• Title/Summary/Keyword: hierarchical estimation

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A Bayesian inference for fixed effect panel probit model

  • Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
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    • v.23 no.2
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    • pp.179-187
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    • 2016
  • The fixed effects panel probit model faces "incidental parameters problem" because it has a property that the number of parameters to be estimated will increase with sample size. The maximum likelihood estimation fails to give a consistent estimator of slope parameter. Unlike the panel regression model, it is not feasible to find an orthogonal reparameterization of fixed effects to get a consistent estimator. In this note, a hierarchical Bayesian model is proposed. The model is essentially equivalent to the frequentist's random effects model, but the individual specific effects are estimable with the help of Gibbs sampling. The Bayesian estimator is shown to reduce reduced the small sample bias. The maximum likelihood estimator in the random effects model is also efficient, which contradicts Green (2004)'s conclusion.

Maximum Likelihood Estimation Using Laplace Approximation in Poisson GLMMs

  • Ha, Il-Do
    • Communications for Statistical Applications and Methods
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    • v.16 no.6
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    • pp.971-978
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    • 2009
  • Poisson generalized linear mixed models(GLMMs) have been widely used for the analysis of clustered or correlated count data. For the inference marginal likelihood, which is obtained by integrating out random effects is often used. It gives maximum likelihood(ML) estimator, but the integration is usually intractable. In this paper, we propose how to obtain the ML estimator via Laplace approximation based on hierarchical-likelihood (h-likelihood) approach under the Poisson GLMMs. In particular, the h-likelihood avoids the integration itself and gives a statistically efficient procedure for various random-effect models including GLMMs. The proposed method is illustrated using two practical examples and simulation studies.

An Improving Motion Estimator based on multi arithmetic Architecture (고밀도 성능향상을 위한 다중연산구조기반의 움직임추정 프로세서)

  • Lee, Kang-Whan
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.631-632
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    • 2006
  • In this paper, acquiring the more desirable to adopt design SoC for the fast hierarchical motion estimation, we exploit foreground and background search algorithm (FBSA) base on the dual arithmetic processor element(DAPE). It is possible to estimate the large search area motion displacement using a half of number PE in general operation methods. And the proposed architecture of MHME improve the VLSI design hardware through the proposed FBSA structure with DAPE to remove the local memory. The proposed FBSA which use bit array processing in search area can improve structure as like multiple processor array unit(MPAU).

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Simultaneous modeling of mean and variance in small area estimation

  • Kim, Myungjin;Kim, Dal Ho
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.5
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    • pp.1423-1431
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    • 2016
  • When the sample size in a certain domain is too small to produce adequate information, small area model with random effects is usually used. Also, if we do not consider an inherent pattern which data possess, it considerably affects inference. In this paper, we mainly focus on modeling to handle increased variation of the Current Population Survey (CPS) median income as the Internal Revenue Service (IRS) mean income increases. In a hierarchical Bayesian framework, most estimations are carried out through the Gibbs sampler while the grid method is used to generate parameters from non-standard form. Numerical study indicates that the performance of proposed model is better than that of CPS method in terms of four comparison measurements.

Bayesian estimation for finite population proportions in multinomial data

  • Kwak, Sang-Gyu;Kim, Dal-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.3
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    • pp.587-593
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    • 2012
  • We study Bayesian estimates for finite population proportions in multinomial problems. To do this, we consider a three-stage hierarchical Bayesian model. For prior, we use Dirichlet density to model each cell probability in each cluster. Our method does not require complicated computation such as Metropolis-Hastings algorithm to draw samples from each density of parameters. We draw samples using Gibbs sampler with grid method. We apply this algorithm to a couple of simulation data under three scenarios and we estimate the finite population proportions using two kinds of approaches We compare results with the point estimates of finite population proportions and their standard deviations. Finally, we check the consistency of computation using differen samples drawn from distinct iterates.

Machining Feature Database for CAD/CAPP Integration in Mold Die Manufaturing (사출 금형의 CAD/CAPP 통합을 위한 가공 형상 데이터베이스)

  • 노형민;이진환
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.16 no.2
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    • pp.259-266
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    • 1992
  • For CAD/CAPP integration, part information on not only geometry but also machining characteristics should be delivered and commonly used between designers and process planners. In this study, the machining features, as linking factors of the integration, are represented as the combination of functional features and atomic features and grouped into a hierarchical database. And the feature based modelling approach is used by generating information on the machining features in design stage. These features are drawn by analyzing real decision rules of process planners. The database using the machining features is built and used for application modules of process planning, operation planning and standard time estimation.

