Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

The One-Parameter Odd Lindley Exponential Model: Mathematical Properties and Applications

The One-Parameter Odd Lindley Exponential Model: Mathematical Properties and Applications AbstractIn this article, an exponential model with only one shape parameter, whichcan be used in modeling survival data, reliability problems and fatigue lifestudies, is studied. We derive explicit expressions for some of itsstatistical and mathematical quantities including the ordinary moments,generating function, incomplete moments, order statistics, moment ofresidual life and reversed residual life. The model parameter is estimatedby using the maximum likelihood method. A real data application is given toillustrate the flexibility of the model. We assess the performance of themaximum likelihood estimators in terms of biases and mean squared errors bymeans of a simulation study. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Economic Quality Control de Gruyter

The One-Parameter Odd Lindley Exponential Model: Mathematical Properties and Applications

Loading next page...
 
/lp/de-gruyter/the-one-parameter-odd-lindley-exponential-model-mathematical-0IMXhXr6H0
Publisher
de Gruyter
Copyright
© 2017 Walter de Gruyter GmbH, Berlin/Boston
ISSN
1869-6147
eISSN
2367-2404
DOI
10.1515/eqc-2017-0008
Publisher site
See Article on Publisher Site

Abstract

AbstractIn this article, an exponential model with only one shape parameter, whichcan be used in modeling survival data, reliability problems and fatigue lifestudies, is studied. We derive explicit expressions for some of itsstatistical and mathematical quantities including the ordinary moments,generating function, incomplete moments, order statistics, moment ofresidual life and reversed residual life. The model parameter is estimatedby using the maximum likelihood method. A real data application is given toillustrate the flexibility of the model. We assess the performance of themaximum likelihood estimators in terms of biases and mean squared errors bymeans of a simulation study.

Journal

Economic Quality Controlde Gruyter

Published: Jun 1, 2017

References