• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.915-922
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• 2013

Quantile regression can estimate multiple conditional quantile functions of the response, and as a result, it provide comprehensive information of the relationship between the response and the predictors. However, when estimating several conditional quantile functions separately, two or more estimated quantile functions may cross or overlap and consequently violate the basic properties of quantiles. In this paper, we propose a new stepwise method to estimate multiple non-crossing quantile functions using constraints on the kernel coefficients. A simulation study are presented to demonstrate satisfactory performance of the proposed method.

• Tribology and Lubricants
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• v.39 no.3
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• pp.94-101
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• 2023

Automotive wheel bearings are a critical component of vehicles that support their weight and facilitate rotation. Life and stiffness are significant performance characteristics of wheel bearings. Designing wheel bearings involves finding optimal design variables that satisfy both performances. CO₂ emission reduction and fuel efficiency regulations attribute to the recent increase in design requirements for lightweight and compact automotive parts while maintaining performance. However, achieving a design that maintains performance while reducing weight poses challenges, as performance and weight are generally inversely proportional. In this study, we perform design optimization of automotive wheel bearings considering life and stiffness. We develop a program that calculates the basic rated life and modified rated life based on international standards for evaluating the life of wheel bearings. We develop a regression equation using regression analysis to address the time-consuming stiffness analysis during repetitive analysis. We perform ANOVA and main effect analyses to understand the statistical characteristics of the developed regression equation. Furthermore, we verify its reliability by comparing the predicted and test results. We perform design optimization using the developed life prediction program, stiffness regression equation and weight regression equation. We select bearing specifications and geometry as design variables, weight as the cost function, and life and stiffness as constraints. Through design optimization, we investigate the influence of design variables on the cost function and constraints by comparing the initial and optimal design values.

• Journal of the Korean Home Economics Association
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• v.29 no.3
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• pp.153-174
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• 1991

The purpose of this study is to examine the leisure activities of housewives, to identify the factors that influence leisure activities, and to explore the factors contribute to their life satisfaction. So, this study analyses the effects of econo-demographic and socio-cultural variables and of leisure constraint factors on the leisure activities of housewives. And it deals with how these variables and the leisure activities influence life satisfaction of housewives. For these puoposes, 508 housewives residing in Seoul & Daegu were selected for interviews. For data analysis such statistical methods as ANOVA, t-test, Pearson's correlation, adn Multiple Regression Analysis can be summarised. The main findings of the research are as follows: 1. Leisure acivities are classified in Self-developmental, Home-oriented, Time-consuming, Social and Children-concerned types by the technique of factor analysis. The average particiation level was high in Time-consuming type, but low in Self-developmental type. 2. The participation level of leisure activities shows significant differences by selected variables: The Self-developmental type shows significant differences by housewife's education level, income, husband's occupation, role orientation, home management type and leisure constraints. And Children-concerned type was differed to number of family nember, number of children, age of housewife and age of housewife and age of the youngst child. 3. The preference level of leisure activities differ by housewife's education level, income, husband's occupation, home management type and leisure constraints in the Self-developmental and the Social type. And the preference level of Home-oriented leisure activities was high in the middle class of income and husband's occupation. 4. The preference and participation level of leisure activities show differences. And the variables affecting the differences were housewife's age, education level, home management type, role orientation, leisure constraint factors in the Self-developmental type, and were demographic variables such as number of family member, housewife's age in the Home-oriented type. 5. The variables which affected the level of life satisfaction independently were leisure space, income, the participation level of the Self-developmental and the Social type and the preference level of the Self-developmental type.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.43-53
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• 2014

This study aims to improve the openness of administrative data and to make extensive use of it in the academic and policy development, analyzing the quality requirements as the users' view of administrative data using statistical purposes. Conducted the exploratory analysis on the case of the Transaction-based Price Index of Housing, applying the administrative data of Realestate Transaction Management System in Korea, based on Denmark's 7 quality indicators for the statistical use of administrative data. According to the results of this study, the administrative data could improve the efficacy of the policy by facilitating the collection of the statistical data which help analyzing the actual market situations. On the other hand, the data have some constraints in adding the required items to producing the statistics, or improving the timeliness problem, due to the characteristics focused on the civil service.

