Nothing
# -----------------------------------------------------------------------
# Function for merging combinations of splits
#
# first.data: first argument for matrix (of any type) for the splits
# second.data: second argument for matrix (of any type) for the splits
merge.combinations <- function(first.data, second.data){
# Creating the matrix by merging the combinations from each group
final.data <- first.data[rep(1:(nrow(first.data)), each=nrow(second.data)),]
final.data <- cbind(final.data, second.data[rep(1:nrow(second.data), times=nrow(first.data)),])
# Removing split groupings where a variable is duplicated (i.e. in more than one group)
final.data <- final.data[apply(final.data, 1, function(x){return(!any(duplicated(x)))}),]
# Returning the split groupings
final.data <- unname(final.data)
return(final.data)
}
# Function to check if object is interger(0)
is.integer0 <- function(x){
return(is.integer(x) && length(x) == 0L)
}
# -----------------------------------------------------------------------
# Function for creating splits for a partition
#
# comb.data: data
# second.data: second argument for matrix (of any type) for the splits
create.subSplits <- function(comb.data, n.times){
# Storing the number of variables
p <- ncol(comb.data)
# Indicator for the groups
p.ind <- c(1, (1:(n.times-1))*(p) + 1)
# Initiation the merging
new.comb.data <- comb.data
# Looping for the number of times the group is repeated
if(n.times>1){
for(n.iter in 2:n.times){
new.comb.data <- merge.combinations(new.comb.data, comb.data)
new.comb.data <- new.comb.data[(new.comb.data[,p.ind[n.iter]] > new.comb.data[,p.ind[n.iter-1]]),]
}
return(new.comb.data)
} else
return(new.comb.data)
}
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