• Title/Summary/Keyword: 비모수적 추정

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인공신경망모형을 이용한 주가의 예측가능성에 관한 연구

  • Jeong, Yong-Gwan;Yun, Yeong-Seop
    • The Korean Journal of Financial Management
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    • v.15 no.2
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    • pp.369-399
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    • 1998
  • Most of the studies on stock price predictability using the linear model conclude that there are little possibility to predict the future price movement. But some anomalous patterns may be generated by remaining market inefficiency or regulation, market system that is facilitated to prevent the market failure. And these anomalous pattern, if exist, make them difficult to predict the stock price movement with linear model. In this study, I try to find the anomalous pattern using the ANN model. And by comparing the predictability of ANN model with the predictability of correspondent linear model, I want to show the importance of recognitions of anomalous pattern in stock price prediction. I find that ANN model could have the superior performance measured with the accuracy of prediction and investment return to correspondent linear model. This result means that there may exist the anomalous pattern that can't be recognized with linear model, and it is necessary to consider the anomalous pattern to make superior prediction performance.

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Estimation of kerosene demand function using time series data (시계열 자료를 이용한 등유수요함수 추정)

  • Jeong, Dong-Won;Hwang, Byoung-Soh;Yoo, Seung-Hoon
    • Journal of Energy Engineering
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    • v.22 no.3
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    • pp.245-249
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    • 2013
  • This paper attempts to estimate the kerosene demand function in Korea over the period 1981-2012. As the kerosene demand function provides us information on the pattern of consumer's kerosene consumption, it can be usefully utilized in predicting the impact of policy variables such as kerosene price and forecasting the demand for kerosene. We apply least absolute deviations and least median squares estimation methods as a robust approach to estimating the parameters of the kerosene demand function. The results show that short-run price and income elasticities of the kerosene demand are estimated to be -0.468 and 0.409, respectively. They are statisitically significant at the 1% level. The short-run price and income elasticities portray that demand for kerosene is price- and income-inelastic. This implies that the kerosene is indispensable goods to human-being's life, thus the kerosene demand would not be promptly adjusted to responding to price and/or income change. However, long-run price and income elasticities reveal that the demand for kerosene is price- and income-elastic in the long-run.

Varying coefficient model with errors in variables (가변계수 측정오차 회귀모형)

  • Sohn, Insuk;Shim, Jooyong
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.5
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    • pp.971-980
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    • 2017
  • The varying coefficient regression model has gained lots of attention since it is capable to model dynamic changes of regression coefficients in many regression problems of science. In this paper we propose a varying coefficient regression model that effectively considers the errors on both input and response variables, which utilizes the kernel method in estimating the varying coefficient which is the unknown nonlinear function of smoothing variables. We provide a generalized cross validation method for choosing the hyper-parameters which affect the performance of the proposed model. The proposed method is evaluated through numerical studies.

Construction of vehicle classification estimation model from the TCS data by using bootstrap Algorithm (붓스트랩 기법을 이용한 TCS 데이터로부터 차종별 교통량 추정모형 구축)

  • 노정현;김태균;차경준;박영선;남궁성;황부연
    • Journal of Korean Society of Transportation
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    • v.20 no.1
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    • pp.39-52
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    • 2002
  • Traffic data by vehicle classification is difficult for mutual exchange of data due to the different vehicle classification from each other by the data sources; as a result, application of the data is very limited. In Particular. in case of TCS vehicle classification in national highways, passenger car, van and truck are mixed in one category and the practical usage is very low. The research standardize the vehicle classification to convert other data and develop the model which can estimate national highway traffic data by the standardized vehicle classification from the raw traffic data obtained at the highway tollgates. The tollgates are categorized into several groups by their features and the model estimates traffic data by the standardized vehicle classification by using the point estimation and bootstrap algorithm. The result indicates that both of the two methods above have the significant level. When considering the bias of the extreme value by the sample size, the bootstrap algorithm is more sophisticated. Using result of this study, we is expect the usage improvement of TCS data and more specific comparison between the freeway traffic investigation and link volume on freeway using the TCS data.

