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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, 02 Dec 2009 14:09:56 -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/Dec/02/t1259788266gbsvy263o14p9u7.htm/, Retrieved Sun, 28 Apr 2024 14:55:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62590, Retrieved Sun, 28 Apr 2024 14:55:33 +0000
QR Codes:

Original text written by user:WS 9 Estimation of Box-Jenkins ARIMA models
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact161

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 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [WS 8 Identifying ...] [2009-11-24 19:14:07] [101f710c1bf3d900563184d79f7da6e1]
-   PD          [(Partial) Autocorrelation Function] [WS 8 Identifying ...] [2009-11-24 19:25:42] [101f710c1bf3d900563184d79f7da6e1]
-   P             [(Partial) Autocorrelation Function] [WS 8 Identifying ...] [2009-11-24 19:34:58] [101f710c1bf3d900563184d79f7da6e1]
-   P                 [(Partial) Autocorrelation Function] [WS 9 Estimation o...] [2009-12-02 21:09:56] [9b6f46453e60f88d91cef176fe926003] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
14.5
14.3
15.3
14.4
13.7
14.2
13.5
11.9
14.6
15.6
14.1
14.9
14.2
14.6
17.2
15.4
14.3
17.5
14.5
14.4
16.6
16.7
16.6
16.9
15.7
16.4
18.4
16.9
16.5
18.3
15.1
15.7
18.1
16.8
18.9
19
18.1
17.8
21.5
17.1
18.7
19
16.4
16.9
18.6
19.3
19.4
17.6
18.6
18.1
20.4
18.1
19.6
19.9
19.2
17.8
19.2
22
21.1
19.5
22.2
20.9
22.2
23.5
21.5
24.3
22.8
20.3
23.7
23.3
19.6
18
17.3
16.8
18.2
16.5
16
18.4

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=62590&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=62590&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62590&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
1-0.487956-3.9340.000103
20.0331910.26760.394929
30.3666322.95590.00217
4-0.290064-2.33860.011222
50.0560060.45150.326553
60.2390931.92760.029136
7-0.36066-2.90770.002488
80.1605541.29440.100049
90.1026630.82770.205436
10-0.245918-1.98270.025818
110.17821.43670.0778
12-0.077174-0.62220.267995
13-0.16504-1.33060.093985
140.1944751.56790.060879
15-0.031894-0.25710.398941
16-0.207681-1.67440.049431
170.2234761.80170.038113
18-0.070977-0.57220.284567
19-0.123466-0.99540.161613
200.1364971.10050.137592
21-0.034399-0.27730.391201
22-0.191316-1.54240.06391
230.3570322.87850.002701
24-0.287964-2.32160.011699
250.0807540.65110.258652
260.161591.30280.098623
27-0.189654-1.5290.065553
280.0374860.30220.381725
290.1595651.28650.101424
30-0.229497-1.85030.034411
310.1176320.94840.173225
320.0597540.48170.315801
33-0.118563-0.95590.171335
340.0322210.25980.39793
350.0579740.46740.320888
36-0.105921-0.8540.198132

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.487956 & -3.934 & 0.000103 \tabularnewline
2 & 0.033191 & 0.2676 & 0.394929 \tabularnewline
3 & 0.366632 & 2.9559 & 0.00217 \tabularnewline
4 & -0.290064 & -2.3386 & 0.011222 \tabularnewline
