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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 computationThu, 03 Dec 2009 16:21:39 -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/04/t1259883008xptshxne8iungn3.htm/, Retrieved Sun, 28 Apr 2024 10:44:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63150, Retrieved Sun, 28 Apr 2024 10:44:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsworkshop8verbeteringen
Estimated Impact143

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 12:26:39] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [Ws8.3ACF3] [2009-11-25 19:50:41] [e0fc65a5811681d807296d590d5b45de]
-   P             [(Partial) Autocorrelation Function] [Workshop 8] [2009-12-03 23:21:39] [682632737e024f9e62885141c5f654cd] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
58608
46865
51378
46235
47206
45382
41227
33795
31295
42625
33625
21538
56421
53152
53536
52408
41454
38271
35306
26414
31917
38030
27534
18387
50556
43901
48572
43899
37532
40357
35489
29027
34485
42598
30306
26451
47460
50104
61465
53726
39477
43895
31481
29896
33842
39120
33702
25094
51442
45594
52518
48564
41745
49585
32747
33379
35645
37034
35681
20972

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=63150&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=63150&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63150&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
1-0.270467-1.60010.059282
20.0851650.50380.308763
3-0.273118-1.61580.05756
40.0018490.01090.495667
50.0603260.35690.361658
6-0.035104-0.20770.418343
7-0.037256-0.22040.413417
8-0.0418-0.24730.403064
90.2762381.63420.055586
10-0.093185-0.55130.292469
110.0743980.44010.331269
12-0.417867-2.47210.009219
130.0413560.24470.404072
14-0.063911-0.37810.353819
150.2431581.43850.079581
16-0.190678-1.12810.133483
170.134570.79610.215662
180.0258660.1530.439628
19-0.010822-0.0640.474659
200.112190.66370.255608
21-0.277611-1.64240.054735
220.0737330.43620.332681
23-0.001618-0.00960.496208
240.1252560.7410.231811
250.0507070.30.382981
260.0306620.18140.428551
27-0.095958-0.56770.286934
280.0071590.04240.483229
29-0.038092-0.22540.411507
30-0.007575-0.04480.482255
31-0.003264-0.01930.492351
32-0.000217-0.00130.499492
330.009160.05420.478546
340.0067480.03990.484191
35NANANA
36NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.270467 & -1.6001 & 0.059282 \tabularnewline
2 & 0.085165 & 0.5038 & 0.308763 \tabularnewline
3 & -0.273118 & -1.6158 & 0.05756 \tabularnewline
4 & 0.001849 & 0.0109 & 0.495667 \tabularnewline
5 & 0.060326 & 0.3569 & 0.361658 \tabularnewline
6 & -0.035104 & -0.2077 & 0.418343 \tabularnewline
7 & -0.037256 & -0.2204 & 0.413417 \tabularnewline
8 & -0.0418 & -0.2473 & 0.403064 \tabularnewline
9 & 0.276238 & 1.6342 & 0.055586 \tabularnewline
