• 제목/요약/키워드: minimum risk estimator

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Estimation for Exponential Distribution under General Progressive Type-II Censored Samples

  • Kang, Suk-Bok;Cho, Young-Suk
    • Journal of the Korean Data and Information Science Society
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    • 제8권2호
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    • pp.239-245
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    • 1997
  • By assuming a general progressive Type-II censored sample, we propose the minimum risk estimator (MRE) and the approximate maximum likelihood estimator (AMLE) of the scale parameter of the one-parameter exponential distribution. An example is given to illustrate the methods of estimation discussed in this paper.

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MRE for Exponential Distribution under General Progressive Type-II Censored Samples

  • Kang, Suk-Bok;Cho, Young-Suk
    • Journal of the Korean Data and Information Science Society
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    • 제9권1호
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    • pp.71-76
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    • 1998
  • By assuming a general progressive Type-II censored sample, we propose the minimum risk estimator (MRE) of the location parameter and the scale parameter of the two-parameter exponential distribution. An example is given to illustrate the methods of estimation discussed in this paper.

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On Estimating the Variance of a Normal Distribution With Known Coefficient of Variation

  • Ray, S.K.;Sahai, A.
    • Journal of the Korean Statistical Society
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    • 제7권2호
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    • pp.95-98
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    • 1978
  • This note deals with the estimations of the variance of a normal distribution $N(\theta,c\theta^2)$ where c, the square of coefficient of variation is assumed to be known. This amounts to the estimation of $\theta^2$. The minimum variance estimator among all unbiased estimators linear in $\bar{x}^2$ and $s^2$ where $\bar{x}$ and $s^2$ are the sample mean and variance, respectively, and the minimum risk estimator in the class of all estimators linear in $\bar{x}^2$ and $s^2$ are obtained. It is shown that the suggested estimators are BAN.

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Bayes and Empirical Bayes Estimation of the Scale Parameter of the Gamma Distribution under Balanced Loss Functions

  • Rezaeian, R.;Asgharzadeh, A.
    • Communications for Statistical Applications and Methods
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    • 제14권1호
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    • pp.71-80
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    • 2007
  • The present paper investigates estimation of a scale parameter of a gamma distribution using a loss function that reflects both goodness of fit and precision of estimation. The Bayes and empirical Bayes estimators rotative to balanced loss functions (BLFs) are derived and optimality of some estimators are studied.

Estimation of the parameters in an Exponential Distribution with Type-II Censoring

  • Suk Bok Kang;Young Soo Suh;Young Suk Cho
    • Communications for Statistical Applications and Methods
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    • 제4권3호
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    • pp.929-941
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    • 1997
  • In this paper, we propose the minimum risk estimator (MRE) and the approximate maximum likelihood estimator (AMLE) of the location and the scale parameters of the two-parameter exponential distribution with Type-II censoring. The MRE's can be derived by minimizing the mean squared error among the class of estimators which include some estimators as special cases. We show that the MRE's are more efficient than the other estimators of the scale and the location parameter in the terms of the mean squared error.

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CONFLICT AMONG THE SHRINKAGE ESTIMATORS INDUCED BY W, LR AND LM TESTS UNDER A STUDENT'S t REGRESSION MODEL

  • Kibria, B.M.-Golam
    • Journal of the Korean Statistical Society
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    • 제33권4호
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    • pp.411-433
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    • 2004
  • The shrinkage preliminary test ridge regression estimators (SPTRRE) based on Wald (W), Likelihood Ratio (LR) and Lagrangian Multiplier (LM) tests for estimating the regression parameters of the multiple linear regression model with multivariate Student's t error distribution are considered in this paper. The quadratic biases and risks of the proposed estimators are compared under both null and alternative hypotheses. It is observed that there is conflict among the three estimators with respect to their risks because of certain inequalities that exist among the test statistics. In the neighborhood of the restriction, the SPTRRE based on LM test has the smallest risk followed by the estimators based on LR and W tests. However, the SPTRRE based on W test performs the best followed by the LR and LM based estimators when the parameters move away from the subspace of the restrictions. Some tables for the maximum and minimum guaranteed efficiency of the proposed estimators have been given, which allow us to determine the optimum level of significance corresponding to the optimum estimator among proposed estimators. It is evident that in the choice of the smallest significance level to yield the best estimator the SPTRRE based on Wald test dominates the other two estimators.

