][C]0.047078[/C][/ROW]
[ROW][C]10[/C][C]-0.202225[/C][C]-1.5533[/C][C]0.062848[/C][/ROW]
[ROW][C]11[/C][C]-0.382796[/C][C]-2.9403[/C][C]0.002338[/C][/ROW]
[ROW][C]12[/C][C]0.199473[/C][C]1.5322[/C][C]0.065411[/C][/ROW]
[ROW][C]13[/C][C]-0.28777[/C][C]-2.2104[/C][C]0.015484[/C][/ROW]
[ROW][C]14[/C][C]-0.183936[/C][C]-1.4128[/C][C]0.081478[/C][/ROW]
[ROW][C]15[/C][C]-0.14939[/C][C]-1.1475[/C][C]0.127907[/C][/ROW]
[ROW][C]16[/C][C]0.035643[/C][C]0.2738[/C][C]0.392607[/C][/ROW]
[ROW][C]17[/C][C]-0.176255[/C][C]-1.3538[/C][C]0.090476[/C][/ROW]
[ROW][C]18[/C][C]-0.159657[/C][C]-1.2263[/C][C]0.11247[/C][/ROW]
[ROW][C]19[/C][C]0.003749[/C][C]0.0288[/C][C]0.488562[/C][/ROW]
[ROW][C]20[/C][C]-0.100914[/C][C]-0.7751[/C][C]0.220678[/C][/ROW]
[ROW][C]21[/C][C]-0.060572[/C][C]-0.4653[/C][C]0.321727[/C][/ROW]
[ROW][C]22[/C][C]-0.013721[/C][C]-0.1054[/C][C]0.458209[/C][/ROW]
[ROW][C]23[/C][C]0.004615[/C][C]0.0354[/C][C]0.485922[/C][/ROW]
[ROW][C]24[/C][C]-0.068633[/C][C]-0.5272[/C][C]0.300024[/C][/ROW]
[ROW][C]25[/C][C]0.092524[/C][C]0.7107[/C][C]0.240038[/C][/ROW]
[ROW][C]26[/C][C]0.011311[/C][C]0.0869[/C][C]0.465531[/C][/ROW]
[ROW][C]27[/C][C]-0.049246[/C][C]-0.3783[/C][C]0.353296[/C][/ROW]
[ROW][C]28[/C][C]-0.065704[/C][C]-0.5047[/C][C]0.307832[/C][/ROW]
[ROW][C]29[/C][C]0.064454[/C][C]0.4951[/C][C]0.311191[/C][/ROW]
[ROW][C]30[/C][C]-0.161424[/C][C]-1.2399[/C][C]0.109957[/C][/ROW]
[ROW][C]31[/C][C]0.010357[/C][C]0.0796[/C][C]0.468432[/C][/ROW]
[ROW][C]32[/C][C]-0.057428[/C][C]-0.4411[/C][C]0.330372[/C][/ROW]
[ROW][C]33[/C][C]-0.047482[/C][C]-0.3647[/C][C]0.358313[/C][/ROW]
[ROW][C]34[/C][C]-0.090112[/C][C]-0.6922[/C][C]0.245775[/C][/ROW]
[ROW][C]35[/C][C]-0.118769[/C][C]-0.9123[/C][C]0.182666[/C][/ROW]
[ROW][C]36[/C][C]0.128949[/C][C]0.9905[/C][C]0.162993[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28677&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28677&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
1-0.027941-0.21460.415402
2-0.177931-1.36670.08845
3-0.426842-3.27860.000876
4-0.434852-3.34020.000728
5-0.329073-2.52770.007091
6-0.077598-0.5960.276714
7-0.161266-1.23870.11018
8-0.180675-1.38780.08521
9-0.221488-1.70130.047078
10-0.202225-1.55330.062848
11-0.382796-2.94030.002338
120.1994731.53220.065411
13-0.28777-2.21040.015484
14-0.183936-1.41280.081478
15-0.14939-1.14750.127907
160.0356430.27380.392607
17-0.176255-1.35380.090476
18-0.159657-1.22630.11247
190.0037490.02880.488562
20-0.100914-0.77510.220678
21-0.060572-0.46530.321727
22-0.013721-0.10540.458209
230.0046150.03540.485922
24-0.068633-0.52720.300024
250.0925240.71070.240038
260.0113110.08690.465531
27-0.049246-0.37830.353296
28-0.065704-0.50470.307832
290.0644540.49510.311191
30-0.161424-1.23990.109957
310.0103570.07960.468432
32-0.057428-0.44110.330372
33-0.047482-0.36470.358313
34-0.090112-0.69220.245775
35-0.118769-0.91230.182666
360.1289490.99050.162993


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 0 ; 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')