get_exceedances: Extract compounding threshold exceedances above outer QR...

In gbstat/tailqr: 'Fit Mixture of Quantile Regression and GPDs'

Description

Extract compounding threshold exceedances above outer QR quantiles and GPD quantiles

Usage

get_exceedances(y, dates, df.lf, df.hf, high.taus = NULL, low.taus = NULL,
  bulk.Xb = NULL, tail.Xb = NULL, tail.df.lf = df.lf,
  tail.df.hf = df.hf, bulk.formula = ~b.lf + b.hf + b.lf:b.hf,
  tail.formula = ~b.lf + b.hf + b.lf:b.hf, use.winter.shape = FALSE)

Arguments

y	response vector
dates	vector of dates of each observation
df.lf	natural spline degrees of freedom on date
df.hf	periodic basis spline degrees of freedom on the day of the year
high.taus	Upper quantile thresholds for fitting GPDs and extracting exceedances
low.taus	Lower quantile thresholds for fitting GPDs and extracting exceedances
bulk.Xb	Basis function matrix for bulk of distribution
tail.Xb	Basis function matrix for tails of distribution
tail.df.lf	natural spline degrees of freedom on date for tail
tail.df.hf	periodic basis spline degrees of freedom on the day of the year for tail
bulk.formula	R formula for quantile regression on bulk
tail.formula	R formula for log(scale) GPD parameters in tails
use.winter.shape	(logical) Should a separate shape parameter be fit for the winter and rest?

Value

List containing exceedances above and below the high.taus and low.taus quantiles of the temperature distributions as estimated by QR and GPD models

gbstat/tailqr documentation built on May 8, 2019, 5:42 p.m.