Commit 4fbe2aee authored by Jana Ulrich's avatar Jana Ulrich
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parent ce35cd60
......@@ -3,7 +3,7 @@ Type: Package
Title: Estimation and Plotting of IDF Curves
Version: 2.0.0
Date: 2020-11-22
Authors@R: c(person("Jana", "Ulrich", email = "jana.ulrich@fu-berlin.de", role = c("aut", "cre")),
Authors@R: c(person("Jana", "Ulrich", email = "jana.ulrich@met.fu-berlin.de", role = c("aut", "cre")),
person("Laura","Mack", email= "laura.mack@fu-berlin.de",role="ctb"),
person("Oscar E.","Jurado", email= "jurado@zedat.fu-berlin.de",role="ctb"),
person("Christoph", "Ritschel", role = "aut"),
......@@ -14,10 +14,10 @@ Description: Intensity-duration-frequency (IDF) curves are a widely used analysi
[e.g. Mailhot et al., 2007, <doi:10.1016/j.jhydrol.2007.09.019>].
The package 'IDF' provides functions to estimate IDF parameters for given
precipitation time series on the basis of a duration-dependent
generalised extreme value distribution
generalized extreme value distribution
[Koutsoyiannis et al., 1998, <doi:10.1016/S0022-1694(98)00097-3>].
Author: Jana Ulrich [aut, cre], Laura Mack [ctb], Oscar E. Jurado [ctb], Christoph Ritschel [aut], Carola Detring [ctb], Sarah Joedicke [ctb]
Maintainer: Jana Ulrich <jana.ulrich@fu-berlin.de>
Maintainer: Jana Ulrich <jana.ulrich@met.fu-berlin.de>
Imports: stats,
evd,
ismev,
......@@ -28,4 +28,4 @@ License: GPL (>=2)
Encoding: UTF-8
URL: https://gitlab.met.fu-berlin.de/Rpackages/idf_package
LazyData: true
RoxygenNote: 7.1.0
RoxygenNote: 7.1.1
......@@ -7,4 +7,4 @@ The packet was extensively revised and restructured and some functions were remo
# IDF 1.0.0
R package for maximum likelihood fitting of duration-dependent generalized extreme value distribution (d-GEV).
Additional functions forprocessing data (obtaining annual maxima) plotting IDF curves.
\ No newline at end of file
Additional functions for processing data (obtaining annual maxima) plotting IDF curves.
\ No newline at end of file
......@@ -19,7 +19,7 @@
#' For more detailed information on the methods and the application of the package for estimating
#' IDF curves with spatial covariates, see Ulrich et. al (2020).
#' @details
#' * The __d-GEV__ is defined following Koutsoyannis et al. (1998):
#' * The __d-GEV__ is defined following Koutsoyiannis et al. (1998):
#' \deqn{G(x)= \exp[-( 1+\xi(x/\sigma(d)- \tilde{\mu}) ) ^{-1/\xi}] }
#' defined on \eqn{ \{ x: 1+\xi(x/\sigma(d)- \tilde{\mu} > 0) \} },
#' with the duration dependent scale parameter \eqn{\sigma(d)=\sigma_0/(d+\theta)^\eta > 0},
......@@ -106,7 +106,7 @@ NULL
#' Afterwards the results can be joint together using `rbind`.
#'
#' @return data.frame containing the annual intensity maxima [mm/h] in `$xdat`, the corresponding duration in `$ds`,
#' the `$year` and month (`$mon`) in which the maxima occured
#' the `$year` and month (`$mon`) in which the maxima occurred
#' and the station id or name in `$station`.
#'
#' @seealso \code{\link{pgev.d}}
......@@ -199,7 +199,7 @@ NULL
#' (modified location, scale offset, shape, duration offset, duration exponent) for chosen station
#' as obtained from \code{\link{gev.d.fit}}
#' (or \code{\link{gev.d.params}} for model with covariates).
#' @param probs vector of non-exeedance probabilities for which to plot IDF curves (p = 1-1/(Return Period))
#' @param probs vector of non-exceedance probabilities for which to plot IDF curves (p = 1-1/(Return Period))
#' @param cols vector of colors for IDF curves. Should have same length as \code{probs}
#' @param add logical indicating if plot should be added to existing plot, default is FALSE
#' @param legend logical indicating if legend should be plotted (TRUE, the default)
......
