2005.10a
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In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and location parameter of the exponential distribution based on multiply Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error for various censored samples. We also obtain the approximate maximum likelihood estimator (AMLE) of the reliability function by using the proposed estimators. And then we compare the proposed estimators in the sense of the mean squared error.
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We consider the problem of estimating the system reliability noninformative priors when both stress and strength follow generalized gamma distributions. We first derive Jeffreys' prior, group ordering reference priors, and matching priors. We investigate the propriety of posterior distributions and provide marginal posterior distributions under those noninformative priors. We also examine whether the reference priors satisfy the probability matching criterion.
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Data fusion is method to combination data. The purpose of this study is to design and implementation for street fashion information analysis system using data fusion. It can offer variety and actually information because it can fuse image data and survey data for street fashion. Data fusion method exists exact matching method, judgemental matching method, probability matching method, statistical matching method, data linking method, etc. In this study, we use exact matching method. Our system can be visual information analysis of customer's viewpoint because it can analyze both each data and fused data for image data and survey data.
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Multidimensional scaling is a multivariate technique for constructing a configuration of n points in Euclidean space using information about the distances between the objects. This can be done by the singular value decomposition of the data matrix. But it is known that the singular value decomposition is not resistant. In this study, we provide a resistant version of the multidimensional scaling.
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지금의 교실 수업은 토론학습에 익숙한 학생들로 수업에 흥미를 가지는 수업에 관심을 많이 갖고 있으며 수준별 수업을 통한 심화.보충형과 특별 보충과정으로 학생 지도를 하고 있다. 교실마다 수학 학습을 기피하는 현상이 두드려지고 있으며 개인별 수준 차가 더욱 심한 상태라서 학생들에게 동기를 유발하여 수학에 대한 학습 의욕을 고취하고 교실 밖의 학습자를 교실내로 흡수하기 위한 방법론으로 모둠별 돌림수학, 수준별 모둠 구성을 통해 박수를 치기, 구구단을 이용한 학습과 수학 모둠 노래를 통하여 학습동기를 유발하는 학습 모형을 소개한다. 그리고 수행평가나 포트폴리오, 수학 감상문을 통해 동기 유발이 가능한 실제 학습을 개발하여 공교육의 내실화와 창의력을 유발하는 자아실현의 일환으로 신선한 교실 수업의 보탬이 되었으면 한다.
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Data mining technique is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. Clustering is the process of grouping the data into clusters so that objects within a cluster have high similarity in comparison to one another. It has been widely used in many applications, such that pattern analysis or recognition, data analysis, image processing, market research on off-line or on-line and so on. We analyze Gyeongnam social indicator survey data by 2001 using twostep clustering technique for environment information. The twostep clustering is classified as a partitional clustering method. We can apply these twostep clustering outputs to environmental preservation and improvement.
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The Fieller-Creasy problem involves statistical inference about the ratio of two independent normal means. It is difficult problem from either a frequentist or a likelihood perspective. As an alternatives, a Bayesian analysis with noninformative priors may provide a solution to this problem. In this paper, we extend the results of Yin and Ghosh (2001) to unbalanced sample case. We find various noninformative priors such as first and second order matching priors, reference and Jeffreys' priors. The posterior propriety under the proposed noninformative priors will be given. Using real data, we provide illustrative examples. Through simulation study, we compute the frequentist coverage probabilities for probability matching and reference priors. Some simulation results will be given.
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Tweedie (1957a) proposed a method for the analysis of residuals from an inverse Gaussian population paralleling the analysis of variance in normal theory. He called it the analysis of reciprocals. In this paper, we propose a Bayesian model selection procedure based on the fractional Bayes factor for the analysis of reciprocals. Using the proposed model procedures, we compare with the classical tests.
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Mathematical packages have the advantages of symbolic computation and powerful graphics interface in contrast with statistical packages. We can use mathematical packages as a support tool in education of mathematics for statistics.
