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| author | Johannes Ranke <jranke@uni-bremen.de> | 2021-04-07 11:38:05 +0200 |
|---|---|---|
| committer | Johannes Ranke <jranke@uni-bremen.de> | 2021-04-07 11:38:05 +0200 |
| commit | 8596a3e82235385b5de50cc5a722ccb68247f084 (patch) | |
| tree | df17246e512751b361c571e4671842ff4d9bbb72 /R/calplot.R | |
| parent | 43d58935483e0d9dda7a74c029e7d7d2adad9ed7 (diff) | |
Argument 'legend_x' for 'calplot'
Also, keep check and test logs in the repository.
Diffstat (limited to 'R/calplot.R')
| -rw-r--r-- | R/calplot.R | 14 |
1 files changed, 9 insertions, 5 deletions
diff --git a/R/calplot.R b/R/calplot.R index 6aed9c0..fd49a54 100644 --- a/R/calplot.R +++ b/R/calplot.R @@ -1,7 +1,8 @@ calplot <- function(object, xlim = c("auto", "auto"), ylim = c("auto", "auto"), - xlab = "Concentration", ylab = "Response", alpha = 0.05, - varfunc = NULL) + xlab = "Concentration", ylab = "Response", + legend_x = "auto", + alpha = 0.05, varfunc = NULL) { UseMethod("calplot") } @@ -9,6 +10,7 @@ calplot <- function(object, calplot.default <- function(object, xlim = c("auto","auto"), ylim = c("auto","auto"), xlab = "Concentration", ylab = "Response", + legend_x = "auto", alpha=0.05, varfunc = NULL) { stop("Calibration plots only implemented for univariate lm objects.") @@ -16,8 +18,9 @@ calplot.default <- function(object, calplot.lm <- function(object, xlim = c("auto","auto"), ylim = c("auto","auto"), - xlab = "Concentration", ylab = "Response", alpha=0.05, - varfunc = NULL) + xlab = "Concentration", ylab = "Response", + legend_x = "auto", + alpha=0.05, varfunc = NULL) { if (length(object$coef) > 2) stop("More than one independent variable in your model - not implemented") @@ -47,6 +50,7 @@ calplot.lm <- function(object, yrange.auto <- range(c(0,pred.lim)) if (ylim[1] == "auto") ylim[1] <- yrange.auto[1] if (ylim[2] == "auto") ylim[2] <- yrange.auto[2] + if (legend_x[1] == "auto") legend_x <- min(object$model[[2]]) plot(1, type = "n", xlab = xlab, @@ -68,7 +72,7 @@ calplot.lm <- function(object, } else { matlines(newdata[[1]], conf.lim, lty = c(1, 3, 3), col = c("black", "green4", "green4")) - legend(min(x), + legend(legend_x, max(pred.lim, na.rm = TRUE), legend = c("Fitted Line", "Confidence Bands", "Prediction Bands"), |