......@@ -65,7 +65,7 @@ dgev.d <- function(q,mut,sigma0,xi,theta,eta,d,...) {
#' @param ... additional parameters passed to \code{\link[evd]{pgev}}
#'
#' @details The duration dependent GEV distribution is defined after
#' [Koutsoyannis et al., 1998]:
#' [Koutsoyiannis et al., 1998]:
#' \deqn{G(x)= \exp[-\left( 1+\xi(x/\sigma(d)-\mu_t) \right)^{-1/\xi}] }
#' with the duration dependent scale \eqn{\sigma(d)=\sigma_0/(d+\theta)^\eta} and
#' modified location parameter \eqn{\mu_t=\mu/\sigma(d)}.
......@@ -111,7 +111,7 @@ pgev.d <- function(q,mut,sigma0,xi,theta,eta,d,...) {
#' @param ... additional parameters passed to \code{\link[evd]{qgev}}
#'
#' @details The duration dependent GEV distribution is defined after
#' [Koutsoyannis et al., 1998]:
#' [Koutsoyiannis et al., 1998]:
#' \deqn{ G(x)= \exp[-\left( 1+\xi(x/\sigma(d)-\mu_t) \right)^{-1/\xi}] }
#' with the duration dependent scale \eqn{\sigma(d)=\sigma_0/(d+\theta)^\eta} and
#' modified location parameter \eqn{\mu_t=\mu/\sigma(d)}.
......
......@@ -265,14 +265,14 @@ gev.d.fit<-
# take given initial values into account, if there are any
# xi -> mean vs. median ... how do we improve that?
# mu_tilde -> is not very good for small sample sizes yet
# improved inital value for eta, by fitting both mu~d and sigma~d in log-log scale
# improved initial value for eta, by fitting both mu~d and sigma~d in log-log scale
#' @title get initial values for gev.d.fit
#' @description obtain initial values by fitting every duration seperately
#' @param xdat vector of maxima for differnt durations
#' @description obtain initial values by fitting every duration separately
#' @param xdat vector of maxima for different durations
#' @param ds vector of durations belonging to maxima in xdat
#' @param link list of 5, link functions for parameters, created with \code{\link{make.link}}
#' @return list of initail values for mu_tilde, sigma_0, xi, eta
#' @return list of initial values for mu_tilde, sigma_0, xi, eta
#' @importFrom stats lm
#' @importFrom stats median
#' @importFrom ismev gev.fit
......@@ -440,7 +440,7 @@ gev.d.diag <- function(fit,subset=NULL,cols=NULL,pch=NULL,which='both',mfrow=c(1
#'
#' @description function to calculate mut, sigma0, xi, theta, eta
#' (modified location, scale offset, shape, duration offset, duration exponent)
#' from results of \code{\link{gev.d.fit}} with covariates or link funktions other than identity.
#' from results of \code{\link{gev.d.fit}} with covariates or link functions other than identity.
#' @param fit fit object returned by \code{\link{gev.d.fit}} or \code{\link{gev.fit}}
#' @param ydat A matrix containing the covariates in the same order as used in \code{gev.d.fit}.
#' @seealso \code{\link{IDF-package}}
......
......@@ -18,7 +18,7 @@ knitr::opts_chunk$set(
<!-- badges: end -->
Intensity-duration-frequency (IDF) curves are a widely used analysis-tool
in hydrology to assessthe characteristics of extreme precipitation.
in hydrology to assess the characteristics of extreme precipitation.
The package 'IDF' functions to estimate IDF relations for given
precipitation time series on the basis of a duration-dependent
generalized extreme value (GEV) distribution.
......
......@@ -8,7 +8,7 @@
<!-- badges: end -->
Intensity-duration-frequency (IDF) curves are a widely used
analysis-tool in hydrology to assessthe characteristics of extreme
analysis-tool in hydrology to assess the characteristics of extreme
precipitation. The package ‘IDF’ functions to estimate IDF relations for
given precipitation time series on the basis of a duration-dependent
generalized extreme value (GEV) distribution. The central function is ,
......@@ -74,13 +74,13 @@ fit <- gev.d.fit(xdat = ann.max$xdat,ds = ann.max$ds,sigma0link = make.link('log
#> [1] 0
#>
#> $nllh
#> [1] 62.01441
#> [1] 58.66546
#>
#> $mle
#> [1] 5.983501e+00 4.844650e-01 -1.860657e-02 2.126704e-08 7.908172e-01
#> [1] 7.861966e+00 2.347229e-01 1.300037e-01 4.145220e-09 7.996548e-01
#>
#> $se
#> [1] 3.974995e-01 8.085273e-02 8.330635e-02 2.000063e-06 1.230878e-02
#> [1] 5.158025e-01 7.464137e-02 7.188928e-02 2.000067e-06 1.056973e-02
# checking the fit
gev.d.diag(fit,pch=1,)
```
......@@ -92,7 +92,7 @@ gev.d.diag(fit,pch=1,)
params <- gev.d.params(fit)
print(params)
#> mut sigma0 xi theta eta
#> 1 5.983501 1.623306 -0.01860657 2.126704e-08 0.7908172
#> 1 7.861966 1.264558 0.1300037 4.14522e-09 0.7996548
# plotting the probability density for a single duration
q.min <- floor(min(ann.max$xdat[ann.max$ds%in%1:2]))
......
