Commit 3994dcb6 authored by Jana Ulrich's avatar Jana Ulrich
Browse files

added example for fit with covariates

parent 99a34ee6
......@@ -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))
}
......
......@@ -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}}
}
......
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