Commit 4fbe2aee authored by Jana Ulrich's avatar Jana Ulrich
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...@@ -3,7 +3,7 @@ Type: Package ...@@ -3,7 +3,7 @@ Type: Package
Title: Estimation and Plotting of IDF Curves Title: Estimation and Plotting of IDF Curves
Version: 2.0.0 Version: 2.0.0
Date: 2020-11-22 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("Laura","Mack", email= "laura.mack@fu-berlin.de",role="ctb"),
person("Oscar E.","Jurado", email= "jurado@zedat.fu-berlin.de",role="ctb"), person("Oscar E.","Jurado", email= "jurado@zedat.fu-berlin.de",role="ctb"),
person("Christoph", "Ritschel", role = "aut"), person("Christoph", "Ritschel", role = "aut"),
...@@ -14,10 +14,10 @@ Description: Intensity-duration-frequency (IDF) curves are a widely used analysi ...@@ -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>]. [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 The package 'IDF' provides functions to estimate IDF parameters for given
precipitation time series on the basis of a duration-dependent 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>]. [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] 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, Imports: stats,
evd, evd,
ismev, ismev,
...@@ -28,4 +28,4 @@ License: GPL (>=2) ...@@ -28,4 +28,4 @@ License: GPL (>=2)
Encoding: UTF-8 Encoding: UTF-8
URL: https://gitlab.met.fu-berlin.de/Rpackages/idf_package URL: https://gitlab.met.fu-berlin.de/Rpackages/idf_package
LazyData: true 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 ...@@ -7,4 +7,4 @@ The packet was extensively revised and restructured and some functions were remo
# IDF 1.0.0 # IDF 1.0.0
R package for maximum likelihood fitting of duration-dependent generalized extreme value distribution (d-GEV). 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. Additional functions for processing data (obtaining annual maxima) plotting IDF curves.
\ No newline at end of file \ No newline at end of file
...@@ -19,7 +19,7 @@ ...@@ -19,7 +19,7 @@
#' For more detailed information on the methods and the application of the package for estimating #' 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). #' IDF curves with spatial covariates, see Ulrich et. al (2020).
#' @details #' @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}] } #' \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) \} }, #' 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}, #' with the duration dependent scale parameter \eqn{\sigma(d)=\sigma_0/(d+\theta)^\eta > 0},
...@@ -106,7 +106,7 @@ NULL ...@@ -106,7 +106,7 @@ NULL
#' Afterwards the results can be joint together using `rbind`. #' 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`, #' @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 `$station`. #' and the station id or name in `$station`.
#' #'
#' @seealso \code{\link{pgev.d}} #' @seealso \code{\link{pgev.d}}
...@@ -199,7 +199,7 @@ NULL ...@@ -199,7 +199,7 @@ NULL
#' (modified location, scale offset, shape, duration offset, duration exponent) for chosen station #' (modified location, scale offset, shape, duration offset, duration exponent) for chosen station
#' as obtained from \code{\link{gev.d.fit}} #' as obtained from \code{\link{gev.d.fit}}
#' (or \code{\link{gev.d.params}} for model with covariates). #' (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 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 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) #' @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,...) { ...@@ -65,7 +65,7 @@ dgev.d <- function(q,mut,sigma0,xi,theta,eta,d,...) {
#' @param ... additional parameters passed to \code{\link[evd]{pgev}} #' @param ... additional parameters passed to \code{\link[evd]{pgev}}
#' #'
#' @details The duration dependent GEV distribution is defined after #' @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}] } #' \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 #' with the duration dependent scale \eqn{\sigma(d)=\sigma_0/(d+\theta)^\eta} and
#' modified location parameter \eqn{\mu_t=\mu/\sigma(d)}. #' modified location parameter \eqn{\mu_t=\mu/\sigma(d)}.
...@@ -111,7 +111,7 @@ pgev.d <- function(q,mut,sigma0,xi,theta,eta,d,...) { ...@@ -111,7 +111,7 @@ pgev.d <- function(q,mut,sigma0,xi,theta,eta,d,...) {
#' @param ... additional parameters passed to \code{\link[evd]{qgev}} #' @param ... additional parameters passed to \code{\link[evd]{qgev}}
#' #'
#' @details The duration dependent GEV distribution is defined after #' @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}] } #' \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 #' with the duration dependent scale \eqn{\sigma(d)=\sigma_0/(d+\theta)^\eta} and
#' modified location parameter \eqn{\mu_t=\mu/\sigma(d)}. #' modified location parameter \eqn{\mu_t=\mu/\sigma(d)}.
