• Title/Summary/Keyword: Likelihood

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Efficient Quasi-likelihood Estimation for Nonlinear Time Series Models and Its Application

  • Kim, Sahmyeong;Cha, Kyungyup;Lee, Sungduck
    • Communications for Statistical Applications and Methods
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    • v.10 no.1
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    • pp.101-113
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    • 2003
  • Quasi likelihood estimators defined by Wedderburn are derived for several nonlinear time series models. And also, the least squared estimator and Quasi-likelihood estimator are compared in sense of asymptotic relative efficiency at those models. Finally, we apply these estimations to a real data on exchanging rate and stock market prices.

Likelihood Function of Order Statistic with a Weibull Distribution (와이벌분포를 갖는 순위설계량의 우도함수)

  • Seo Nam-Su
    • Journal of the military operations research society of Korea
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    • v.9 no.2
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    • pp.39-43
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    • 1983
  • In this paper, we derive the likelihood function for the independent random order statistic whose underlying lifetime distribution is a two parameter Weibull form. For this purpose we first discuss the order statistic which represent a characteristic feature of most life and fatigue tests that they give rise to ordered observations. And, we describe the properties of the underlying Weibull model. The derived likelihood function is essential for establishing the statistical life test plans in the case of Weibull distribution using a likelihood ratio method.

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Notes on the Comparative Study of the Reliability Estimation for Standby System with Rayleigh Lifetime Distribution

  • Kim, Hee-Jae
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.1
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    • pp.239-250
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    • 2004
  • We shall propose maximum likelihood, Bayesian and generalized maximum likelihood estimation for the reliability of the two-unit hot standby system with Rayleigh lifetime distribution that switch is perfect. Each estimation will be compared numerically in terms of various mission times, parameter values and asymptotic relative efficiency through Monte Carlo simulation.

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Likelihood Based Confidence Intervals for the Common Scale Parameter in the Inverse Gaussian Distributions

  • Lee, Woo-Dong;Cho, Kil-Ho;Cha, Young-Joon;Ko, Jung-Hwan
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.3
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    • pp.963-972
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    • 2006
  • This paper focuses on the likelihood based confidence intervals for two inverse gaussian distributions when the parameter of interest is common scale parameter. Confidence intervals based on signed loglikelihood ratio statistic and modified signed loglikelihood ratio statistics will be compared in small sample through an illustrative simulation study.

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Tests For and Against a Positive Dependence Restriction in Two-Way Ordered Contingency Tables

  • Oh, Myongsik
    • Journal of the Korean Statistical Society
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    • v.27 no.2
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    • pp.205-220
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    • 1998
  • Dependence concepts for ordered two-way contingency tables have been of considerable interest. We consider a dependence concept which is less restrictive than likelihood ratio dependence and more restrictive than regression dependence. Maximum likelihood estimation of cell probability under this dependence restriction is studied. The likelihood ratio statistics for and against this dependence are proposed and their large sample distributions are derived. A real data is analyzed to illustrate the estimation and testing procedures.

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The Effect of Population-Level Learning on Entry Likelihood in the Mobile Game Industry

  • Seong, Dusan;Kim, Sahangsoon
    • Asia Marketing Journal
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    • v.21 no.4
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    • pp.77-89
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    • 2020
  • Population-level learning has traditionally been used to provide an explanation for the underlying mechanism of industry change. But it has yet to examine the impact on strategic decisions such as market entry. This conceptual paper aims to provide an insight into how population-level learning affects entry likelihood by acting as a tool for interpreting population-level changes. We study this in the context of the fast-paced mobile gaming industry where population-level information is salient and develop a set of propositions with regard to the likelihood of entry.

Assessment of the uncertainty in the SWAT parameters based on formal and informal likelihood measure (정형·비정형 우도에 의한 SWAT 매개변수의 불확실성 평가)

  • Seong, Yeon Jeong;Lee, Sang Hyup;Jung, Younghun
    • Journal of Korea Water Resources Association
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    • v.52 no.11
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    • pp.931-940
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    • 2019
  • In hydrologic models, parameters are mainly used to reflect hydrologic elements or to supplement the simplified models. In this process, the proper selection of the parameters in the model can reduce the uncertainty. Accordingly, this study attempted to quantify the uncertainty of SWAT parameters using the General Likelihood Uncertainty Estimation (GLUE). Uncertainty analysis on SWAT parameters was conducted by using the formal and informal likelihood measures. The Lognormal function and Nash-Sutcliffe Efficiency (NSE) were used for formal and informal likelihood, respectively. Subjective factors are included in the selection of the likelihood function and the threshold, but the behavioral models were created by selecting top 30% lognormal for formal likelihood and NSE above 0.5 for informal likelihood. Despite the subjectivity in the selection of the likelihood and the threshold, there was a small difference between the formal and informal likelihoods. In addition, among the SWAT parameters, ALPHA_BF which reflects baseflow characteristics is the most sensitive. Based on this study, if the range of SWAT model parameters satisfying a certain threshold for each watershed is classified, it is expected that users will have more practical or academic access to the SWAT model.

A Simplified Blind Decision Method of Modulation Type in impaired AWGN Channel Environment (Impaired AWGN 채널에서의 간단한 Blind 변조 신호 구분 방식)

  • Kim, Young-Wan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.1
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    • pp.1-6
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    • 2007
  • In this paper, a simplified new modulation classification method that utilizes likelihood function for received signal in an impaired AWGN channel environment. The proposed method provides the superior to ML method, although the likelihood under the assumption that each modulated signal is sent utilized. On the other hand, the ML method gets the performance characteristics of high computational complexity and weakness to channel impairment such as phase offsets and frequency offsets. The proposed method has lower computational complexity than that of the ML method. Moreover, the proposed method is robust to the channel impairment such as phase offsets and frequency offsets. The correct classification probabilities of the proposed method and the ML method are given for an AWGN channel with phase offsets and frequency offsets, which were simulated with extensive Monte-Carlo simulation. As shown in simulation resole, a more accurate classification performance both in phase offset environment and in frequency offset can be achieved with the low computational complexity of the proposed method.

LIKELIHOOD DISTANCE IN CONSTRAINED REGRESSION

  • Kim, Myung-Geun
    • Journal of applied mathematics & informatics
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    • v.25 no.1_2
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    • pp.489-493
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    • 2007
  • Two diagnostic measures based on the likelihood distance for constrained regression with linear constraints on regression coefficients are derived. They are used for identifying influential observations in constrained regression. A numerical example is provided for illustration.

Regularity of Maximum Likelihood Estimation for ARCH Regression Model with Lagged Dependent Variables

  • Hwang, Sun Y.
    • Journal of the Korean Statistical Society
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    • v.29 no.1
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    • pp.9-16
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    • 2000
  • This article addresses the problem of maximum likelihood estimation in ARCH regression with lagged dependent variables. Some topics in asymptotics of the model such as uniform expansion of likelihood function and construction of a class of MLE are discussed, and the regularity property of MLE is obtained. The error process here is possibly non-Gaussian.

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