• Title/Summary/Keyword: exponential estimator

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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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    • v.4 no.3
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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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Estimation of Reliability for a Parallel System with Dependent Exponential Components (종속 지수 성분을 가지는 병렬시스템의 신뢰도 추정)

  • 안정향;윤상철
    • Journal of Korea Society of Industrial Information Systems
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    • v.8 no.4
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    • pp.94-100
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    • 2003
  • In this paper, we study the estimation of reliability function for a parallel system with k dependent exponential components. We assume that the failure of one of the k components changes the life distribution of the remaining components. Also, we compare with Cramer-Rna lower bound for variances of the minimum variance unbiased estimator, and the mean square errors of the maximum likelihood estimator of reliability system with the through the Monte Carlo simulation.

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Determination of Minimum Eigenvalue in a Continuous-time Weighted Least Squares Estimator (연속시간 하중최소자승 식별기의 최소고우치 결정)

  • Kim, Sung-Duck
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.41 no.9
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    • pp.1021-1030
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    • 1992
  • When using a least squares estimator with exponential forgetting factor to identify continuous-time deterministic system, the problem of determining minimum eigenvalue is described in this paper. It is well known fact that the convergence rate of parameter estimates relies on various factors consisting of the estimator and especially, theirproperties can be directly affected by all eigenvalues in the parameter error differential equation. Fortunately, there exists only one adjusting eigenvalue in the given estimator and then, the parameter convergence rates depend on this minimum eigenvalue. In this note, a new result to determine the minimum eigenvalue is proposed. Under the assumption that the input has as many spectral lines as the number of parameter estimates, it can be proven that the minimum eigenvalue converges to a constant value, which is a function of the forgetting factor and the parameter estimates number.

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Estimation for the Exponential ARMA Model (지수혼합 시계열 모형의 추정)

  • Won Kyung Kim;In Kyu Kim
    • The Korean Journal of Applied Statistics
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    • v.7 no.2
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    • pp.239-248
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    • 1994
  • The Yule-Walker estimator and the approximate conditional least squares estimator of the parameter of the EARMA(1, 1) model are obtained. These two estimators are compared by simulation study. It is shown that the approximate conditional least squares estimator is better in the sense of the mean square error than the Yul-Walker estimator.

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Multivariate Rotation Design for Population Mean in Sampling on Successive Occasions

  • Priyanka, Kumari;Mittal, Richa;Kim, Jong-Min
    • Communications for Statistical Applications and Methods
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    • v.22 no.5
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    • pp.445-462
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    • 2015
  • This article deals with the problem of estimation of the population mean in presence of multi-auxiliary information in two occasion rotation sampling. A multivariate exponential ratio type estimator has been proposed to estimate population mean at current (second) occasion using information on p-additional auxiliary variates which are positively correlated to study variates. The theoretical properties of the proposed estimator are investigated along with the discussion of optimum replacement strategies. The worthiness of proposed estimator has been justified by comparing it to well-known recent estimators that exist in the literature of rotation sampling. Theoretical results are justified through empirical investigations and a detailed study has been done by taking different choices of the correlation coefficients. A simulation study has been conducted to show the practicability of the proposed estimator.

ON THE EXISTENCE OF THE TWEEDIE POWER PARAMETER IMPLICIT ESTIMATOR

  • Ghribi, Abdelaziz;Hassin, Aymen;Masmoudi, Afif
    • Bulletin of the Korean Mathematical Society
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    • v.59 no.4
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    • pp.979-991
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    • 2022
  • A special class of exponential dispersion models is the class of Tweedie distributions. This class is very significant in statistical modeling as it includes a number of familiar distributions such as Gaussian, Gamma and compound Poisson. A Tweedie distribution has a power parameter p, a mean m and a dispersion parameter 𝜙. The value of the power parameter lies in identifying the corresponding distribution of the Tweedie family. The basic objective of this research work resides in investigating the existence of the implicit estimator of the power parameter of the Tweedie distribution. A necessary and sufficient condition on the mean parameter m, suggesting that the implicit estimator of the power parameter p exists, was established and we provided some asymptotic properties of this estimator.

Performance Analysis of Qos over CBQ Estimator (CBQ Estimator을 고려한 QoS 성능 분석)

  • 박우출;박상준;이병호
    • Proceedings of the IEEK Conference
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    • 2000.11a
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    • pp.287-290
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    • 2000
  • This paper analyze link-sharing mechanisms in packet networks based on the hierarchical class based queueing. The CBQ outlines a set of flexible, efficiently implemented gateway mechanisms that can meet a range of service and link-sharing requirements. We have analyzed the Class level(B, C, D) using the EWMA (Exponential Weighted Moving Average) weight value and EWMA average limit value.

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The Estimation of the Coverage Probability in a Redundant System with a Control Module

  • Lim, Jae-Hak
    • Journal of Korea Society of Industrial Information Systems
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    • v.12 no.1
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    • pp.80-86
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    • 2007
  • The concept of the coverage has been played an important role in the area of reliability evaluation of a system. The widely used measures of reliability include the m time between failures, the availability and so on. In this paper, we propose an estimator of the coverage probability in a redundant system with a control unit and investigate some moments of the proposed estimator. And assuming exponential distribution of all units, we conduct a simulation study for calculating the estimates of the coverage probability and its confidence bounds. An example of evaluating the availability of an optical transportation system is illustrated.

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Comparison of Bootstrap Methods for LAD Estimator in AR(1) Model

  • Kang, Kee-Hoon;Shin, Key-Il
    • Communications for Statistical Applications and Methods
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    • v.13 no.3
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    • pp.745-754
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    • 2006
  • It has been shown that LAD estimates are more efficient than LS estimates when the error distribution is double exponential in AR(1) model. In order to explore the performance of LAD estimates one can use bootstrap approaches. In this paper we consider the efficiencies of bootstrap methods when we apply LAD estimates with highly variable data. Monte Carlo simulation results are given for comparing generalized bootstrap, stationary bootstrap and threshold bootstrap methods.

On Optimal Estimates of System Reliability (시스템 신뢰성(信賴性)의 최적추정(最適推定))

  • Kim, Jae-Ju
    • Journal of Korean Society for Quality Management
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    • v.7 no.2
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    • pp.7-10
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    • 1979
  • In this paper the Rao-Blackwell and Lehmann-$Scheff{\acute{e}}$ Theorem are used to drive the minimum variance unbiased estimators of system reliability for a number of distributions when a system consists of n Components whose random life times are assumed to be independent and identically distributed. For the case of a negative exponential life time, we obtain the maximum likelihood estimator of the system reliability and compair it with minimum variance unbiased estimator of the system reliability.

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