디지털 경제의 긴꼬리 효과에 관한 실증 연구

  • 안용길;이철성
    • 한국벤처창업학회:학술대회논문집
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    • 2024.04a
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    • pp.17-20
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    • 2024
  • 우리는 대표적인 디지털 플랫폼인 온라인 음식 주문 배달 산업을 대상으로 디지털 경제의 긴꼬리 효과를 계량화한다. 특히, 코로나19 시기를 거치면서 음식배달플랫폼 입점으로 인한 긴꼬리 효과의 변화 양상을 고찰한다. 배달의민족에 입점한 음식점 15,000곳을 무작위로 선별하고 이들 매장의 2019년부터 2021년까지 전체 주문 정보를 취합(aggregation)하여 선형로그변환 후 기울기를 추정하여 디지털 경제의 긴꼬리 효과를 실증 분석하였다. 2019년부터 2021년까지 관찰기간 동안 음식 배달 플랫폼 활용 음식점 주비모수 분포의 긴꼬리 효과는 강건하게 관찰되었다. 이는 코로나19 이후 음식배달 플랫폼을 통한 음식점의 디지털 전환이 틈새시장 확장에 일정 부분 기여하였음을 의미한다. 또한, 긴꼬리 효과는 객단가가 높을수록 매출액 상위 집단일수록 더 커지는 반면, 비황금 시간대 매출비중이 높은 경우 긴꼬리 효과가 통계적으로 유의하게 증가하지 않았다. 이 결과는 피자, 족발 등 단가가 높고 비교적 배달서비스가 활발한 카테고리에서 음식 주문 및 배달 산업의 디지털 전환 효과가 증가한다는 업계 실무자들의 관찰과 부합한다. 타 업종에서도 상대적으로 경쟁이 치열한 시장 구분에서 디지털 경제의 긴꼬리 효과가 보다 강건하게 관찰될 것이라고 여겨진다. 음식점 간 경쟁강도가 상대적으로 약한 비황금시간대 매출비중이 긴꼬리 효과에 통계학적으로 유의한 영향을 주지 않는다는 실증결과 또한 동일한 함의가 있다.

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Nonparametric compositional data analysis for tourism industry in Gangwon area (강원도 관광산업에 대한 비모수적 구성비 자료 분석)

  • Seongeun Park;Jeong Min Jeon;Young Kyung Lee
    • The Korean Journal of Applied Statistics
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    • v.36 no.5
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    • pp.473-488
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    • 2023
  • Gangwon-do is one of Korea's most popular tourist destinations, with varying tourism demands and trends across its subregions. It is crucial to identify the characteristics of tourism in each area and compare the tourism patterns over time to devise policies that revitalize tourism in each local government and promote balanced development across regions. In this paper, we classify the regions in Gangwon-do based on tourism data from the last four years and analyze the tourism pattern of each region using the non-Euclidean additive model proposed by Jeon et al. (2021). The model incorporates the proportions of visitors by age groups and the proportions of navigation searches by destination types as two covariates, and the proportions of tourism expenditure types as a response variable. We estimate the model using the smooth-backfitting method and coordinate-wise bandwidth selection. The results are visualized in ternary plots, and changes in tourism patterns over time are analyzed by comparing the ratios of prediction errors to fitting errors.

다변량회귀모형(多變量回歸模型)을 이용한 규제변동(規制變動)의 재무효과 측정(測定)

  • Yu, Beom-Jun
    • The Korean Journal of Financial Management
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    • v.9 no.1
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    • pp.83-109
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    • 1992
  • 본 연구는 다변량회귀모형(多變量回歸模型)이 동일한 산업내 동일한 시기에 이루어진 규제변동(規制變動)의 재무효과를 측정하는 데에 시장모형(市場模型)보다 장기간에 걸친 복수의 가변적 발표내용, 규제관련기업의 차별적 주가수익반응, 그리고 주가수익잔차간 높은 상관관계 등의 규제특성과 방법론적 문제점을 해결하는 데에 유용한 사건모형(事件模型)임을 실증하고자 한다. 본 연구는 규제변동의 실증적 사례로서 1988년 12월 2일 정부가 발표한 ${\ulcorner}$자본시장국제화의 단계적 확대추진계획${\lrcorner}$에 이르기까지의 일련의 법제적 조치와 발표내용을 사건으로 하여 금융증권산업내 은행, 증권회사, 보험회사 그리고 투자금융회사의 평균적, 개별적, 포트폴리오 비정상수익에 관한 제반공동가설을 모수추정(母數推定)의 제약(制約)에 따라 비제약적(非制約的) 다변량회귀모형(多變量回歸模型) 또는 제약적(制約的) 다변량회귀모형(多變量回歸模型)으로 검증하였다. 모든 13개 발표사건에 대한 평균적, 개별적, 포트폴리오 비정상수익의 가설검증결과에서 은행과 증권회사는 모두 통계적으로 비유의적 반응을 보인 반면, 보험회사와 투자금융회사는 최종발표일이 다가오면서 일부 발표사건에 유의적인 평균반응과 개별반응을 보였다. 특히 모든 금융증권기관은 모든 사건에 비유의적 포트폴리오반응을 보여, Stigler가 제시한 '부(富)의 이전가설(移轉假說)'은 기각되지 못하였다.