......
...@@ -265,14 +265,14 @@ gev.d.fit<- ...@@ -265,14 +265,14 @@ gev.d.fit<-
# take given initial values into account, if there are any # take given initial values into account, if there are any
# xi -> mean vs. median ... how do we improve that? # xi -> mean vs. median ... how do we improve that?
# mu_tilde -> is not very good for small sample sizes yet # 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 #' @title get initial values for gev.d.fit
#' @description obtain initial values by fitting every duration seperately #' @description obtain initial values by fitting every duration separately
#' @param xdat vector of maxima for differnt durations #' @param xdat vector of maxima for different durations
#' @param ds vector of durations belonging to maxima in xdat #' @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}} #' @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 lm
#' @importFrom stats median #' @importFrom stats median
#' @importFrom ismev gev.fit #' @importFrom ismev gev.fit
...@@ -440,7 +440,7 @@ gev.d.diag <- function(fit,subset=NULL,cols=NULL,pch=NULL,which='both',mfrow=c(1 ...@@ -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 #' @description function to calculate mut, sigma0, xi, theta, eta
#' (modified location, scale offset, shape, duration offset, duration exponent) #' (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 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}. #' @param ydat A matrix containing the covariates in the same order as used in \code{gev.d.fit}.
#' @seealso \code{\link{IDF-package}} #' @seealso \code{\link{IDF-package}}
......
...@@ -18,7 +18,7 @@ knitr::opts_chunk$set( ...@@ -18,7 +18,7 @@ knitr::opts_chunk$set(
<!-- badges: end --> <!-- badges: end -->
Intensity-duration-frequency (IDF) curves are a widely used analysis-tool 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 The package 'IDF' functions to estimate IDF relations for given
precipitation time series on the basis of a duration-dependent precipitation time series on the basis of a duration-dependent
generalized extreme value (GEV) distribution. generalized extreme value (GEV) distribution.
......
...@@ -8,7 +8,7 @@ ...@@ -8,7 +8,7 @@
<!-- badges: end --> <!-- badges: end -->
Intensity-duration-frequency (IDF) curves are a widely used 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 precipitation. The package ‘IDF’ functions to estimate IDF relations for
given precipitation time series on the basis of a duration-dependent given precipitation time series on the basis of a duration-dependent
generalized extreme value (GEV) distribution. The central function is , 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 ...@@ -74,13 +74,13 @@ fit <- gev.d.fit(xdat = ann.max$xdat,ds = ann.max$ds,sigma0link = make.link('log
#> [1] 0 #> [1] 0
#> #>
#> $nllh #> $nllh
#> [1] 62.01441 #> [1] 58.66546
#> #>
#> $mle #> $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 #> $se
#> [1] 3.974995e-01 8.085273e-02 8.330635e-02 2.000063e-06 1.230878e-02 #> [1] 5.158025e-01 7.464137e-02 7.188928e-02 2.000067e-06 1.056973e-02
# checking the fit # checking the fit
gev.d.diag(fit,pch=1,) gev.d.diag(fit,pch=1,)
``` ```
...@@ -91,8 +91,8 @@ gev.d.diag(fit,pch=1,) ...@@ -91,8 +91,8 @@ gev.d.diag(fit,pch=1,)
# parameter estimates # parameter estimates
params <- gev.d.params(fit) params <- gev.d.params(fit)
print(params) print(params)
#> mut sigma0 xi theta eta #> mut sigma0 xi theta eta
#> 1 5.983501 1.623306 -0.01860657 2.126704e-08 0.7908172 #> 1 7.861966 1.264558 0.1300037 4.14522e-09 0.7996548
# plotting the probability density for a single duration # plotting the probability density for a single duration
q.min <- floor(min(ann.max$xdat[ann.max$ds%in%1:2])) q.min <- floor(min(ann.max$xdat[ann.max$ds%in%1:2]))
......
...@@ -17,7 +17,7 @@ IDF curves with spatial covariates, see Ulrich et. al (2020). ...@@ -17,7 +17,7 @@ IDF curves with spatial covariates, see Ulrich et. al (2020).