......@@ -17,7 +17,7 @@ IDF curves with spatial covariates, see Ulrich et. al (2020).
}
\details{
\itemize{
\item The \strong{d-GEV} is defined following Koutsoyannis et al. (1998):
\item The \strong{d-GEV} is defined following Koutsoyiannis et al. (1998):
\deqn{G(x)= \exp[-( 1+\xi(x/\sigma(d)- \tilde{\mu}) ) ^{-1/\xi}] }
defined on \eqn{ \{ x: 1+\xi(x/\sigma(d)- \tilde{\mu} > 0) \} },
with the duration dependent scale parameter \eqn{\sigma(d)=\sigma_0/(d+\theta)^\eta > 0},
......
......@@ -37,7 +37,7 @@ containing names of elements in data. If not given, all elements in `data` will
}
\value{
data.frame containing the annual intensity maxima [mm/h] in `$xdat`, the corresponding duration in `$ds`,
the `$year` and month (`$mon`) in which the maxima occured
the `$year` and month (`$mon`) in which the maxima occurred
and the station id or name in `$station`.
}
\description{
......
......@@ -22,7 +22,7 @@ IDF.plot(
as obtained from \code{\link{gev.d.fit}}
(or \code{\link{gev.d.params}} for model with covariates).}
\item{probs}{vector of non-exeedance probabilities for which to plot IDF curves (p = 1-1/(Return Period))}
\item{probs}{vector of non-exceedance probabilities for which to plot IDF curves (p = 1-1/(Return Period))}
\item{cols}{vector of colors for IDF curves. Should have same length as \code{probs}}
......
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......@@ -7,16 +7,16 @@
gev.d.init(xdat, ds, link)
}
\arguments{
\item{xdat}{vector of maxima for differnt durations}
\item{xdat}{vector of maxima for different durations}
\item{ds}{vector of durations belonging to maxima in xdat}
\item{link}{list of 5, link functions for parameters, created with \code{\link{make.link}}}
}
\value{
list of initail values for mu_tilde, sigma_0, xi, eta
list of initial values for mu_tilde, sigma_0, xi, eta
}
\description{
obtain initial values by fitting every duration seperately
obtain initial values by fitting every duration separately
}
\keyword{internal}
......@@ -17,7 +17,7 @@ data.frame containing mu_tilde, sigma0, xi, theta, eta (or mu, sigma, xi for gev
\description{
function to calculate mut, sigma0, xi, theta, eta
(modified location, scale offset, shape, duration offset, duration exponent)
from results of \code{\link{gev.d.fit}} with covariates or link funktions other than identity.
from results of \code{\link{gev.d.fit}} with covariates or link functions other than identity.
}
\examples{
data('example',package = 'IDF')
......
......@@ -28,7 +28,7 @@ Cumulative probability distribution function of duration-dependent GEV distribut
}
\details{
The duration dependent GEV distribution is defined after
[Koutsoyannis et al., 1998]:
[Koutsoyiannis et al., 1998]:
\deqn{G(x)= \exp[-\left( 1+\xi(x/\sigma(d)-\mu_t) \right)^{-1/\xi}] }
with the duration dependent scale \eqn{\sigma(d)=\sigma_0/(d+\theta)^\eta} and
modified location parameter \eqn{\mu_t=\mu/\sigma(d)}.
......
......@@ -28,7 +28,7 @@ Quantile function of duration-dependent GEV distribution (inverse of the cumulat
}
\details{
The duration dependent GEV distribution is defined after
[Koutsoyannis et al., 1998]:
[Koutsoyiannis et al., 1998]:
\deqn{ G(x)= \exp[-\left( 1+\xi(x/\sigma(d)-\mu_t) \right)^{-1/\xi}] }
with the duration dependent scale \eqn{\sigma(d)=\sigma_0/(d+\theta)^\eta} and
modified location parameter \eqn{\mu_t=\mu/\sigma(d)}.
......
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