Title : ( Bayesian Nonparametric Estimation of Distribution Function for Length-Biased Data )
Authors: Najmeh Nakhaei Rad , Vahid Fakoor ,
Full TextAbstract
The length-biased sampling occurs when an appropriate sampling schemeis absent. Then units are chosen at a rate proportional to their length. As a result,the greater values have more chances to be selected. When observations are notcoming directly from the distribution of interest, but from a length biased version,Cox (1969) proposed an estimator for distribution function which plays the samerole as the empirical distribution for direct data. In this paper, by using Bayesiannonparametric approach the estimation of distribution function is derived underlength bias and its consistency is also discussed. A simulation study is presented aswell as a real data example to illustrate obtained results.
Keywords
, Bayesian nonparametric inference; Dirichlet process; Length, biased data; Monte Carlo method
@inproceedings{paperid:1076514,
author = {نجمه نخعی راد and Fakoor, Vahid},
title = {Bayesian Nonparametric Estimation of Distribution Function for Length-Biased Data},
booktitle = {The 12thSeminar On Probability and Random Processes},
year = {2019},
location = {سمنان, IRAN},
keywords = {Bayesian nonparametric inference; Dirichlet process; Length-biased data; Monte Carlo method},
}
%0 Conference Proceedings
%T Bayesian Nonparametric Estimation of Distribution Function for Length-Biased Data
%A نجمه نخعی راد
%A Fakoor, Vahid
%J The 12thSeminar On Probability and Random Processes
%D 2019
