cost.effectiveness.table {arvoRe} | R Documentation |
Usage
cost.effectiveness.table(TheTree)
Arguments
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(TheTree) {
Matrixset <- convert2matrix(TheTree)
x <- Matrixset$x
y <- Matrixset$y
probMAT <- Matrixset$probMAT
utilityMAT <- Matrixset$utilityMAT
effectivenessMAT <- Matrixset$effectivenessMAT
typeMAT <- Matrixset$typeMAT
rollbackLIST <- rollback(TheTree)
num.col <- dim(x)[2]
num.lin <- dim(x)[1]
levelnode <- array(,0)
paispos <- array(,0)
nnode <- array(,0)
namenode <- array(,0)
probnode <- array(,0)
utilitynode <- array(,0)
effectivenessnode <- array(,0)
typenode <- array(,0)
paisnodos.n <- array(,0)
paisnodos.name <- array(,0)
paisnodos <- array(,0)
expectedvalue.cost <- array(,0)
expectedvalue.effectiveness <- array(,0)
expectedvalue.ce <- array(,0)
for (i in 1:num.col) {
max.node <- max(x[,i], na.rm = TRUE)
pais <- 1:max.node
for (k in pais) {
levelnode <- c(levelnode,i)
nodepos <- which(x[,i] == k)[1]
paispos <- c(paispos, nodepos)
if (i == 1) {
paisnodos.n <- c(paisnodos.n, 1)
paisnodos.name <- c(paisnodos.name, " ")
} else {
paisnodos.n <- c(paisnodos.n, x[nodepos, i-1])
paisnodos.name <- c(paisnodos.name, y[nodepos, i-1])
}
nnode <- c(nnode, k)
namenode <- c(namenode, y[nodepos, i])
probnode <- c(probnode, probMAT[nodepos, i])
utilitynode <- c(utilitynode, utilityMAT[nodepos, i])
effectivenessnode <- c(effectivenessnode, effectivenessMAT[nodepos, i])
typenode <- c(typenode, typeMAT[nodepos, i])
expectedvalue.cost <- c(expectedvalue.cost, rollbackLIST[["Cost"]][nodepos, i])
expectedvalue.effectiveness <- c(expectedvalue.effectiveness, rollbackLIST[["Effectiveness"]][nodepos, i])
expectedvalue.ce <- c(expectedvalue.ce, rollbackLIST[["CE"]][nodepos, i])
}
}
tabela <- data.frame(Level = levelnode, Node.N = nnode, Node.name = namenode,
Mean.Cost = expectedvalue.cost,
Mean.Effectiveness = expectedvalue.effectiveness,
Mean.C.E.ratio = expectedvalue.ce
)
tabela <- subset(tabela, Level == 2)
tabela <- as.data.frame(tabela)
tabela$Level <- as.numeric(tabela$Level)
tabela$Node.N <- as.numeric(tabela$Node.N)
tabela$Node.name <- as.character(tabela$Node.name)
tabela$Mean.Cost <- as.numeric(as.numeric(tabela$Mean.Cost))
tabela$Mean.Effectiveness <- as.numeric(as.numeric(tabela$Mean.Effectiveness))
tabela$Mean.C.E.ratio <- as.numeric(as.numeric(tabela$Mean.C.E.ratio))
return(tabela)
}
[Package
arvoRe version 0.1.7
Index]