Using partial probability weighted moments and partial maximum entropy to estimate quantiles from censored samples |
| |
| Authors: | Jian Deng MD Pandey |
| |
| Affiliation: | 1. School of Resources and Safety Engineering, Central South University, Changsha, 410083, China;2. Department of Civil Engineering, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada |
| |
| Abstract: | The maximum entropy principle constrained by probability weighted moments is an useful technique for unbiasedly and efficiently estimating the quantile function of a random variable from a sample of complete observations. However, censored or incomplete data are often encountered in engineering reliability and lifetime distribution analysis. This paper presents a new distribution free method for the estimation of the quantile function of a non-negative random variable using a censored sample of data, which is based on the principle of partial maximum entropy (MaxEnt) in which partial probability weighted moments (PPWMs) are used as constraints. Numerical results and practical examples presented in the paper confirm the accuracy and efficiency of the proposed partial MaxEnt quantile function estimation method for censored samples. |
| |
| Keywords: | Quantile function Censored samples Partial probability weighted moment Partial maximum entropy principle |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