5 & 0.056006 & 0.4515 & 0.326553 \tabularnewline
6 & 0.239093 & 1.9276 & 0.029136 \tabularnewline
7 & -0.36066 & -2.9077 & 0.002488 \tabularnewline
8 & 0.160554 & 1.2944 & 0.100049 \tabularnewline
9 & 0.102663 & 0.8277 & 0.205436 \tabularnewline
10 & -0.245918 & -1.9827 & 0.025818 \tabularnewline
11 & 0.1782 & 1.4367 & 0.0778 \tabularnewline
12 & -0.077174 & -0.6222 & 0.267995 \tabularnewline
13 & -0.16504 & -1.3306 & 0.093985 \tabularnewline
14 & 0.194475 & 1.5679 & 0.060879 \tabularnewline
15 & -0.031894 & -0.2571 & 0.398941 \tabularnewline
16 & -0.207681 & -1.6744 & 0.049431 \tabularnewline
17 & 0.223476 & 1.8017 & 0.038113 \tabularnewline
18 & -0.070977 & -0.5722 & 0.284567 \tabularnewline
19 & -0.123466 & -0.9954 & 0.161613 \tabularnewline
20 & 0.136497 & 1.1005 & 0.137592 \tabularnewline
21 & -0.034399 & -0.2773 & 0.391201 \tabularnewline
22 & -0.191316 & -1.5424 & 0.06391 \tabularnewline
23 & 0.357032 & 2.8785 & 0.002701 \tabularnewline
24 & -0.287964 & -2.3216 & 0.011699 \tabularnewline
25 & 0.080754 & 0.6511 & 0.258652 \tabularnewline
26 & 0.16159 & 1.3028 & 0.098623 \tabularnewline
27 & -0.189654 & -1.529 & 0.065553 \tabularnewline
28 & 0.037486 & 0.3022 & 0.381725 \tabularnewline
29 & 0.159565 & 1.2865 & 0.101424 \tabularnewline
30 & -0.229497 & -1.8503 & 0.034411 \tabularnewline
31 & 0.117632 & 0.9484 & 0.173225 \tabularnewline
32 & 0.059754 & 0.4817 & 0.315801 \tabularnewline
33 & -0.118563 & -0.9559 & 0.171335 \tabularnewline
34 & 0.032221 & 0.2598 & 0.39793 \tabularnewline
35 & 0.057974 & 0.4674 & 0.320888 \tabularnewline
36 & -0.105921 & -0.854 & 0.198132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62590&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]-0.487956[/C][C]-3.934[/C][C]0.000103[/C][/ROW]
[ROW][C]2[/C][C]0.033191[/C][C]0.2676[/C][C]0.394929[/C][/ROW]
[ROW][C]3[/C][C]0.366632[/C][C]2.9559[/C][C]0.00217[/C][/ROW]
[ROW][C]4[/C][C]-0.290064[/C][C]-2.3386[/C][C]0.011222[/C][/ROW]
[ROW][C]5[/C][C]0.056006[/C][C]0.4515[/C][C]0.326553[/C][/ROW]
[ROW][C]6[/C][C]0.239093[/C][C]1.9276[/C][C]0.029136[/C][/ROW]
[ROW][C]7[/C][C]-0.36066[/C][C]-2.9077[/C][C]0.002488[/C][/ROW]
[ROW][C]8[/C][C]0.160554[/C][C]1.2944[/C][C]0.100049[/C][/ROW]
[ROW][C]9[/C][C]0.102663[/C][C]0.8277[/C][C]0.205436[/C][/ROW]
[ROW][C]10[/C][C]-0.245918[/C][C]-1.9827[/C][C]0.025818[/C][/ROW]
[ROW][C]11[/C][C]0.1782[/C][C]1.4367[/C][C]0.0778[/C][/ROW]
[ROW][C]12[/C][C]-0.077174[/C][C]-0.6222[/C][C]0.267995[/C][/ROW]
[ROW][C]13[/C][C]-0.16504[/C][C]-1.3306[/C][C]0.093985[/C][/ROW]
[ROW][C]14[/C][C]0.194475[/C][C]1.5679[/C][C]0.060879[/C][/ROW]
[ROW][C]15[/C][C]-0.031894[/C][C]-0.2571[/C][C]0.398941[/C][/ROW]
[ROW][C]16[/C][C]-0.207681[/C][C]-1.6744[/C][C]0.049431[/C][/ROW]
[ROW][C]17[/C][C]0.223476[/C][C]1.8017[/C][C]0.038113[/C][/ROW]
[ROW][C]18[/C][C]-0.070977[/C][C]-0.5722[/C][C]0.284567[/C][/ROW]
[ROW][C]19[/C][C]-0.123466[/C][C]-0.9954[/C][C]0.161613[/C][/ROW]
