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The goal of esreg is to simultaneously model the quantile and the expected shortfall of a response variable given a set of covariates.

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esreg

The goal of esreg is to simultaneously model the quantile and the Expected Shortfall of a response variable given a set of covariates.

Installation

CRAN (stable release)

You can install the released version from CRAN:

install.packages("esreg")

GitHub (development)

The latest version of the package is under development at GitHub. You can install the development version using these commands:

install.packages("devtools")
devtools::install_github("BayerSe/esreg")

If you are using Windows, you need to install the Rtools for compilation of the codes.

Examples

# Load the esreg package
library(esreg)

# Simulate data from DGP-(2) in the paper
set.seed(1)

x <- rchisq(1000, df = 1)
y <- -x + (1 + 0.5 * x) * rnorm(1000)

# Estimate the model and the covariance
fit <- esreg(y ~ x, alpha = 0.025)
cov <- vcov(object = fit, sparsity = "nid", sigma_est = "scl_sp")

References

A Joint Quantile and Expected Shortfall Regression Framework

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The goal of esreg is to simultaneously model the quantile and the expected shortfall of a response variable given a set of covariates.

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