10 & -0.093185 & -0.5513 & 0.292469 \tabularnewline
11 & 0.074398 & 0.4401 & 0.331269 \tabularnewline
12 & -0.417867 & -2.4721 & 0.009219 \tabularnewline
13 & 0.041356 & 0.2447 & 0.404072 \tabularnewline
14 & -0.063911 & -0.3781 & 0.353819 \tabularnewline
15 & 0.243158 & 1.4385 & 0.079581 \tabularnewline
16 & -0.190678 & -1.1281 & 0.133483 \tabularnewline
17 & 0.13457 & 0.7961 & 0.215662 \tabularnewline
18 & 0.025866 & 0.153 & 0.439628 \tabularnewline
19 & -0.010822 & -0.064 & 0.474659 \tabularnewline
20 & 0.11219 & 0.6637 & 0.255608 \tabularnewline
21 & -0.277611 & -1.6424 & 0.054735 \tabularnewline
22 & 0.073733 & 0.4362 & 0.332681 \tabularnewline
23 & -0.001618 & -0.0096 & 0.496208 \tabularnewline
24 & 0.125256 & 0.741 & 0.231811 \tabularnewline
25 & 0.050707 & 0.3 & 0.382981 \tabularnewline
26 & 0.030662 & 0.1814 & 0.428551 \tabularnewline
27 & -0.095958 & -0.5677 & 0.286934 \tabularnewline
28 & 0.007159 & 0.0424 & 0.483229 \tabularnewline
29 & -0.038092 & -0.2254 & 0.411507 \tabularnewline
30 & -0.007575 & -0.0448 & 0.482255 \tabularnewline
31 & -0.003264 & -0.0193 & 0.492351 \tabularnewline
32 & -0.000217 & -0.0013 & 0.499492 \tabularnewline
33 & 0.00916 & 0.0542 & 0.478546 \tabularnewline
34 & 0.006748 & 0.0399 & 0.484191 \tabularnewline
35 & NA & NA & NA \tabularnewline
36 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63150&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]-0.270467[/C][C]-1.6001[/C][C]0.059282[/C][/ROW]
[ROW][C]2[/C][C]0.085165[/C][C]0.5038[/C][C]0.308763[/C][/ROW]
[ROW][C]3[/C][C]-0.273118[/C][C]-1.6158[/C][C]0.05756[/C][/ROW]
[ROW][C]4[/C][C]0.001849[/C][C]0.0109[/C][C]0.495667[/C][/ROW]
[ROW][C]5[/C][C]0.060326[/C][C]0.3569[/C][C]0.361658[/C][/ROW]
[ROW][C]6[/C][C]-0.035104[/C][C]-0.2077[/C][C]0.418343[/C][/ROW]
[ROW][C]7[/C][C]-0.037256[/C][C]-0.2204[/C][C]0.413417[/C][/ROW]
[ROW][C]8[/C][C]-0.0418[/C][C]-0.2473[/C][C]0.403064[/C][/ROW]
[ROW][C]9[/C][C]0.276238[/C][C]1.6342[/C][C]0.055586[/C][/ROW]
[ROW][C]10[/C][C]-0.093185[/C][C]-0.5513[/C][C]0.292469[/C][/ROW]
[ROW][C]11[/C][C]0.074398[/C][C]0.4401[/C][C]0.331269[/C][/ROW]
[ROW][C]12[/C][C]-0.417867[/C][C]-2.4721[/C][C]0.009219[/C][/ROW]
[ROW][C]13[/C][C]0.041356[/C][C]0.2447[/C][C]0.404072[/C][/ROW]
[ROW][C]14[/C][C]-0.063911[/C][C]-0.3781[/C][C]0.353819[/C][/ROW]
[ROW][C]15[/C][C]0.243158[/C][C]1.4385[/C][C]0.079581[/C][/ROW]
[ROW][C]16[/C][C]-0.190678[/C][C]-1.1281[/C][C]0.133483[/C][/ROW]
[ROW][C]17[/C][C]0.13457[/C][C]0.7961[/C][C]0.215662[/C][/ROW]
[ROW][C]18[/C][C]0.025866[/C][C]0.153[/C][C]0.439628[/C][/ROW]
[ROW][C]19[/C][C]-0.010822[/C][C]-0.064[/C][C]0.474659[/C][/ROW]
[ROW][C]20[/C][C]0.11219[/C][C]0.6637[/C][C]0.255608[/C][/ROW]
[ROW][C]21[/C][C]-0.277611[/C][C]-1.6424[/C][C]0.054735[/C][/ROW]
