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#' Impute missing values
#'
#' Uses the bootstrap EM Algorithm on incomplete data and creates imputed datasets
#'
#' @param data an object of class \code{idframe}
#' @param m the number of imputed datasets to create.
#'
#' @return
#' A list containing the following elements
#'
#' \tabular{ll}{
#' \code{imputations} \tab a list of length \code{m} with an imputed dataset in each
#' entry. Each element is of class \code{idframe} \cr
#' \code{m} \tab an integer indicating the number of imputations run
#' }
#'
#' @details
#' This function uses the \code{\link[Amelia]{amelia}} function, provided by the
#' \pkg{amelia} package, to perform multiple imputation.
#'
#' @references
#' Honaker, J., King, G., Blackwell, M. (2011). Amelia II: A Program for Missing Data.
#' Journal of Statistical Software, 45(7), 1–47. URL http://www.jstatsoft.org/v45/i07/.
#'
#' @seealso \code{\link[Amelia]{amelia}}
#' @export
dataImpute <- function(data,m=1){
# check if the class is correct
if(class(data)!='idframe')
stop("Not an idframe data")
dataMatrix <- cbind(data$input,data$output)
a.out <- amelia(dataMatrix,m=m,p2s = 0)
a.assign <- function(dataMatrix,data){
ninputs <- dim(data$input)[2]
out <- data
colIndex <- 1:(dim(dataMatrix)[2])
inputIndex <- 1:ninputs
outputIndex <- colIndex[!(colIndex %in% inputIndex)]
out$input <- dataMatrix[,1:inputIndex,drop=F]
out$output <- dataMatrix[,1:outputIndex,drop=F]
return(out)
}
imputations <- lapply(X=a.out$imputations,FUN=a.assign,data=data)
return(list(imputations=imputations,m=m))
}
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