• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.633-644
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• 1998

혼합설계의 교호작용에 대한 F 검정이 유효하려면 다표본 구형성(multisample sphericity) 가정과 다변량 정규분포 가정이 만족되어야 한다. F 검정을 실시하기 위한 가정들이 위반된 조건하에서 혼합설계의 교호작용에 대한 검정법들의 1종오류가 비교되었다. 비교된 검정법들은 (1) F 검정(F), (2) 절사평균을 사용한 F 검정($F_T$)(3)$\varepsilon$-수정 F 검정($\varepsilon)$(4) 절사평균을 사용한 $\varepsilon$-수정 F 검정$(\varepsilon_T$) (5) CIGA검정(CIGA), (6) 절사평균을 사용한 CIGA검정($CIGA_T$)이었다. 결과는 CIGA와 $CIGA_T$는 1종오류를 대체로 잘 관리하나, F검정들과 ($\varepsilon$)검정들은 일부 조건에서 아주 작은 1종오류나 아주 큰 1종오류를 갖는 것으로 나타났다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.8
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• pp.1493-1502
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• 1994

In this paper we propose a new wideband channel simulation algorithm which exactly simulates the Suzuki fading channel, a mixture of short term and long term fading. Proposed algorithm generates the incoming reflected waves as Suzuki distributed random signals and is possible to arbitrarily adjust the correlations among long term fading components of the incoming waves by using the Gaussian-to-lognormal transformation. Proposed algorithm can be applied to the simulation of the system performance.

• Journal of Animal Science and Technology
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• v.46 no.4
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• pp.509-516
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• 2004

This study is to investigate the amount of biased estimates for heritability and genetic correlation according to data structure on marbling scores in Korean cattle. Breeding population with 5 generations were simulated by way of selection for carcass weight, Longissimus muscle area and latent values of marbling scores and random mating. Latent variables of marbling scores were categorized into five by the thresholds of 0, I, 2, and 3 SD(DSI) or seven by the thresholds of -2, -1, 0,1I, 2, and 3 SD(DS2). Variance components and genetic pararneters(Heritabilities and Genetic correlations) were estimated by restricted maximum likelihood on multivariate linear mixed animal models and by Gibbs sampling algorithms on multivariate threshold mixed animal models in DS1 and DS2. Simulation was performed for 10 replicates and averages and empirical standard deviation were calculated. Using REML, heritabilitis of marbling score were under-estimated as 0.315 and 0.462 on DS1 and DS2, respectively, with comparison of the pararneter(0.500). Otherwise, using Gibbs sampling in the multivariate threshold animal models, these estimates did not significantly differ to the parameter. Residual correlations of marbling score to other traits were reduced with comparing the parameters when using REML algorithm with assuming linear and normal distribution. This would be due to loss of information and therefore, reduced variation on marbling score. As concluding, genetic variation of marbling would be well defined if liability concepts were adopted on marbling score and implemented threshold mixed model on genetic parameter estimation in Korean cattle.

• The Korean Journal of Applied Statistics
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• v.7 no.1
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• pp.131-140
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• 1994

In order to find the identification function from data and to apply the identification function for the pattern classification, we consider the existing problem of the number of patterns in such data. In this paper, a new criteria for the identification of Gaussaian mixture distribution could be established as a charateristic of the sample variance, which is a bootstrap estimate of the sample variance. We examine the properties and fittness of the criteria through a large scale of computer simulations.