[ROW][C]22[/C][C]0.073733[/C][C]0.4362[/C][C]0.332681[/C][/ROW]
[ROW][C]23[/C][C]-0.001618[/C][C]-0.0096[/C][C]0.496208[/C][/ROW]
[ROW][C]24[/C][C]0.125256[/C][C]0.741[/C][C]0.231811[/C][/ROW]
[ROW][C]25[/C][C]0.050707[/C][C]0.3[/C][C]0.382981[/C][/ROW]
[ROW][C]26[/C][C]0.030662[/C][C]0.1814[/C][C]0.428551[/C][/ROW]
[ROW][C]27[/C][C]-0.095958[/C][C]-0.5677[/C][C]0.286934[/C][/ROW]
[ROW][C]28[/C][C]0.007159[/C][C]0.0424[/C][C]0.483229[/C][/ROW]
[ROW][C]29[/C][C]-0.038092[/C][C]-0.2254[/C][C]0.411507[/C][/ROW]
[ROW][C]30[/C][C]-0.007575[/C][C]-0.0448[/C][C]0.482255[/C][/ROW]
[ROW][C]31[/C][C]-0.003264[/C][C]-0.0193[/C][C]0.492351[/C][/ROW]
[ROW][C]32[/C][C]-0.000217[/C][C]-0.0013[/C][C]0.499492[/C][/ROW]
[ROW][C]33[/C][C]0.00916[/C][C]0.0542[/C][C]0.478546[/C][/ROW]
[ROW][C]34[/C][C]0.006748[/C][C]0.0399[/C][C]0.484191[/C][/ROW]
[ROW][C]35[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]36[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63150&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63150&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
1-0.270467-1.60010.059282
20.0851650.50380.308763
3-0.273118-1.61580.05756
40.0018490.01090.495667
50.0603260.35690.361658
6-0.035104-0.20770.418343
7-0.037256-0.22040.413417
8-0.0418-0.24730.403064
90.2762381.63420.055586
10-0.093185-0.55130.292469
110.0743980.44010.331269
12-0.417867-2.47210.009219
130.0413560.24470.404072
14-0.063911-0.37810.353819
150.2431581.43850.079581
16-0.190678-1.12810.133483
170.134570.79610.215662
180.0258660.1530.439628
19-0.010822-0.0640.474659
200.112190.66370.255608
21-0.277611-1.64240.054735
220.0737330.43620.332681
23-0.001618-0.00960.496208
240.1252560.7410.231811
250.0507070.30.382981
260.0306620.18140.428551
27-0.095958-0.56770.286934
280.0071590.04240.483229
29-0.038092-0.22540.411507
30-0.007575-0.04480.482255
31-0.003264-0.01930.492351
32-0.000217-0.00130.499492
330.009160.05420.478546
340.0067480.03990.484191
35NANANA
36NANANA






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.270467-1.60010.059282
20.0129610.07670.469658
3-0.266406-1.57610.062002
4-0.159388-0.9430.176084
50.0305480.18070.428812
6-0.094791-0.56080.289256
7-0.13366-0.79070.21721
8-0.074547-0.4410.330953
90.26531.56950.06276
100.0023970.01420.494382
110.027960.16540.434785
12-0.309733-1.83240.037705
13-0.190471-1.12680.133738
14-0.18668-1.10440.138474
150.0408050.24140.405324
16-0.266637-1.57740.061845
170.0002280.00130.499466
180.0578830.34240.367035
19-0.095607-0.56560.287632
200.0674070.39880.346237
21-0.020021-0.11840.453196
22-0.052037-0.30790.380008
230.0450570.26660.395687
24-0.144307-0.85370.19953
250.0358460.21210.416641
26-0.020959-0.1240.451015
27-0.027207-0.1610.436527
28-0.151685-0.89740.187824
29-0.052409-0.31010.379179
