R/incl_prob.R

In effectFusion: Bayesian Effect Fusion for Categorical Predictors

inclProb <- function(S, mvars, model) {
    
    diff <- as.numeric(model$diff)
    lowd <- cumsum(diff) - diff + 1
    upd <- cumsum(diff)
    
    categories <- as.numeric(model$categories)
    index <- c(0, cumsum(c(categories - 1)))
    low <- index + 1
    up <- index[-1]
    
    jk <- sum(diff)
    incl_prob <- rep(0, jk)
    for (m in 1:length(S[, 1])) {
        delta <- c()
        for (j in 1:model$n_nom) {
            Sv <- S[m, low[j]:up[j]]
            x <- outer(Sv, Sv, "==")
            delta <- c(delta, Sv == 1, t(x)[lower.tri(t(x), diag = FALSE)])
        }
        incl_prob <- incl_prob + delta
    }
    
    incl_prob <- incl_prob/length(S[, 1])
    
    
    return(incl_prob)
    
    
}