Description Usage Arguments Details Examples
Compute the confidence intervales for the probability of exceeding xp at time t using resampling bootstrap.
1 2 3 4 5 |
object |
an object of class gauss_fit, gev_fit, gpd_fit or of class trans. If object is of class trans, the argument y_fit must be passed. |
... |
Arguments to be passed to methods, |
xp |
the threshold used to compute the probability of exeeding that threshold. |
t |
the time t to compute the probability of exeeding xp. If the time t0 is not present in dataset used for fitting the model, the closes time of the dataset is used. |
ci_p |
the confidence level of the confidence intervals (between 0 and 1). |
use_init |
whether to use the parameters fitted in object of class gauss_fit, gev_fit, or gpd_fit, to initialize the fir on the bootstrap sample. |
R |
the number of bootstrap samples. |
Resamplin bootstrap is done by drawing with replacement points (which are at least pairs of date and time serie value) to reconstruct a bootstrap time series. Thus, in the bootstraped sample, there might be dates with no points and dates with several points.
1 2 3 4 5 6 7 8 9 10 11 12 | data(tas)
ge_fit <- gev_fit(eur_tas, data=tas, mu_mod=~gbl_tas, sig_mod=~gbl_tas, time_var="year")
gp_fit <- gpd_fit(eur_tas, data=tas, mu_mod=~gbl_tas, sig_mod=~gbl_tas, time_var="year", qthreshold=0.9)
ga_fit <- gauss_fit(eur_tas, data=tas, mu_mod=~gbl_tas, sig_mod=~gbl_tas, time_var="year")
t1 <- 2003
t0 <- 1990
xp <- 1.6
b_gpd <- boot_p(gp_fit, xp, t0, ci_p=0.95, under_threshold=TRUE)
b_gev <- boot_p(ge_fit, xp, t0, ci_p=0.95)
b_gauss <- boot_p(ga_fit, xp, t0, ci_p=0.95)
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