300.0427610.2530.400883
310.0139420.08250.467367
32-0.021284-0.12590.45026
33-0.078091-0.4620.323473
34-0.082421-0.48760.314434
35NANANA
36NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.270467 & -1.6001 & 0.059282 \tabularnewline
2 & 0.012961 & 0.0767 & 0.469658 \tabularnewline
3 & -0.266406 & -1.5761 & 0.062002 \tabularnewline
4 & -0.159388 & -0.943 & 0.176084 \tabularnewline
5 & 0.030548 & 0.1807 & 0.428812 \tabularnewline
6 & -0.094791 & -0.5608 & 0.289256 \tabularnewline
7 & -0.13366 & -0.7907 & 0.21721 \tabularnewline
8 & -0.074547 & -0.441 & 0.330953 \tabularnewline
9 & 0.2653 & 1.5695 & 0.06276 \tabularnewline
10 & 0.002397 & 0.0142 & 0.494382 \tabularnewline
11 & 0.02796 & 0.1654 & 0.434785 \tabularnewline
12 & -0.309733 & -1.8324 & 0.037705 \tabularnewline
13 & -0.190471 & -1.1268 & 0.133738 \tabularnewline
14 & -0.18668 & -1.1044 & 0.138474 \tabularnewline
15 & 0.040805 & 0.2414 & 0.405324 \tabularnewline
16 & -0.266637 & -1.5774 & 0.061845 \tabularnewline
17 & 0.000228 & 0.0013 & 0.499466 \tabularnewline
18 & 0.057883 & 0.3424 & 0.367035 \tabularnewline
19 & -0.095607 & -0.5656 & 0.287632 \tabularnewline
20 & 0.067407 & 0.3988 & 0.346237 \tabularnewline
21 & -0.020021 & -0.1184 & 0.453196 \tabularnewline
22 & -0.052037 & -0.3079 & 0.380008 \tabularnewline
23 & 0.045057 & 0.2666 & 0.395687 \tabularnewline
24 & -0.144307 & -0.8537 & 0.19953 \tabularnewline
25 & 0.035846 & 0.2121 & 0.416641 \tabularnewline
26 & -0.020959 & -0.124 & 0.451015 \tabularnewline
27 & -0.027207 & -0.161 & 0.436527 \tabularnewline
28 & -0.151685 & -0.8974 & 0.187824 \tabularnewline
29 & -0.052409 & -0.3101 & 0.379179 \tabularnewline
30 & 0.042761 & 0.253 & 0.400883 \tabularnewline
31 & 0.013942 & 0.0825 & 0.467367 \tabularnewline
32 & -0.021284 & -0.1259 & 0.45026 \tabularnewline
33 & -0.078091 & -0.462 & 0.323473 \tabularnewline
34 & -0.082421 & -0.4876 & 0.314434 \tabularnewline
35 & NA & NA & NA \tabularnewline
36 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63150&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]-0.270467[/C][C]-1.6001[/C][C]0.059282[/C][/ROW]
[ROW][C]2[/C][C]0.012961[/C][C]0.0767[/C][C]0.469658[/C][/ROW]
[ROW][C]3[/C][C]-0.266406[/C][C]-1.5761[/C][C]0.062002[/C][/ROW]
[ROW][C]4[/C][C]-0.159388[/C][C]-0.943[/C][C]0.176084[/C][/ROW]
[ROW][C]5[/C][C]0.030548[/C][C]0.1807[/C][C]0.428812[/C][/ROW]
[ROW][C]6[/C][C]-0.094791[/C][C]-0.5608[/C][C]0.289256[/C][/ROW]
[ROW][C]7[/C][C]-0.13366[/C][C]-0.7907[/C][C]0.21721[/C][/ROW]
[ROW][C]8[/C][C]-0.074547[/C][C]-0.441[/C][C]0.330953[/C][/ROW]
[ROW][C]9[/C][C]0.2653[/C][C]1.5695[/C][C]0.06276[/C][/ROW]
[ROW][C]10[/C][C]0.002397[/C][C]0.0142[/C][C]0.494382[/C][/ROW]
[ROW][C]11[/C][C]0.02796[/C][C]0.1654[/C][C]0.434785[/C][/ROW]
