Goodness–of–fit tests for quantile regression with missing responses

A. Pérez-González, T. R. Cotos Yáñez, W. González–Manteiga, R. M. Crujeiras

Goodness–of–fit tests for quantile regression models, in the presence of missing observations in the response variable, are introduced and analyzed in this paper. The different proposals are based on the construction of empirical processes considering three different approaches which involve the use of the gradient vector of the quantile function, a linear projection of the covariates (suitable for high-dimensional settings) and a projection of the estimating equations. In addition, for the three proposals, two types of estimators for the null parametric model to be tested are considered. The performance
of the different test statistics is analyzed in an extensive simulation study. An application to real data is also included.

Keywords: goodness–of–fit test, missing data, quantile regression

PO-1 Poster Session
September 4, 2019  10:40 AM
Multifunctional room. Carbonell building

A. García Galindo, O. González Velasco, J. M. Sánchez Santos, J. De Las Rivas Sanz, E. Sánchez Luis

P. Pérez Fernández, A. García Nogales

C. E. Carleos Artime, N. Corral Blanco, S. Álvarez Morán, A. Shatla

P. Román Román, S. Román- Román, J. J. Serrano Pérez, F. Torres Ruiz

I. Morillo, L. Bermúdez, D. Karlis

R. Caballero Águila, A. Hermoso Carazo, J. Linares Pérez

R. Caballero Águila, D. A. Hermoso Carazo, D. J. Linares Pérez

M. J. García-Ligero Ramírez, M. A. Hermoso Carazo, J. Linares Pérez

R. Caballero Águila, M. A. Hermoso Carazo, J. Linares Pérez

J. A. Cristóbal Cristóbal, P. Olave

A. Vaamonde Liste, M. Meijide Vecino, P. Muñoz Dueñas

A. V. García Luengo, I. Oña Casado

R. Mata Crespo

L. Davila Pena, B. Casas Méndez

T. R. Cotos Yáñez, M. A. Mosquera Rodríguez, A. Pérez González, B. Reguengo Lareo

J. García Rodríguez, B. Sinova Fernández, C. E. Carleos Artime

A. García Nogales, P. Pérez Fernández

C. González Martín, A. Sedeño Noda

S. A. Mulema, A. Carrión García