summary.rollback.table {ArvoRe} | R Documentation |
~~ A concise (1-5 lines) description of what the function does. ~~
summary.rollback.table(TheTree)
TheTree |
~~Describe TheTree here~~ |
~~ If necessary, more details than the description above ~~
~Describe the value returned If it is a LIST, use
comp1 |
Description of 'comp1' |
comp2 |
Description of 'comp2' |
...
....
~~further notes~~
~Make other sections like Warning with section{Warning }{....} ~
~~who you are~~
~put references to the literature/web site here ~
~~objects to See Also as help
, ~~~
##---- 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, # Father = paisnodos.n, Father.Name = paisnodos.name, Prob = probnode, Cost = utilitynode, Effectiveness = effectivenessnode, Type = typenode ) return(tabela) }