• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.10 no.2
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• pp.1-17
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• 2000

We investigated dissatisfaction of elements of local exhaust system, needs for local exhaust system, and information networks for local exhaust system from June 1998 to September 1999 using the questionnaire structured. It contained questions concerning general characteristics of factory and local exhaust system, troubles and dissatisfaction of elements of local exhaust system, and information networks for local exhaust system. The collected data were analyzed by descriptive statistics analysis. Information networks for local exhaust system were analyzed by multidimensional scaling using path distance of network analysis and by graph analysis using Krackplot. Among complaints of local exhaust system, that of duct has show the highest percentage of complaint. In the information network for local exhaust system, Seoul is positioned in the center of network with mediating role.

• Communications of the Korean Mathematical Society
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• v.11 no.3
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• pp.855-865
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• 1996

In this paper, we establish the weak convergences of processes occurring in a generalized Curie-Weiss model and its dual.

• Health Policy and Management
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• v.31 no.3
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• pp.301-311
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• 2021

Background: This study purposed to analyze the relationship between the local extinction index and medical service uses of chronic diseases. The local extinction index is an indicator of the demographic structure and population aging of the region. Methods: The 2014-2018 statistics of National Health Insurance Corporation and Korean Statistical Information Service data were used for the analysis. First, descriptive statistics were used to analyze the general status of research variables. Second, a panel analysis was performed to analyze the relationship between the local extinction index and medical service uses of chronic diseases (hypertension, diabetes mellitus, periodontal disease, arthritis, mental health, epidemic disease, liver disease). Medical service uses were measured by the number of visits/inpatient days and medical charges of seven chronic diseases. Results: Panel analysis results showed that higher local extinction risks (meaning lower local extinction index) had a positive relationship with the number of visits/inpatient days and medical charges of chronic diseases. But the relationships were varied when the seven chronic diseases were analyzed separately. Conclusion: This study showed a significant relationship between the local demographic structure and medical service uses of chronic disease. Analyzing the local demographic structure will be an essential prerequisite step for implementing appropriate regional health care policies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.4
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• pp.639-644
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• 2002

Nonlinear filters which are utilized rank-order information and temporal-order information, have many proposed, in order to restore nonstationary signals which are corrupted by additive noise. In this paper, we propose a data-dependent LWOS filter whose coefficients change based on local statistics. LWOS(Linear Combination of Weighted Order Statistics) filters［1］which also utilized two informations, and have properties of efficient impulsive and nonimpulsive noise attenuation and sufficiently details and edges preservation. DD-LWOS filters can remove non-impulsive oises while preserving signal details. DD-LWOS2 filter gets more better performance than DD-LWOS filter when input image corrupted by additive noise which includes Impulsive noise components.

• Communications for Statistical Applications and Methods
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• v.30 no.4
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• pp.369-388
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• 2023

In this paper, we develop the two-step procedure that detects and estimates the position of structural changes for multivariate nonstationary time series, either on mean parameters or second-order structures. We first investigate the presence of mean structural change by monitoring data through the aggregated cumulative sum (CUSUM) type statistic, a sequential procedure identifying the likely position of the change point on its trend. If no mean change point is detected, the proposed method proceeds to scan the second-order structural change by modeling the multivariate nonstationary time series with a multivariate locally stationary Wavelet process, allowing the time-localized auto-correlation and cross-dependence. Under this framework, the estimated dynamic spectral matrices derived from the local wavelet periodogram capture the time-evolving scale-specific auto- and cross-dependence features of data. We then monitor the change point from the lower-dimensional approximated space of the spectral matrices over time by applying the dynamic principal component analysis. Different from existing methods requiring prior information on the type of changes between mean and covariance structures as an input for the implementation, the proposed algorithm provides the output indicating the type of change and the estimated location of its occurrence. The performance of the proposed method is demonstrated in simulations and the analysis of two real finance datasets.

• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.971-986
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• 2014

When thousands of hypotheses are tested simultaneously, the probability of rejecting any true hypotheses increases, and large multiplicity problems are generated. To solve these problems, researchers have proposed different approaches to multiple testing methods, considering family-wise error rate (FWER), false discovery rate (FDR) or false nondiscovery rate (FNR) as a type I error and some test statistics. In this article, we discuss Bonferroni (1960), Holm (1979), Benjamini and Hochberg (1995) and Benjamini and Yekutieli (2001) procedures based on T statistics, modified T statistics or local-pooled-error (LPE) statistics. We also consider Sun and Cai (2007) procedure based on Z statistics. These procedures are compared in the simulation and applied to Arabidopsis microarray gene expression data to identify differentially expressed genes.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.43-52
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• 1999

The local influence method is adapted to quadratic discriminant analysis for the identification of influential observations affecting the estimation of probability density function probabilities and log odds. The method allows a simultaneous perturbation on all observations so that it can identify multiple influential observations. The proposed method is applied to a real data set and satisfactory result is obtained.

• Journal of the Korean Statistical Society
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• v.31 no.2
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• pp.237-250
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• 2002

Motivated by Cook's (1986) assessment of local influence by investigating the curvature of a surface associated with the overall discrepancy measure, this paper extends this idea to the linear regression model with AR(p) disturbances. Diagnostic for the linear regression models with AR(p) disturbances are discussed when simultaneous perturbations of the response vector are allowed. For the derived criterion, numerical studies demonstrate routine application of this work.

• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.299-310
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• 2022

As interest in social network analysis increases, researchers' interest in detecting changes in social networks is also increasing. Changes in social networks appear as structural changes in the network. Therefore, detecting a change in a social network is detecting a change in the structural characteristics of the network. A local change in a social network is a change that occurs in a part of the network. It usually occurs between close neighbors. The purpose of this paper is to propose a procedure to efficiently detect local changes occurring in the network. In this paper, we divide the network into partitioned networks and monitor each partitioned network to detect local changes more efficiently. By monitoring partitioned networks, we can detect local changes more quickly and obtain information about where the changes are occurring. Simulation studies show that the proposed method is efficient when the network size is small and the amount of change is small. In addition, under a fixed overall false alarm rate, when we partition the network into smaller sizes and monitor smaller partitioned networks, it detects local changes better.

• Asian Journal of Business Environment
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• v.12 no.2
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• pp.43-53
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• 2022

Purpose: This study aims to analyze the performance of local taxes in Indonesia through the estimation of tax capacity and tax effort, as well as classifying provinces based on the estimated value of tax capacity and tax effort. Research design, data and methodology: this study uses panel data of 34 provinces in Indonesia for the period of 2014-2018. The analytical method used in the tax capacity model is panel data regression to explain the factors that influence tax performance. Tax effort is estimated by the ratio of tax to tax capacity. Results: The results of the analysis show that gini ratio and regional expenditures have a significant positive effect on the tax ratio, while the share of GRDP in the manufacturing sector and HDI has a significant negative effect on the tax ratio. Based on the results, there are 19 provinces that have low tax capacity and 16 provinces that have low tax effort. Conclusions: The development of local tax performance tends to fluctuate with an average of 1.24 percent per year. Gini ratio and regional expenditure have a significant positive effect on the tax ratio, while the share of GRDP in the manufacturing sector and HDI have a significant negative effect on the tax ratio.