found some small mistakes: gev.d.params + in two examples i forgot to change...

found some small mistakes: gev.d.params + in two examples i forgot to change parameter names -> fixed

R/IDF.R

@@ -209,7 +209,7 @@ NULL
 #' data('example',package = 'IDF')
 #' # fit d-gev
 #' fit <- gev.d.fit(example$dat,example$d,ydat = as.matrix(example[,c("cov1","cov2")])
-#'                  ,mul = c(1,2),sigl = 1)
+#'                  ,mutl = c(1,2),sigma0l = 1)
 #' # get parameters for cov1 = 1, cov2 = 1
 #' par <- gev.d.params(fit = fit, ydat = matrix(1,1,2))
 #' # plot quantiles

R/gevdfit.R

@@ -71,7 +71,7 @@
 #' data('example',package ='IDF')
 #' 
 #' gev.d.fit(xdat=example$dat,ds = example$d,ydat=as.matrix(example[,c('cov1','cov2')])
-#' ,mul=c(1,2),sigl=1)
+#' ,mutl=c(1,2),sigma0l=1)
 
 gev.d.fit<-
   function(xdat, ds, ydat = NULL, mutl = NULL, sigma0l = NULL, xil = NULL, thetal = NULL, etal = NULL, 
@@ -322,7 +322,7 @@ gev.d.init <- function(xdat,ds,link){
 #' # compute log-likelihood of observation values not included in fit
 #' train.set <- example[example$d!=2,]
 #' test.set <- example[example$d==2,]
-#' fit <- gev.d.fit(train.set$dat,train.set$d,mul = c(1,2),sigl = 1
+#' fit <- gev.d.fit(train.set$dat,train.set$d,mutl = c(1,2),sigma0l = 1
 #'           ,ydat = as.matrix(train.set[c('cov1','cov2')]))
 #' params <- gev.d.params(fit,ydat = as.matrix(test.set[c('cov1','cov2')]))
 #' gev.d.lik(xdat = test.set$dat,ds = test.set$d,mut = params[,1],sigma0 = params[,2],xi = params[,3]
@@ -450,18 +450,21 @@ gev.d.diag <- function(fit,subset=NULL,cols=NULL,pch=NULL,which='both',mfrow=c(1
 #' @examples
 #' data('example',package = 'IDF')
 #' fit <- gev.d.fit(example$dat,example$d,ydat = as.matrix(example[,c("cov1","cov2")])
-#'                  ,mul = c(1,2),sigl = 1)
+#'                  ,mutl = c(1,2),sigma0l = 1)
 #' gev.d.params(fit = fit,ydat = cbind(c(0.9,1),c(0.5,1)))
 
 
 gev.d.params <- function(fit,ydat=NULL){
   if(!class(fit)%in%c("gev.d.fit","gev.fit"))stop("'fit' must be an object returned by 'gev.d.fit' or 'gev.fit'.")
-  if(fit$trans){
+  if(!is.null(ydat)){
     # check covariates matrix 
     if(!is.matrix(ydat))stop("'ydat' must be of class matrix.")
     n.par <- max(sapply(fit$model,function(x){return(ifelse(is.null(x),0,max(x)))}))
     if(n.par>ncol(ydat))stop("Covariates-Matrix 'ydat' has ",ncol(ydat), " columns, but ", n.par," are required.")
-  }else(ydat <- matrix(1))
+  }else{if(!fit$trans){# no model -> no covariates matrix
+    ydat <- matrix(1)
+    }else{stop("To calculate parameter estimates, covariates matrix 'ydat' must be provided.")}
+  }
   
   # number of parameters
   npmu <- length(fit$model[[1]]) + 1

man/IDF.plot.Rd

@@ -39,7 +39,7 @@ Plotting of IDF curves at a chosen station
 data('example',package = 'IDF')
 # fit d-gev
 fit <- gev.d.fit(example$dat,example$d,ydat = as.matrix(example[,c("cov1","cov2")])
-                 ,mul = c(1,2),sigl = 1)
+                 ,mutl = c(1,2),sigma0l = 1)
 # get parameters for cov1 = 1, cov2 = 1
 par <- gev.d.params(fit = fit, ydat = matrix(1,1,2))
 # plot quantiles

man/gev.d.fit.Rd

@@ -103,7 +103,7 @@ For details on the d-GEV and the parameter definitions, see \link{IDF-package}.
 data('example',package ='IDF')
 
 gev.d.fit(xdat=example$dat,ds = example$d,ydat=as.matrix(example[,c('cov1','cov2')])
-,mul=c(1,2),sigl=1)
+,mutl=c(1,2),sigma0l=1)
 }
 \seealso{
 \code{\link{IDF-package}}, \code{\link{IDF.agg}}, \code{\link{gev.fit}}, \code{\link{optim}}

man/gev.d.lik.Rd

@@ -25,7 +25,7 @@ Computes (log-) likelihood of d-GEV model
 # compute log-likelihood of observation values not included in fit
 train.set <- example[example$d!=2,]
 test.set <- example[example$d==2,]
-fit <- gev.d.fit(train.set$dat,train.set$d,mul = c(1,2),sigl = 1
+fit <- gev.d.fit(train.set$dat,train.set$d,mutl = c(1,2),sigma0l = 1
           ,ydat = as.matrix(train.set[c('cov1','cov2')]))
 params <- gev.d.params(fit,ydat = as.matrix(test.set[c('cov1','cov2')]))
 gev.d.lik(xdat = test.set$dat,ds = test.set$d,mut = params[,1],sigma0 = params[,2],xi = params[,3]

man/gev.d.params.Rd

@@ -22,7 +22,7 @@ from results of \code{\link{gev.d.fit}} with covariates or link funktions other
 \examples{
 data('example',package = 'IDF')
 fit <- gev.d.fit(example$dat,example$d,ydat = as.matrix(example[,c("cov1","cov2")])
-                 ,mul = c(1,2),sigl = 1)
+                 ,mutl = c(1,2),sigma0l = 1)
 gev.d.params(fit = fit,ydat = cbind(c(0.9,1),c(0.5,1)))
 }
 \seealso{