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이영선,Mano Shuhei,이재용 한국통계학회 2020 Journal of the Korean Statistical Society Vol.49 No.2
We propose a fully Bayesian methodology for estimation of functions that have jump discontinuities. The proposed model is an extension of the LARK model, which enables functions to be represented by the small number of elements from an overcomplete system. In the proposed model, multiple kernels are used as the elements of an overcomplete system. Since these elements are composed of different types of functions such as Haar, Laplacian, and Gaussian kernel, the proposed model can estimate discontinuous as well as smooth functions without model selection. The location of jumps, the number of basis functions, and even the smoothness of the target function are automatically determined by the Levy random measure. A simulation study and a real data analysis illustrate that the proposed model performs better than the standard nonparametric methods for the estimation of discontinuous functions. Finally, we prove prior positivity of the model and show that the prior has sufficiently large support including discontinuous functions with a finite number of jumps.
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진로 미결정에 대한 심리적 독립, 애착 및 특성 불안의 관계
이영선,김정희,이영순 한국진로상담학회 1999 한국진로상담학회지 Vol.4 No.1
The purpose of this study was to investigate the relationship of psychological separation, attachment and trait anxiety to career indecision, in order to understand the clients' relationship with their parents which is important on career counseling. Two hundred and twenty five male and female college students answered a questionnaire consisted of Career Decision Scale, Psychological Separation Inventory, The Inventory of Parent Attachment, and Trait Anxiety Inventory. The results of this study were as follows. First, there were significant differences in career indecision, trait anxiety, attachment to mother, attachment to and psychological separation from father by sex. In addition, the degree of attachment to and psychological separation from mother is significantly higher than that of gather. Second, for male students, career indecision was predicted by trait anxiety and attachment to mother, while for female students, career indecision was predicted by attachment to father and trait anxiety. However, psychological separation from each parents did not contribute meaningful variance in career indecision. Third, path analysis indicated that, for both male and female students, attachment to each parent had influence on career indecision mediated by trait anxiety. Finally, implications and limitations of this research as well as some suggestions for future research were discussed.
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COVID-19 백신 접종 후 발생한 전신 부종에 대한 한양방 복합치료 치험 1례
이영선,정소민,이한결,조기호,문상관,정우상,권승원 대한한방내과학회 2023 대한한방내과학회지 Vol.44 No.5
Background: According to Vaccine Adverse Events Reporting System data, generalized edema followed by the COVID-19 vaccine is uncommon, with only 333 reported cases, and of those, 224 (69%) are associated with the Pfizer-BioNTech vaccine. Case report: A 76-year-old male patient with heart failure with preserved ejection fraction presented with spontaneous generalized edema and otherwise normal cardiac exams following administration of BNT162b2 (Pfizer-BioNTech) COVID-19 vaccination that had lasted for approximately 60 days and was treated successfully using Korean medicine treatment. After the administration of Korean medicine treatment, the patient’s symptoms in the bilateral limbs were dramatically controlled, without recurrence, for 2 months. As a result, generalized edema, which had been present for approximately 50 days, dramatically improved. Conclusion: This clinical case study suggests that a Korean medicine approach with Mokbangki-tang and Oryeong-san might be effective for the pleural effusion resolution of generalized edema after COVID-19 vaccination.
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이영선,이경재,이광민,이재용,서진욱,Lee, Youngseon,Lee, Kyoungjae,Lee, Kwangmin,Lee, Jaeyong,Seo, Jinwook 한국통계학회 2015 응용통계연구 Vol.28 No.2
The Indian Buffet Process is a stochastic process on equivalence classes of binary matrices having finite rows and infinite columns. The Indian Buffet Process can be imposed as the prior distribution on the binary matrix in an infinite feature model. We describe the derivation of the Indian buffet process from a finite feature model, and briefly explain the relation between the Indian buffet process and the beta process. Using a Gaussian linear model, we describe three algorithms: Gibbs sampling algorithm, Stick-breaking algorithm and variational method, with application for finding features in image data. We also illustrate the use of the Indian Buffet Process in various type of analysis such as dyadic data analysis, network data analysis and independent component analysis.
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