Resumen de Asymptotic properties of conditional distribution estimator with truncated, censored and dependent data
Han-Ying Liang, Jacobo de Uña Álvarez 
, María del Carmen Iglesias Pérez
In this paper we study the strong and weak convergence with rates for the estimators of the conditional distribution function as well as conditional cumulative hazard rate function for a left truncated and right censored model. It is assumed that the lifetime observations with multivariate covariates form a stationary α-mixing sequence. Also, the almost sure representations and asymptotic normality of the estimators are established. The finite sample performance of the estimators is investigated via simulations.
