• Title/Summary/Keyword: empirical process

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Rate of Convergence of Empirical Distributions and Quantiles in Linear Processes with Applications to Trimmed Mean

  • Lee, Sangyeol
    • Journal of the Korean Statistical Society
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    • v.28 no.4
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    • pp.435-441
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    • 1999
  • A 'convergence in probability' rate of the empirical distributions and quantiles of linear processes is obtained. As an application of the limit theorems, a trimmed mean for the location of the linear process is considered. It is shown that the trimmed mean is asymptotically normal. A consistent estimator for the asymptotic variance of the trimmed mean is provided.

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Nonparametric empirical bayes estimation of a distribution function with respect to dirichlet process prior in case of the non-identical components (분포함수의 추정및 응용에 관한연구(Dirichlet Process에 의한 비모수 결정이론을 중심으로))

  • 정인하
    • The Korean Journal of Applied Statistics
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    • v.6 no.1
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    • pp.173-181
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    • 1993
  • Nonparametric empirical Bayes estimation of a distribution function with respect to dirichlet process prior is considered when sample sizes are varying from component to component. Zehnwirth's estimate of $\alpha$(R) is modified to be used in our empirical Bayes problem with non-identical components.

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On the Residual Empirical Distribution Function of Stochastic Regression with Correlated Errors

  • Zakeri, Issa-Fakhre;Lee, Sangyeol
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.291-297
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    • 2001
  • For a stochastic regression model in which the errors are assumed to form a stationary linear process, we show that the difference between the empirical distribution functions of the errors and the estimates of those errors converges uniformly in probability to zero at the rate of $o_{p}$ ( $n^{-}$$\frac{1}{2}$) as the sample size n increases.

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ON THE EMPIRICAL MEAN LIFE PROCESSES FOR RIGHT CENSORED DATA

  • Park, Hyo-Il
    • Journal of the Korean Statistical Society
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    • v.32 no.1
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    • pp.25-32
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    • 2003
  • In this paper, we define the mean life process for the right censored data and show the asymptotic equivalence between two kinds of the mean life processes. We use the Kaplan-Meier and Susarla-Van Ryzin estimates as the estimates of survival function for the construction of the mean life processes. Also we show the asymptotic equivalence between two mean residual life processes as an application and finally discuss some difficulties caused by the censoring mechanism.

A Study on the Differentiation Strategies of Policy Process in governance Using the Case of Gumi City (거버넌스 시대 정책프로세스 차별화 전략 - 구미시 혁신사례를 중심으로 -)

  • Lee, Hong-Hui;Lee, Seung-Hui
    • 한국디지털정책학회:학술대회논문집
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    • 2006.06a
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    • pp.197-204
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    • 2006
  • This paper tried to develop differentiation strategies of policy process in governance. Firstly, we reviewed model of policy making(output-oriented model and process-oriented model, normative or idealistic approach and realistic or empirical approach, rational model and cognitive model etc). Now gumi city is making the policy based on the process-oriented model, realistic or empirical approach, cognitive model. So gumi city was winner the test of provinces innovation in 2005. Therefore, when we make the policy, consider these factor: citizen and public service personnel participate policy making process and control policy quality.

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An Experimental study on Prediction of Back-bead Geometry in Pipeline Using the GMA Welding Process (GMA를 이용한 배관용접의 이면비드 형상예측에 관한 실험적 연구)

  • Kim, Ji-Sun;Kim, Ill-Soo;Na, Hyun-Ho;Lee, Ji-Hye
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.20 no.1
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    • pp.74-80
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    • 2011
  • In this study, a variety of welding experiments were carried out to optimize root-pass welding process using GMA process. Based on the experimental results, optimal welding conditions were selected after analyzing correlation between welding parameters and back-bead geometry. Then, effectiveness of empirical models developed was compared and analyzed, and optimized empirical models were finally developed for predicting back-bead by analyzing the main effect of each factor which affects back-bead geometry and their influence on interaction. Also, functions proper for expressing the surface of back-bead were selected using diverse quadratic functions, and back-bead geometry was visualized using empirical models developed and quadratic functions.

A NOTE ON WEAK CONVERGENCE OF EMPIRICAL PROCESSES FOR A STATIONARY PHI-MIXING SEQUENCE

  • Kim, Tae-Yoon;Kim, Jang-Han;Lee, Tai-Sup
    • Journal of the Korean Statistical Society
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    • v.32 no.2
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    • pp.203-211
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    • 2003
  • A new result of weak convergence of the empirical process is established for a stationary ${\phi}-mixing$ sequence of random variables, which relaxes the existing conditions on mixing coefficients. The result is basically obtained from bounds for even moments of sums of ${\phi}-mixing$ r.v.'s useful for handling triangular arrays with entries decreasing in size.

CENTRAL LIMIT THEOREMS FOR BELLMAN-HARRIS PROCESSES

  • Kang, Hye-Jeong
    • Journal of the Korean Mathematical Society
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    • v.36 no.5
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    • pp.923-943
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    • 1999
  • In this paper we consider functionals of the empirical age distribution of supercritical Bellman-Harris processes. Let f : R+ longrightarrow R be a measurable function that integrates to zero with respect to the stable age distribution in a supercritical Bellman-Harris process with no extinction. We present sufficient conditions for the asymptotic normality of the mean of f with respect to the empirical age distribution at time t.

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EMPIRICAL BAYES ESTIMATION OF RESIDUAL SURVIVAL FUNCTION AT AGE

  • Liang, Ta-Chen
    • Journal of the Korean Statistical Society
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    • v.33 no.2
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    • pp.191-202
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    • 2004
  • The paper considers nonparametric empirical Bayes estimation of residual survival function at age t using a Dirichlet process prior V(a). Empirical Bayes estimators are proposed for the case where both the function ${\alpha}$(0, $\chi$] and the size a(R$\^$+/) are unknown. It is shown that the proposed empirical Bayes estimators are asymptotically optimal at a rate n$\^$-1/, where n is the number of past data available for the present estimation problem. Therefore, the result of Lahiri and Park (1988) in which a(R$\^$+/) is assumed to be known and a rate n$\^$-1/ is achieved, is extended to a(R$\^$+/) unknown case.