• Communications for Statistical Applications and Methods
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• 제22권6호
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• pp.675-683
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• 2015

In the 21st century, we now face the serious problems of the enormous consumption of the energy resources. Depending on the power consumption increases, both China and South Korea face a reduction in available resources. This paper considers the regression models and time-series models to compare the performance of the forecasting accuracy based on Mean Absolute Percentage Error (MAPE) in order to forecast the electricity demand accurately on the short-term period (68 months) data in Northeast China and find the relationship with Korea. Among the models the support vector regression (SVR) model shows superior performance than time-series models for the short-term period data and the time-series models show similar results with the SVR model when we use long-term period data.

• 수산경영론집
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• 제48권2호
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• pp.19-32
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• 2017

The purpose of this study is to identify problems and suggest improvements of estimating procedures and item of fisheries supply-demand statistics served as a basis for the fisheries supply-demand policies. Korea Rural Economic Institute(KREI) and Ministry of Oceans and Fisheries(MOF) respectively publish the fisheries supply-demand statistics. But the reliability of data is low as the statistics of these two organizations are limited and show discrepancy in the numbers. It is therefore difficult to use them as the basic data for policies. Also, an accurate data aggregation is difficult due to following problems in the items of statistics. 1) Problems in estimating route sales and non-route sales of production, 2) adequacy of fishery product yield rate compared to raw material in the fisheries import/export sector, 3) selection of target companies for understand stocks and survey scope of fish species, 4) applying'0'to non-edible product demand etc. In order to develop the fisheries industry as a future growth industry, it is necessary to establish the accurate fisheries supply-demand policy as the instability of fisheries supply and demand is increasing. To do this, statistical reliability has to be improved. The improvements proposed in this study should be implemented considering urgency. First of all, an exhaustive analysis of stock statistics and conversion rates of raw material yield in the fisheries import/export sector should be conducted. In the medium term and the long term, transferring production statistics to MOF and surveys on the use demand of non-food product and the level of reduced and discarded seafood products should be carried out in consecutive order.

• Journal of the Korean Data and Information Science Society
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• 제19권4호
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• pp.1397-1408
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• 2008

Mathematics develops the ability to solve a problem and the spirit of inquiry by logical thinking, and statistics develops the ability to making a decision scientifically or rationally by various data processing techniques. Even though mathematics is a compulsory subject in most of IT-related departments, the reality of Korean education is serious. This research studies on the necessity of mathematics/statistics education for a person studying IT and analyzes the contents of mathematics/statistics among IT-related subjects. And the research makes a plan for specializing IT-related departments by use of specialized education programs using mathematics/statistics and examines a development plan in the short or long term period for connectivity with mathematics/statistics fields. This connectivity between IT-related departments and mathematics/statistics in the 21st century would certainly contribute to creating more practical or technical knowledge.

• 대한수학회지
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• 제42권2호
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• pp.223-241
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• 2005

Inequalities on the rank of the sum and the product of two matrices over semirings are surveyed. Preferences are given to the factor rank, row and column ranks, term rank, and zero-term rank of matrices over antinegative semirings.

• 유통과학연구
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• 제14권1호
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• pp.93-102
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• 2016

Purpose - The purpose of paper is studying the static and dynamic side for long-term memory storage properties, and increase the explanatory power regarding the long-term memory process by looking at the long-term storage attributes, Korea Composite Stock Price Index. The reason for the use of GPH statistic is to derive the modified statistic Korea's stock market, and to research a process of long-term memory. Research design, data, and methodology - Level shifts were subjected to be an empirical analysis by applying the GPH method. It has been modified by taking into account the daily log return of the Korea Composite Stock Price Index a. The Data, used for the stock market to analyze whether deciding the action by the long-term memory process, yield daily stock price index of the Korea Composite Stock Price Index and the rate of return a log. The studies were proceeded with long-term memory and long-term semiparametric method in deriving the long-term memory estimators. Chapter 2 examines the leading research, and Chapter 3 describes the long-term memory processes and estimation methods. GPH statistics induced modifications of statistics and discussed Whittle statistic. Chapter 4 used Korea Composite Stock Price Index to estimate the long-term memory process parameters. Chapter 6 presents the conclusions and implications. Results - If the price of the time series is generated by the abnormal process, it may be located in long-term memory by a time series. However, test results by price fixed GPH method is not followed by long-term memory process or fractional differential process. In the case of the time-series level shift, the present test method for a long-term memory processes has a considerable amount of bias, and there exists a structural change in the stock distribution market. This structural change has implications in level shift. Stratum level shift assays are not considered as shifted strata. They exist distinctly in the stock secondary market as bias, and are presented in the test statistic of non-long-term memory process. It also generates an error as a long-term memory that could lead to false results. Conclusions - Changes in long-term memory characteristics associated with level shift present the following two suggestions. One, if any impact outside is flowed for a long period of time, we can know that the long-term memory processes have characteristic of the average return gradually. When the investor makes an investment, the same reasoning applies to him in the light of the characteristics of the long-term memory. It is suggested that when investors make decisions on investment, it is necessary to consider the characters of the long-term storage in reference with causing investors to increase the uncertainty and potential. The other one is the thing which must be considered variously according to time-series. The research for price-earnings ratio and investment risk should be composed of the long-term memory characters, and it would have more predictability.

