2012/02/17_Carla Moreira and Jacobo de Uña (University of Vigo)

February 17th 2012

Faculty of Economic and Business Sciences | Salón de Grados

Nonparametric regression with doubly truncated data

2012/02/17 – 11:15 h | Carla Moreira, University of Vigo.


In this paper nonparametric regression with a doubly truncated response is introduced. Local constant and local linear kernel-type estimators are proposed. Asymptotic expressions for the bias and the variance of the estimators are obtained, showing the deterioration provoked by the random truncation. To solve the crucial problem of bandwidth choice, two different bandwidth selectors based on plug-in and cross-validation ideas are introduced. The performance of both the estimators and the bandwidth selectors is investigated through simulations. A real data illustration is included. The main conclusion is that the introduced regression methods perform satisfactorily in the complicated scenario of random double truncation. This is joint work with Luis F Meria-Machado and Jacobo de Uña-Álvarez.

The Beta-Binomial SGoF method for multiple dependent tests

2012/02/17 – 12:00 h | Jacobo de Uña Álvarez, University of Vigo.


In this paper, a correction of SGoF multitesting method for dependent tests is introduced. The correction is based on the beta-binomial model, and therefore the new method is called Beta-Binomial SGoF. Basic properties of the new method are stated, and its practical implementation is discussed. Besides, the performance of the new method is investigated through simulations. Two real data sets on gene/protein expression levels are deeply analyzed with Beta-Binomial SGoF for illustration purposes. One of the main conclusions is that SGoF strategy may have a large statistical power even in the presence of dependent tests.