map.joint.sample <-
function (sample.to.plot, base.line.p, type.position, newdata,
distribution)
{
if (distribution == "weibull") {
y.to.plot <- 1/sample.to.plot[, 2]
ylab <- "beta"
}
else {
y.to.plot <- sample.to.plot[, 2]
ylab <- "sigma"
}
y.axis <- "linear"
switch(type.position, quantile = , Quantile = {
newp <- newdata
if (newp == base.line.p) {
x.to.plot <- sample.to.plot[, 1]
} else {
x.to.plot <- exp(logb(sample.to.plot[, 1]) + sample.to.plot[,
2] * (quant(newp, distribution) - quant(base.line.p,
distribution)))
}
xlab <- paste(newp, "quantile")
if (is.logdist(distribution)) {
x.axis <- "log"
} else {
x.axis <- "linear"
}
}, parameter = , Parameter = {
newp <- wqmf.phibf(0, distribution)
x.to.plot <- (logb(sample.to.plot[, 1]) + sample.to.plot[,
2] * (quant(newp, distribution) - quant(base.line.p,
distribution)))
if (distribution == "weibull") {
xlab <- "eta"
x.axis <- "log"
x.to.plot <- exp(x.to.plot)
} else {
xlab <- "mu"
x.axis <- "linear"
}
}, `failure probability` = , `Failure probability` = {
newp <- wqmf.phibf(0, distribution)
x.to.plot <- (logb(sample.to.plot[, 1]) + sample.to.plot[,
2] * (quant(newp, distribution) - quant(base.line.p,
distribution)))
x.to.plot <- wqmf.phibf((logb(newdata) - x.to.plot)/sample.to.plot[,
2], distribution)
xlab <- paste("F(", newdata, ")", sep = "")
x.axis <- "linear"
}, `Base Quantile` = {
x.to.plot <- sample.to.plot[, 1]
xlab <- paste(base.line.p, "quantile")
if (is.logdist(distribution)) {
x.axis <- "log"
} else {
x.axis <- "linear"
}
}, {
stop(paste("bad type.position", type.position))
})
return.list <- list(x.to.plot = x.to.plot, y.to.plot = y.to.plot,
x.axis = x.axis, y.axis = y.axis, xlab = xlab, ylab = ylab)
return(return.list)
}
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