• 제목/요약/키워드: Dummy variables

검색결과 161건 처리시간 0.032초

더미변수(Dummy Variable)를 포함하는 다변수 시계열 모델을 이용한 단기부하예측 (Short-Term Load Forecasting Using Multiple Time-Series Model Including Dummy Variables)

  • 이경훈;김진오
    • 대한전기학회논문지:전력기술부문A
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    • 제52권8호
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    • pp.450-456
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    • 2003
  • This paper proposes a multiple time-series model with dummy variables for one-hour ahead load forecasting. We used 11 dummy variables that were classified by day characteristics such as day of the week, holiday, and special holiday. Also, model specification and selection of input variables including dummy variables were made by test statistics such as AIC(Akaike Information Criterion) and t-test statistics of each coefficient. OLS (Ordinary Least Squares) method was used for estimation and forecasting. We found out that model specifications for each hour are not identical usually at 30% of optimal significance level, and dummy variables reduce the forecasting error if they are classified properly. The proposed model has much more accurate estimates in forecasting with less MAPE (Mean Absolute Percentage Error).

엑셀 VBA을 이용한 가변수 회귀모형 교육도구 개발 (An educational tool for regression models with dummy variables using Excel VBA)

  • 최현석;박철용
    • Journal of the Korean Data and Information Science Society
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    • 제24권3호
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    • pp.593-601
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    • 2013
  • 회귀모형에서 범주형 변수를 독립변수로 포함시켜야 할 경우가 발생한다. 회귀모형의 범주형 변수는 가변수를 통해 수량화된다. 이 연구에서는 하나의 양적 독립변수와 하나 혹은 두 개의 범주형 독립변수를 가지는 회귀모형에 대해 가설검정 결과와 함께 회귀직선을 보여주는 교육용 도구를 엑셀 VBA (Visual Basic for application)를 통해서 구현한다. 가설검정 결과와 회귀직선은 교호작용이 포함된 모형, 교호작용이 없는 모형 및 가변수가 없는 모형에 대해 단계별로 제공된다. 이 교육도구를 통해 가변수와 교호작용의 의미를 더 쉽게 이해할 수 있으며, 나아가 어떤 모형이 주어진 자료에 가장 적합한지 그림을 통해 판단할 수 있게 된다.

더미(dummy) 변수를 활용한 다중인자 차원 축소(MDR) 방법 (Multifactor Dimensionality Reduction(MDR) Analysis by Dummy Variables)

  • 이제영;이호근
    • 응용통계연구
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    • 제22권2호
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    • pp.435-442
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    • 2009
  • 통계모형의 상호작용 효과를 분석하기 위해 비모수적인 방법인 다중인자 차원 축소(MDR) 방법을 사용해왔다. MDR 방법은 사례-대조 데이터에만 적용 할 수 있다. 본 논문에서는 연속형 데이터에도 적용 할 수 있는 더미(dummy) 변수를 활용한 MDR방법을 소개한다. 아울러 이를 통해 한우의 주요 경제형질인 등심단면적 (longissimus muscle dorsi area: LMA), 도체중(carcass cold weight: CWT), 일당증체량(average daily gain: ADC)에 영향을 주는 우수 유전자 단일염기다형성(SNP)을 규명한다.

Localizing Growth Model of Chamaecyparis obtusa Stands Using Dummy Variables in a Single Equation

  • Lee, Sang-Hyun;Kim, Hyun
    • 한국산림과학회지
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    • 제94권2호통권159호
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    • pp.121-126
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    • 2005
  • This study was carried out to construct a single diameter and a single height model that could localize Chamaecyparis obtusa stand grown in 3 Southern regions of Korea. Dummy variables, which convert qualitative information such as geographical regions into quantitative information by means of a coding scheme (0 or 1), were used to localize growth models. In results, modified form of Gompertz equation, $Y_2={\exp}({\ln}(Y_1){\exp}(-{\beta}(T_2-T_1)+{\gamma}({T_2}^2-{T_1}^2))+({\alpha}+{\alpha}_1Al+{\beta}_1k_1+{\beta}_2k_2)(1-{\exp}(-{\beta}(T_2-T_1)+{\gamma}({T_2}^2-{T_1}^2))$, for diameter and height was successfully disaggregated to provide different projection equation for each of the 3 regions individually. The use of dummy variables on a single equation, therefore, provides potential capabilities for testing the justification of having different models for different sub-populations, where a number of site variables such as altitude, annual rainfall and soil type can be considered as possible variables to explain growth variation across regions.

