An Efficient Estimation of the Mean Residual Life Function with Length-Biased Right-Censored Data | Zendy

Hongping Wu | Zendy; Yihui Luan | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

An Efficient Estimation of the Mean Residual Life Function with Length-Biased Right-Censored Data

Author(s) -

Hongping Wu,

Yihui Luan

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/937397

Subject(s) - estimator , monte carlo method , residual , censoring (clinical trials) , statistics , mean squared error , algorithm , function (biology) , random variable , mathematics , computer science , evolutionary biology , biology

The mean residual life (MRL) function for a lifetime random variable T0 is one of the basic parameters of interest in survival analysis. In this paper, we propose a new estimator of the MRL function with length-biased right-censored data and evaluate its performance through a small Monte Carlo simulation study. The results of the simulations show that the proposed estimator outperforms the existing one referred to in Data and Model Setup Section in terms of Monte Carlo bias and mean square error, especially when the censoring rate is heavy. We also show that the proposed estimator converges in distribution under some conditions

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research