Updated documentation to add the theta_zero parameter

R/gevdfit.R

@@ -33,6 +33,8 @@
 #' @param show Logical; if TRUE (the default), print details of the fit.
 #' @param method The optimization method used in \code{\link{optim}}.
 #' @param maxit The maximum number of iterations.
+#' @param theta_zero Logical value, indicating if theta parameter should be estimated (TRUE, the default) or
+#' remain zero. 
 #' @param ... Other control parameters for the optimization.
 #' @return A list containing the following components. 
 #' A subset of these components are printed after the fit. 
@@ -474,15 +476,13 @@ gev.d.params <- function(fit,ydat){
   mut <- mulink(mumat %*% (fit$mle[1:npmu]))
   sc0 <- siglink(sigmat %*% (fit$mle[seq(npmu + 1, length = npsc)]))
   xi <- shlink(shmat %*% (fit$mle[seq(npmu + npsc + 1, length = npsh)]))
-  if(class(fit)=="gev.d.fit" & !fit$theta_zero){theta <- thetalink(thmat %*% (fit$mle[seq(npmu + npsc + npsh + 1, length = npth)]))}
+  if(class(fit)=="gev.d.fit" ){
+    if(!fit$theta_zero){theta <- thetalink(thmat %*% (fit$mle[seq(npmu + npsc + npsh + 1, length = npth)]))
+    }else{theta <- rep(0,dim(ydat)[1])}}
   if(class(fit)=="gev.d.fit"){eta <- etalink(etmat %*% (fit$mle[seq(npmu + npsc + npsh + npth + 1, length = npet)]))}
   
   if(class(fit)=="gev.d.fit"){
-    if(!fit$theta_zero){ #When theta parameter is used (default)
-      return(data.frame(mut=mut,sig0=sc0,xi=xi,theta=theta,eta=eta))
-    }else{ #When theta parameter was not used
-      return(data.frame(mut=mut,sig0=sc0,xi=xi,eta=eta))
-    }
+    return(data.frame(mut=mut,sig0=sc0,xi=xi,theta=theta,eta=eta))
   }else{return(data.frame(mu=mut,sig=sc0,xi=xi))}
 }
 

man/gev.d.fit.Rd

@@ -10,7 +10,8 @@ gev.d.fit(xdat, ds, ydat = NULL, mul = NULL, sigl = NULL,
   shlink = make.link("identity"), thetalink = make.link("identity"),
   etalink = make.link("identity"), muinit = NULL, siginit = NULL,
   shinit = NULL, thetainit = NULL, etainit = NULL, show = TRUE,
-  method = "Nelder-Mead", maxit = 10000, init.vals = NULL, ...)
+  method = "Nelder-Mead", maxit = 10000, init.vals = NULL,
+  theta_zero = FALSE, ...)
 }
 \arguments{
 \item{xdat}{A vector containing maxima for different durations. 
@@ -45,6 +46,9 @@ used to model the parameters. If NULL (the default) is given, initial parameters
 internally by fitting the GEV seperately for each duration and applying a linear model to optain the 
 duration dependency of the location and shape parameter.}
 
+\item{theta_zero}{Logical value, indicating if theta parameter should be estimated (TRUE, the default) or
+remain zero.}
+
 \item{...}{Other control parameters for the optimization.}
 }
 \value{