더미 기반 부채널 분석 대응기법 신규 취약점 - Case Study: XMEGA (Novel Vulnerability against Dummy Based Side-Channel Countermeasures - Case Study: XMEGA)

  • 이종혁;한동국
    • 정보보호학회논문지
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    • 제29권2호
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    • pp.287-297
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    • 2019
  • 부채널 분석에 안전하게 암호 알고리즘을 구현하는 경우, 설계자들은 일반적으로 1차 마스킹 기법과 하이딩 기법을 혼합하여 사용한다. 1차 마스킹 기법과 하이딩 기법을 혼합하여 사용한 구현은 충분한 안전성과 효율성 모두 만족하는 방법이다. 그러나 더미 연산이 실제 연산과 구별될 수 있다면, 공격자는 설계자가 더미 연산을 추가함으로써 의도한 공격 복잡도보다 낮은 공격 복잡도로 비밀 키를 획득할 수 있다. 본 논문에서는 C언어 이용 시 더미 연산에 사용되는 변수의 형태를 4가지로 분류하고, 변수의 형태를 달리 사용하여 하이딩 대응기법을 적용한 경우 모두에 대해 더미 연산을 구분할 수 있는 신규 취약점을 제시한다. 그리고 이에 대한 대응기법을 제시한다.

가계특성과 주거비지출: 근로자가계 분석 (The Effects of Household Characteristics on Housing Expenditure)

  • 양세화;오찬옥;양세정
    • 한국주거학회논문집
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    • 제10권2호
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    • pp.235-245
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    • 1999
  • The purpose of the study is to examine the effects of household characteristics on housing expenditure. The data from the National Survey of Family Income and Expenditure 1996 were used for the analysis of this study, and the final sample included 12,323 households. It was found that total housing expenditure was significantly different according to the tenure type, household income, household size, age, occupation and education of the head, or location of housing. The significantly explanatory variables in the model of total housing expenditure were owner and yearly-renter dummy, household income and the household income squared, mortgage-off dummy, Seoul and metropolitan city dummy, and employed-wife dummy.

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전자부품 검사에서 대용특성을 이용한 사례연구 (A Case Study on Electronic Part Inspection Based on Screening Variables)

  • 이종설;윤원영
    • 품질경영학회지
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    • 제29권3호
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    • pp.124-137
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    • 2001
  • In general, it is very efficient and effective to use screening variables that are correlated with the performance variable in case that measuring the performance variable is impossible (destructive) or expensive. The general methodology for searching surrogate variables is regression analysis. This paper considers the inspection problem in CRT (Cathode Ray Tube) production line, in which the performance variable (dependent variable) is binary type and screening variables are continuous. The general regression with dummy variable, discriminant analysis and binary logistic regression are considered. The cost model is also formulated to determine economically inspection procedure with screening variables.

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Development of the Plywood Demand Prediction Model

  • Kim, Dong-Jun
    • 한국산림과학회지
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    • 제97권2호
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    • pp.140-143
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    • 2008
  • This study compared the plywood demand prediction accuracy of econometric and vector autoregressive models using Korean data. The econometric model of plywood demand was specified with three explanatory variables; own price, construction permit area, dummy. The vector autoregressive model was specified with lagged endogenous variable, own price, construction permit area and dummy. The dummy variable reflected the abrupt decrease in plywood consumption in the late 1990's. The prediction accuracy was estimated on the basis of Residual Mean Squared Error, Mean Absolute Percentage Error and Theil's Inequality Coefficient. The results showed that the plywood demand prediction can be performed more accurately by econometric model than by vector autoregressive model.

운전 유형에 따른 가로구간 사고모형 개발 (Developing the Traffic Accident Models of Arterial Link Sections by Driving Type)

  • 김경환;박병호
    • 한국안전학회지
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    • 제25권6호
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    • pp.197-202
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    • 2010
  • This study deals with the accident models of arterial link sections by driving type. The objectives is to develop models by driving type using the accident data of 24 arterial links in Cheong-ju. In pursuing the above, this study gives particular emphasis to modeling such the accidents as the straight, lane change and others. The main results analyzed are as follows. First, the number of accidents is analyzed to account for about 59% in straight, 31% in lane change and 10% in others. Second, the number of left-turn lane as common variables, and the ADT, number of pedestrian crossings, connecting roads and link length as specific variables are selected in developing models(number of accident and EPDO). Third, 8 models which are all statistically significant are developed. Finally, RMSE of the driving type models was analyzed to be better than that of dummy variable.

Development of the Lumber Demand Prediction Model

  • Kim, Dong-Jun
    • 한국산림과학회지
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    • 제95권5호
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    • pp.601-604
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    • 2006
  • This study compared the accuracy of partial multivariate and vector autoregressive models for lumber demand prediction in Korea. The partial multivariate model has three explanatory variables; own price, construction permit area and dummy. The dummy variable reflected the boom of lumber demand in 1988, and the abrupt decrease in 1998. The VAR model consists of two endogenous variables, lumber demand and construction permit area with one lag. On the other hand, the prediction accuracy was estimated by Root Mean Squared Error. The results showed that the estimation by partial multivariate and vector autoregressive model showed similar explanatory power, and the prediction accuracy was similar in the case of using partial multivariate and vector autoregressive model.