.qrs.prop.fast {fastqrs}R Documentation

qrs.prop.fast

Description

Algorithm 3: algorithm with preprocessing and quantile grid reduction for Quantile Regression with Selection (QRS); propensity score estimated previously.

Usage

.qrs.prop.fast(y, x, prop, w = NULL, Q1, Q2, P = 10, family, gridtheta, m)

Arguments

y

= Dependent variable (N x 1)

x

= Regressors matrix (N x K)

prop

= Propensity score (N x 1)

w

= Sample weights (N x 1)

Q1

= Number of quantiles in reduced grid

Q2

= Number of quantiles in large grid

P

= Number of evaluated values of parameter with large quantile grid

family

= Parametric copula family

gridtheta

= Grid of values for copula parameter (T x 1)

m

= Parameter to select interval of observations in top and bottom groups

Value

beta = Estimated beta coefficients (K x Q2)

theta = Estimated copula parameter

objf_min = Value of objective function at the optimum

b1 = Estimated beta coefficients for the grid of values of the copula parameter with the reduced quantile grid (K x Q1 x T)

objf1 = Value of objective function for the grid of values of the copula parameter with the reduced quantile grid

gridtheta2 = Grid of values for copula parameter selected during the first part of the algorithm (P x 1)

b2 = Estimated beta coefficients for the grid of values of the copula parameter with large quantile grid (K x Q2 x P)

objf2 = Value of objective function for the grid of values of the copula parameter with large quantile grid (P x 1)


[Package fastqrs version 1.0.0 Index]