• Title/Summary/Keyword: Asymmetric Linex loss

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EMPIRICAL BAYES ESTIMATION OF THE TRUNCATION PARAMETER WITH ASYMMETRIC LOSS FUNCTION USING NA SAMPLES

  • Shi, Yimin;Shi, Xiaolin;Gao, Shesheng
    • Journal of applied mathematics & informatics
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    • v.14 no.1_2
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    • pp.305-317
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    • 2004
  • We construct the empirical Bayes (EB)estimation of the parameter in two-side truncated distribution families with asymmetric Linex loss using negatively associated (NA) samples. The asymptotical optimality and convergence rate of the EB estimation is obtained. We will show that the convergence rate can be arbitrarily close to $O(n^{-q}),\;q\;=\;{\lambda}s(\delta\;-\;2)/\delta(s\;+\;2)$.

A Non-Linear Exponential(NLINEX) Loss Function in Bayesian Analysis

  • Islam, A.F.M.Saiful;Roy, M.K.;Ali, M.Masoom
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.4
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    • pp.899-910
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    • 2004
  • In this paper we have proposed a new loss function, namely, non-linear exponential(NLINEX) loss function, which is quite asymmetric in nature. We obtained the Bayes estimator under exponential(LINEX) and squared error(SE) loss functions. Moreover, a numerical comparison among the Bayes estimators of power function distribution under SE, LINEX, and NLINEX loss function have been made.

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Bayesian Estimation of the Reliability Function of the Burr Type XII Model under Asymmetric Loss Function

  • Kim, Chan-Soo
    • Communications for Statistical Applications and Methods
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    • v.14 no.2
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    • pp.389-399
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    • 2007
  • In this paper, Bayes estimates for the parameters k, c and reliability function of the Burr type XII model based on a type II censored samples under asymmetric loss functions viz., LINEX and SQUAREX loss functions are obtained. An approximation based on the Laplace approximation method (Tierney and Kadane, 1986) is used for obtaining the Bayes estimators of the parameters and reliability function. In order to compare the Bayes estimators under squared error loss, LINEX and SQUAREX loss functions respectively and the maximum likelihood estimator of the parameters and reliability function, Monte Carlo simulations are used.

Bayes Estimation of Stress-Strength System Reliability under Asymmetric Loss Functions

  • Hong, Yeon-Woong
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.3
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    • pp.631-639
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    • 2003
  • Bayes estimates of reliability for the stress-strength system are obtained with respect to LINEX loss function. A reference prior distribution of the reliability is derived and Bayes estimates of the reliability are also obtained. These Bayes estimates are compared with corresponding estimates under squared-error loss function.

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Bayesian Estimation of Shape Parameter of Pareto Income Distribution Using LINEX Loss Function

  • Saxena, Sharad;Singh, Housila P.
    • Communications for Statistical Applications and Methods
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    • v.14 no.1
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    • pp.33-55
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    • 2007
  • The economic world is full of patterns, many of which exert a profound influence over society and business. One of the most contentious is the distribution of wealth. Way back in 1897, an Italian engineer-turned-economist named Vilfredo Pareto discovered a pattern in the distribution of wealth that appears to be every bit as universal as the laws of thermodynamics or chemistry. The present paper proposes some Bayes estimators of shape parameter of Pareto income distribution in censored sampling. Asymmetric LINEX loss function has been considered to study the effects of overestimation and underestimation. For the prior distribution of the parameter involved a number of priors including one and two-parameter exponential, truncated Erlang and doubly truncated gamma have been contemplated to express the belief of the experimenter s/he has regarding the parameter. The estimators thus obtained have been compared theoretically and empirically with the corresponding estimators under squared error loss function, some of which were reported by Bhattacharya et al. (1999).

BAYESIAN AND CLASSICAL INFERENCE FOR TOPP-LEONE INVERSE WEIBULL DISTRIBUTION BASED ON TYPE-II CENSORED DATA

  • ZAHRA SHOKOOH GHAZANI
    • Journal of applied mathematics & informatics
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    • v.42 no.4
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    • pp.819-829
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    • 2024
  • This paper delves into an examination of both non-Bayesian and Bayesian estimation techniques for determining the Topp-leone inverse Weibull distribution parameters based on progressive Type-II censoring. The first approach employs expectation maximization (EM) algorithms to derive maximum likelihood estimates for these variables. Subsequently, Bayesian estimators are obtained by utilizing symmetric and asymmetric loss functions such as Squared error and Linex loss functions. The Markov chain Monte Carlo method is invoked to obtain these Bayesian estimates, solidifying their reliability in this framework.

SOME POINT ESTIMATES FOR THE SHAPE PARAMETERS OF EXPONENTIATED-WEIBULL FAMILY

  • Singh Umesh;Gupta Pramod K.;Upadhyay S.K.
    • Journal of the Korean Statistical Society
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    • v.35 no.1
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    • pp.63-77
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    • 2006
  • Maximum product of spacings estimator is proposed in this paper as a competent alternative of maximum likelihood estimator for the parameters of exponentiated-Weibull distribution, which does work even when the maximum likelihood estimator does not exist. In addition, a Bayes type estimator known as generalized maximum likelihood estimator is also obtained for both of the shape parameters of the aforesaid distribution. Though, the closed form solutions for these proposed estimators do not exist yet these can be obtained by simple appropriate numerical techniques. The relative performances of estimators are compared on the basis of their relative risk efficiencies obtained under symmetric and asymmetric losses. An example based on simulated data is considered for illustration.

RELIABILITY ANALYSIS FOR THE TWO-PARAMETER PARETO DISTRIBUTION UNDER RECORD VALUES

  • Wang, Liang;Shi, Yimin;Chang, Ping
    • Journal of applied mathematics & informatics
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    • v.29 no.5_6
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    • pp.1435-1451
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    • 2011
  • In this paper the estimation of the parameters as well as survival and hazard functions are presented for the two-parameter Pareto distribution by using Bayesian and non-Bayesian approaches under upper record values. Maximum likelihood estimation (MLE) and interval estimation are derived for the parameters. Bayes estimators of reliability performances are obtained under symmetric (Squared error) and asymmetric (Linex and general entropy (GE)) losses, when two parameters have discrete and continuous priors, respectively. Finally, two numerical examples with real data set and simulated data, are presented to illustrate the proposed method. An algorithm is introduced to generate records data, then a simulation study is performed and different estimates results are compared.