• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.31-38
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• 2003

A simple method is proposed to detect the number of change points and test the location and size of multiple change points with jump discontinuities in an otherwise smooth regression model. The proposed estimators are based on a local linear regression fit by the comparison of left and right one-side kernel smoother. Our proposed methodology is explained and applied to real data and simulated data.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.843-848
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• 1999

Support vector machine(SVM) is a new and very promising classification and regression technique developed by Bapnik and his group at AT&T Bell laboratories. However it has failed to establish itself as common machine learning tool. This is partly due to the fact that SVM is not easy to implement and its standard implementation requires the optimization package for quadratic programming. In this paper we present simple iterative Kernl Adatron algorithm for nonparametric regression which is easy to implement and guaranteed to converge to the optimal solution and compare it with neural networks and projection pursuit regression.

• The Pure and Applied Mathematics
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• v.20 no.2
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• pp.109-116
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• 2013

In this paper, we propose a Jonckheere type test statistic for testing the parallelism of k regression lines against ordered alternatives. The order restriction problems could arise in various settings such as location, scale, and regression problems. But most of theory about the statistical inferences under order restrictions has been developed to deal with location parameters. The proposed test is an application of Jonckheere's procedure to regression problem. Asymptotic normality and asymptotic distribution-free properties of the test statistic are obtained under some regularity conditions.

• Journal of Labour Economics
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• v.36 no.2
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• pp.37-65
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• 2013

This study compares the return to seniority and experience among different groups of workers. Skilled workers in large company appear to enjoy the biggest seniority premium, while non-regular workers and small company workers hardly have any. Trade union did not have significant effect. Return to experience increased especially in large firms. Nonparametric model specification test shows that the biases for returns to seniority and experience of 30 years to be between -25~29%, and -42%~6%, respectively.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.237-245
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• 1993

A nonparametric test for the parallelisim of k regression lines against ordered alternatives is proposed. The test statistic is weighted Jonckheere-type statistic applied to slope estimators obtained from each lines. The distribution of the proposed test statistic is asymptotically distribution-free. From the viewpoint of efficiencies, the proposed test desirable properties and is more efficient than the other nonparametric tests.

• The Korean Journal of Applied Statistics
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• v.7 no.1
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• pp.19-34
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• 1994

In this paper we propose nonparametric tests of parallelism against umbrella alternatives of slopes in k-regression lines and investigate the asymptotic properties of the proposed test statistics. For the known peak and unknown peak, we suggest the test statistics and show that, from Monte Carlo study, the proposed test statistics have good empirical powers for heavy tailed distributions than the likelihood ratio tests.

• Communications for Statistical Applications and Methods
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• v.27 no.5
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• pp.511-521
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• 2020

In this paper, a partially linear multivariate model with error in the explanatory variable of the nonparametric part, and an m dimensional response variable is considered. Using the uniform consistency results found for the estimator of the nonparametric part, we derive an estimator of the parametric part. The dependence of the convergence rates on the errors distributions is examined and demonstrated that proposed estimator is asymptotically normal. In main results, both ordinary and super smooth error distributions are considered. Moreover, the derived estimators are applied to the economic behaviors of consumers. Our method handles contaminated data is founded more effectively than the semiparametric method ignores measurement errors.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.867-889
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• 2014

Nonparametric Bayesian (np Bayes) statistical models are popularly used in a variety of research areas because of their flexibility and computational convenience. This paper reviews the np Bayes models focusing on biomedical research applications. We review key probability models for np Bayes inference while illustrating how each of the models is used to answer different types of research questions using biomedical examples. The examples are chosen to highlight the problems that are challenging for standard parametric inference but can be solved using nonparametric inference. We discuss np Bayes inference in four topics: (1) density estimation, (2) clustering, (3) random effects distribution, and (4) regression.

• 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.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.251-260
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• 2002

The aim of this paper is to consider of detecting the location, the jump size and the number of change-points in regression functions by using the local linear fit which is one of nonparametric regression techniques. It is obtained the asymptotic properties of the change points and the jump sizes. and the correspondin grates of convergence for change-point estimators.