diff options
author | ranke <ranke@5fad18fb-23f0-0310-ab10-e59a3bee62b4> | 2015-08-22 09:03:10 +0000 |
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committer | ranke <ranke@5fad18fb-23f0-0310-ab10-e59a3bee62b4> | 2015-08-22 09:03:10 +0000 |
commit | d8d6012e98fb4c7f158bcc7c173407c2b5f3e42e (patch) | |
tree | 92bcbbc548431b214fb387e20dc423745b2ab897 /branches/0.1/chemCal/R/loq.R | |
parent | 2be973ef45816e04a6a59f59a4fae50f8f17a5e1 (diff) |
Get rid of the branched svn layout I never used
git-svn-id: http://kriemhild.uft.uni-bremen.de/svn/chemCal@36 5fad18fb-23f0-0310-ab10-e59a3bee62b4
Diffstat (limited to 'branches/0.1/chemCal/R/loq.R')
-rw-r--r-- | branches/0.1/chemCal/R/loq.R | 41 |
1 files changed, 0 insertions, 41 deletions
diff --git a/branches/0.1/chemCal/R/loq.R b/branches/0.1/chemCal/R/loq.R deleted file mode 100644 index f832265..0000000 --- a/branches/0.1/chemCal/R/loq.R +++ /dev/null @@ -1,41 +0,0 @@ -loq <- function(object, ..., alpha = 0.05, k = 3, n = 1, w.loq = "auto", - var.loq = "auto", tol = "default") -{ - UseMethod("loq") -} - -loq.default <- function(object, ..., alpha = 0.05, k = 3, n = 1, w.loq = "auto", - var.loq = "auto", tol = "default") -{ - stop("loq is only implemented for univariate lm objects.") -} - -loq.lm <- function(object, ..., alpha = 0.05, k = 3, n = 1, w.loq = "auto", - var.loq = "auto", tol = "default") -{ - 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]] - xvalues <- 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.loq, - var.s = var.loq, alpha = alpha) - (p[["Prediction"]] - k * p[["Confidence"]])^2 - } - if (tol == "default") tol = min(xvalues[xvalues !=0]) / 1000 - loq.x <- optimize(f, interval = c(0, max(xvalues) * 10), tol = tol)$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) -} |