[ROW][C]20[/C][C]0.136497[/C][C]1.1005[/C][C]0.137592[/C][/ROW]
[ROW][C]21[/C][C]-0.034399[/C][C]-0.2773[/C][C]0.391201[/C][/ROW]
[ROW][C]22[/C][C]-0.191316[/C][C]-1.5424[/C][C]0.06391[/C][/ROW]
[ROW][C]23[/C][C]0.357032[/C][C]2.8785[/C][C]0.002701[/C][/ROW]
[ROW][C]24[/C][C]-0.287964[/C][C]-2.3216[/C][C]0.011699[/C][/ROW]
[ROW][C]25[/C][C]0.080754[/C][C]0.6511[/C][C]0.258652[/C][/ROW]
[ROW][C]26[/C][C]0.16159[/C][C]1.3028[/C][C]0.098623[/C][/ROW]
[ROW][C]27[/C][C]-0.189654[/C][C]-1.529[/C][C]0.065553[/C][/ROW]
[ROW][C]28[/C][C]0.037486[/C][C]0.3022[/C][C]0.381725[/C][/ROW]
[ROW][C]29[/C][C]0.159565[/C][C]1.2865[/C][C]0.101424[/C][/ROW]
[ROW][C]30[/C][C]-0.229497[/C][C]-1.8503[/C][C]0.034411[/C][/ROW]
[ROW][C]31[/C][C]0.117632[/C][C]0.9484[/C][C]0.173225[/C][/ROW]
[ROW][C]32[/C][C]0.059754[/C][C]0.4817[/C][C]0.315801[/C][/ROW]
[ROW][C]33[/C][C]-0.118563[/C][C]-0.9559[/C][C]0.171335[/C][/ROW]
[ROW][C]34[/C][C]0.032221[/C][C]0.2598[/C][C]0.39793[/C][/ROW]
[ROW][C]35[/C][C]0.057974[/C][C]0.4674[/C][C]0.320888[/C][/ROW]
[ROW][C]36[/C][C]-0.105921[/C][C]-0.854[/C][C]0.198132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62590&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62590&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
1-0.487956-3.9340.000103
20.0331910.26760.394929
30.3666322.95590.00217
4-0.290064-2.33860.011222
50.0560060.45150.326553
60.2390931.92760.029136
7-0.36066-2.90770.002488
80.1605541.29440.100049
90.1026630.82770.205436
10-0.245918-1.98270.025818
110.17821.43670.0778
12-0.077174-0.62220.267995
13-0.16504-1.33060.093985
140.1944751.56790.060879
15-0.031894-0.25710.398941
16-0.207681-1.67440.049431
170.2234761.80170.038113
18-0.070977-0.57220.284567
19-0.123466-0.99540.161613
200.1364971.10050.137592
21-0.034399-0.27730.391201
22-0.191316-1.54240.06391
230.3570322.87850.002701
24-0.287964-2.32160.011699
250.0807540.65110.258652
260.161591.30280.098623
27-0.189654-1.5290.065553
280.0374860.30220.381725
290.1595651.28650.101424
30-0.229497-1.85030.034411
310.1176320.94840.173225
320.0597540.48170.315801
33-0.118563-0.95590.171335
340.0322210.25980.39793
350.0579740.46740.320888
36-0.105921-0.8540.198132






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.487956-3.9340.000103
2-0.268946-2.16830.016901
30.3621312.91960.002406
40.1293461.04280.150448
5-0.075857-0.61160.271475
60.1203350.97020.167779
7-0.156019-1.25790.106471
8-0.137445-1.10810.135948
90.0453440.36560.357934
100.0398740.32150.37444
110.0317910.25630.399261
12-0.125526-1.0120.15764
13-0.188016-1.51580.067205
14-0.048394-0.39020.348844
150.1925821.55260.062681
16-0.028262-0.22790.410237
17-0.072519-0.58470.280398
180.03370.27170.393356
19-0.062177-0.50130.308931
20-0.166337-1.34110.092286
210.071010.57250.28448
22-0.060228-0.48560.314451
230.2084811.68080.048798
24-0.082103-0.66190.255177
25-0.015783-0.12720.449569
260.0252710.20370.419597
