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- Zhang, Jia; Chen, Xin
- Computational statistics & data analysis 2019 v.140 pp. 144-154
- covariance; model validation; regression analysis; simulation models
- ... Sufficient dimension reduction is an important branch of dimension reduction, which includes variable selection and projection methods. Most of the sufficient dimension reduction methods are sensitive to outliers and heavy-tailed predictors, and require strict restrictions on the predictors and the response. In order to widen the applicability of sufficient dimension reduction, we propose BCov-SDR ...
- Shen, Pao-sheng; Chen, Hsin-Jen; Pan, Wen-Harn; Chen, Chyong-Mei
- Computational statistics & data analysis 2019 v.140 pp. 74-87
- algorithms; cardiovascular diseases; cohort studies; data collection; models; regression analysis; risk factors; statistical inference; variance
- ... Interval censoring and truncation arise often in cohort studies, longitudinal and sociological research. In this article, we formulate the effects of covariates on left-truncated and mixed case interval-censored (LTIC) data without or with a cure fraction through a general class of semiparametric transformation models. We propose the conditional likelihood approach for statistical inference. For d ...