diff options
Diffstat (limited to 'R/loq.R')
| -rw-r--r-- | R/loq.R | 18 |
1 files changed, 14 insertions, 4 deletions
@@ -1,22 +1,32 @@ -loq <- function(object, ..., alpha = 0.05, k = 3, n = 1, w = "auto") +loq <- function(object, ..., alpha = 0.05, k = 3, n = 1, w.loq = "auto", + var.loq = "auto") { UseMethod("loq") } -loq.default <- function(object, ..., alpha = 0.05, k = 3, n = 1, w = "auto") +loq.default <- function(object, ..., alpha = 0.05, k = 3, n = 1, w.loq = "auto", + var.loq = "auto") { stop("loq is only implemented for univariate lm objects.") } -loq.lm <- function(object, ..., alpha = 0.05, k = 3, n = 1, w = "auto") +loq.lm <- function(object, ..., alpha = 0.05, k = 3, n = 1, w.loq = "auto", + var.loq = "auto") { + if (length(object$weights) > 0 && var.loq == "auto" && w.loq == "auto") { + stop(paste("If you are using a model from weighted regression,", + "you need to specify a reasonable approximation for the", + "weight (w.loq) or the variance (var.loq) at the", + "limit of quantification")) + } xname <- names(object$model)[[2]] yname <- names(object$model)[[1]] f <- function(x) { newdata <- data.frame(x = x) names(newdata) <- xname y <- predict(object, newdata) - p <- inverse.predict(object, rep(y, n), ws = w, alpha = alpha) + p <- inverse.predict(object, rep(y, n), ws = w.loq, + var.s = var.loq, alpha = alpha) (p[["Prediction"]] - k * p[["Confidence"]])^2 } tmp <- optimize(f,interval=c(0,max(object$model[[2]]))) |