Estimation of the hazard rate function in the presence of measurement errors

Autor:	Parviz Nasiri, Roghaieh Kheirazar, Abbas Rasouli, Ali Shadrokh
Jazyk:	angličtina
Rok vydání:	2023
Předmět:	hazard rate function additive measurement errors standard deconvolution kernel density estimator mean square error local polynomial estimator Finance HG1-9999 Mathematics QA1-939
Zdroj:	Mathematics and Modeling in Finance, Vol 3, Iss 1, Pp 49-66 (2023)
Druh dokumentu:	article
ISSN:	2783-0578 2783-056X
DOI:	10.22054/jmmf.2023.72868.1084
Popis:	In this article, according to the importance of the hazard rate function criterion in theevaluation of statistical distributions, its estimation methods are presented. Here, we suggestestimators for the hazard rate function. First, we use the standard deconvolution kerneldensity estimator and suggest a plug-in estimator. In the following we investigate asymptoticbehavior of our estimator. For another estimator, we construct the new estimation thehazard rate function according plug-in and CDF. Finally, we consider the performance ofthe suggested estimators by simulation. Mean square error of estimators λˆ(t, p), λˆ(t) and λˆc(t) present in tables 1 till 6.
Databáze:	Directory of Open Access Journals
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