270.0593490.47850.316954
28-0.11452-0.92330.179636
29-0.032391-0.26110.397405
300.0824360.66460.254321
31-0.016886-0.13610.446066
32-0.112313-0.90550.184273
330.1238320.99840.160902
34-0.067024-0.54040.295397
35-0.038836-0.31310.377602
36-0.019216-0.15490.43868

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.487956 & -3.934 & 0.000103 \tabularnewline
2 & -0.268946 & -2.1683 & 0.016901 \tabularnewline
3 & 0.362131 & 2.9196 & 0.002406 \tabularnewline
4 & 0.129346 & 1.0428 & 0.150448 \tabularnewline
5 & -0.075857 & -0.6116 & 0.271475 \tabularnewline
6 & 0.120335 & 0.9702 & 0.167779 \tabularnewline
7 & -0.156019 & -1.2579 & 0.106471 \tabularnewline
8 & -0.137445 & -1.1081 & 0.135948 \tabularnewline
9 & 0.045344 & 0.3656 & 0.357934 \tabularnewline
10 & 0.039874 & 0.3215 & 0.37444 \tabularnewline
11 & 0.031791 & 0.2563 & 0.399261 \tabularnewline
12 & -0.125526 & -1.012 & 0.15764 \tabularnewline
13 & -0.188016 & -1.5158 & 0.067205 \tabularnewline
14 & -0.048394 & -0.3902 & 0.348844 \tabularnewline
15 & 0.192582 & 1.5526 & 0.062681 \tabularnewline
16 & -0.028262 & -0.2279 & 0.410237 \tabularnewline
17 & -0.072519 & -0.5847 & 0.280398 \tabularnewline
18 & 0.0337 & 0.2717 & 0.393356 \tabularnewline
19 & -0.062177 & -0.5013 & 0.308931 \tabularnewline
20 & -0.166337 & -1.3411 & 0.092286 \tabularnewline
21 & 0.07101 & 0.5725 & 0.28448 \tabularnewline
22 & -0.060228 & -0.4856 & 0.314451 \tabularnewline
23 & 0.208481 & 1.6808 & 0.048798 \tabularnewline
24 & -0.082103 & -0.6619 & 0.255177 \tabularnewline
25 & -0.015783 & -0.1272 & 0.449569 \tabularnewline
26 & 0.025271 & 0.2037 & 0.419597 \tabularnewline
27 & 0.059349 & 0.4785 & 0.316954 \tabularnewline
28 & -0.11452 & -0.9233 & 0.179636 \tabularnewline
29 & -0.032391 & -0.2611 & 0.397405 \tabularnewline
30 & 0.082436 & 0.6646 & 0.254321 \tabularnewline
31 & -0.016886 & -0.1361 & 0.446066 \tabularnewline
32 & -0.112313 & -0.9055 & 0.184273 \tabularnewline
33 & 0.123832 & 0.9984 & 0.160902 \tabularnewline
34 & -0.067024 & -0.5404 & 0.295397 \tabularnewline
35 & -0.038836 & -0.3131 & 0.377602 \tabularnewline
36 & -0.019216 & -0.1549 & 0.43868 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62590&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]-0.487956[/C][C]-3.934[/C][C]0.000103[/C][/ROW]
[ROW][C]2[/C][C]-0.268946[/C][C]-2.1683[/C][C]0.016901[/C][/ROW]
[ROW][C]3[/C][C]0.362131[/C][C]2.9196[/C][C]0.002406[/C][/ROW]
[ROW][C]4[/C][C]0.129346[/C][C]1.0428[/C][C]0.150448[/C][/ROW]
[ROW][C]5[/C][C]-0.075857[/C][C]-0.6116[/C][C]0.271475[/C][/ROW]
[ROW][C]6[/C][C]0.120335[/C][C]0.9702[/C][C]0.167779[/C][/ROW]
[ROW][C]7[/C][C]-0.156019[/C][C]-1.2579[/C][C]0.106471[/C][/ROW]
[ROW][C]8[/C][C]-0.137445[/C][C]-1.1081[/C][C]0.135948[/C][/ROW]
[ROW][C]9[/C][C]0.045344[/C][C]0.3656[/C][C]0.357934[/C][/ROW]
[ROW][C]10[/C][C]0.039874[/C][C]0.3215[/C][C]0.37444[/C][/ROW]
[ROW][C]11[/C][C]0.031791[/C][C]0.2563[/C][C]0.399261[/C][/ROW]