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ROC Curve Fitting with Normal Mixtures (정규혼합분포를 이용한 ROC 분석)

  • Hong, Chong-Sun;Lee, Won-Yong
    • The Korean Journal of Applied Statistics
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    • v.24 no.2
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    • pp.269-278
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    • 2011
  • There are many researches that have considered the distribution functions and appropriate covariates corresponding to the scores in order to improve the accuracy of a diagnostic test, including the ROC curve that is represented with the relations of the sensitivity and the specificity. The ROC analysis was used by the regression model including some covariates under the assumptions that its distribution function is known or estimable. In this work, we consider a general situation that both the distribution function and the elects of covariates are unknown. For the ROC analysis, the mixtures of normal distributions are used to estimate the distribution function fitted to the credit evaluation data that is consisted of the score random variable and two sub-populations of parameters. The AUC measure is explored to compare with the nonparametric and empirical ROC curve. We conclude that the method using normal mixtures is fitted to the classical one better than other methods.

Estimation of Growth Curve for Evaluation of Growth Characteristics for Hanwoo cows (한우암소의 성장특성 평가를 위한 성장곡선의 추정)

  • Lee, C.W.;Choi, J.G.;Jeon, K.J.;Na, K.J.;Lee, C.;Yang, B.K.;Kim, J.B.
    • Journal of Animal Science and Technology
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    • v.45 no.4
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    • pp.509-516
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    • 2003
  • Growth curves were estimated for 1083 female Korean cattle raised in Daekwanryeong branch, National Livestock Research Institute (NLRI). Comparisons were made among various growth curve models for goodness of fit for the growth of the cows. Estimated growth curve functions were $W_t=370.2e^{-2.208e^{-0.00327t}$ for Gompertz model, for von Bertalanffy model, and $W_t=341.2(1+5.652e^{-0.00524t})^{-1}$ for Logistic model. Ages at inflection estimated from Gompertz model, von Bertalanffy model and Logistic model were 242.2 days, 191.5 days, and 330.5 days respectively, body weight at inflection were 136kg, 115kg, and 170kg, and daily gain at inflection were 0.445kg, 0.451kg, and 0.446kg. The predicted weights by ages from Gompertz model, von Bertalanffy model, and Logistic model were onsistently overestimated at birth weight and underestimated at 36 month weight. The von Bertalanffy model which had a variable point of inflection fit the data best.

Estimation of city gas demand function using time series data (시계열 자료를 이용한 도시가스의 수요함수 추정)

  • Lee, Seung-Jae;Euh, Seung-Seob;Yoo, Seung-Hoon
    • Journal of Energy Engineering
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    • v.22 no.4
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    • pp.370-375
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    • 2013
  • This paper attempts to estimate the city gas demand function in Korea over the period 1981-2012. As the city gas demand function provides us information on the pattern of consumer's city gas consumption, it can be usefully utilized in predicting the impact of policy variables such as city gas price and forecasting the demand for city gas. We apply lagged dependent variable model and ordinary least square method as a robust approach to estimating the parameters of the city gas demand function. The results show that short-run price and income elasticities of the city gas demand are estimated to be -0.522 and 0.874, respectively. They are statistically significant at the 1% level. The short-run price and income elasticities portray that demand for city gas is price- and income-inelastic. This implies that the city gas is indispensable goods to human-being's life, thus the city gas demand would not be promptly adjusted to responding to price and/or income change. However, long-run price and income elasticities reveal that the demand for city gas is price- and income-elastic in the long-run.