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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 computationFri, 27 Nov 2009 09:20:28 -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/Nov/27/t1259338858bpvb06rk262h1gs.htm/, Retrieved Mon, 29 Apr 2024 07:01:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60950, Retrieved Mon, 29 Apr 2024 07:01:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact128

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]
-   PD          [(Partial) Autocorrelation Function] [WS8: acf 2] [2009-11-27 16:20:28] [b090d569c0a4c77894e0b029f4429f19] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
13.4
14
14.7
16.1
16.3
16.1
16.5
19
18.7
17.7
17.2
16.6
17.4
15.5
12.4
11.1
11.1
13.7
12.1
11.3
9.9
10.9
13.2
14.2
16.8
17
19.6
18.3
20.6
17.7
19.6
17.4
17.6
19
17.8
17
15.7
16
17.1
17
15.7
15.6
16.1
17.4
16
15
14.3
14.5
14.3
16.2
14.8
16.3
14
15.4
13.4
12.9
14.3
11.9
8.6
5.5
0.8

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=60950&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=60950&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60950&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
10.0447150.34640.365141
20.2840182.20.015835
3-0.145409-1.12630.132255
40.1073250.83130.20454
50.1589321.23110.111548
60.0367680.28480.388388
7-0.109339-0.84690.200198
8-0.122631-0.94990.172988
9-0.049338-0.38220.351842
10-0.048633-0.37670.353859
11-0.081141-0.62850.266026
12-0.184071-1.42580.079553
13-0.006468-0.05010.480104
14-0.001572-0.01220.495163
150.063430.49130.312494
160.0848780.65750.2567
17-0.027329-0.21170.416534
180.0218750.16940.433008
190.0404830.31360.377465
20-0.018091-0.14010.444513
210.2139061.65690.051379
22-0.135596-1.05030.148891
230.1952851.51270.067806
24-0.127738-0.98950.163207
250.1445161.11940.133713
260.0598280.46340.322367
270.0109880.08510.466229
28-0.086407-0.66930.252934
29-0.026655-0.20650.418562
30-0.02143-0.1660.434358
310.0473610.36690.357508
32-0.040033-0.31010.378782
33-0.152209-1.1790.121525
34-0.105852-0.81990.207752
35-0.140294-1.08670.140755
36-0.103998-0.80560.211838

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.044715 & 0.3464 & 0.365141 \tabularnewline
2 & 0.284018 & 2.2 & 0.015835 \tabularnewline
3 & -0.145409 & -1.1263 & 0.132255 \tabularnewline
4 & 0.107325 & 0.8313 & 0.20454 \tabularnewline
5 & 0.158932 & 1.2311 & 0.111548 \tabularnewline
6 & 0.036768 & 0.2848 & 0.388388 \tabularnewline
7 & -0.109339 & -0.8469 & 0.200198 \tabularnewline
8 & -0.122631 & -0.9499 & 0.172988 \tabularnewline
9 & -0.049338 & -0.3822 & 0.351842 \tabularnewline
10 & -0.048633 & -0.3767 & 0.353859 \tabularnewline
11 & -0.081141 & -0.6285 & 0.266026 \tabularnewline
12 & -0.184071 & -1.4258 & 0.079553 \tabularnewline
13 & -0.006468 & -0.0501 & 0.480104 \tabularnewline
