• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.83-126
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• 2005

Single-index models have found applications in econometrics and biometrics, where multidimensional regression models are often encountered. Here we propose a nonparametric estimation approach that combines wavelet methods for non-equispaced designs with Bayesian models. We consider a wavelet series expansion of the unknown regression function and set prior distributions for the wavelet coefficients and the other model parameters. To ensure model identifiability, the direction parameter is represented via its polar coordinates. We employ ad hoc hierarchical mixture priors that perform shrinkage on wavelet coefficients and use Markov chain Monte Carlo methods for a posteriori inference. We investigate an independence-type Metropolis-Hastings algorithm to produce samples for the direction parameter. Our method leads to simultaneous estimates of the link function and of the index parameters. We present results on both simulated and real data, where we look at comparisons with other methods.

• Korean Journal of Human Ecology
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• v.23 no.1
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• pp.1-14
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• 2014

The purpose of this study is to examine the effects of gender role attitudes and family service utilization on self-esteem among single parents. This study used data from the seventh wave of Korean Welfare Panel Study and analyzed 90 single parents. Hierarchical multiple regression analyses showed that health status, economic situation, gender role attitudes, and non-monetary family welfare service had significant effects on single parents' self-esteem. Single parents who had higher traditional gender role attitudes show lower levels of self-esteem. Also use of a non-monetary family service increased the levels of self-esteem. However, use of a monetary family service was not significantly associated with the levels of self-esteem. The findings indicate that services and programs to promote single parents' gender role flexibility should be developed. Also, it is necessary to establish a service system to reduce multiple role stress among single parents.

• The Korean Journal of Applied Statistics
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• v.13 no.1
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• pp.189-196
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• 2000

Conjugate prior density families were motivated by considerations of tractability in implementing the Bayesian paradigm. But we consider problem that the conjugate prior p($\Theta$) cannot be used in restriction of the parameter $\Theta$. This article considers the nonconjugate prior problem of hierarchical Poisson model. We demonstrate the use of latent variables for sampling non-standard densities which arise in the context of the Bayesian analysis of non-conjugate by using a Gibbs sampler.

• KIEAE Journal
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• v.3 no.4
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• pp.15-22
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• 2003

Open housing is an emerging, new concept in housing development that combines demand-orientation with environment-friendliness. Its methodology, however, has not been analyzed in a systematic way. In this study, the features of planning method in open housing were analyzed to systematize types of the planning method. The existing planning methods of open housing was reviewed and they can be classified into three approaches such as pattern, module and organization planning. Given three approaches, the existing planning methods of open housing can be sub-classified as follows; free and patterned planning by patterns, modular and non-modular planning by modules, and hierarchical and non-hierarchial planning by organizations. The framework for the typological analysis was made based on the classification and a composite typological system was drawn from the analysis of the existing planning features. The suggested classification of features in open housing is expected to contribute to the clear definition of characteristics on open housing to provide a basis for the concrete realization method, to analyzing problems with the existing planning methods and to providing their solutions.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.69.2-69.2
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• 2016

We study the environmental dependence of the mass-size relation for the most massive early type galaxies (M>$10^{10.7}M_{\odot}$) in the redshift range 0.10~0.15. The sizes of galaxies are measured by non-parametric method. We find that galaxies more massive than $10^{11.1}M_{\odot}$ show the environmental dependence in the mass-size relation. The galaxies with M>$10^{11.1}M_{\odot}$ located in the densest, cluster like environment have larger sizes and extended surface brightness profiles than their counterparts located in a low dense environment. We also find that the environmental dependence of the mass-size relation is more significant for the brightest cluster galaxies (BCGs) than non-BCGs. We use the semi analytic galaxy formation simulation based on the Millennium 1 Simulation for interpretation. Our result can be explained with a hierarchical growth of the most massive galaxies through dissipation-less merger in dense environment.

