• Title/Summary/Keyword: approximate model

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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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Analysis of Nested Case-Control Study Designs: Revisiting the Inverse Probability Weighting Method

  • Kim, Ryung S.
    • Communications for Statistical Applications and Methods
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    • v.20 no.6
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    • pp.455-466
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    • 2013
  • In nested case-control studies, the most common way to make inference under a proportional hazards model is the conditional logistic approach of Thomas (1977). Inclusion probability methods are more efficient than the conditional logistic approach of Thomas; however, the epidemiology research community has not accepted the methods as a replacement of the Thomas' method. This paper promotes the inverse probability weighting method originally proposed by Samuelsen (1997) in combination with an approximate jackknife standard error that can be easily computed using existing software. Simulation studies demonstrate that this approach yields valid type 1 errors and greater powers than the conditional logistic approach in nested case-control designs across various sample sizes and magnitudes of the hazard ratios. A generalization of the method is also made to incorporate additional matching and the stratified Cox model. The proposed method is illustrated with data from a cohort of children with Wilm's tumor to study the association between histological signatures and relapses.

Free vibration of orthotropic functionally graded beams with various end conditions

  • Lu, Chao-Feng;Chen, W.Q.
    • Structural Engineering and Mechanics
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    • v.20 no.4
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    • pp.465-476
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    • 2005
  • Free vibration of orthotropic functionally graded beams, whose material properties can vary arbitrarily along the thickness direction, is investigated based on the two-dimensional theory of elasticity. A hybrid state-space/differential quadrature method is employed along with an approximate laminate model, which allows us to obtain the semi-analytical solution easily. With the introduction of continuity conditions at each fictitious interface and boundary conditions at the top and bottom surfaces, the frequency equation for an inhomogeneous beam is derived. A completely exact solution of an FGM beam with material constants varying in exponential way through the thickness is also presented, which serves a benchmark to verify the present method. Numerical results are performed and discussed.

On Information Criteria in Linear Regression Model

  • Park, Man-Sik
    • The Korean Journal of Applied Statistics
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    • v.22 no.1
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    • pp.197-204
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    • 2009
  • In the model selection problem, the main objective is to choose the true model from a manageable set of candidate models. An information criterion gauges the validity of a statistical model and judges the balance between goodness-of-fit and parsimony; "how well observed values ran approximate to the true values" and "how much information can be explained by the lower dimensional model" In this study, we introduce some information criteria modified from the Akaike Information Criterion (AIC) and the Bayesian Information Criterion(BIC). The information criteria considered in this study are compared via simulation studies and real application.

Bayesian Analysis for Multiple Capture-Recapture Models using Reference Priors

  • Younshik;Pongsu
    • Communications for Statistical Applications and Methods
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    • v.7 no.1
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    • pp.165-178
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    • 2000
  • Bayesian methods are considered for the multiple caputure-recapture data. Reference priors are developed for such model and sampling-based approach through Gibbs sampler is used for inference from posterior distributions. Furthermore approximate Bayes factors are obtained for model selection between trap and nontrap response models. Finally one methodology is implemented for a capture-recapture model in generated data and real data.

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A Study on Adaptation of Neural Network to Warren Truss Design (와렌 트러스 설계에의 신경망 적용에 관한 연구)

  • Shin, Dong Cheol;Lee, Seung Chang;Cho, Young Sang
    • Journal of Korean Society of Steel Construction
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    • v.15 no.4 s.65
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    • pp.413-422
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    • 2003
  • Most engineers tend to rely on their intuition or existing data in formulating structural design or preliminary estimate of various conditions. Because of these variations, the artificial neural network is used as an alternative design model of the warren truss since it can handle uncertainty through the probability method. This research validated the approximate structural design model of the warren truss, with its proper parameter values of the neural network and design process falling within 10 percent torrence of the different designs that resulted between this model and the MIDAS program. The suggested model for the process was adapted for the truss design using the member section table, while time saving and efficiency are based on the allowed range of torrence.

Numerical Simulation of Solute Transport in Coastal Areas (해안지역에서의 용존성 물질의 이송확산 거동 수치모의)

  • Kim, Dae-Hong
    • Ecology and Resilient Infrastructure
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    • v.1 no.1
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    • pp.1-7
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    • 2014
  • In this study, a numerical simulation technique for coastal area where wave and current interactions are observed is proposed. Considering the spatial scale of coastal area and the coastal processes such as wave, current, shoaling, wave breaking, and inundation processes, boussinesq equation model is used. A depth-integrated transport model based on the consistent assumption with the boussinesq equation model is used for the prediction of solute transport. To solve the equations, finite volume method with an approximate riemann solver is used. The proposed model is applied to a coastal area and reasonable computational results are obtained.

The Study on the Effect of Loading Condition on Ship Manoeuvrability (흘수변화가 선박 조종 성능에 미치는 영향에 관한 연구)

  • Im, Nam-Kyun;Kweon, Suk-Am;Kim, Se-Eun
    • Journal of the Society of Naval Architects of Korea
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    • v.42 no.2 s.140
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    • pp.105-112
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    • 2005
  • IMO standards for ship manoeuvrability were applied from January 1, 2004. Though model test or sea trial in full load condition is needed, it is not always possible to get such data for every ships. Therefore it is required to study the effect of loading conditions on ship manoeuvrability. Approximate formulae to estimate the hydrodynamic forces acting on a ship and the 2nd overshoot angle of $10^{\circ}$/$10^{\circ}$ zig-zag test in certain loading condition are proposed in this study These were derived from the results of model test and sea trial data. Captive model tests for 7 ships with 15 different loading conditions and sea trial data including free running test of 6 cases were used. Compared with experiment data and prediction formulae already proposed by others, the approximate formulae in this study show good agreement with model test results.

An Efficient Model Based on Smoothed ℓ0 Norm for Sparse Signal Reconstruction

  • Li, Yangyang;Sun, Guiling;Li, Zhouzhou;Geng, Tianyu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.4
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    • pp.2028-2041
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    • 2019
  • Compressed sensing (CS) is a new theory. With regard to the sparse signal, an exact reconstruction can be obtained with sufficient CS measurements. Nevertheless, in practical applications, the transform coefficients of many signals usually have weak sparsity and suffer from a variety of noise disturbances. What's worse, most existing classical algorithms are not able to effectively solve this issue. So we proposed an efficient algorithm based on smoothed ${\ell}_0$ norm for sparse signal reconstruction. The direct ${\ell}_0$ norm problem is NP hard, but it is unrealistic to directly solve the ${\ell}_0$ norm problem for the reconstruction of the sparse signal. To select a suitable sequence of smoothed function and solve the ${\ell}_0$ norm optimization problem effectively, we come up with a generalized approximate function model as the objective function to calculate the original signal. The proposed model preserves sharper edges, which is better than any other existing norm based algorithm. As a result, following this model, extensive simulations show that the proposed algorithm is superior to the similar algorithms used for solving the same problem.

STABILITY OF POSITIVE PERIODIC NUMERICAL SOLUTION OF AN EPIDEMIC MODEL

  • Kim, Mi-Young
    • Korean Journal of Mathematics
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    • v.13 no.2
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    • pp.149-159
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    • 2005
  • We study an age-dependent s-i-s epidemic model with spatial diffusion. The model equations are described by a nonlinear and nonlocal system of integro-differential equations. Finite difference methods along the characteristics in age-time domain combined with finite elements in the spatial variable are applied to approximate the solution of the model. Stability of the discrete periodic solution is investigated.

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