} }
\details{ \details{
\itemize{ \itemize{
\item The \strong{d-GEV} is defined following Koutsoyannis et al. (1998): \item The \strong{d-GEV} is defined following Koutsoyiannis et al. (1998):
\deqn{G(x)= \exp[-( 1+\xi(x/\sigma(d)- \tilde{\mu}) ) ^{-1/\xi}] } \deqn{G(x)= \exp[-( 1+\xi(x/\sigma(d)- \tilde{\mu}) ) ^{-1/\xi}] }
defined on \eqn{ \{ x: 1+\xi(x/\sigma(d)- \tilde{\mu} > 0) \} }, defined on \eqn{ \{ x: 1+\xi(x/\sigma(d)- \tilde{\mu} > 0) \} },
with the duration dependent scale parameter \eqn{\sigma(d)=\sigma_0/(d+\theta)^\eta > 0}, with the duration dependent scale parameter \eqn{\sigma(d)=\sigma_0/(d+\theta)^\eta > 0},
......
...@@ -37,7 +37,7 @@ containing names of elements in data. If not given, all elements in `data` will ...@@ -37,7 +37,7 @@ containing names of elements in data. If not given, all elements in `data` will
} }
\value{ \value{
data.frame containing the annual intensity maxima [mm/h] in `$xdat`, the corresponding duration in `$ds`, data.frame containing the annual intensity maxima [mm/h] in `$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`. and the station id or name in `$station`.
} }
\description{ \description{
......
...@@ -22,7 +22,7 @@ IDF.plot( ...@@ -22,7 +22,7 @@ IDF.plot(
as obtained from \code{\link{gev.d.fit}} as obtained from \code{\link{gev.d.fit}}
(or \code{\link{gev.d.params}} for model with covariates).} (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}} \item{cols}{vector of colors for IDF curves. Should have same length as \code{probs}}
......
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...@@ -7,16 +7,16 @@ ...@@ -7,16 +7,16 @@
gev.d.init(xdat, ds, link) gev.d.init(xdat, ds, link)
} }
\arguments{ \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{ds}{vector of durations belonging to maxima in xdat}
\item{link}{list of 5, link functions for parameters, created with \code{\link{make.link}}} \item{link}{list of 5, link functions for parameters, created with \code{\link{make.link}}}
} }
\value{ \value{
list of initail values for mu_tilde, sigma_0, xi, eta list of initial values for mu_tilde, sigma_0, xi, eta
} }
\description{ \description{
obtain initial values by fitting every duration seperately obtain initial values by fitting every duration separately
} }
\keyword{internal} \keyword{internal}
...@@ -17,7 +17,7 @@ data.frame containing mu_tilde, sigma0, xi, theta, eta (or mu, sigma, xi for gev ...@@ -17,7 +17,7 @@ data.frame containing mu_tilde, sigma0, xi, theta, eta (or mu, sigma, xi for gev
\description{ \description{
function to calculate mut, sigma0, xi, theta, eta function to calculate mut, sigma0, xi, theta, eta
(modified location, scale offset, shape, duration offset, duration exponent) (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{ \examples{
data('example',package = 'IDF') data('example',package = 'IDF')
......
...@@ -28,7 +28,7 @@ Cumulative probability distribution function of duration-dependent GEV distribut ...@@ -28,7 +28,7 @@ Cumulative probability distribution function of duration-dependent GEV distribut
} }
\details{ \details{
The duration dependent GEV distribution is defined after 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}] } \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 with the duration dependent scale \eqn{\sigma(d)=\sigma_0/(d+\theta)^\eta} and
modified location parameter \eqn{\mu_t=\mu/\sigma(d)}. modified location parameter \eqn{\mu_t=\mu/\sigma(d)}.
......
...@@ -28,7 +28,7 @@ Quantile function of duration-dependent GEV distribution (inverse of the cumulat ...@@ -28,7 +28,7 @@ Quantile function of duration-dependent GEV distribution (inverse of the cumulat
} }
\details{ \details{
The duration dependent GEV distribution is defined after 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}] } \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 with the duration dependent scale \eqn{\sigma(d)=\sigma_0/(d+\theta)^\eta} and
modified location parameter \eqn{\mu_t=\mu/\sigma(d)}. modified location parameter \eqn{\mu_t=\mu/\sigma(d)}.
......
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