[ROW][C]12[/C][C]-0.309733[/C][C]-1.8324[/C][C]0.037705[/C][/ROW]
[ROW][C]13[/C][C]-0.190471[/C][C]-1.1268[/C][C]0.133738[/C][/ROW]
[ROW][C]14[/C][C]-0.18668[/C][C]-1.1044[/C][C]0.138474[/C][/ROW]
[ROW][C]15[/C][C]0.040805[/C][C]0.2414[/C][C]0.405324[/C][/ROW]
[ROW][C]16[/C][C]-0.266637[/C][C]-1.5774[/C][C]0.061845[/C][/ROW]
[ROW][C]17[/C][C]0.000228[/C][C]0.0013[/C][C]0.499466[/C][/ROW]
[ROW][C]18[/C][C]0.057883[/C][C]0.3424[/C][C]0.367035[/C][/ROW]
[ROW][C]19[/C][C]-0.095607[/C][C]-0.5656[/C][C]0.287632[/C][/ROW]
[ROW][C]20[/C][C]0.067407[/C][C]0.3988[/C][C]0.346237[/C][/ROW]
[ROW][C]21[/C][C]-0.020021[/C][C]-0.1184[/C][C]0.453196[/C][/ROW]
[ROW][C]22[/C][C]-0.052037[/C][C]-0.3079[/C][C]0.380008[/C][/ROW]
[ROW][C]23[/C][C]0.045057[/C][C]0.2666[/C][C]0.395687[/C][/ROW]
[ROW][C]24[/C][C]-0.144307[/C][C]-0.8537[/C][C]0.19953[/C][/ROW]
[ROW][C]25[/C][C]0.035846[/C][C]0.2121[/C][C]0.416641[/C][/ROW]
[ROW][C]26[/C][C]-0.020959[/C][C]-0.124[/C][C]0.451015[/C][/ROW]
[ROW][C]27[/C][C]-0.027207[/C][C]-0.161[/C][C]0.436527[/C][/ROW]
[ROW][C]28[/C][C]-0.151685[/C][C]-0.8974[/C][C]0.187824[/C][/ROW]
[ROW][C]29[/C][C]-0.052409[/C][C]-0.3101[/C][C]0.379179[/C][/ROW]
[ROW][C]30[/C][C]0.042761[/C][C]0.253[/C][C]0.400883[/C][/ROW]
[ROW][C]31[/C][C]0.013942[/C][C]0.0825[/C][C]0.467367[/C][/ROW]
[ROW][C]32[/C][C]-0.021284[/C][C]-0.1259[/C][C]0.45026[/C][/ROW]
[ROW][C]33[/C][C]-0.078091[/C][C]-0.462[/C][C]0.323473[/C][/ROW]
[ROW][C]34[/C][C]-0.082421[/C][C]-0.4876[/C][C]0.314434[/C][/ROW]
[ROW][C]35[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]36[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63150&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63150&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
1-0.270467-1.60010.059282
20.0129610.07670.469658
3-0.266406-1.57610.062002
4-0.159388-0.9430.176084
50.0305480.18070.428812
6-0.094791-0.56080.289256
7-0.13366-0.79070.21721
8-0.074547-0.4410.330953
90.26531.56950.06276
100.0023970.01420.494382
110.027960.16540.434785
12-0.309733-1.83240.037705
13-0.190471-1.12680.133738
14-0.18668-1.10440.138474
150.0408050.24140.405324
16-0.266637-1.57740.061845
170.0002280.00130.499466
180.0578830.34240.367035
19-0.095607-0.56560.287632
200.0674070.39880.346237
21-0.020021-0.11840.453196
22-0.052037-0.30790.380008
230.0450570.26660.395687
24-0.144307-0.85370.19953
250.0358460.21210.416641
26-0.020959-0.1240.451015
27-0.027207-0.1610.436527
28-0.151685-0.89740.187824
29-0.052409-0.31010.379179
300.0427610.2530.400883
310.0139420.08250.467367
32-0.021284-0.12590.45026
33-0.078091-0.4620.323473
34-0.082421-0.48760.314434
35NANANA
36NANANA


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 2 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 2 ; 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')