added example for fit with covariates

R/IDF.R

@@ -333,6 +333,20 @@ IDF.nll <- function(mu=0,sigma=1,xi=0,theta=0,eta=1,x,d,use.log=F,DEBUG=F) {
 #' @seealso \code{\link{IDF.agg}}, \code{\link{gev.fit}}, \code{\link{optim}}
 #' @author Jana Ulrich \email{jana.ulrich@@met.fu-berlin.de}
 #' @export
+#' 
+#' @examples 
+#' # sampled random data from d-gev with covariates
+#' # GEV parameters:
+#' # mu = 4 + 0.2*cov1 +0.5*cov2
+#' # sigma = 2+0.5*cov1
+#' # xi = 0.5
+#' # theta = 0
+#' # eta = 0.5
+#' 
+#' 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)
 
 'gev.d.fit'<-
   function(xdat, ds, ydat = NULL, mul = NULL, sigl = NULL, shl = NULL, thetal = NULL, etal = NULL, 
@@ -429,7 +443,7 @@ IDF.nll <- function(mu=0,sigma=1,xi=0,theta=0,eta=1,x,d,use.log=F,DEBUG=F) {
       y <- xdat/sigma.d - mu
       y <- 1 + xi * y
       
-      if(any(eta <= 0) ||any(ds.t <= 0) || any(sigma.d <= 0) || any(y <= 0)) return(10^6)
+      if(any(eta <= 0) ||any(theta <= -0.5) || any(sigma.d <= 0) || any(y <= 0)) return(10^6)
       sum(log(sigma.d)) + sum(y^(-1/xi)) + sum(log(y) * (1/xi + 1))
     }
     

man/gev.d.fit.Rd

@@ -8,7 +8,7 @@ gev.d.fit(xdat, ds, ydat = NULL, mul = NULL, sigl = NULL,
   shl = NULL, thetal = NULL, etal = NULL, mulink = identity,
   siglink = identity, shlink = identity, thetalink = identity,
   etalink = identity, muinit = NULL, siginit = NULL, shinit = NULL,
-  thetainit = 0, etainit = NULL, show = TRUE,
+  thetainit = NULL, etainit = NULL, show = TRUE,
   method = "Nelder-Mead", maxit = 10000, ...)
 }
 \arguments{
@@ -60,6 +60,20 @@ Maximum-likelihood fitting for the duration dependent generalized extreme
 value distribution, following Koutsoyiannis et al. (1988), including generalized linear 
 modelling of each parameter based on \code{\link{gev.fit}}.
 }
+\examples{
+# sampled random data from d-gev with covariates
+# GEV parameters:
+# mu = 4 + 0.2*cov1 +0.5*cov2
+# sigma = 2+0.5*cov1
+# xi = 0.5
+# theta = 0
+# eta = 0.5
+
+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)
+}
 \seealso{
 \code{\link{IDF.agg}}, \code{\link{gev.fit}}, \code{\link{optim}}
 }