• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.407-426
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• 2003

We consider the missing covariates problem in generalized estimating equations(GEE) model. If the covariate is partially missing, GEE can not be calculated. In this paper, we study the performance of 7 imputation methods to handle missing covariates in GEE models, and the properties of GEE estimators are investigated after missing covariates are imputed for ordinal data of repeated measurements. The 7 imputation methods include i) Naive Deletion ii) Sample Average Imputation iii) Row Average Imputation iv) Cross-wave Regression Imputation v) Carry-over Imputation vi) Bayesian Bootstrap vii) Approximate Bayesian Bootstrap. A Monte-Carlo simulation is used to compare the performance of these methods. For the missing mechanism generating the missing data, we assume ignorable nonresponse. Furthermore, we generate missing covariates with or without considering wave nonresp onse patterns.

• The Korean Journal of Financial Management
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• v.14 no.1
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• pp.207-217
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• 1997

본 연구에서는 효율적 시장가설을 검증할 때 일반적으로 이용하는 주가의 로그변환방법은 마팅게일과 서브마팅게일을 구분할 수 없다는 것을 이론적으로 보여주고, 이러한 문제를 해결하기 위해서는 로그변환없이 일차 차분을 한 시계열 데이타를 이용하는 것이 바람직하다는 것을 제시한다. 또한 마팅게일과 서브마팅게일의 구분하기 위해서는 주가 차분 시계열 데이타의 공분산이라는 검정통계량을 이용하는데, 이 공분산이라는 검정통계량을 이용하여 실증적으로 검증을 하기 위해서는 이 통계량의 분포를 알아야 한다. 본 연구에서는 bootstrap방법론을 이용하여 이 공분산의 분포를 구하는 방법론을 제시한다.

• Journal of Veterinary Clinics
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• v.24 no.4
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• pp.509-513
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• 2007

Parametric and nonparametric coupled with bootstrap simulation technique were used to reevaluate previously defined reference intervals of serum chemistry parameters. A population-based study was performed in 100 clinically healthy dogs that were retrieved from the medical records of Kangwon National University Animal Hospital during 2005-2006. Data were from 52 males and 48 females(1 to 8 years old, 2.2-5.8 kg of body weight). Chemistry parameters examined were blood urea nitrogen(BUN)(mg/dl), cholesterol(mg/dl), calcium(mg/dl), aspartate aminotransferase(AST)(U/L), alanine aminotransferase(ALT)(U/L), alkaline phosphatase(ALP)(U/L), and total protein(g/dl), and were measured by Ektachem DT 60 analyzer(Johnson & Johnson). All but calcium were highly skewed distributions. Outliers were commonly identified particularly in enzyme parameters, ranging 5-9% of the samples and the remaining were only 1-2%. Regardless of distribution type of each analyte, nonparametric methods showed better estimates for use in clinical chemistry compare to parametric methods. The mean and reference intervals estimated by nonparametric bootstrap methods of BUN, cholesterol, calcium, AST, ALT, ALP, and total protein were 14.7(7.0-24.2), 227.3(120.7-480.8), 10.9(8.1-12.5), 25.4(11.8-66.6), 25.5(11.7-68.9), 87.7(31.1-240.8), and 6.8(5.6-8.2), respectively. This study indicates that bootstrap methods could be a useful statistical method to establish population-based reference intervals of serum chemistry parameters, as it is often the case that many laboratory values do not confirm to a normal distribution. In addition, the results emphasize on the confidence intervals of the analytical parameters showing distribution-related variations.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.301-309
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• 2009

Multidimensional scaling(MDS) is a statistical multivariate analysis technique that is often used in information visualization for exploring similarities or dissimilarities in data. In order to analyse and visualize data, MDS measures the dissimilarities between objects and uses them or their mean if they are repeatedly measured. When there exist outliers or when the variation of data is too large, we can hardly get reliable results on the research using MDS. In this paper, we consider the MDS based on bootstrap method when the variation of data is large. Standardized residual sum of squares is considered as measuring goodness-of-fit of the model. A real data analysis is include to examine our approach.