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본 연구에서는 우리나라 국방 분야의 신뢰성의 제고하기 위한 국방 신뢰성 Master Plan의 구축이 시급하다고 판단하여 우리나라 국방 분야의 신뢰성 업무를 종합하는 기본 계획서인 "국방 신뢰성 Master Plan"을 제안하고자 한다. 이를 통하여 소요제기단계부터 설계 및 개발 단계, 양산 및 유지정비보수 단계, 운용단계에 이르기까지 신뢰성을 적용할 수 있게 됨으로써 무기체계의 작전수행능력 제고는 물론, 무기체계의 성능향상, 무기체계의 개발기간 단축뿐만 아니라 막대한 비용 절감 효과가 기대된다. 또한 무기체계의 각 개발 단계의 주요시점마다 신뢰성의 개념을 적용함으로써 체계의 운용유지비용을 획기적으로 절감할 수 있을 것으로 기대되며, 국산무기체계의 국제경쟁력 향상을 통하여 경제발전에도 크게 기여할 것으로 전망된다.
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In this paper, we consider the problem of testing for parameter change in time series models based on a cusum of squares. Although the test procedure is well-established for the mean and variance in time series models, a general parameter case was not discussed in literatures. Therefore, here we develop the cusum of squares type test for parameter change in a more general framework. As an example, we consider the change of the parameters in an RCA(1) model. Simulation results are reported for illustration.
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본 연구에서는 잡음이 섞인 카오스 시스템으로부터 생성된 자료와 단순한 무질서를 갖는 불규칙한 자료를 구별할 수 있는 고전적인 비모수적 검정을 알아보고, 낮은 차원의 카오스 자료와 무질서한 자료를 구별할 수 있는 위상공간에서의 재구성(reconstruction) 기법을 로지스틱 및 지수 사상을 이용하여 살펴보았다.
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IGARCH and Stochastic Volatility Model(SVM, for short) have frequently provided useful approximations to the real aspects of financial time series. This article is concerned with modeling various Korean financial time series using both IGARCH and Stochastic Volatility Models. Daily data sets with sample period ranging from 2000 and 2004 including KOSPI, KOSDAQ and won-dollar exchange rate are comparatively analyzed using IGARCH and SVM.
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Microarray gene expression technology has applications that could refine diagnosis and therapeutic monitoring as well as improve disease prevention through risk assessment and early detection. Especially, microarray expression data can provide important information regarding specific genes related with metastasis through an appropriate analysis. Various methods for clustering analysis microarray data have been introduced so far. We used twostep clustering fot ascertain metastasis related gene through t-test. Through t-test between two groups for two publicly available medulloblastoma microarray data sets, we intended to find significant gene for metastasis. The paper describes the process in detail showing how the process is applied to clustering analysis and t-test for microarray datasets and how the metastasis-associated genes are explorated.
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In this paper we propose a fuzzy c-regression model based on weighted least squares support vector machine(LS-SVM), which can be used to detect outliers in the switching regression model while preserving simultaneous yielding the estimates of outputs together with a fuzzy c-partitions of data. It can be applied to the nonlinear regression which does not have an explicit form of the regression function. We illustrate the new algorithm with examples which indicate how it can be used to detect outliers and fit the mixed data to the nonlinear regression models.
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An infinite dam with compound Poisson inputs and a state-dependent release rate is considered. We build the Kolmogorov's backward differential equation and solve it to obtain the Laplace transforms of the first exit times for this dam.
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Association rule mining searches for interesting relationships among items in a given large data set. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary threshold measures in association rule; support and confidence and lift. In the case of appling real world to association rules, we have some difficulties in data interpretation because we obtain many rules. In this paper, we develop the model of association rules using latent variables for environmental survey data.
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Recently, the decrease of the number of a high-school graduate influences the number of limit matriculation. Based on the resident registration population, we forecast for the number of a high-school graduate until 2022 year in Daegu city. Most college and universities in Daegu city have to reduce the 37.5% of the number of limit matriculation until 2022 year to avert a disaster by prompt action.
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