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- 저자 : Liuquan Sun (검색결과 2 건)
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Regularized estimation in GINAR(p) process
Haixiang Zhang,Dehui Wang,Liuquan Sun 한국통계학회 2017 Journal of the Korean Statistical Society Vol.46 No.4
This article is concerned with the regularized estimation methodology for generalized pthorder integer-valued autoregressive (GINAR(p)) process, especially when the regression coefficients are sparse. Under some mild regularity conditions, we show that the regularized estimators perform as well as if the correct submodel was known. The oracle properties of the estimators are established. Extensive Monte Carlo simulation studies demonstrate that the proposed procedure works well. To illustrate its usefulness, an application to a real data about epileptic patient is also provided.
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Variable selection for semiparametric accelerated failure time models with nonignorable missing data
Liu Tianqing,Yuan Xiaohui,Sun Liuquan 한국통계학회 2024 Journal of the Korean Statistical Society Vol.53 No.1
The regularization approach for variable selection was well developed for semipara- metric accelerated failure time (AFT) models, where the response variable is right censored. In the presence of missing data, this approach needs to be tailored to dif- ferent missing data mechanisms. In this paper, we propose a flexible and generally applicable missing data mechanism for AFT models, which contains both ignorable and nonignorable missing data mechanism assumptions. We propose weighted rank (WR) estimators and corresponding penalized estimators of regression parameters under this missing data mechanism. An advantage of the WR estimators and cor- responding penalized estimators is that they do not require specifying a missing data model for the proposed missing data mechanism. The theoretical properties of the WR and corresponding penalized estimators are established. Comprehensive simulation studies and a real data application further demonstrate the merits of our approach.
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