model_selection_MEV: Find best linear models for MEV distributed data according to...

In SpatialModelsZAMG: Spatial Modeling of Extreme Events

Description

this function calculates the pointwise MEV parameter estimates for each station and finds the best linear models according to Akaike Information Criterion (AIC)

Usage

model_selection_MEV(fitted_par, covariables, plot_station_distr = FALSE)

Arguments

fitted_par	data.frame with MEV parameters w,c,n as columns. Each row corresponds to one station.
covariables	data.frame with covariables for each station. Each row corresponds to one station, columns should include at least 'lon' (longitude), 'lat' (latitude) and 'alt' (altitude).
plot_station_distr	logical value; if TRUE, a plot with the distribution of the used stations for the model selection is generated. default is FALSE

Value

a list with

fitted_par	the given fitted_par matrix
covariables	the given covariables matrix
models	a list of lm-class objects with the best fitted linear models for the MEV parameters: scale_model: scale ~ … , shape_model: shape ~ …

See Also

optimizer_smooth_model_MEV_pwm, optimizer_smooth_model_MEV_mle

SpatialModelsZAMG documentation built on Nov. 11, 2019, 3 p.m.