Description Usage Arguments Details Value Examples
gev_fit
fits a time serie with a GEV distribution a where the location and scale parameters depend linearly on a set of covariates.
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y |
the time serie to be fitted. |
data |
a data.frame object with where the function looks first for the variables y, time_var and the covariates specified in the mu_mod and sig_mod arguments. |
mu_mod |
a formula defining the covariates the location parameter of the GEV depends linearly on. |
sig_mod |
a formula defining the covariates the scale parameter of the GEV depends linearly on. |
sig_link |
a link function name for the parameter sigma: sig_link(sigma) is a linear function of the covariates. |
time_var |
a variable used to define the time in the time serie. It can also be a string giving the variable name. |
init |
vector of initialization parameter for the minimization of the negative log-likelihood. if NULL, the initialisation is done using the function fevd from the extRemes packages. |
MLE fit of a time serie y using a GEV distribution where the location and the scale parameters depend linearly on a set of covariates. The optimization of the negative log-likelihood is done with the nlminb function in R.
returns an object of class gev_fit. It contains the nlminb output which provides the estimated parameters as well the minimum of the negative log-likelihood. The arguments use to call gev_fit are included in the list as well.
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#Example with the same covariate for the mean and variance parameter
ge_fit <- gev_fit(eur_tas, data=tas, mu_mod=~gbl_tas, sig_mod=~gbl_tas, time_var="year")
# get the values of the mean and variance parameters of the GEV at each time
compute_par(ge_fit, tas)
# plot diagnostic plot of the fit : standardized residuals plots, qqplot, density of fitted vs theorical density, times series ans return levels
plot(ge_fit)
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