• Journal of Integrative Natural Science
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• v.5 no.3
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• pp.186-189
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• 2012

For the mean vector of a p-variate normal distribution ($p{\geq}3$), the optimal estimation within the class of James-Stein type decision rules under the quadratic loss are given when the underlying distribution is that of a variance mixture of normals and when the norm ${\parallel}\underline{{\theta}}{\parallel}$ in known. It also demonstrated that the optimal estimation within the class of Lindley type decision rules under the same loss when the underlying distribution is the previous type and the norm ${\parallel}{\theta}-\overline{\theta}\underline{1}{\parallel}$ with $\overline{\theta}=\frac{1}{p}\sum\limits_{i=1}^{n}{\theta}_i$ and $\underline{1}=(1,{\cdots},1)^{\prime}$ is known.

• Journal of the military operations research society of Korea
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• v.9 no.2
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• pp.39-43
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• 1983

In this paper, we derive the likelihood function for the independent random order statistic whose underlying lifetime distribution is a two parameter Weibull form. For this purpose we first discuss the order statistic which represent a characteristic feature of most life and fatigue tests that they give rise to ordered observations. And, we describe the properties of the underlying Weibull model. The derived likelihood function is essential for establishing the statistical life test plans in the case of Weibull distribution using a likelihood ratio method.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.49.1-49
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• 2001

The skin color model is a very important concept in face detection, face recognition and face tracking. Usually, this model is obtained by estimating a probability density function of skin color distribution. In many cases, it is assumed that the underlying density function follows a Gaussian distribution. In this paper, a new method for non-parametric estimation of the probability density function, by using feed-forward neural network, is used to estimate the underlying skin color model. By using this method, the resulting skin color model is better than the Gaussian estimation and substantially approaches the real distribution. Applications to face detection and face ...

• Journal of Integrative Natural Science
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• v.6 no.4
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• pp.251-255
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• 2013

For the mean vector of a p-variate normal distribution ($p{\geq}4$), the optimal estimation within the class of modified James-Stein type decision rules under the quadratic loss is given when the underlying distribution is that of a variance mixture of normals and when the norm ${\parallel}{\theta}-\bar{\theta}1{\parallel}$ it known.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1495-1500
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• 2015

We obtain means and variances of max {X, Y} and min {X, Y} in the underlying Morgenstern type bivariate uniform variables X and Y with same scale parameters and different scale parameters respectively. And we obtain the conditional expectations in the underlying Morgenstern type bivariate uniform variables. Here, we shall consider the conditional expectations to know the dependence of one variable on the other variable and we consider the behaviors of means and variances of max {X, Y} and min {X, Y} with respect to changes in means, variances, and the correlation coeffcient of the underlying Morgenstern type bivariate uniform variables.

• Korean journal of dermatology
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• v.56 no.9
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• pp.531-538
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• 2018

Background: Herpes zoster is a common dermatologic disorder. However, it rarely occurs in children and adolescents in Gwangju-Jeonnam province. Objective: This study aimed to analyze the epidemiological features and clinical characteristics of herpes zoster in children and adolescents. Methods: A retrospective survey was conducted on patients who visited the department of dermatology of Chosun University Hospital in Gwangju-Jeonnam province within the past 8 years. The medical records of 103 patients aged <18 years were reviewed. We analyzed for age, gender, accompanying symptoms, dermatomal distribution, underlying disease, treatment, and complications with serologic test. Results: The male-to-female ratio of the participants was 1.08:1, and their mean age was 13.0 years. Underlying diseases were observed in 3% (3/102) of the patients. The most common dermatomal distribution was thoracic dermatome (34%), followed by trigeminal (26%), cervical (20%), lumbar (15%), and non-skin (6%). The most common accompanying symptoms were headache (10%), fever (3%), and myalgia (3%). No difference was observed between patients who were varicella-zoster virus (VZV) IgM-positive and those who were VZV IgM-negative in terms of dermatome, visual analogue scale (VAS), severity, and body mass index (BMI). Conclusion: In children and adolescents with herpes zoster, the gender ratio and dermatomal distribution were similar to those previously reported, except for the low rate of underlying diseases. The incidence of herpes zoster in children was not significantly associated with immunosuppression and underlying diseases. Higher VZV IgM titer was not associated with dermatomal distribution, higher VAS score, or BMI. This study first compared the serological test results of children.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.441-452
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• 2021

Federated learning provides an efficient integrated model for distributed data, allowing the local training of different data. Meanwhile, the goal of multi-task learning is to simultaneously establish models for multiple related tasks, and to obtain the underlying main structure. However, traditional federated multi-task learning models not only have strict requirements for the data distribution, but also demand large amounts of calculation and have slow convergence, which hindered their promotion in many fields. In our work, we apply the rank constraint on weight vectors of the multi-task learning model to adaptively adjust the task's similarity learning, according to the distribution of federal node data. The proposed model has a general framework for solving optimal solutions, which can be used to deal with various data types. Experiments show that our model has achieved the best results in different dataset. Notably, our model can still obtain stable results in datasets with large distribution differences. In addition, compared with traditional federated multi-task learning models, our algorithm is able to converge on a local optimal solution within limited training iterations.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.355-370
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• 1993

The estimations of variance components for the unbalanced one way random effects model when the underlying distributions are not necessarily normal are considered. ANOVA, REML, ML, MIVQUE, and MINQE estimators are compared with respect to their mean squared errors and biases through a simulation study. Explicit, computable expressions with no matrix inversion necessary are given for these estimators. An efficient rule to provide a prior guess of MINQE is given. Our results indicate that the efficiency of MINQE is excellent for arbitrary underlying distribution in the sense of MSE even in the presence of nontrivial bias. Also, MINQE is a worthwhile improvement over other estimators when kurtosis of underlying distributions become large 1.

• Journal of the Korean Statistical Society
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• v.13 no.1
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• pp.42-47
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• 1984

In this paper, the means of the estimators for the coefficient of variation (CV) in an underlying Pareto distribution are expressed in terms of confluent hypergeometric functions. The numericla values of the biases for the CV estimators in the Pareto distribution are also obtained.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1661-1662
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• 2006

Internet communication network quality characteristics are analyzed using Beta probability distribution. Beta probability distribution is chosen for the underlying probability distribution because it is an extremely flexible probability distribution used to model bounded random variables. Based on the fitted Beta probability distribution, a dataset regarding each network quality characteristic is summarized concisely.