A presmooth estimator of unbiased distributions with length-biased data

Reza Heidari; Vahid Fakoor; Ali Shariati

doi:10.1007/s40096-019-00301-z

A presmooth estimator of unbiased distributions with length-biased data

Reza Heidari, Vahid Fakoor^*, Ali Shariati

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

In this paper, we propose a presmooth product-limit estimator to draw statistical inference on the unbiased distribution function representing the population of interest. The strong consistency of the estimator proposed is investigated. The finite sample performance of the proposed estimator is evaluated using simulation studies. It is observed that the proposed estimator exhibits greater efficiency in comparison with the alternative method in de Uña-Álvarez (Test 11(1):109–125, 2002).

Original language	English
Pages (from-to)	317-323
Number of pages	7
Journal	Mathematical Sciences
Volume	13
Issue number	4
DOIs	https://doi.org/10.1007/s40096-019-00301-z
Publication status	Published - Dec 2019
Externally published	Yes

Keywords

Kaplan–Meier estimator
Length-biased data
Presmooth estimator
Random right censoring

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10.1007/s40096-019-00301-z

Cite this

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abstract = "In this paper, we propose a presmooth product-limit estimator to draw statistical inference on the unbiased distribution function representing the population of interest. The strong consistency of the estimator proposed is investigated. The finite sample performance of the proposed estimator is evaluated using simulation studies. It is observed that the proposed estimator exhibits greater efficiency in comparison with the alternative method in de U{\~n}a-{\'A}lvarez (Test 11(1):109–125, 2002).",

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AU - Fakoor, Vahid

AU - Shariati, Ali

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N2 - In this paper, we propose a presmooth product-limit estimator to draw statistical inference on the unbiased distribution function representing the population of interest. The strong consistency of the estimator proposed is investigated. The finite sample performance of the proposed estimator is evaluated using simulation studies. It is observed that the proposed estimator exhibits greater efficiency in comparison with the alternative method in de Uña-Álvarez (Test 11(1):109–125, 2002).

AB - In this paper, we propose a presmooth product-limit estimator to draw statistical inference on the unbiased distribution function representing the population of interest. The strong consistency of the estimator proposed is investigated. The finite sample performance of the proposed estimator is evaluated using simulation studies. It is observed that the proposed estimator exhibits greater efficiency in comparison with the alternative method in de Uña-Álvarez (Test 11(1):109–125, 2002).

KW - Kaplan–Meier estimator

KW - Length-biased data

KW - Presmooth estimator

KW - Random right censoring

UR - https://www.scopus.com/pages/publications/85119519030

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DO - 10.1007/s40096-019-00301-z

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AN - SCOPUS:85119519030

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VL - 13

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JO - Mathematical Sciences

JF - Mathematical Sciences

IS - 4

ER -

A presmooth estimator of unbiased distributions with length-biased data

Abstract

Keywords

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