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loq <- function(object, ..., alpha = 0.05, k = 3, n = 1, w = "auto")
{
UseMethod("loq")
}
loq.default <- function(object, ..., alpha = 0.05, k = 3, n = 1, w = "auto")
{
stop("loq is only implemented for univariate lm objects.")
}
loq.lm <- function(object, ..., alpha = 0.05, k = 3, n = 1, w = "auto")
{
xname <- names(object$model)[[2]]
yname <- names(object$model)[[1]]
f <- function(x) {
newdata <- data.frame(x = x)
names(newdata) <- xname
y <- predict(object, newdata)
p <- inverse.predict(object, rep(y, n), ws = w, alpha = alpha)
(p[["Prediction"]] - k * p[["Confidence"]])^2
}
tmp <- optimize(f,interval=c(0,max(object$model[[2]])))
loq.x <- tmp$minimum
newdata <- data.frame(x = loq.x)
names(newdata) <- xname
loq.y <- predict(object, newdata)
loq <- list(loq.x, loq.y)
names(loq) <- c(xname, yname)
return(loq)
}
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