select.markov.propertiesMAT {ArvoRe} | R Documentation |
~~ A concise (1-5 lines) description of what the function does. ~~
select.markov.propertiesMAT(TheTree, SubTree, markov.propertiesMAT)
TheTree |
~~Describe TheTree here~~ |
SubTree |
~~Describe SubTree here~~ |
markov.propertiesMAT |
~~Describe markov.propertiesMAT 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' |
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~~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, SubTree, markov.propertiesMAT) { require(abind) selected.lines <- rownames(SubTree) check.tree <- TheTree[selected.lines,] wanted.level <- check.tree$Level[1]+1 check.tree <- check.tree[check.tree$Level == wanted.level,] ans <- data.frame( "Level" = array(,0), "Node.N" = array(,0), "Node.name" = array(,0), "Father" = array(,0), "Father.Name" = array(,0), "Initial.cost" = array(,0), "Incremental.cost" = array(,0), "Final.cost" = array(,0), "Initial.effectiveness" = array(,0), "Incremental.effectiveness" = array(,0), "Final.effectiveness" = array(,0)) for (i in 1:length(check.tree$Node.N) ) { balde <- subset(markov.propertiesMAT, Node.N == check.tree$Node.N[i]) n.lin.balde <- dim(balde)[1] if (n.lin.balde > 0) { ans <- abind(ans, balde, along = 1) } else { balde <- data.frame( "Level" = check.tree$Level[i], "Node.N" = check.tree$Node.N[i], "Node.name" = check.tree$Node.name[i], "Father" = check.tree$Father[i], "Father.Name" = check.tree$Father.Name[i], "Initial.cost" = 0, "Incremental.cost" = check.tree$Payoff1[i], "Final.cost" = 0, "Initial.effectiveness" = 0, "Incremental.effectiveness" = check.tree$Payoff2[i], "Final.effectiveness" = 0) ans <- abind(ans, balde, along = 1) } } ans <- as.data.frame(ans) wanted.level.sub <- SubTree$Level[1]+1 subSubTree <- subset(SubTree, Level == wanted.level.sub) ans$Level <- subSubTree$Level ans$Node.N <- subSubTree$Node.N ans$Father <- subSubTree$Father ans$Father.Name <- subSubTree$Father.Name rownames(ans) <- rownames(subSubTree) ans$Level <- as.numeric(as.character(ans$Level)) ans$Node.N <- as.numeric(as.character(ans$Node.N)) ans$Node.name <- (as.character(ans$Node.name)) ans$Father <- as.numeric(as.character(ans$Father)) ans$Father.Name <- (as.character(ans$Father.Name)) ans$Initial.cost <- as.numeric(as.character(ans$Initial.cost)) ans$Incremental.cost <- as.numeric(as.character(ans$Incremental.cost)) ans$Final.cost <- as.numeric(as.character(ans$Final.cost)) ans$Initial.effectiveness <- as.numeric(as.character(ans$Initial.effectiveness)) ans$Incremental.effectiveness <- as.numeric(as.character(ans$Incremental.effectiveness)) ans$Final.effectiveness <- as.numeric(as.character(ans$Final.effectiveness)) return(ans) }