• Journal of Environmental Impact Assessment
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• v.15 no.3
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• pp.179-191
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• 2006

The authors argue that the current Government Information System for asthmatics appears to be non-user friendly due to lack of the cartographic representation for the text based statistical data. Acknowledging these constraints, an operational, user-friendly map for asthmatic prevalence has been generated by combining existing statistical data with the administrative Dong boundary map under GIS environment. The Geographical User Interface, in particular, were ideally suited to deriving the major distribution patterns that more asthmatic prevalence tends to be occurred on conventional commercial district and industrial complex. A visual map using spatial modelling technology were generated to show the fact that some degree of increasing or decreasing trends of asthmatic prevalence already exists in the experimental sites. It could be used as an evidence to restrict initiation of development activities causing negative influence to asthma such as road construction. The result of this study would play a crucial role in improving the quality of environmental health information service if it is operationally introduced into the Government since the highly user-friendly interface provides a completely new means for disseminating information for asthmatics in a visual and interactive manner to the general public.

• The Korean Journal of Applied Statistics
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• v.22 no.1
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• pp.75-88
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• 2009

Gross Regional Domestic Product (GRDP) is regarded as an essential information to understand regional economy. However, GRDP is hardly used for establishment of regional economic plan and related statistical research due to its late and yearly publication. Therefore, it is necessary to estimate quarterly GRDP to grasp the current regional economy faster In this study, considering the comovement between GDP and GRDP for the same industry, reference series are made. Quarterly GRDP is estimated the following two steps; First, preliminary quarterly GRDP is estimated using Chow-Lin's method based on the reference series to eliminate temporal discrepancies. Second, preliminary quarterly GRDP is adjusted using Denton's multivariate method to eliminate contemporaneous discrepancies.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.11_12
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• pp.675-681
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• 2005

Noise is used to create realistic animations that look like natural phenomena as well as procedural textures and shapes by adding randomness to graphical applications. In this paper, we suggest a method to edit noise values to satisfy the constraints that reflect the user's demands while maintaining the inherent statistical features of the noise function. Noise editing uses optimization to minimize the difference between the statistical characteristics of the ideal and edited versions of a noise source. Using our editing method, detailed control of animation and shape data that include noise is possible.

• Communications for Statistical Applications and Methods
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• v.15 no.4
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• pp.633-642
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• 2008

Variable selection algorithm for partial least square regression using penalty function is proposed. We use the fact that usual partial least square regression problem can be expressed as a maximization problem with appropriate constraints and we will add penalty function to this maximization problem. Then simulated annealing algorithm can be used in searching for optimal solutions of above maximization problem with penalty functions added. The HARD penalty function would be suggested as the best in several aspects. Illustrations with real and simulated examples are provided.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.17-23
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• 2005

In this paper we consider the well-known semiparametric proportional hazards models for survival analysis. These models are usually used with few covariates and many observations (subjects). But, for a typical setting of gene expression data from DNA microarray, we need to consider the case where the number of covariates p exceeds the number of samples n. For a given vector of response values which are times to event (death or censored times) and p gene expressions(covariates), we address the issue of how to reduce the dimension by selecting the significant genes. This approach enables us to estimate the survival curve when n ${\ll}$p. In our approach, rather than fixing the number of selected genes, we will assign a prior distribution to this number. The approach creates additional flexibility by allowing the imposition of constraints, such as bounding the dimension via a prior, which in effect works as a penalty To implement our methodology, we use a Markov Chain Monte Carlo (MCMC) method. We demonstrate the use of the methodology to diffuse large B-cell lymphoma (DLBCL) complementary DNA (cDNA) data and Breast Carcinomas data.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.10
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• pp.38-47
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• 1998

The syntactic analysis for the practical machine translation should be able to analyze a long sentence, but the long sentence analysis is a critical problem because of its high analysis complexity. In this paper a sentence segmentation method is proposed for an efficient analysis of a long sentence and the method of determining optimal sentence segmentation positions using statistical information and genetic learning is introduced. It consists of two modules: (1) decomposable position determination which uses lexical contextual constraints acquired from a training data tagged with segmentation positions. (2) segmentation position selection by the selection function of which the weights of parameters are determined through genetic learning, which selects safe segmentation positions with enhancing the analysis efficiency as much as possible. The safe segmentation by the proposed sentence segmentation method and the efficiency enhancement of the analysis are presented through experiments.