This is a mostly ggplot-ish implementation of the plot for dbchoice and sbchoice models in the DCchoice package.

ggplot-dcchoice.R

### This is a mostly ggplot-ish implementation of the plot for dbchoice
### and sbchoice models in the DCchoice package.

ggplot.dbchoice <- function(x, ...) {
    minbid <- min(x$bid)
    maxbid <- max(x$bid)
    bidseq <- seq(minbid, maxbid, by = (maxbid - minbid) / 100)
    
    b <- x$coefficients
    npar <- length(b)
    Xcov <- colMeans(x$covariates)
    Vcov <- sum(Xcov * b[-npar])
    V <- Vcov + bidseq * b[npar]
    dist <- x$distribution

    if (dist == "logistic" | dist == "log-logistic") {
        pr <- plogis(-V, lower.tail = FALSE, log.p = FALSE)
    } else if (dist == "normal" | dist == "log-normal") {
        pr <- pnorm(-V, lower.tail = FALSE, log.p = FALSE)
    } else if (dist == "weibull") {
        pr <- pweibull(exp(-V), shape = 1, lower.tail = FALSE, log.p = FALSE)
    }

    xlimits <- c(0.96 * minbid, 1.04 * maxbid)
    ylimits <- c(0, 1)
    
    df <- data.frame(x = bidseq, y = pr)
    p <- ggplot(df, aes(x, y)) + geom_line() + xlim(xlimits) + ylim(ylimits)
    
    invisible(p) 
}

ggplot.sbchoice <- function (x, ...) {
    minbid <- min(x$bid)
    maxbid <- max(x$bid)
    bidseq <- seq(minbid, maxbid, by = (maxbid - minbid) / 100)
    
    b <- x$coefficients
    npar <- length(b)
    Xcov <- colMeans(x$covariates)
    Vcov <- sum(Xcov * b[-npar])
    V <- Vcov + bidseq * b[npar]
    dist <- x$distribution

    if(dist == "logistic" | dist == "log-logistic") {
        pr <- plogis(-V, lower.tail = FALSE, log.p = FALSE)
    } else if (dist == "normal" | dist == "log-normal") {
        pr <- pnorm(-V, lower.tail = FALSE, log.p = FALSE)
    } else if (dist == "weibull") {
        pr <- pweibull(exp(-V), shape = 1, lower.tail = FALSE, log.p = FALSE)
    }

    xlimits <- c(0.96 * minbid, 1.04 * maxbid)
    ylimits <- c(0, 1)
    
    df <- data.frame(x = bidseq, y = pr)
    p <- ggplot(df, aes(x, y)) + geom_line() + xlim(xlimits) + ylim(ylimits)
    
    invisible(p)
}