• Communications for Statistical Applications and Methods
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• v.29 no.3
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• pp.373-391
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• 2022

The distribution of observations in most econometric studies with spatial heterogeneity is skewed. Usually, a single transformation of the data is used to approximate normality and to model the transformed data with a normal assumption. This assumption is however not always appropriate due to the fact that panel data often exhibit non-normal characteristics. In this work, the normality assumption is relaxed in spatial mixed models, allowing for spatial heterogeneity. An inference procedure based on Bayesian mixed modeling is carried out with a multivariate skew-elliptical distribution, which includes the skew-t, skew-normal, student-t, and normal distributions as special cases. The methodology is illustrated through a simulation study and according to the empirical literature, we fit our models to non-life insurance consumption observed between 1998 and 2002 across a spatial panel of 103 Italian provinces in order to determine its determinants. Analyzing the posterior distribution of some parameters and comparing various model comparison criteria indicate the proposed model to be superior to conventional ones.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.5C
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• pp.534-539
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• 2006

In this paper, we propose a new frame prediction filtering technique and a hardware(H/W) architecture for scalable video coding. We try to evaluate MCTF(motion compensated temporal filtering) and hierarchical B-picture which are a technique for eliminate correlation between video frames. Since the techniques correspond to non-causal system in time, these have fundamental defects which are long latency time and large size of frame buffer. We propose a new architecture to be efficiently implemented by reconfiguring non-causal system to causal system. We use the property of a repetitive arithmetic and propose a new frame prediction filtering cell(FPFC). By expanding FPFC we reconfigure the whole arithmetic architecture. After the operational sequence of arithmetic is analyzed in detail and the causality is imposed to implement in hardware, the unit cell is optimized. A new FPFC kernel was organized as simple as possible by repeatedly arranging the unit cells and a FPFC processor is realized for scalable video coding.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.2
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• pp.21-31
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• 1999

This paper presents a new possibility of calculating optimal control for large scale which consist of non-linear dynamic sub-systems using two level hierarchical structures method. And the proposed method is based on the idea of block pulse transformation to simplify the algorithm and its calculation. This algorithm used an expansion around the equilibrium point of the system to fix the second and higher order terms. These terms are compensated for iteratively at the second level by providing a prediction for the states and controls which form of a part of the higher order terms. In this new approach the quadratic penalty terms are not used in the cost function. This allows convergence over a longer time horizon and also provides faster convergence. And the method is applied to the problem of optimization of the synchronous machine. Results show that the new approach is superior to conventional numerical method or other previous algorithm.

• The Korean Journal of Applied Statistics
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• v.16 no.1
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• pp.101-115
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• 2003

Lately there has been much theoretical and applied interest in linear models with non-normal heavy tailed error distributions. Starting Zellner(1976)'s study, many authors have explored the consequences of non-normality and heavy-tailed error distributions. We consider hierarchical models including selection models under a skewed heavy-tailed e..o. distribution proposed originally by Chen, Dey and Shao(1999) and Branco and Dey(2001) with Dirichlet process prior(Ferguson, 1973) in order to use a meta-analysis. A general calss of skewed elliptical distribution is reviewed and developed. Also, we consider the detail computational scheme under skew normal and skew t distribution using MCMC method. Finally, we introduce one example from Johnson(1993)'s real data and apply our proposed methodology.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.3
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• pp.17-30
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• 2000

In this paper, we propose an efficient algorithm to produce 3-D surface model from a set of range data, based on NURBS (Non-Uniform Rational B-Splines) surface fitting technique. It is assumed that the range data is initially unorganized and scattered 3-D points, while their connectivity is also unknown. The proposed algorithm consists of three steps: initial model approximation, hierarchical representation, and construction of the NURBS patch network. The mitral model is approximated by polyhedral and triangular model using K-means clustering technique Then, the initial model is represented by hierarchically decomposed tree structure. Based on this, $G^1$ continuous NURBS patch network is constructed efficiently. The computational complexity as well as the modeling error is much reduced by means of hierarchical decomposition and precise approximation of the NURBS control mesh Experimental results show that the initial model as well as the NURBS patch network are constructed automatically, while the modeling error is observed to be negligible.