• The Korean Journal of Applied Statistics
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• v.27 no.5
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• pp.833-842
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• 2014

Non-inferiority trials indicate whether the effect of an experimental treatment is not worse than an active control. Chen et al. (2006) and Kang (2010) proposed a test method for non-inferiority trials using confidence intervals. In this paper, we suggest a new nonparametric method using a confidence interval based on Wilcoxon rank-sum test and Hodges-Lehmann estimator of active control. A Monte-Carlo simulation study compares the type I error and the power of the proposed method with previous methods.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.931-941
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• 2017

Typical Nonparametric methods for randomized block design with replications are two methods proposed by Mack (1981) and Mack and Skillings (1980). This method is likely to cause information loss because it uses the average of repeated observations instead of each repeated observation in the processing of each block. In order to compensate for this, we proposed a test method using linear placement statistics, which is a score function applied to the joint placement method proposed by Chung and Kim (2007). Monte Carlo simulation study is adapted to compare the power with previous methods.

• Environmental Engineering Research
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• v.18 no.1
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• pp.9-20
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• 2013

In this paper, the rainfall elasticity of streamflow was estimated to quantify the effects of climate change on 5 river basins. Rainfall elasticity denotes the sensitivity of annual streamflow for the variations of potential annual rainfall. This is a simple, useful method that evaluates how the balance of a water cycle on river basins changes due to long-term climate change and offers information to manage water resources and environment systems. The elasticity method was first used by Schaake in 1990 and is commonly used in the United States and Australia. A semi-distributed hydrological model (SLURP, semi-distributed land use-based runoff processes) was used to simulate the variations of area streamflow, and potential evapotranspiration. A nonparametric method was then used to estimate the rainfall elasticity on five river basins of Korea. In addition, the A2 (SRES IPCC AR4, Special Report on Emission Scenarios IPCC Fourth Assessment Report) climate change scenario and stochastic downscaling technique were used to create a high-resolution weather change scenario in river basins, and the effects of climate change on the rainfall elasticity of each basin were then analyzed.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.689-700
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• 2016

We study estimation and inference of the joint conditional distributions of bivariate longitudinal outcomes using regression models and copulas. For the estimation of marginal models we consider a class of time-varying transformation models and combine the two marginal models using nonparametric empirical copulas. Regression parameters in the transformation model can be obtained as the solution of estimating equations and our models and estimation method can be applied in many situations where the conditional mean-based models are not good enough. Nonparametric copulas combined with time-varying transformation models may allow quite flexible modeling for the joint conditional distributions for bivariate longitudinal data. We apply our method to an epidemiological study of repeatedly measured bivariate cholesterol data.

• KDI Journal of Economic Policy
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• v.34 no.2
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• pp.139-171
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• 2012

This paper examines the effect of private tutoring expenditures on academic performance of middle school students in South Korea, using data from "Analysis of the Level of School Education and Its Actual condition: Middle School". In the face of endogeneity of private tutoring expenditures, the paper employs an instrumental variable (IV) method and a nonparametric bounding method. Using both methods we show that the true effect of private tutoring on middle school students remains at most modest in Korea. The IV results suggest that a 10 percent increase in tutoring expenditure for Korean, English and math raises a student's test score of the subject at the largest by 1.24, 1.28, and 0.75 percent, respectively. The bounding results also fail to show evidence that an increase in tutoring expenditure leads to economically and statistically significant improvements in test score.

• Journal of the Korean Statistical Society
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• v.22 no.2
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• pp.361-368
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• 1993

In recent years, kernel type estimates are abundant. In this paper, we propose a bandwidth selection method for kernel regression of fixed design based on bootstrap procedure. Mathematical properties of proposed bootstrap-based bandwidth selection method are discussed. Performance of the proposed method for small sample case is compared with that of cross-validation method via a simulation study.

• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.83-126
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• 2005

Single-index models have found applications in econometrics and biometrics, where multidimensional regression models are often encountered. Here we propose a nonparametric estimation approach that combines wavelet methods for non-equispaced designs with Bayesian models. We consider a wavelet series expansion of the unknown regression function and set prior distributions for the wavelet coefficients and the other model parameters. To ensure model identifiability, the direction parameter is represented via its polar coordinates. We employ ad hoc hierarchical mixture priors that perform shrinkage on wavelet coefficients and use Markov chain Monte Carlo methods for a posteriori inference. We investigate an independence-type Metropolis-Hastings algorithm to produce samples for the direction parameter. Our method leads to simultaneous estimates of the link function and of the index parameters. We present results on both simulated and real data, where we look at comparisons with other methods.

• Communications for Statistical Applications and Methods
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• v.20 no.2
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• pp.115-127
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• 2013

This paper provides an effective stock portfolio screening tool for socially responsible investment (SRI) based upon corporate social responsibility (CSR) and financial performance. The proposed approach utilizes nonparametric frontier models. Data envelopment analysis (DEA) has been used to build SRI portfolios in a few previous works; however, we show that free disposal hull (FDH), a similar model that does not assume the convexity of the technology, yields superior results when applied to a stock universe of 253 Korean companies. Over a four-year time span (from 2006 to 2009) the portfolios selected by the proposed method consistently outperform those selected by DEA as well as the benchmark.

• Environmental and Resource Economics Review
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• v.10 no.3
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• pp.323-344
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• 2001

This study analyzes the relative efficiencies of three types of non-landfill treatment of food wastes; recycling to fertilizers or animal feeds, reducing the size of food wastes, and fermentation of food wastes. Unlike previous studies our study incorporates not only usual inputs and outputs but also emissions of pollutants such as odor and noise generated by the treatment facilities into the analysis. A nonparametric method suggested by Fare et al. (1989) has been used to estimate the relative efficiencies of facilities incorporating emission of pollutants. The results show that recycling is more efficient than the other two treatment methods. It is also shown that the usual models that do not incorporate the environmental aspects of the treatment facilities derive a biased conclusion on the relative efficiencies.

• Journal of the Korean Statistical Society
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• v.25 no.4
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• pp.499-514
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• 1996

Consider an additive regression model of Y on X = (X$_1$,X$_2$,. . .,$X_p$), Y = $sum_{j=1}^pf_j(X_j) + $\varepsilon$$, where $f_j$s are smooth functions to be estimated and $\varepsilon$ is a random error. If $X_j$s are fixed design points, we call it the fixed design additive model. Since the response variable Y is observed at fixed p-dimensional design points, the behavior of the nonparametric regression estimator depends on the design. We propose a fixed design called permutation fixed design, and fit the regression function by the kernel method. The estimator in the permutation fixed design achieves the univariate optimal rate of convergence in mean squared error for any p $\geq$ 2.