Hierarchical Feature Based Block Motion Estimation for Ultrasound Image (초음파 영상을 위한 계층적 특징점 기반 블록 움직임 추출)

  • Shin, Seong-Chul;Kim, Baek-Sop;Bae, Moo-Ho
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.07b
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    • pp.745-747
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    • 2005
  • 본 논문은 연속 초음파 영상으로부터 모자이크 영상을 구하기 위한 특징점 기반 블록 움직임 추출 방법에서 정확도를 높이고 계산 시간을 줄이기 위해 다해상도(multi-resolution)영상을 이용한 계층적 특징점 기반 블록 움직임 추출 방법을 제시하였다. 초음파 영상에서의 Speckle 노이즈의 영향을 줄이기 위해 저해상도의 영상에서 특징점을 추출하고, 계산 시간을 줄이기 위해 저해상도 영상의 추정된 움직임을 고해상도 영상의 움직임 추정에 적용하여 탐색 범위를 줄였다. 그 결과 계산 시간을 개선하면서 모자이크 영상의 정확도를 높일 수 있었다.

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A study on Face Image Classification for Efficient Face Detection Using FLD

  • Nam, Mi-Young;Kim, Kwang-Baek
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2004.05a
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    • pp.106-109
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    • 2004
  • Many reported methods assume that the faces in an image or an image sequence have been identified and localization. Face detection from image is a challenging task because of variability in scale, location, orientation and pose. In this paper, we present an efficient linear discriminant for multi-view face detection. Our approaches are based on linear discriminant. We define training data with fisher linear discriminant to efficient learning method. Face detection is considerably difficult because it will be influenced by poses of human face and changes in illumination. This idea can solve the multi-view and scale face detection problem poses. Quickly and efficiently, which fits for detecting face automatically. In this paper, we extract face using fisher linear discriminant that is hierarchical models invariant pose and background. We estimation the pose in detected face and eye detect. The purpose of this paper is to classify face and non-face and efficient fisher linear discriminant..

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Optimization of preventive maintenance of nuclear safety-class DCS based on reliability modeling

  • Peng, Hao;Wang, Yuanbing;Zhang, Xu;Hu, Qingren;Xu, Biao
    • Nuclear Engineering and Technology
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    • v.54 no.10
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    • pp.3595-3603
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    • 2022
  • Nuclear safety-class DCS is used for nuclear reactor protection function, which is one of the key facilities to ensure nuclear power plant safety, the maintenance for DCS to keep system in a high reliability is significant. In this paper, Nuclear safety-class DCS system developed by the Nuclear Power Institute of China is investigated, the model of reliability estimation considering nuclear power plant emergency trip control process is carried out using Markov transfer process. According to the System-Subgroup-Module hierarchical iteration calculation, the evolution curve of failure probability is established, and the preventive maintenance optimization strategy is constructed combining reliability numerical calculation and periodic overhaul interval of nuclear power plant, which could provide a quantitative basis for the maintenance decision of DCS system.

Enhanced Multiresolution Motion Estimation Using Reduction of One-Pixel Shift (단화소 이동 감쇠를 이용한 향상된 다중해상도 움직임 예측 방법)

  • 이상민;이지범;고형화
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.9C
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    • pp.868-875
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    • 2003
  • In this paper, enhanced multiresolution motion estimation(MRME) using reduction of one-pixel shift in wavelet domain is proposed. Conventional multiresolution motion estimation using hierarchical relationship of wavelet coefficient has difficulty for accurate motion estimation due to shift-variant property by decimation process of the wavelet transform. Therefore, to overcome shift-variant property of wavelet coefficient, two level wavelet transform is performed. In order too reduce one-pixel shift on low band signal, S$_4$ band is interpolated by inserting average value. Secondly, one level wavelet transform is applied to the interpolated S$_4$ band. To estimate initial motion vector, block matching algorithm is applied to low band signal S$_{8}$. Multiresolution motion estimation is performed at the rest subbands in low level. According to the experimental results, proposed method showed 1-2dB improvement of PSNR performance at the same bit rate as well as subjective quality compared with the conventional multiresolution motion estimation(MRME) methods and full-search block matching in wavelet domain.