compute_forall: Compute the FAR for all the models
In thaos/FARallnat: FAR analysis on European Summer Temperature

Description Usage Arguments Value Examples

compute_forall computes the FAR evolution for all models according to the compute_far function taken as an argument. if the argument p is provided, it also computes the evolution of the corresponding quantile.

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compute_forall(compute_far, l_models = NULL, xp = 1.6, p = NULL,
  y = "eur_tas", x = "gbl_tas", time = "year", ci_p = 0.9,
  res_folder = deparse(substitute(compute_far)), ...)

`compute_far`	a function used to compute the FAR
`l_models`	a character vectors giving the list of models for which the FAR needs to be computed. by default all models present in this packages are used
`xp`	the selected threshold used to define the FAR
`p`	the selected probability of exceedance to define the corresponding quantile
`y`	the name of the variable that will be used as y in the compute_far function
`x`	the name of the variable that will be used as the covariate x in the compute_far function
`time`	the name of the variable that will be used as the time variable in the compute_far function
`ci_p`	the level of the confidence intervals
`res_folder`	the folder where the results of compute_far for each model are saved as .rds. By default, creates a folder the name of which is the name of the function compute_far
`...`	additional parameters needed in the compute_far function if required

return a dataframe with the confidence intervals for the FAR and all the other computed parameters (e.g, p and q) at each time

# compute the FAR for the CNRM and the IPSL GCMs using a  gam decomposition
# and a gaussian fit with only three bootstrap samples
ans <- compute_forall(compute_far.default, stat_model=gauss_fit, p=0.01, R=3)
# same with ebm decompositon and a gpd fit over the 90% quantil
ans <- compute_forall(compute_far.dx_ebm_fit, l_models=c("cnrm", "ipsl"), stat_model=gpd_fit, qthreshold =0.90, p=0.01, R=3)