14 & -0.001572 & -0.0122 & 0.495163 \tabularnewline
15 & 0.06343 & 0.4913 & 0.312494 \tabularnewline
16 & 0.084878 & 0.6575 & 0.2567 \tabularnewline
17 & -0.027329 & -0.2117 & 0.416534 \tabularnewline
18 & 0.021875 & 0.1694 & 0.433008 \tabularnewline
19 & 0.040483 & 0.3136 & 0.377465 \tabularnewline
20 & -0.018091 & -0.1401 & 0.444513 \tabularnewline
21 & 0.213906 & 1.6569 & 0.051379 \tabularnewline
22 & -0.135596 & -1.0503 & 0.148891 \tabularnewline
23 & 0.195285 & 1.5127 & 0.067806 \tabularnewline
24 & -0.127738 & -0.9895 & 0.163207 \tabularnewline
25 & 0.144516 & 1.1194 & 0.133713 \tabularnewline
26 & 0.059828 & 0.4634 & 0.322367 \tabularnewline
27 & 0.010988 & 0.0851 & 0.466229 \tabularnewline
28 & -0.086407 & -0.6693 & 0.252934 \tabularnewline
29 & -0.026655 & -0.2065 & 0.418562 \tabularnewline
30 & -0.02143 & -0.166 & 0.434358 \tabularnewline
31 & 0.047361 & 0.3669 & 0.357508 \tabularnewline
32 & -0.040033 & -0.3101 & 0.378782 \tabularnewline
33 & -0.152209 & -1.179 & 0.121525 \tabularnewline
34 & -0.105852 & -0.8199 & 0.207752 \tabularnewline
35 & -0.140294 & -1.0867 & 0.140755 \tabularnewline
36 & -0.103998 & -0.8056 & 0.211838 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60950&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]0.044715[/C][C]0.3464[/C][C]0.365141[/C][/ROW]
[ROW][C]2[/C][C]0.284018[/C][C]2.2[/C][C]0.015835[/C][/ROW]
[ROW][C]3[/C][C]-0.145409[/C][C]-1.1263[/C][C]0.132255[/C][/ROW]
[ROW][C]4[/C][C]0.107325[/C][C]0.8313[/C][C]0.20454[/C][/ROW]
[ROW][C]5[/C][C]0.158932[/C][C]1.2311[/C][C]0.111548[/C][/ROW]
[ROW][C]6[/C][C]0.036768[/C][C]0.2848[/C][C]0.388388[/C][/ROW]
[ROW][C]7[/C][C]-0.109339[/C][C]-0.8469[/C][C]0.200198[/C][/ROW]
[ROW][C]8[/C][C]-0.122631[/C][C]-0.9499[/C][C]0.172988[/C][/ROW]
[ROW][C]9[/C][C]-0.049338[/C][C]-0.3822[/C][C]0.351842[/C][/ROW]
[ROW][C]10[/C][C]-0.048633[/C][C]-0.3767[/C][C]0.353859[/C][/ROW]
[ROW][C]11[/C][C]-0.081141[/C][C]-0.6285[/C][C]0.266026[/C][/ROW]
[ROW][C]12[/C][C]-0.184071[/C][C]-1.4258[/C][C]0.079553[/C][/ROW]
[ROW][C]13[/C][C]-0.006468[/C][C]-0.0501[/C][C]0.480104[/C][/ROW]
[ROW][C]14[/C][C]-0.001572[/C][C]-0.0122[/C][C]0.495163[/C][/ROW]
[ROW][C]15[/C][C]0.06343[/C][C]0.4913[/C][C]0.312494[/C][/ROW]
[ROW][C]16[/C][C]0.084878[/C][C]0.6575[/C][C]0.2567[/C][/ROW]
[ROW][C]17[/C][C]-0.027329[/C][C]-0.2117[/C][C]0.416534[/C][/ROW]
[ROW][C]18[/C][C]0.021875[/C][C]0.1694[/C][C]0.433008[/C][/ROW]
[ROW][C]19[/C][C]0.040483[/C][C]0.3136[/C][C]0.377465[/C][/ROW]
[ROW][C]20[/C][C]-0.018091[/C][C]-0.1401[/C][C]0.444513[/C][/ROW]
[ROW][C]21[/C][C]0.213906[/C][C]1.6569[/C][C]0.051379[/C][/ROW]
[ROW][C]22[/C][C]-0.135596[/C][C]-1.0503[/C][C]0.148891[/C][/ROW]
[ROW][C]23[/C][C]0.195285[/C][C]1.5127[/C][C]0.067806[/C][/ROW]
