Maximum Approximate Likelihood Estimation in Accelerated Failure Time Model for Interval-Censored Data

2019/11/16 by Zhong Zhen Guan, Guan, Zhong
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #FOS: Mathematics #Statistical Distribution Estimation and Applications #Statistical Methods and Inference #Statistics Theory (math.ST)

paper · pdf · doi:10.48550/arxiv.1911.07087

openalex publication_date 2019/11/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

The approximate Bernstein polynomial model, a mixture of beta distributions, is applied to obtain maximum likelihood estimates of the regression coefficients, and the baseline density and survival functions in an accelerated failure time model based on interval censored data including current status data. The rate of convergence of the proposed estimates are given under some conditions for uncensored and interval censored data. Simulation shows that the proposed method is better than its competitors. The proposed method is illustrated by fitting the Breast Cosmetic Data using the accelerated failure time model.

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