• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1491-1498
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• 2014

The major criticism of optimal experimental design is that it depends heavily on the model and its accompanying assumption that often leads the number of support points equal to the number of parameters in the model. Often in the past, a polynomial model of higher degree is assumed to handle the experimental design for the polynomial regression of lower degree. In this paper we searched the possible set of designs which are robust to the departure of the assumed model. The designs are categorized with respect to D-efficiency. The approach by O'Brien (1995) was discussed in univariate polynomial regression model setting.

• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.1-9
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• 2009

Let us consider that the variance function in regression model has a discontinuity/change point at unknown location. Yu and Jones (2004) proposed the local polynomial fit to estimate the log-variance function which break the positivity of the variance. Using the local polynomial fit, Huh (2008) estimate the discontinuity point of the log-variance function. We propose a test for the existence of a discontinuity point in the log-variance function with the estimated jump size in Huh (2008). The proposed method is based on the asymptotic distribution of the estimated jump size. Numerical works demonstrate the performance of the method.

• Journal of the Korean Data and Information Science Society
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• v.21 no.1
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• pp.51-59
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• 2010

In the case that the regression function has a discontinuity point in generalized linear model, Huh (2009) estimated the location and jump size using the log-likelihood weighted the one-sided kernel function. In this paper, we consider estimation of the unknown number of the discontinuity points in the regression function. The proposed algorithm is based on testing of the existence of a discontinuity point coming from the asymptotic distribution of the estimated jump size described in Huh (2009). The finite sample performance is illustrated by simulated example.

• Journal of Korean Society of Transportation
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• v.24 no.4 s.90
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• pp.7-17
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• 2006

The purpose or this paper is to investigate the relationship between highway improvement and Induced Travel Demand(ITD) focusing on the Seoul metropolitan area data. In addition, authors tried to estimate basic unit of demand elasticity focusing on zone and trip purpose which can be applied for the ITD forecasting. The results are based on the 2002 Metropolitan Household Transportation Survey Data, where the demand elasticity (DE) is -0.582 in Seoul, -0.597 in Incheon and -0.559 in Gyounggi province, respectively. This study revealed part of the relationship between highway improvement and ITD for metropolitan region and provided the framework for yielding real estimated values by applying the concept of demand elasticity in terms of the relationship by using regional and long-term data. We expect that the basic unit of demand elasticity focusing on zone and trip purpose can be applied for the ITD forecasting to analyze the whole demand exactly The estimated DE's for age group and day of week can also be used for Proper transportation management and transport Policy making. Some limitations have also been discussed.