Home » date » 2009 » Jun » 07 »

Opdracht 6bis oefening 2

*Unverified author*
R Software Module: rwasp_autocorrelation.wasp (opens new window with default values)
Title produced by software: (Partial) Autocorrelation Function
Date of computation: Sun, 07 Jun 2009 07:18:41 -0600
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Jun/07/t1244380756vpws98r7spqeurl.htm/, Retrieved Sun, 07 Jun 2009 15:19:19 +0200
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2009/Jun/07/t1244380756vpws98r7spqeurl.htm/},
    year = {2009},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2009},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
thomas cammaert
 
Dataseries X:
» Textbox « » Textfile « » CSV «
8,5968 8,5114 8,3884 8,2671 8,2410 8,3177 8,4070 8,3917 8,4145 8,5245 8,6289 8,6622 8,9055 8,9770 9,1264 9,1120 9,0576 9,2106 9,2637 9,3107 9,6744 9,5780 9,4166 9,4359 9,2275 9,1828 9,0594 9,1358 9,2208 9,1137 9,2689 9,2489 9,1679 9,1051 9,0818 9,0961 9,1733 9,1455 9,2265 9,1541 9,1559 9,1182 9,1856 9,2378 9,0682 9,0105 8,9939 9,0228 9,1368 9,1763 9,2346 9,1653 9,1277 9,1430 9,1962 9,1861 9,0920 9,0620 8,9981 8,9819 9,0476 9,0852 9,0884 9,1670 9,1931 9,2628 9,4276 9,3398 9,3342 9,4223 9,5614 9,4316 9,3111 9,3414 9,4017 9,3346 9,3310 9,2349 9,2170 9,2098 9,2665 9,2533 9,1008 9,0377 9,0795 9,1896 9,2992 9,2372 9,2061 9,3290 9,1842 9,3231 9,2835 9,1735 9,2889 9,4319
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0671210.65420.257276
2-0.044986-0.43850.331021
30.0918340.89510.186502
4-0.131221-1.2790.10201
50.080090.78060.218483
60.0164470.16030.436491
7-0.010651-0.10380.458768
80.0638250.62210.267687
9-0.199592-1.94540.027343
100.0495590.4830.315088
110.033830.32970.371165
12-0.174937-1.70510.045724
13-0.093284-0.90920.182767
14-0.164388-1.60230.056209
150.0592110.57710.282612
16-0.033099-0.32260.37385
17-0.164351-1.60190.05625
180.0098890.09640.461707
19-0.044567-0.43440.332497
200.0622960.60720.272589
210.0491910.47950.316358
220.0435140.42410.336219
230.0606750.59140.277833
24-0.107402-1.04680.148918
250.0173260.16890.43313
260.0154780.15090.440204
27-0.088594-0.86350.195016
280.0234690.22870.40978
29-0.027708-0.27010.39385
300.0673190.65610.256657
310.0599570.58440.280172
32-0.000931-0.00910.496389
33-0.026626-0.25950.397898
34-0.002803-0.02730.489129
35-0.014527-0.14160.443849
360.0272720.26580.39548
37-0.007887-0.07690.469442
380.0373380.36390.358361
39-0.094628-0.92230.17935
40-0.051529-0.50220.308328
41-0.039525-0.38520.350459
42-0.004233-0.04130.483587
430.1135851.10710.135524
44-0.090221-0.87940.19071
45-0.070858-0.69060.24574
460.0752890.73380.232432
47-0.071795-0.69980.242889
480.0286810.27960.390215
490.1214781.1840.119679
500.0472960.4610.322932
510.0136790.13330.447107
52-0.051967-0.50650.306835
530.1049641.02310.154438
540.0397630.38760.349604
550.0070190.06840.472799
560.105271.0260.153738
570.000990.00970.49616
580.0150070.14630.442008
59-0.020292-0.19780.421819
60-0.03312-0.32280.373773


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0671210.65420.257276
2-0.049715-0.48460.314551
30.099030.96520.168441
4-0.149844-1.46050.073727
50.1174931.14520.127506
6-0.029941-0.29180.385526
70.0343120.33440.369396
80.0202940.19780.421813
9-0.18792-1.83160.035071
100.0942620.91880.180276
11-0.021492-0.20950.417262
12-0.122829-1.19720.117105
13-0.147413-1.43680.077029
14-0.126708-1.2350.109938
150.1151741.12260.132224
16-0.112653-1.0980.137489
17-0.117049-1.14080.1284
18-0.063869-0.62250.267546
190.0276070.26910.394225
200.1053851.02720.153475
21-0.073414-0.71560.238011
220.0728390.710.239737
23-0.007781-0.07580.469851
24-0.039549-0.38550.350374
25-0.029781-0.29030.386123
26-0.13082-1.27510.102696
27-0.051988-0.50670.306764
28-0.040656-0.39630.3464
29-0.023862-0.23260.408294
30-0.002743-0.02670.489364
31-0.010811-0.10540.45815
320.0915180.8920.187322
33-0.110836-1.08030.141372
340.0802430.78210.218046
35-0.05132-0.50020.309044
360.0360950.35180.362879
37-0.021891-0.21340.41575
38-0.013589-0.13240.447456
39-0.093913-0.91540.181163
40-0.095307-0.92890.177637
41-0.100181-0.97640.165662
42-0.013762-0.13410.446791
430.0919130.89590.186297
44-0.117447-1.14470.127598
45-0.093333-0.90970.182641
460.1100221.07240.143136
47-0.031514-0.30720.379698
480.0406750.39650.34633
490.0874970.85280.197953
500.0677740.66060.255241
51-0.028863-0.28130.389538
52-0.091592-0.89270.187129
530.0511680.49870.309565
54-0.076139-0.74210.229927
550.1200221.16980.122497
56-0.000575-0.00560.497771
57-0.03952-0.38520.350479
580.0354450.34550.365252
59-0.032692-0.31860.375349
600.0791340.77130.221221
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244380756vpws98r7spqeurl/1aunc1244380719.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244380756vpws98r7spqeurl/1aunc1244380719.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244380756vpws98r7spqeurl/2du4u1244380719.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244380756vpws98r7spqeurl/2du4u1244380719.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; 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('http://www.xycoon.com/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('http://www.xycoon.com/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')
 





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