20 citations · 57 across the 19 of their papers we have counts for
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Right-censored models on massive data
Gabriela Ciuperca
This article considers the automatic selection problem of the relevant explanatory variables in a right-censored model on a massive database. We propose and study four aggregated c…
Right-censored models by the expectile method
Gabriela Ciuperca
Based on the expectile loss function and the adaptive LASSO penalty, the paper proposes and studies the estimation methods for the accelerated failure time (AFT) model. In this app…
Automatic selection by penalized asymmetric Lq-norm in an high-dimensional model with grouped variables
Angelo Alcaraz, Gabriela Ciuperca
The paper focuses on the automatic selection of the grouped explanatory variables in an high-dimensional model, when the model errors are asymmetric. After introducing the model an…
Change-point Detection by the Quantile LASSO Method
Gabriela Ciuperca, Matúš Maciak
A simultaneous change-point detection and estimation in a piece-wise constant model is a common task in modern statistics. If, in addition, the whole estimation can be performed au…
Change-point detection in a linear model by adaptive fused quantile method
Gabriela Ciuperca, Matus Maciak
A novel approach to quantile estimation in multivariate linear regression models with change-points is proposed: the change-point detection and the model estimation are both perfor…
Variable selection in high-dimensional linear model with possibly asymmetric or heavy-tailed errors
Gabriela Ciuperca
We consider the problem of automatic variable selection in a linear model with asymmetric or heavy-tailed errors when the number of explanatory variables diverges with the sample s…