• 제목/요약/키워드: Maximum partial likelihood estimator

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Convergence of Score process in the Cox Proportional Hazards Model

  • Hwang, Jin-Soo
    • Journal of the Korean Statistical Society
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    • 제26권1호
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    • pp.117-130
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    • 1997
  • We study the asymptotic behavior of the maximum partial likelihood estimator in the Cox proportional hazards model in the presence of nuisance parameters when the entry of patients is staggered. When entry of patients is simultaneous and there is only one regression parameter in the Cox model, the efficient score process of the partial likelihood is martingale and converges weakly to a time-chnaged Brownian motion. Our problem is to get a similar result in the presence of nuisance parameters when entry of patient is staggered.

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A correction of SE from penalized partial likelihood in frailty models

  • Ha, Il-Do
    • Journal of the Korean Data and Information Science Society
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    • 제20권5호
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    • pp.895-903
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    • 2009
  • The penalized partial likelihood based on restricted maximum likelihood method has been widely used for the inference of frailty models. However, the standard-error estimate for frailty parameter estimator can be downwardly biased. In this paper we show that such underestimation can be corrected by using hierarchical likelihood. In particular, the hierarchical likelihood gives a statistically efficient procedure for various random-effect models including frailty models. The proposed method is illustrated via a numerical example and simulation study. The simulation results demonstrate that the corrected standard-error estimate largely improves such bias.

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Parameter Estimation for an Infinite Dimensional Stochastic Differential Equation

  • Kim, Yoon-Tae
    • Journal of the Korean Statistical Society
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    • 제25권2호
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    • pp.161-173
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    • 1996
  • When we deal with a Hilbert space-valued Stochastic Differential Equation (SDE) (or Stochastic Partial Differential Equation (SPDE)), depending on some unknown parameters, the solution usually has a Fourier series expansion. In this situation we consider the maximum likelihood method for the statistical estimation problem and derive the asymptotic properties (consistency and normality) of the Maximum Likelihood Estimator (MLE).

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On Asymptotic Properties of a Maximum Likelihood Estimator of Stochastically Ordered Distribution Function

  • Oh, Myongsik
    • Communications for Statistical Applications and Methods
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    • 제20권3호
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    • pp.185-191
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    • 2013
  • Kiefer (1961) studied asymptotic behavior of empirical distribution using the law of the iterated logarithm. Robertson and Wright (1974a) discussed whether this type of result would hold for a maximum likelihood estimator of a stochastically ordered distribution function; however, we show that this cannot be achieved. We provide only a partial answer to this problem. The result is applicable to both estimation and testing problems under the restriction of stochastic ordering.

Parameter Estimation for a Hilbert Space-valued Stochastic Differential Equation ?$\pm$

  • Kim, Yoon-Tae;Park, Hyun-Suk
    • Journal of the Korean Statistical Society
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    • 제31권3호
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    • pp.329-342
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    • 2002
  • We deal with asymptotic properties of Maximum Likelihood Estimator(MLE) for the parameters appearing in a Hilbert space-valued Stochastic Differential Equation(SDE) and a Stochastic Partial Differential Equation(SPDE). In paractice, the available data are only the finite dimensional projections to the solution of the equation. Using these data we obtain MLE and consider the asymptotic properties as the dimension of projections increases. In particular we explore a relationship between the conditions for the solution and asymptotic properties of MLE.

Comparison of Change-point Estimators in Hazard Rate Models

  • Kim, Jaehee
    • Communications for Statistical Applications and Methods
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    • 제9권3호
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    • pp.753-763
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    • 2002
  • When there is one change-point in the hazard rate model, a change-point estimator with the partial score process is suggested and compared with the previously developed estimators. The limiting distribution of the partial score process we used is a function of the Brownian bridge. Simulation study gives the comparison of change-point estimators.

Estimator of Mean Residual Life for Some Parametric Families Using Censored Data

  • Cho, Byung Yup;Choi, Kuey Chung;Choi, Sook Hee;Son, Young Nam
    • 품질경영학회지
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    • 제23권2호
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    • pp.80-90
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    • 1995
  • In this paper we consider a new estimator of mean residual life(MRL) under the random censorship model, based on the partial moment of the distribution. The parameters of a partial moment are estimated by its maximum likelihood estimators when the underlying distribution is known. Though the new estimator is not a consistent estimator of the MRL, it is shown to have smaller mean squared error than the well known empirical MRL estimator for a parametric family. We also compare the proposed estimator with some other estimators in terms of MSE for exponential and lognormal distributions using censored data.

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모수족에서 평균 잔여수명의 추정량 (Estimator of the Mean Residual Life for Some Parametric Families)

  • Kuey Chung Choi;Kyung Hyun Nam
    • 응용통계연구
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    • 제7권2호
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    • pp.89-100
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    • 1994
  • 본 논문에서는 평균 잔여수명의 추정에 있어서 Weibull과 gamma 분포의 평균 잔여수명을 구하는데 적분이 쉽게 되지 않으므로 부분적률에 근거한 새로운 추정량을 제시하였으며, 비록 이 추정량은 일치추정량이 아니지만 소표본인 경우에서 일치추정량인 기존의 경험적 추정량보다 평균제곱오차가 작다는 것을 몬테칼로 기법을 써서 보였다.

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