Bayes Estimation of Parameter of Laplace Distribution Under a New LINEX-Based Loss Function

Lanping Li

doi:doi:10.11648/j.ijdsa.20170306.14

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Bayes Estimation of Parameter of Laplace Distribution Under a New LINEX-Based Loss Function

Lanping Li

Published in International Journal of Data Science and Analysis (Volume 3, Issue 6)

Received: 27 October 2017 Accepted: 29 November 2017 Published: 26 December 2017

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Abstract

Loss function is one of the most topics in Bayesian analysis. The aim of this paper is to study the estimation of the shape parameter of Laplace distribution using Bayesian technique under a new loss function, which is a compound function of LINEX function. The Bayes estimator of the parameter is derived under the prior distribution of the parameter based on Gamma prior distribution. Furthermore, Monte Carlo statistical simulations illustrate that the Bayes estimators obtained under LINEX-based loss function is affected by the prior parameter and the value of the shape parameter of the LINEX-based loss function. But when the sample size is large, they have less influence on the estimation result.

Published in	International Journal of Data Science and Analysis (Volume 3, Issue 6)
DOI	10.11648/j.ijdsa.20170306.14
Page(s)	85-89
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Laplace Distribution, Bayes Estimation, LINEX-Based Loss Function, Prior Distribution

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APA Style

Lanping Li. (2017). Bayes Estimation of Parameter of Laplace Distribution Under a New LINEX-Based Loss Function. International Journal of Data Science and Analysis, 3(6), 85-89. https://doi.org/10.11648/j.ijdsa.20170306.14

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ACS Style

Lanping Li. Bayes Estimation of Parameter of Laplace Distribution Under a New LINEX-Based Loss Function. Int. J. Data Sci. Anal. 2017, 3(6), 85-89. doi: 10.11648/j.ijdsa.20170306.14

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AMA Style

Lanping Li. Bayes Estimation of Parameter of Laplace Distribution Under a New LINEX-Based Loss Function. Int J Data Sci Anal. 2017;3(6):85-89. doi: 10.11648/j.ijdsa.20170306.14

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@article{10.11648/j.ijdsa.20170306.14,
  author = {Lanping Li},
  title = {Bayes Estimation of Parameter of Laplace Distribution Under a New LINEX-Based Loss Function},
  journal = {International Journal of Data Science and Analysis},
  volume = {3},
  number = {6},
  pages = {85-89},
  doi = {10.11648/j.ijdsa.20170306.14},
  url = {https://doi.org/10.11648/j.ijdsa.20170306.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdsa.20170306.14},
  abstract = {Loss function is one of the most topics in Bayesian analysis. The aim of this paper is to study the estimation of the shape parameter of Laplace distribution using Bayesian technique under a new loss function, which is a compound function of LINEX function. The Bayes estimator of the parameter is derived under the prior distribution of the parameter based on Gamma prior distribution. Furthermore, Monte Carlo statistical simulations illustrate that the Bayes estimators obtained under LINEX-based loss function is affected by the prior parameter and the value of the shape parameter of the LINEX-based loss function. But when the sample size is large, they have less influence on the estimation result.},
 year = {2017}
}

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TY  - JOUR
T1  - Bayes Estimation of Parameter of Laplace Distribution Under a New LINEX-Based Loss Function
AU  - Lanping Li
Y1  - 2017/12/26
PY  - 2017
N1  - https://doi.org/10.11648/j.ijdsa.20170306.14
DO  - 10.11648/j.ijdsa.20170306.14
T2  - International Journal of Data Science and Analysis
JF  - International Journal of Data Science and Analysis
JO  - International Journal of Data Science and Analysis
SP  - 85
EP  - 89
PB  - Science Publishing Group
SN  - 2575-1891
UR  - https://doi.org/10.11648/j.ijdsa.20170306.14
AB  - Loss function is one of the most topics in Bayesian analysis. The aim of this paper is to study the estimation of the shape parameter of Laplace distribution using Bayesian technique under a new loss function, which is a compound function of LINEX function. The Bayes estimator of the parameter is derived under the prior distribution of the parameter based on Gamma prior distribution. Furthermore, Monte Carlo statistical simulations illustrate that the Bayes estimators obtained under LINEX-based loss function is affected by the prior parameter and the value of the shape parameter of the LINEX-based loss function. But when the sample size is large, they have less influence on the estimation result.
VL  - 3
IS  - 6
ER  -

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Author Information

Lanping Li

School of Mathematics and Statistics, Hunan University of Finance and Economics, Changsha, China

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APA Style

Lanping Li. (2017). Bayes Estimation of Parameter of Laplace Distribution Under a New LINEX-Based Loss Function. International Journal of Data Science and Analysis, 3(6), 85-89. https://doi.org/10.11648/j.ijdsa.20170306.14

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ACS Style

Lanping Li. Bayes Estimation of Parameter of Laplace Distribution Under a New LINEX-Based Loss Function. Int. J. Data Sci. Anal. 2017, 3(6), 85-89. doi: 10.11648/j.ijdsa.20170306.14

Copy | Download

AMA Style

Lanping Li. Bayes Estimation of Parameter of Laplace Distribution Under a New LINEX-Based Loss Function. Int J Data Sci Anal. 2017;3(6):85-89. doi: 10.11648/j.ijdsa.20170306.14

Copy | Download

@article{10.11648/j.ijdsa.20170306.14,
  author = {Lanping Li},
  title = {Bayes Estimation of Parameter of Laplace Distribution Under a New LINEX-Based Loss Function},
  journal = {International Journal of Data Science and Analysis},
  volume = {3},
  number = {6},
  pages = {85-89},
  doi = {10.11648/j.ijdsa.20170306.14},
  url = {https://doi.org/10.11648/j.ijdsa.20170306.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdsa.20170306.14},
  abstract = {Loss function is one of the most topics in Bayesian analysis. The aim of this paper is to study the estimation of the shape parameter of Laplace distribution using Bayesian technique under a new loss function, which is a compound function of LINEX function. The Bayes estimator of the parameter is derived under the prior distribution of the parameter based on Gamma prior distribution. Furthermore, Monte Carlo statistical simulations illustrate that the Bayes estimators obtained under LINEX-based loss function is affected by the prior parameter and the value of the shape parameter of the LINEX-based loss function. But when the sample size is large, they have less influence on the estimation result.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Bayes Estimation of Parameter of Laplace Distribution Under a New LINEX-Based Loss Function
AU  - Lanping Li
Y1  - 2017/12/26
PY  - 2017
N1  - https://doi.org/10.11648/j.ijdsa.20170306.14
DO  - 10.11648/j.ijdsa.20170306.14
T2  - International Journal of Data Science and Analysis
JF  - International Journal of Data Science and Analysis
JO  - International Journal of Data Science and Analysis
SP  - 85
EP  - 89
PB  - Science Publishing Group
SN  - 2575-1891
UR  - https://doi.org/10.11648/j.ijdsa.20170306.14
AB  - Loss function is one of the most topics in Bayesian analysis. The aim of this paper is to study the estimation of the shape parameter of Laplace distribution using Bayesian technique under a new loss function, which is a compound function of LINEX function. The Bayes estimator of the parameter is derived under the prior distribution of the parameter based on Gamma prior distribution. Furthermore, Monte Carlo statistical simulations illustrate that the Bayes estimators obtained under LINEX-based loss function is affected by the prior parameter and the value of the shape parameter of the LINEX-based loss function. But when the sample size is large, they have less influence on the estimation result.
VL  - 3
IS  - 6
ER  -

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