R/GetApproximateMaximumDValueFromThreeByTwoContingencyTable.r

In CausalR: Causal network analysis methods

#' @title returns approximate maximum D value or weight for a 3x2 superfamily
#' @description
#' Computes an approximate maximum D value (or weight) for a superfamily (3x2 table).
#' The result is only approximate as only the first valid D value that is return. This has been
#' done to speed up the overall algorithm. 
#' 
#' @param threeByTwoContingencyTable  approximate values of n++, n+-, n-+, n--, n0+ and n0-, these values are
#' calculated to optimise the D-value (see page 6 of Assessing
#' statistical significance of causal graphs)
#' @param predictionListStats a vector containing the values q+, q- and q0 
#' (the number of positive/negative/non-significant 
#' (or contradictory) predictions)
#' @param logOfFactorialOfPredictionListStats a vector containing the log of the factorial value for
#' each entry in predictionListStats
#' @param returnlog return the result as a log, default is FALSE
#' @return an approximate maximum D value or weight


GetApproximateMaximumDValueFromThreeByTwoContingencyTable <- function(threeByTwoContingencyTable, predictionListStats, logOfFactorialOfPredictionListStats, 
    returnlog = FALSE) {
    # *** Summary *** Description: A function that will compute an approximate maximum D value (or weight) for a superfamily (3x2 table).  The reason it
    # is described as approiximate is that this function returns the first valid D value that is found. This has been done to speed up the overall
    # algorithm.
    
    
    n_pz <- predictionListStats[1] - (threeByTwoContingencyTable[1] + threeByTwoContingencyTable[2])
    n_mz <- predictionListStats[2] - (threeByTwoContingencyTable[3] + threeByTwoContingencyTable[4])
    n_zz <- predictionListStats[3] - (threeByTwoContingencyTable[5] + threeByTwoContingencyTable[6])
    threeByThreeContingencyTable <- c(threeByTwoContingencyTable, n_pz, n_mz, n_zz)
    weight <- CalculateWeightGivenValuesInThreeByThreeContingencyTable(threeByThreeContingencyTable, logOfFactorialOfPredictionListStats, returnlog)
    return(weight)
}