SEQUENTIAL INTERVAL ESTIMATION FOR THE EXPONENTIAL HAZARD RATE WHEN THE LOSS FUNCTION IS STRICTLY CONVEX

  • Jang, Yu Seon
    • Korean Journal of Mathematics
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    • 제21권4호
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    • pp.429-437
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    • 2013
  • Let $X_1$, $X_2$, ${\cdots}$, $X_n$ be independent and identically distributed random variables having common exponential density with unknown mean ${\mu}$. In the sequential confidence interval estimation for the exponential hazard rate ${\theta}=1/{\mu}$, when the loss function is strictly convex, the following stopping rule is proposed with the half length d of prescribed confidence interval $I_n$ for the parameter ${\theta}$; ${\tau}$ = smallest integer n such that $n{\geq}z^2_{{\alpha}/2}\hat{\theta}^2/d^2+2$, where $\hat{\theta}=(n-1)\bar{X}{_n}^{-1}/n$ is the minimum risk estimator for ${\theta}$ and $z_{{\alpha}/2}$ is defined by $P({\mid}Z{\mid}{\leq}{\alpha}/2)=1-{\alpha}({\alpha}{\in}(0,1))$ Z ~ N(0, 1). For the confidence intervals $I_n$ which is required to satisfy $P({\theta}{\in}I_n){\geq}1-{\alpha}$. These estimated intervals $I_{\tau}$ have the asymptotic consistency of the sequential procedure; $$\lim_{d{\rightarrow}0}P({\theta}{\in}I_{\tau})=1-{\alpha}$$, where ${\alpha}{\in}(0,1)$ is given.

산사태 위험도 추정을 위한 지하수위 변동의 추계론적 수치 해석 (A Stochastic Numerical Analysis of Groundwater Fluctuations in Hillside Slopes for Assessing Risk of Landslides)

  • 이인모
    • 한국지반공학회지:지반
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    • 제3권4호
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    • pp.41-54
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    • 1987
  • 본 논문에서는 무한사면에서 강우에 따른 지하수위 변동을 합리적으로 추정할 수 있는 추계론적 수치해석모델이 개발되었다. 특히, 투수계수, 비산출율(Specific Yield) 등의 지하수흐름에 필요한 계수들과 지하암반층의 공간적 변화에 의하여 지하수위가 공간적으로 변하는 효과에 관해 중점적으로 연구하였으며, 이러한 계수들의 공간적 변화를 추정하기 위하여 Kriging 이론을 도입하였다. Kriging 이론은 몇개의 제한된 실측치로부터 실측을 하지 못한 각각의 수치해석 요소에 불편, 최소 분산을 갖는 값들을 추정할 수 있는 방법이다. 사면방향의 일차원 수치해석 모델, Kriging 이론, 1차근사해법을 조합하여 추계론적 1차원 수치해석 프로그램을 개발하였다. 또한 사면방향의 지하수위 변동뿐만 아니라, 횡방향의 변동도 조사하기 위하여 확정론적 2차원 모델도 개발하였다. 한 무한사면에 대하여 개발된 모델을 이용하여 예제해석을 한 결과 투수계수나 비산출율의 공간적 변화뿐만 아니라 지하암반층의 공간에 따른 요철도 지하수위의 공간적 변화에 큰 영향을 미침을 알게 되었다. 또한 지하수위는 사면방향으로 큰 변동을 보일뿐 아니라 횡방향으로의 변동 또한 무시할 수 없을 정도로 큼을 알 수 있었다. 개발된 모델의 결과들은 지하수위 변동에 의한 산사태 위 험도 분석시에 이용될 수 있다.

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