• Communications for Statistical Applications and Methods
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• 제31권2호
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• pp.213-234
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• 2024

In recent decades, increasing research attention has been directed toward predicting the price of stocks in financial markets using deep learning methods. For instance, recurrent neural network (RNN) is known to be competitive for datasets with time-series data. Long short term memory (LSTM) further improves RNN by providing an alternative approach to the gradient loss problem. LSTM has its own advantage in predictive accuracy by retaining memory for a longer time. In this paper, we combine both supervised and unsupervised dimension reduction methods with LSTM to enhance the forecasting performance and refer to this as a dimension reduction based LSTM (DR-LSTM) approach. For a supervised dimension reduction method, we use methods such as sliced inverse regression (SIR), sparse SIR, and kernel SIR. Furthermore, principal component analysis (PCA), sparse PCA, and kernel PCA are used as unsupervised dimension reduction methods. Using datasets of real stock market index (S&P 500, STOXX Europe 600, and KOSPI), we present a comparative study on predictive accuracy between six DR-LSTM methods and time series modeling.

• Journal of the Korean Data and Information Science Society
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• 제25권2호
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• pp.411-422
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• 2014

본 연구는 2011학년도 입학하여 여섯 학기 연속 이수한 학생을 대상으로 평균 GPA의 초기값(intercept), 기울기 (slope), 2차항 (quadratic term)을 구하여 이수학기가 늘어나면서 평균 GPA가 어떻게 변화하는지 분석하였다. 구체적으로 이수학기가 늘어나면서 성별과 모집단위에 따라 평균 GPA의 초기값, 기울기, 2차항에 차이가 있는지 분석하였다. 그 결과 초기값에 영향을 주는 변수는 모집단위, 기울기에 영향을 주는 변수는 성별이며 2차항에 영향을 미치는 변수는 하나도 없었다.

• Communications for Statistical Applications and Methods
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• 제18권1호
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• pp.137-146
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• 2011

노인장기요양보험은 고령이나 노인성질병 등으로 인하여 혼자서 일상 생활을 수행하기 어려운 노인 등에게 신체활동 또는 가사지원 등의 장기요양급여를 사회적 연대원리에 의해 제공하는 사회보험 제도로써, 우리나라에서는 2008년 7월부터 시행하고 있다. 신뢰성있는 등급판정을 위하여, 안정적인 수급자의 요양인정점수를 산출하는 것은 노인장기요양보험제도의 시행에 있어 매우 중요한 요소라고 할 수 있다. 본 연구에서는 요양인정점수 산출과 등급판정에 의사결정나무 모형을 사용하였고 안정적인 모형을 위해 원자료의 변환 및 절사, 다양한 분리기준(splitting criterion), 정지규칙(stopping rule)을 적용하였다. 본 연구에서 생성한 모형이 기존의 모형보다 안정적임을 확인하였다.

• 응용통계연구
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• 제26권5호
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• pp.725-736
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• 2013

최근 노년기의 삶에 대비하기 위한 은퇴자금 마련이 중요한 개인적, 사회적 문제로 부각되고 있다. 특히, 앞으로 노년인구의 비율이 지속적으로 상승할 것이라는 전망과 더불어 이러한 개인의 재무설계 및 그와 관련한 리스크와 관련한 문제는 그 중요성이 날로 커질 것이다. 노년기의 질병에 따른 의료비 지출은 특히 재무적인 리스크와 밀접한 관련이 있는데, 유병 기간이 상대적으로 긴 질병의 경우에는 수발비용을 포함한 장기적인 의료비 지출로 인하여 재무적인 위험을 증가시키고 노년기의 삶의 질을 크게 떨어뜨릴 수 있다. 따라서, 각 개인이 장기적인 비용 지출을 요하는 질병에 대하여 예상되는 비용의 규모를 파악하고 이를 사전에 대비할 수 있는 방안을 모색하는 것이 필요하다. 본 연구에서는 노인장기요양보험의 실적 자료와 다중상태모형을 토대로, 노년기에 노인장기요양보험을 통하여 장기요양보호가 필요한 기간과 이에 따른 비용 규모의 추정을 통하여, 각 개인이 장기간병을 위해 준비해야 하는 필요금액을 도출하여 보았다.

• Journal of the Korean Data and Information Science Society
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• 제19권2호
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• pp.421-429
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• 2008

We consider a general semiparametric additive risk model that consists of three components. They are parametric, purely and smoothly nonparametric components. In parametric component, time dependent term is known up to proportional constant. In purely nonparametric component, time dependent term is an unknown function, and time dependent term in smoothly nonparametric component is an unknown but smoothly function. As an estimation method of this model, we use the weighted least square estimation by Huffer and McKeague (1991). We provide an illustrative example as well as a simulation study that compares the performance of our method with the ordinary least square method.