[ROW][C]24[/C][C]-0.127738[/C][C]-0.9895[/C][C]0.163207[/C][/ROW]
[ROW][C]25[/C][C]0.144516[/C][C]1.1194[/C][C]0.133713[/C][/ROW]
[ROW][C]26[/C][C]0.059828[/C][C]0.4634[/C][C]0.322367[/C][/ROW]
[ROW][C]27[/C][C]0.010988[/C][C]0.0851[/C][C]0.466229[/C][/ROW]
[ROW][C]28[/C][C]-0.086407[/C][C]-0.6693[/C][C]0.252934[/C][/ROW]
[ROW][C]29[/C][C]-0.026655[/C][C]-0.2065[/C][C]0.418562[/C][/ROW]
[ROW][C]30[/C][C]-0.02143[/C][C]-0.166[/C][C]0.434358[/C][/ROW]
[ROW][C]31[/C][C]0.047361[/C][C]0.3669[/C][C]0.357508[/C][/ROW]
[ROW][C]32[/C][C]-0.040033[/C][C]-0.3101[/C][C]0.378782[/C][/ROW]
[ROW][C]33[/C][C]-0.152209[/C][C]-1.179[/C][C]0.121525[/C][/ROW]
[ROW][C]34[/C][C]-0.105852[/C][C]-0.8199[/C][C]0.207752[/C][/ROW]
[ROW][C]35[/C][C]-0.140294[/C][C]-1.0867[/C][C]0.140755[/C][/ROW]
[ROW][C]36[/C][C]-0.103998[/C][C]-0.8056[/C][C]0.211838[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60950&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60950&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
10.0447150.34640.365141
20.2840182.20.015835
3-0.145409-1.12630.132255
40.1073250.83130.20454
50.1589321.23110.111548
60.0367680.28480.388388
7-0.109339-0.84690.200198
8-0.122631-0.94990.172988
9-0.049338-0.38220.351842
10-0.048633-0.37670.353859
11-0.081141-0.62850.266026
12-0.184071-1.42580.079553
13-0.006468-0.05010.480104
14-0.001572-0.01220.495163
150.063430.49130.312494
160.0848780.65750.2567
17-0.027329-0.21170.416534
180.0218750.16940.433008
190.0404830.31360.377465
20-0.018091-0.14010.444513
210.2139061.65690.051379
22-0.135596-1.05030.148891
230.1952851.51270.067806
24-0.127738-0.98950.163207
250.1445161.11940.133713
260.0598280.46340.322367
270.0109880.08510.466229
28-0.086407-0.66930.252934
29-0.026655-0.20650.418562
30-0.02143-0.1660.434358
310.0473610.36690.357508
32-0.040033-0.31010.378782
33-0.152209-1.1790.121525
34-0.105852-0.81990.207752
35-0.140294-1.08670.140755
36-0.103998-0.80560.211838






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0447150.34640.365141
20.2825832.18890.016254
3-0.182026-1.410.081856
40.0514610.39860.345795
50.2703042.09380.020257
6-0.082805-0.64140.261851
7-0.247601-1.91790.029943
8-0.005701-0.04420.482462
90.0524650.40640.34295
10-0.148146-1.14750.127859
11-0.10398-0.80540.211878
12-0.041162-0.31880.375477
130.1082060.83820.202635
140.0299020.23160.408811
15-0.032787-0.2540.400195
160.178791.38490.085606
170.0099950.07740.469273
18-0.158361-1.22670.112371
190.0455450.35280.362741
20-0.02568-0.19890.421499
210.1757921.36170.089196
22-0.202197-1.56620.061279
230.1354291.0490.149186
240.0775490.60070.275154
25-0.00327-0.02530.489938
260.1016370.78730.21711
27-0.029687-0.230.409454
28-0.130816-1.01330.157493
290.0355730.27550.39192
300.0009220.00710.497163
31-0.042338-0.3280.372045
32-0.033552-0.25990.397919
