autocorrelatie: consumenten vertrouwen
| Summary of compuational transaction | |
| Raw Input | view raw input (R code) |
| Raw Output | view raw output of R engine |
| Computing time | 2 seconds |
| R Server | 'Gwilym Jenkins' @ 72.249.127.135 |
| Autocorrelation Function | |||
| Time lag k | ACF(k) | T-STAT | P-value |
| 0 | 1 | 8.4853 | 0 |
| 1 | -0.142507 | -1.2092 | 0.884731 |
| 2 | -0.142638 | -1.2103 | 0.884944 |
| 3 | -0.030371 | -0.2577 | 0.601316 |
| 4 | -0.065998 | -0.56 | 0.711396 |
| 5 | -0.025455 | -0.216 | 0.585197 |
| 6 | -0.073376 | -0.6226 | 0.732248 |
| 7 | 0.150636 | 1.2782 | 0.102644 |
| 8 | -0.107304 | -0.9105 | 0.817202 |
| 9 | 0.056703 | 0.4811 | 0.315938 |
| 10 | 0.052674 | 0.447 | 0.328125 |
| 11 | -0.197889 | -1.6791 | 0.951271 |
| 12 | -0.021693 | -0.1841 | 0.572763 |
| 13 | -0.039586 | -0.3359 | 0.631037 |
| 14 | -0.034904 | -0.2962 | 0.616024 |
| 15 | 0.013957 | 0.1184 | 0.453028 |
| 16 | 0.188244 | 1.5973 | 0.057289 |
| 17 | -0.075581 | -0.6413 | 0.738327 |
| 18 | -0.114295 | -0.9698 | 0.83231 |
| 19 | 0.044009 | 0.3734 | 0.354963 |
| 20 | 0.025201 | 0.2138 | 0.415638 |
| 21 | -0.025571 | -0.217 | 0.58558 |
| 22 | -0.061329 | -0.5204 | 0.697807 |
| 23 | 0.175997 | 1.4934 | 0.069853 |
| 24 | -0.046865 | -0.3977 | 0.653974 |
| 25 | 0.002676 | 0.0227 | 0.490973 |
| 26 | 0.073562 | 0.6242 | 0.267236 |
| 27 | -0.107239 | -0.91 | 0.817058 |
| 28 | 0.005839 | 0.0495 | 0.480311 |
| 29 | 0.1112 | 0.9436 | 0.174273 |
| 30 | -0.041481 | -0.352 | 0.63706 |
| 31 | 0.042326 | 0.3592 | 0.360266 |
| 32 | -0.018857 | -0.16 | 0.563337 |
| 33 | 0.057575 | 0.4885 | 0.313327 |
| 34 | -0.121422 | -1.0303 | 0.84684 |
| 35 | -0.013104 | -0.1112 | 0.544113 |
| 36 | 0.032932 | 0.2794 | 0.390354 |
| 37 | -0.028382 | -0.2408 | 0.594813 |
| 38 | 0.185403 | 1.5732 | 0.060029 |
| 39 | -0.131077 | -1.1122 | 0.86513 |
| 40 | -0.143163 | -1.2148 | 0.88579 |
| 41 | 0.049905 | 0.4235 | 0.336612 |
| 42 | -0.012246 | -0.1039 | 0.541236 |
| 43 | 0.013047 | 0.1107 | 0.456077 |
| 44 | -0.063333 | -0.5374 | 0.703675 |
| 45 | 0.087412 | 0.7417 | 0.230337 |
| 46 | 0.048803 | 0.4141 | 0.340015 |
| 47 | 0.00198 | 0.0168 | 0.493321 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | -0.142507 | -1.2092 | 0.884731 |
| 1 | -0.166324 | -1.4113 | 0.918769 |
| 2 | -0.081652 | -0.6928 | 0.754681 |
| 3 | -0.114933 | -0.9752 | 0.833647 |
| 4 | -0.080327 | -0.6816 | 0.75116 |
| 5 | -0.135614 | -1.1507 | 0.873174 |
| 6 | 0.089172 | 0.7566 | 0.225865 |
| 7 | -0.124924 | -1.06 | 0.853659 |
| 8 | 0.042814 | 0.3633 | 0.358726 |
| 9 | 0.028143 | 0.2388 | 0.405969 |
| 10 | -0.18358 | -1.5577 | 0.938159 |
| 11 | -0.092915 | -0.7884 | 0.783476 |
| 12 | -0.120734 | -1.0245 | 0.845477 |
| 13 | -0.165408 | -1.4035 | 0.917622 |
| 14 | -0.079676 | -0.6761 | 0.74942 |
| 15 | 0.092368 | 0.7838 | 0.217873 |
| 16 | -0.126511 | -1.0735 | 0.856679 |
| 17 | -0.107406 | -0.9114 | 0.81743 |
| 18 | -0.081914 | -0.6951 | 0.755373 |
| 19 | -0.03087 | -0.2619 | 0.602941 |
| 20 | -0.06102 | -0.5178 | 0.696897 |
| 21 | -0.160427 | -1.3613 | 0.911163 |
| 22 | 0.039657 | 0.3365 | 0.368735 |
| 23 | -0.0781 | -0.6627 | 0.745182 |
| 24 | -0.072948 | -0.619 | 0.731061 |
| 25 | 0.000551 | 0.0047 | 0.498141 |
| 26 | -0.081265 | -0.6896 | 0.753656 |
| 27 | -0.069177 | -0.587 | 0.720476 |
| 28 | 0.101284 | 0.8594 | 0.196479 |
| 29 | -0.099314 | -0.8427 | 0.798908 |
| 30 | 0.076478 | 0.6489 | 0.259221 |
| 31 | -0.053665 | -0.4554 | 0.67489 |
| 32 | 0.051264 | 0.435 | 0.332435 |
| 33 | -0.019163 | -0.1626 | 0.564355 |
| 34 | -0.044134 | -0.3745 | 0.645431 |
| 35 | -0.036156 | -0.3068 | 0.620057 |
| 36 | 0.070852 | 0.6012 | 0.274799 |
| 37 | 0.2013 | 1.7081 | 0.045964 |
| 38 | -0.102105 | -0.8664 | 0.805423 |
| 39 | -0.097301 | -0.8256 | 0.794128 |
| 40 | 0.034637 | 0.2939 | 0.384839 |
| 41 | -0.015266 | -0.1295 | 0.551351 |
| 42 | 0.009631 | 0.0817 | 0.467548 |
| 43 | -0.049893 | -0.4234 | 0.663353 |
| 44 | -0.03073 | -0.2607 | 0.602485 |
| 45 | 0.094889 | 0.8052 | 0.21169 |
| 46 | 0.037863 | 0.3213 | 0.374465 |
| 47 | 0.078134 | 0.663 | 0.254728 |
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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 1:par1) {
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(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-1,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(mytstat,lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
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