fitGwexModel: fitGwexModel: fit a GWex model to observations.

In GWEX: Multi-Site Stochastic Models for Daily Precipitation and Temperature

fitGwexModel: fit a GWex model to observations.

Description

fitGwexModel: fit a GWex model to observations.

Usage

fitGwexModel(objGwexObs, parMargin = NULL, listOption = NULL)

Arguments

objGwexObs	an object of class GwexObs
parMargin	(not required for temperature) list parMargin where and each element corresponds to a month (1...12) and contains a matrix nStation x 3 of pre-estimated parameters of the marginal distributions (EGPD or Mixture of Exponentials)
listOption	for precipitation, a list with the following fields: th: threshold value in mm above which precipitation observations are considered to be non-zero (=0.2 by default) nLag: order of the Markov chain for the transitions between dry and wet states (=2 by default) typeMargin: 'EGPD' (Extended GPD) or 'mixExp' (Mixture of Exponentials). 'mixExp' by default copulaInt: 'Gaussian' or 'Student': type of dependence for amounts (='Gaussian' by default) isMAR: logical value, do we apply a Autoregressive Multivariate Autoregressive model (order 1) = FALSE by default is3Damount: logical value, do we apply the model on 3D-amount. =FALSE by default nChainFit: integer, length of the runs which are generated during the fitting procedure. =100000 by default nCluster: integer, number of clusters which can be used for the parallel computation and for temperature, a list with the following fields: hasTrend: logical value, do we fit a linear trend for the long-term change, =FALSE by default objGwexPrec: object of class GwexObs containing precipitation observations. If provided, we assume that temperature must be modelled and simulated according to the precipitation states 'dry' and 'wet'. For each state, a seasonal cycle is fitted (mean and sd). typeMargin: 'SGED' (default) or 'Gaussian': type of marginal distribution. depStation: 'MAR1' (default) or 'Gaussian': MAR1 (Multivariate Autoregressive model order 1) for the spatial and temporal dependence or 'Gaussian' for the spatial dependence only.

Value

Return an object of class GwexFit with:

• p: The number of station,

• version: package version,

• variable: the type of variable,

• fit: a list containing the list of options listOption and the list of estimated parameters listPar.

Author(s)

Guillaume Evin

Examples

# Format dates corresponding to daily observations of precipitation and temperature
vecDates = seq(from=as.Date("01/01/2005",format="%d/%m/%Y"),
to=as.Date("31/12/2014",format="%d/%m/%Y"),by='day')

###############################################################
#               FIT THE PRECIPITATION MODEL
###############################################################

# Format observations: create a Gwex object for one station only to show a quick
# example. The syntax is similar for multi-site applications.
myObsPrec = GwexObs(variable='Prec',date=vecDates,obs=dailyPrecipGWEX[,1,drop=FALSE])

# Fit precipitation model with a threshold of 0.5 mm to distinguish wet and dry 
# states (th) and keep default options otherwise, e.g. a Gaussian
# copula for the spatial dependence (copulaInt) and a mixExp distribution for 
# marginal intensities ('typeMargin')
myParPrec = fitGwexModel(myObsPrec,listOption=list(th=0.5))
myParPrec # print object

###############################################################
#     FIT THE TEMPERATURE MODEL, COND. TO PRECIPITATION
###############################################################
# Format observations: create a G-Wex object
myObsTemp = GwexObs(variable='Temp',date=vecDates,obs=dailyTemperGWEX)

# Fit temperature model with a long-term linear trend ('hasTrend'), Gaussian margins 
# ('typeMargin') and Gaussian spatial dependence ('depStation')
myParTemp = fitGwexModel(myObsTemp,listOption=list(hasTrend=TRUE,typeMargin='Gaussian',
depStation='Gaussian'))
myParTemp # print object

GWEX documentation built on Nov. 8, 2023, 5:06 p.m.