• Journal of the Korean Magnetics Society
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• v.26 no.3
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• pp.81-85
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• 2016

This paper introduces a performance integration method to predict variation characteristic of a performance function of electromagnetic machines or devices due to manufacturing tolerances. A normalized performance function space and a hybrid mean value technique are adapted to effectively predict mean and variance, which can identify probabilistic distribution of the performance function. To verify the effectiveness and accuracy of the proposed method, a mathematical problem and a loudspeaker model are tested, and numerical results are compared with those of existing methods such as Monte Carlo simulation and univariate dimension reduction method.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.12
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• pp.12-19
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• 2014

In this paper, an advanced UWB (ultra wideband) Rake receiving technique based on the statistical distribution model is studied in the M-ary TH-PPM system with multiple access interference (MAI). In order to improve the performance of the Rake receiver, the stochastic model, which can flexibly express the behavior of MAI-plus-noise, is required and the Laplace distribution and the generalized normal Laplace (GNL) model applied by the curtosis matching method are considered. The performance of Rake receiver based on each probability distribution is evaluated in the IEEE multipath fading channel and compared to that of the conventional Rake receiver. The suggested approach shows a superior BER performance than that of conventional Rake receiver.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.968-976
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• 2004

In the paper, deformation characteristics of fiber-mixed-soils, mixed polypropylene staple fibers of 0.3% fiber content with sands of various gradation, and their effectiveness of reinforcement were evaluated. A series of Resonant Column tests were performed with specimens prepared with varying Uniformity Coefficient and constant Curvature Coefficient. Maximum shear moduli 01 fiber-mixed-soils were increased by up to 30% and modulus reduction was also restrained in nonlinear range. Normalized shear modulus reduction curves of fiber-mixed-soils shift close to the upper limit of Seed curd Idriss's curves and are located within narrower band than those of unmixed soils, which proves the effectiveness on stiffness increment by reinforcing soils with fibers.

• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.395-407
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• 2020

Most classification accuracy measures for optimal threshold are divided into two types: one is expressed with cumulative distribution functions and probability density functions, the other is based on ROC curve and AUC. Unal (2017) proposed the index of union (IU) as an accuracy measure that considers two types to get them. In this study, ten kinds of accuracy measures (including IU) are divided into six categories, and the advantages of the IU are studied by comparing the measures belonging to each category. The optimal thresholds of these measures are obtained by setting various normal mixture distributions; subsequently, the first and second type of errors as well as the error sums corresponding to each threshold are calculated. The properties and characteristics of the IU statistic are explored by comparing the discriminative power of other accuracy measures based on error values.The values of the first type error and error sum of IU statistic converge to those of the best accuracy measures of the second category as the mean difference between the two distributions increases. Therefore, IU could be an accuracy measure to evaluate the discriminant power of a model.

• Economic and Environmental Geology
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• v.55 no.4
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• pp.353-366
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• 2022

Spatial estimation of geoscience data (geo-data) is challenging due to spatial heterogeneity, data scarcity, and high dimensionality. A novel spatial estimation method is needed to consider the characteristics of geo-data. In this study, we proposed the application of Gaussian Mixture Model (GMM) among machine learning algorithms with multivariate data for robust spatial predictions. The performance of the proposed approach was tested through soil chemical concentration data from a former smelting area. The concentrations of As and Pb determined by ex-situ ICP-AES were the primary variables to be interpolated, while the other metal concentrations by ICP-AES and all data determined by in-situ portable X-ray fluorescence (PXRF) were used as auxiliary variables in GMM and ordinary cokriging (OCK). Among the multidimensional auxiliary variables, important variables were selected using a variable selection method based on the random forest. The results of GMM with important multivariate auxiliary data decreased the root mean-squared error (RMSE) down to 0.11 for As and 0.33 for Pb and increased the correlations (r) up to 0.31 for As and 0.46 for Pb compared to those from ordinary kriging and OCK using univariate or bivariate data. The use of GMM improved the performance of spatial interpretation of anthropogenic metals in soil. The multivariate spatial approach can be applied to understand complex and heterogeneous geological and geochemical features.

• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.225-237
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• 1994

A generalized likelihood ratio test is developed to detect an outlier associated with monitoring nuclear proliferation. While the classical outlier detection methods consider continuous variables only, our approach allows both continuous and discrete variables or a mixture of continuous and discrete variables to be used. In addition, our method is free of the normality assumption, which is the key assumption in most of the classical methods. The proposed test is constructed by applying the bootstrap to a generalized likelihood ratio. We investigate the performance of the test by studying the power with simulations.