• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.909-922
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• 2014

This paper reviews Bayesian inference with inequality constraints. It focuses on ⅰ) comparison of models with various inequality/equality constraints on parameters, ⅱ) multiple tests on equalities of parameters when parameters are under inequality constraints, ⅲ) multiple test on equalities of score parameters in models for contingency tables with ordinal categorical variables.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.147-154
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• 2005

본 논문에서는 집단화된 자료의 분위수들을 계산하는 수정된 방법을 제시하였다. 제시된 방법은 각 계급구간 안의 자료들이 그 구간에 걸쳐 균등한 간격으로, 그리고 구간의 중간점에 관하여 대칭으로 분포하고 있다고 가정하고 분위수들을 계산하는 방법이다. 개개의 자료값들이 주어진 자료를 통하여, 제시된 방법과 기존의 방법을 비교하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.12
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• pp.1381-1388
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• 2014

This paper is proposed a wavelet-based the order statistics MAD(Median Absolute Deviation) method of SAR(Synthetic Aperture Radar) image for image enhancement. also The method of compared and defined the threshold the wavelet coefficients using MAD of the wavelet coefficients of the detail subbands was proposed to effectively image enhancement. In order to complement the disadvantage, the threshold of the proposed method sets up the image statistic and excludes the distortion. The hardware design is used FPGA of Xilinx and DSP system for the image enhancement and compressed encoding of the proposed algorithm. Therefore the proposed method is totally verified by comparing with the several other images.

• The Korean Journal of Applied Statistics
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• v.20 no.1
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• pp.147-157
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• 2007

Edge detection has been widely used in computer vision and image processing. We describe a new edge detector based on the robust rank-order test which is a useful alternative to Wilcoxon test. Our method is based on detecting pixel intensity changes between two neighborhoods with a $r{\times}r$ window using an edge-height model to perform effectively on noisy images. Some experiments of our robust rank-order detector with several existing edge detectors are carried out on both synthetic images and real images with and without noise.

• The Korean Journal of Applied Statistics
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• v.18 no.3
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• pp.597-606
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• 2005

The nonresponse in sample survey causes a problem when it comes time to analyze dataset in public-use files where the user has only complete-data methods available and has limited information about the reasons for nonresponse. Recently imputation for nonresponse is becoming a standard approach for handling nonresponse and various imputation methods have been devised . However, most imputation methods concern with continuous traits while many interesting features are measured by binary or ordered categorical scales in sample survey. In this note. an imputation method for ignorable nonresponse in binary or ordered categorical traits is considered.

• Proceedings of the Korean Statistical Society Conference
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• 2001.11a
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• pp.131-136
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• 2001

projection pursuit을 이용하여 이변량 정규분포의 적합도 검정을 위한 통계량을 제안한다. 기본적인 생각은 이변량 정규분포의 가정하에 표준정규분포를 갖는 모든 선형조합을 고려하여 이들의 순서통계량과 이론적인 분위수를 비교하는 것이다. 이와 같이 제안된 통계량은 선형변환에 대해서 불변(invariant)이다. 본 논문에서는 제안된 통계량의 극한분포를 적절한 Gaussian process의 적분으로 표현한다.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.61-70
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• 2014

A randomized block design is a method to apply a treatment into the experimental unit of each block after dividing into several blocks with a binded homogeneous experimental unit. Jonckheere (1964) and Terpstra (1952), Page (1963), Hollander (1967) proposed various methods of ordered alternative in randomized block design. Especially, Page (1963) test is a weighted combination of within block rank sums for ordered alternatives. In this paper, we suggest a new nonparametric method expanding the Page test for an ordered alternative. A Monte Carlo simulation study is also adapted to compare the power of the proposed methods with previous methods.

• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.297-310
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• 2002

Liang and Zeger proposed generalized estimating equations(GEE) for analyzing repeated data which is discrete or continuous. GEE model can be extended to model for repeated categorical data and its estimator has asymptotic multivariate normal distribution in large sample sizes. But GEE is based on large sample asymptotic theory. In this paper, we study the properties of GEE estimators for repeated ordinal data in small sample sizes. We generate ordinal repeated measurements for two groups using two methods. Through Monte Carlo simulation studies we investigate the empirical type 1 error rates, powers, relative efficiencies of the GEE estimators, the effect of unequal sample size of two groups, and the performance of variance estimators for polytomous ordinal response variables, especially in small sample sizes.

• The Korean Journal of Applied Statistics
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• v.26 no.4
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• pp.595-610
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• 2013

Testing of order-restricted alternative hypothesis in $2{\times}k$ contingency tables can be applied to various fields of medicine, sociology, and business administration. Most testing methods have been developed based on a large sample theory. In the case of a small sample size or unbalanced sample size, the Type I error rate of the testing method (based on a large sample theory) is very different from the target point of 5%. In this paper, the exact testing method is introduced in regards to the testing of an order-restricted alternative hypothesis in categorical data (particularly if a small sample size or extreme unbalanced data). Power and exact p-value are calculated, respectively.

• The Korean Journal of Applied Statistics
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• v.3 no.1
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• pp.11-25
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• 1990

The objective of this paper is to propose a nonparametric distribution-free test for ordered alternatives in k crossed factor designs by using the concepts of combined factor and within-blocks ranks. We investigate the asymptotic normality of the proposed test statistic and the Pitman efficiencies. We also compared the small empirical powers of the tests considered in this paper by Monte Carlo study. Thus we can conclude that the proposed test is efficient and robust for the underlying distribution.