G_vec

String, either G1, G1_prime, G2_curly, G2 or G2_curly

Numeric, for G1: 1-2; G2: 1-5
(see <a rd-options="" href="/link/G1_fun?package=esreg&version=0.3.1" data-mini-rdoc="esreg::G1_fun">G1_fun</a>, <a rd-options="" href="/link/G1_prime_fun?package=esreg&version=0.3.1" data-mini-rdoc="esreg::G1_prime_fun">G1_prime_fun</a>, <a rd-options="" href="/link/G2_curly_fun?package=esreg&version=0.3.1" data-mini-rdoc="esreg::G2_curly_fun">G2_curly_fun</a>, <a rd-options="" href="/link/G2_fun?package=esreg&version=0.3.1" data-mini-rdoc="esreg::G2_fun">G2_fun</a>, <a rd-options="" href="/link/G2_prime_fun?package=esreg&version=0.3.1" data-mini-rdoc="esreg::G2_prime_fun">G2_prime_fun</a>)

type

Vectorized call to the G1 / G2 functions

internal

Simultaneous modeling of the quantile and the expected shortfall of a response variable given
a set of covariates, see Dimitriadis and Bayer (2017) <arXiv:1704.02213>.

Sebastian Bayer

esreg

Joint Quantile and Expected Shortfall Regression

Timo Dimitriadis

G_vec function

Numeric, for G1: 1-2; G2: 1-5
(see <a rd-options='' href='G1_fun'>G1_fun</a>, <a rd-options='' href='G1_prime_fun'>G1_prime_fun</a>, <a rd-options='' href='G2_curly_fun'>G2_curly_fun</a>, <a rd-options='' href='G2_fun'>G2_fun</a>, <a rd-options='' href='G2_prime_fun'>G2_prime_fun</a>)

G_vec: Vectorized call to the G1 / G2 functions

Description

Usage

Arguments