• Journal of Korean Public Health Nursing
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• v.31 no.1
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• pp.5-18
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• 2017

Purpose: This study was conducted to suggest a method for financial projection of health insurance expenditures that reflects future changes in demographic structure. Methods: Using data associated with the number of patients and health insurance cost per patient, generalized linear models (GLM) were fitted with demographic explanatory variables. Models were constructed separately for individual medical departments, types of medical service, and types of public health insurance. Goodness-of-fit of most of the applied GLM models was quite satisfactory. By combining estimates of frequency and severity from the constructed models and results of the population projection, total annual health insurance expenditures were projected through year 2060. Results: Expenditures for medical departments associated with diseases that are more frequent in elderly peoples are expected to increase steeply, leading to considerable increases in overall health insurance expenditures. The suggested method can contribute to improvement of the accuracy of financial projection. Conclusion: The overall demands for medical service, medical personnel, and relevant facilities in the future are expected to increase as the proportion of elderly people increases. Application of a more reasonable estimation method reflecting changes in demographic structure will help develop health policies relevant to above mentioned resources.

• Communications for Statistical Applications and Methods
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• v.27 no.5
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• pp.523-533
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• 2020

This paper suggests three available methods for finding nonnegative estimates of variance components of the random effects in mixed models. The three proposed methods based on the concepts of projections are called projection method I, II, and III. Each method derives sums of squares uniquely based on its own method of projections. All the sums of squares in quadratic forms are calculated as the squared lengths of projections of an observation vector; therefore, there is discussion on the decomposition of the observation vector into the sum of orthogonal projections for establishing a projection model. The projection model in matrix form is constructed by ascertaining the orthogonal projections defined on vector subspaces. Nonnegative estimates are then obtained by the projection model where all the coefficient matrices of the effects in the model are orthogonal to each other. Each method provides its own system of linear equations in a different way for the estimation of variance components; however, the estimates are given as the same regardless of the methods, whichever is used. Hartley's synthesis is used as a method for finding the coefficients of variance components.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.401-410
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• 2021

Popular in discriminant classification analysis, k-nearest neighbor classification methods have limitations that do not reflect the local characteristic of the data, considering only the number of fixed neighbors. Considering the local structure of the data, the adaptive nearest neighbor method has been developed to select the number of neighbors. In the analysis of high-dimensional data, it is common to perform dimension reduction such as random projection techniques before using k-nearest neighbor classification. Recently, an ensemble technique has been developed that carefully combines the results of such random classifiers and makes final assignments by voting. In this paper, we propose a novel discriminant classification technique that combines adaptive nearest neighbor methods with random projection ensemble techniques for analysis on high-dimensional data. Through simulation and real-world data analyses, we confirm that the proposed method outperforms in terms of classification accuracy compared to the previously developed methods.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.41-59
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• 2016

There have been continuous improvements in human life expectancy. Life expectancy is as a key factor in an aging population and can wreak severe damage on the financial integrity of pension providers. Hence, the projection of the accurate future mortality is a critical point to prevent possible losses to pension providers. However, improvements in future mortality would be overestimated by a typical mortality projection method using the Lee-Carter model since it underestimates the mortality index ${\kappa}_t$. This paper suggests a mortality projection based on the projection of the skewness of the mortality versus the typical mortality projection of the Lee-Carter model based on the projection of the mortality index, ${\kappa}_t$. The paper shows how to indirectly estimate future t trend with the skewness of the mortality and compares the results under each estimation method of the mortality index, ${\kappa}_t$. The analysis of the results shows that mortality projection based on the skewness presents less improved mortality at an elderly ages than the original projection.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1549-1555
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• 2014

Consider a p-variate normal distribution ($p-q{\geq}3$, q = rank($P_V$) with a projection matrix $P_V$). Using a simple property of noncentral chi square distribution, the generalized Bayes estimators dominating the James-Stein estimator shrinking towards projection vectors under quadratic loss are given based on the methods of Brown, Brewster and Zidek for estimating a normal variance. This result can be extended the cases where covariance matrix is completely unknown or ${\sum}={\sigma}^2I$ for an unknown scalar ${\sigma}^2$.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.373-381
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• 2011

This paper discusses how to get the sums of squares due to treatment factors when Type I Analysis is used by projections for the analysis of data under the assumption of a two-way ANOVA model. The suggested method does not need to calculate the residual sums of squares for the calculation of sums of squares. There-fore, the calculation is easier and faster than classical ANOVA methods. It also discusses how eigenvectors and eigenvalues of the projection matrices can be used to get the calculation of sums of squares. An example is given to illustrate the calculation procedure by projections for unbalanced data.

• The Korean Journal of Applied Statistics
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• v.14 no.2
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• pp.321-332
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• 2001

본 논문에서는 반응변수가 두 가지의 값을 갖는 회귀분석에 적용할 수 있는 사영추적회귀를 고려하였다. 회귀모형에 필요한 설명변수들의 선형결합이 하나이고 연결함수의 형태를 사전에 알지 못한다는 가정하에서 모의담금질 기법을 이용하여 모형에 필요한 선형결합을 찾는 알고리즘을 제시하였다. 이진 반응변수의 경우에는 평활모수의 값에 따라 잔차이탈도함수의 반응표면이 단봉의 형태를 갖지 않는 경우가 있어 비동질적 마코프체인을 이용한 모의담금질 기법을 적용하면 효율적으로 선형결합을 탐색할 수 있다.

• Journal of Biomedical Engineering Research
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• v.5 no.2
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• pp.111-120
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• 1984

A new restoration method of chest X-ray image (dual project filter) was proposed to improve SNR (signal to noise ratio) characteristics. In this method, a priori information of system and anatomical structure and statistics of projected object are used in the design of filter. Dual projection filter varies its parameters, adapting to the local regions of chest(lungregion, mediasternum, subdiaphragm) and the structure of chest (bone, tissue, blood vessel, bronchia). The performance of Dual Projection Filter was 0.1-0.2dB better than Dual Sensor Wiener Filter, which was used for initial estimate of Dual Porjection Filter.

• Communications for Statistical Applications and Methods
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• v.15 no.1
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• pp.87-94
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• 2008

Andrews (1972) proposed to combine trigonometric functions to represent n observations of p variates, where the coefficients in linear sums are taken from the values of corresponding observation's respective variates. By viewing Andrews' plot as a collection of n trajectories of p-dimensional objects (observations) as a weighting point loaded with dimensional weights moves along a certain path on the hyper-dimensional sphere, we develop graphical techniques for further uses in data visualization. Specifically, we show that the parallel coordinate plot is a special case of Andrews' plot and we demonstrate the versatility of Andrews' plot with a projection pursuit engine.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.313-322
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• 2007

Several robust censored depth regression methods are compared under contamination. Park and Hwang(2003) suggested a way to circumvent the censoring issue by incorporating Kaplan-Meier type weight in halfspace regression depth and Park(2003) used a similar technique to simplicial regression depth. Hubert et al. (2001) suggested a high breakdown point regression depth based on projection called rcent. A new method to implement censoring in rcent is suggested and compared with two precedents under various contamination and censoring schemes.