[ROW][C]12[/C][C]-0.125526[/C][C]-1.012[/C][C]0.15764[/C][/ROW]
[ROW][C]13[/C][C]-0.188016[/C][C]-1.5158[/C][C]0.067205[/C][/ROW]
[ROW][C]14[/C][C]-0.048394[/C][C]-0.3902[/C][C]0.348844[/C][/ROW]
[ROW][C]15[/C][C]0.192582[/C][C]1.5526[/C][C]0.062681[/C][/ROW]
[ROW][C]16[/C][C]-0.028262[/C][C]-0.2279[/C][C]0.410237[/C][/ROW]
[ROW][C]17[/C][C]-0.072519[/C][C]-0.5847[/C][C]0.280398[/C][/ROW]
[ROW][C]18[/C][C]0.0337[/C][C]0.2717[/C][C]0.393356[/C][/ROW]
[ROW][C]19[/C][C]-0.062177[/C][C]-0.5013[/C][C]0.308931[/C][/ROW]
[ROW][C]20[/C][C]-0.166337[/C][C]-1.3411[/C][C]0.092286[/C][/ROW]
[ROW][C]21[/C][C]0.07101[/C][C]0.5725[/C][C]0.28448[/C][/ROW]
[ROW][C]22[/C][C]-0.060228[/C][C]-0.4856[/C][C]0.314451[/C][/ROW]
[ROW][C]23[/C][C]0.208481[/C][C]1.6808[/C][C]0.048798[/C][/ROW]
[ROW][C]24[/C][C]-0.082103[/C][C]-0.6619[/C][C]0.255177[/C][/ROW]
[ROW][C]25[/C][C]-0.015783[/C][C]-0.1272[/C][C]0.449569[/C][/ROW]
[ROW][C]26[/C][C]0.025271[/C][C]0.2037[/C][C]0.419597[/C][/ROW]
[ROW][C]27[/C][C]0.059349[/C][C]0.4785[/C][C]0.316954[/C][/ROW]
[ROW][C]28[/C][C]-0.11452[/C][C]-0.9233[/C][C]0.179636[/C][/ROW]
[ROW][C]29[/C][C]-0.032391[/C][C]-0.2611[/C][C]0.397405[/C][/ROW]
[ROW][C]30[/C][C]0.082436[/C][C]0.6646[/C][C]0.254321[/C][/ROW]
[ROW][C]31[/C][C]-0.016886[/C][C]-0.1361[/C][C]0.446066[/C][/ROW]
[ROW][C]32[/C][C]-0.112313[/C][C]-0.9055[/C][C]0.184273[/C][/ROW]
[ROW][C]33[/C][C]0.123832[/C][C]0.9984[/C][C]0.160902[/C][/ROW]
[ROW][C]34[/C][C]-0.067024[/C][C]-0.5404[/C][C]0.295397[/C][/ROW]
[ROW][C]35[/C][C]-0.038836[/C][C]-0.3131[/C][C]0.377602[/C][/ROW]
[ROW][C]36[/C][C]-0.019216[/C][C]-0.1549[/C][C]0.43868[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62590&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62590&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
1-0.487956-3.9340.000103
2-0.268946-2.16830.016901
30.3621312.91960.002406
40.1293461.04280.150448
5-0.075857-0.61160.271475
60.1203350.97020.167779
7-0.156019-1.25790.106471
8-0.137445-1.10810.135948
90.0453440.36560.357934
100.0398740.32150.37444
110.0317910.25630.399261
12-0.125526-1.0120.15764
13-0.188016-1.51580.067205
14-0.048394-0.39020.348844
150.1925821.55260.062681
16-0.028262-0.22790.410237
17-0.072519-0.58470.280398
180.03370.27170.393356
19-0.062177-0.50130.308931
20-0.166337-1.34110.092286
210.071010.57250.28448
22-0.060228-0.48560.314451
230.2084811.68080.048798
24-0.082103-0.66190.255177
25-0.015783-0.12720.449569
260.0252710.20370.419597
270.0593490.47850.316954
28-0.11452-0.92330.179636
29-0.032391-0.26110.397405
300.0824360.66460.254321
31-0.016886-0.13610.446066
32-0.112313-0.90550.184273
330.1238320.99840.160902
34-0.067024-0.54040.295397
35-0.038836-0.31310.377602
36-0.019216-0.15490.43868


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = -0.2 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = -0.2 ; 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')