33-0.033238-0.25750.398851
34-0.107733-0.83450.203656
35-0.086878-0.6730.251781
36-0.15424-1.19470.118446

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.044715 & 0.3464 & 0.365141 \tabularnewline
2 & 0.282583 & 2.1889 & 0.016254 \tabularnewline
3 & -0.182026 & -1.41 & 0.081856 \tabularnewline
4 & 0.051461 & 0.3986 & 0.345795 \tabularnewline
5 & 0.270304 & 2.0938 & 0.020257 \tabularnewline
6 & -0.082805 & -0.6414 & 0.261851 \tabularnewline
7 & -0.247601 & -1.9179 & 0.029943 \tabularnewline
8 & -0.005701 & -0.0442 & 0.482462 \tabularnewline
9 & 0.052465 & 0.4064 & 0.34295 \tabularnewline
10 & -0.148146 & -1.1475 & 0.127859 \tabularnewline
11 & -0.10398 & -0.8054 & 0.211878 \tabularnewline
12 & -0.041162 & -0.3188 & 0.375477 \tabularnewline
13 & 0.108206 & 0.8382 & 0.202635 \tabularnewline
14 & 0.029902 & 0.2316 & 0.408811 \tabularnewline
15 & -0.032787 & -0.254 & 0.400195 \tabularnewline
16 & 0.17879 & 1.3849 & 0.085606 \tabularnewline
17 & 0.009995 & 0.0774 & 0.469273 \tabularnewline
18 & -0.158361 & -1.2267 & 0.112371 \tabularnewline
19 & 0.045545 & 0.3528 & 0.362741 \tabularnewline
20 & -0.02568 & -0.1989 & 0.421499 \tabularnewline
21 & 0.175792 & 1.3617 & 0.089196 \tabularnewline
22 & -0.202197 & -1.5662 & 0.061279 \tabularnewline
23 & 0.135429 & 1.049 & 0.149186 \tabularnewline
24 & 0.077549 & 0.6007 & 0.275154 \tabularnewline
25 & -0.00327 & -0.0253 & 0.489938 \tabularnewline
26 & 0.101637 & 0.7873 & 0.21711 \tabularnewline
27 & -0.029687 & -0.23 & 0.409454 \tabularnewline
28 & -0.130816 & -1.0133 & 0.157493 \tabularnewline
29 & 0.035573 & 0.2755 & 0.39192 \tabularnewline
30 & 0.000922 & 0.0071 & 0.497163 \tabularnewline
31 & -0.042338 & -0.328 & 0.372045 \tabularnewline
32 & -0.033552 & -0.2599 & 0.397919 \tabularnewline
33 & -0.033238 & -0.2575 & 0.398851 \tabularnewline
34 & -0.107733 & -0.8345 & 0.203656 \tabularnewline
35 & -0.086878 & -0.673 & 0.251781 \tabularnewline
36 & -0.15424 & -1.1947 & 0.118446 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60950&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]0.044715[/C][C]0.3464[/C][C]0.365141[/C][/ROW]
[ROW][C]2[/C][C]0.282583[/C][C]2.1889[/C][C]0.016254[/C][/ROW]
[ROW][C]3[/C][C]-0.182026[/C][C]-1.41[/C][C]0.081856[/C][/ROW]
[ROW][C]4[/C][C]0.051461[/C][C]0.3986[/C][C]0.345795[/C][/ROW]
[ROW][C]5[/C][C]0.270304[/C][C]2.0938[/C][C]0.020257[/C][/ROW]
[ROW][C]6[/C][C]-0.082805[/C][C]-0.6414[/C][C]0.261851[/C][/ROW]
[ROW][C]7[/C][C]-0.247601[/C][C]-1.9179[/C][C]0.029943[/C][/ROW]
[ROW][C]8[/C][C]-0.005701[/C][C]-0.0442[/C][C]0.482462[/C][/ROW]
[ROW][C]9[/C][C]0.052465[/C][C]0.4064[/C][C]0.34295[/C][/ROW]
[ROW][C]10[/C][C]-0.148146[/C][C]-1.1475[/C][C]0.127859[/C][/ROW]
[ROW][C]11[/C][C]-0.10398[/C][C]-0.8054[/C][C]0.211878[/C][/ROW]