• Korean Journal of Plant Resources
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• v.24 no.4
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• pp.358-369
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• 2011

The internal transcribed spacer (ITS) regions of nuclear ribosomal DNA from genus Chrysosplenium were sequenced to address phylogenetic relationship. ITS including 5.8S sequence varied in length from 647 bp to 653 bp. Among them, 219 sites were variable sites with parsimony-informative. The aligned sequences were analyzed by maximum parsimony (MP) and neighbor-joining (NJ) methods. In the strict consensus trees of parsimony analysis, the monophyly of Chrysosplenium was supported by 100% bootstrap value. The first clade, C. pseudofauriei was at the basal position of the genus, and others formed two clades with high bootstrap support. The second clade included Ser. Pilosa and Ser. Oppositifolia and third clade included Ser. Alternifolia and Ser. Flagellifera. The NJ trees showed essentially the same topology. Finally, DNA sequences of ITS regions were useful phylogenetic marker in this genus. Based on the ITS and ridge seed morphological results, C. sphaerospermum Maxim. and C. valdepilosum (Ohwi) S.H. Kang & J.W. Han were discussed their scientific names and taxonomic positions.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.331-334
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• 2003

마이크로 어레이(microarray)실험에서 표준화(normalization)는 유전자의 발현수준에 영향을 미치는 여러 기술적인 변인을 제거하는 과정이다. cDNA microarray normalization에 있어 여러 방법이 제안되었지만, 이중 print-tip 효과가 존재할 때 사용되는 방법으로 print-tip lowess normalization이 대표적으로 사용된다. normalization에 사용되는 lowess 함수는 데이터의 특성에 따라 window width를 정해야만 연구의 목적에 맞는 결과를 도출할 수 있다. 본 논문에서는 각각의 tip에서 최적의 window width를 계산하는 절차를 논의하였다. 또한 이의 결과와 기존의 같은 window width를 사용하는 print-tip lowess normalization 결과와 비교 평가하여 normalization의 기본 원칙에 대한 타당성을 확인하였다.

• Proceedings of the Korea Society for Simulation Conference
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• 2004.05a
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• pp.25-29
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• 2004

VoIP는 인터넷 프로토콜(IP)를 이용하여 음성을 데이터 packet처럼 전송하는 것을 의미한다. 최근 VoIP 기술의 도입으로 기존 망 성능 관리에 대한 관심이 높아지고 있다. 보다 원활한 기술 구현을 위해서는 VoIP 트래픽에 대한 체계적인 분석과 위험성 검증을 할 수 있는 도구가 필요하다. 또한 기존의 트래픽 시뮬레이션 기법에서 실제 망에서의 자기유사성을 적용한 사례가 적다는 것 또한 본 연구가 행하여진 동기이다. 본 연구에서는 자기유사성을 반영하여 소량의 샘플을 갖고 전체 VoIP 망 트래픽을 생성할 수 있는 방법론을 개발하고자 시도하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.308-310
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• 2000

관찰학습(OLA: Observational Learning Algorithm)은 앙상블 네트워크의 각 구성 모델들이 아른 모델들을 관찰함으로써 얻어진 가상 데이터와 초기에 bootstrap된 실제 데이터를 학습에 함께 이용하는 방법이다. 본 논문에서는, 초기 학습 데이터 셋을 분할하고 분할된 각 데이터 셋에 대하여 앙상블의 구성 모델들을 전문화(specialize)시키는 방법을 적용하여 기존의 관찰학습 알고리즘을 개선시켰다. 제안된 알고리즘은 bagging 및 boosting과의 비교 실험에 의하여, 보다 적은 수의 구성 모델로 동일 내지 보다 나은 성능을 나타냄이 실험적으로 검증되었다.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.1-12
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• 2024

Predicting path loss is one of the important factors for wireless network design, such as selecting the installation location of base stations in cellular networks. In the past, path loss values were measured through numerous field tests to determine the optimal installation location of the base station, which has the disadvantage of taking a lot of time to measure. To solve this problem, in this study, we propose a path loss prediction method based on machine learning (ML). In particular, an ensemble learning approach is applied to improve the path loss prediction performance. Bootstrap dataset was utilized to obtain models with different hyperparameter configurations, and the final model was built by ensembling these models. We evaluated and compared the performance of the proposed ensemble-based path loss prediction method with various ML-based methods using publicly available path loss datasets. The experimental results show that the proposed method outperforms the existing methods and can predict the path loss values accurately.

• Journal of Digital Convergence
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• v.17 no.6
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• pp.51-57
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• 2019

The objective of the study was to determine the mediation effects of hope and grit in the relationship between human rights damage and self-esteem. A sample of students was recruited from two universities in Korea. For data analysis, SPSS PC+ and SPSS PROCESS macro were used. Frequency, reliability, correlation and mediating effect analysis were performed. Bootstrap technique was done to verify the mediating effect. Results showed as follows. First, grit, self-esteem and hope were negatively correlated with human rights damage, but grit, self-esteem and hope were positively correlated with each other. Second, hope and grit mediated in the relationship between human rights damage and self-esteem. For further research, it was discussed how university students who experienced human rights abuses could use grit and hope to maintain their lowered self-esteem.