.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)