[ROW][C]12[/C][C]-0.041162[/C][C]-0.3188[/C][C]0.375477[/C][/ROW]
[ROW][C]13[/C][C]0.108206[/C][C]0.8382[/C][C]0.202635[/C][/ROW]
[ROW][C]14[/C][C]0.029902[/C][C]0.2316[/C][C]0.408811[/C][/ROW]
[ROW][C]15[/C][C]-0.032787[/C][C]-0.254[/C][C]0.400195[/C][/ROW]
[ROW][C]16[/C][C]0.17879[/C][C]1.3849[/C][C]0.085606[/C][/ROW]
[ROW][C]17[/C][C]0.009995[/C][C]0.0774[/C][C]0.469273[/C][/ROW]
[ROW][C]18[/C][C]-0.158361[/C][C]-1.2267[/C][C]0.112371[/C][/ROW]
[ROW][C]19[/C][C]0.045545[/C][C]0.3528[/C][C]0.362741[/C][/ROW]
[ROW][C]20[/C][C]-0.02568[/C][C]-0.1989[/C][C]0.421499[/C][/ROW]
[ROW][C]21[/C][C]0.175792[/C][C]1.3617[/C][C]0.089196[/C][/ROW]
[ROW][C]22[/C][C]-0.202197[/C][C]-1.5662[/C][C]0.061279[/C][/ROW]
[ROW][C]23[/C][C]0.135429[/C][C]1.049[/C][C]0.149186[/C][/ROW]
[ROW][C]24[/C][C]0.077549[/C][C]0.6007[/C][C]0.275154[/C][/ROW]
[ROW][C]25[/C][C]-0.00327[/C][C]-0.0253[/C][C]0.489938[/C][/ROW]
[ROW][C]26[/C][C]0.101637[/C][C]0.7873[/C][C]0.21711[/C][/ROW]
[ROW][C]27[/C][C]-0.029687[/C][C]-0.23[/C][C]0.409454[/C][/ROW]
[ROW][C]28[/C][C]-0.130816[/C][C]-1.0133[/C][C]0.157493[/C][/ROW]
[ROW][C]29[/C][C]0.035573[/C][C]0.2755[/C][C]0.39192[/C][/ROW]
[ROW][C]30[/C][C]0.000922[/C][C]0.0071[/C][C]0.497163[/C][/ROW]
[ROW][C]31[/C][C]-0.042338[/C][C]-0.328[/C][C]0.372045[/C][/ROW]
[ROW][C]32[/C][C]-0.033552[/C][C]-0.2599[/C][C]0.397919[/C][/ROW]
[ROW][C]33[/C][C]-0.033238[/C][C]-0.2575[/C][C]0.398851[/C][/ROW]
[ROW][C]34[/C][C]-0.107733[/C][C]-0.8345[/C][C]0.203656[/C][/ROW]
[ROW][C]35[/C][C]-0.086878[/C][C]-0.673[/C][C]0.251781[/C][/ROW]
[ROW][C]36[/C][C]-0.15424[/C][C]-1.1947[/C][C]0.118446[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60950&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60950&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
10.0447150.34640.365141
20.2825832.18890.016254
3-0.182026-1.410.081856
40.0514610.39860.345795
50.2703042.09380.020257
6-0.082805-0.64140.261851
7-0.247601-1.91790.029943
8-0.005701-0.04420.482462
90.0524650.40640.34295
10-0.148146-1.14750.127859
11-0.10398-0.80540.211878
12-0.041162-0.31880.375477
130.1082060.83820.202635
140.0299020.23160.408811
15-0.032787-0.2540.400195
160.178791.38490.085606
170.0099950.07740.469273
18-0.158361-1.22670.112371
190.0455450.35280.362741
20-0.02568-0.19890.421499
210.1757921.36170.089196
22-0.202197-1.56620.061279
230.1354291.0490.149186
240.0775490.60070.275154
25-0.00327-0.02530.489938
260.1016370.78730.21711
27-0.029687-0.230.409454
28-0.130816-1.01330.157493
290.0355730.27550.39192
300.0009220.00710.497163
31-0.042338-0.3280.372045
32-0.033552-0.25990.397919
33-0.033238-0.25750.398851
34-0.107733-0.83450.203656
35-0.086878-0.6730.251781
36-0.15424-1.19470.118446


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; 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')