volta.cokri {geoComp} | R Documentation |
Usage
volta.cokri(mat.cokri, num.simu, int.conf = 0.95, predictor.fc=mean)
Arguments
mat.cokri |
|
num.simu |
|
int.conf |
|
predictor.fc |
|
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function(mat.cokri, num.simu, int.conf=0.95){
nlinhas <- dim(mat.cokri[[1]])[1]
compos1 <- data.frame(matrix(nrow=nlinhas/2,ncol=3))
compos <- data.frame(matrix(nrow=nlinhas/2,ncol=3))
for(i in 1:num.simu){
g <- mvrnorm(n=1, mat.cokri[[1]],mat.cokri[[2]])
seq1 <- seq(1,nlinhas,by=2)
seq2 <- seq(2,nlinhas,by=2)
y1 <- g[seq1]
y2 <- g[seq2]
gerado <- data.frame(y1,y2)
compos <- agl(gerado)
compos1 <- cbind(compos,compos1)
}
compos2 <- as.matrix(compos1)
dim.vetor <- num.simu*3
sy1 <- seq(1,dim.vetor,by=3) #sy1 <- seq(1,30,by=3)
sy2 <- seq(2,dim.vetor,by=3) #sy2 <- seq(2,30,by=3)
sy3 <- seq(3,dim.vetor,by=3) #sy3 <- seq(3,30,by=3)
amostra1 <- as.matrix(compos2[,sy1],ncol=num.simu)
amostra2 <- as.matrix(compos2[,sy2],ncol=num.simu)
amostra3 <- as.matrix(compos2[,sy3],ncol=num.simu)
med1 <- apply(amostra1,1,median)
med2 <- apply(amostra2,1,median)
med3 <- apply(amostra3,1,median)
q1 <- t(apply(amostra1,1,quantile,prob=c(1-int.conf,int.conf)))
q2 <- t(apply(amostra2,1,quantile,prob=c(1-int.conf,int.conf)))
q3 <- t(apply(amostra3,1,quantile,prob=c(1-int.conf,int.conf)))
quantis <- cbind(q1,q2,q3)
resultado <- list()
resultado$preditos <- data.frame(med1,med2,med3)
names(resultado$preditos) <- c("Areia","Silte","Argila")
resultado$intervalo <- data.frame(quantis)
names(resultado$intervalo) <- c("LI Areia", "LS Areia", "LI Silte", "LS Silte", "LI Argila", "LS Argila")
return(resultado)
}
[Package
geoComp version 0.1-0
Index]