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

• Journal of the Korean Data and Information Science Society
• /
• v.18 no.2
• /
• pp.515-524
• /
• 2007

This paper deals with local linear estimation of fuzzy regression models based on Diamond(1998) as a new class of non-linear fuzzy regression. The purpose of this paper is to introduce a use of smoothing in testing for lack of fit of parametric fuzzy regression models.

• 한국데이터정보과학회:학술대회논문집
• /
• 2005.04a
• /
• pp.193-199
• /
• 2005

A simple method is proposed to detect the number of change points with jump discontinuities in nonparamteric regression functions. The proposed estimators are based on a local linear regression fit by the comparison of left and right one-side kernel smoother. Also, the proposed methodology is suggested as the test statistic for detecting of change points and the direction of jump discontinuities.

• Communications for Statistical Applications and Methods
• /
• v.10 no.1
• /
• pp.31-38
• /
• 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
• /
• v.14 no.2
• /
• pp.401-411
• /
• 2007

In this paper we propose an influence measure for detecting potentially influential observations using the infinitesimal perturbation and the local influence in the log-linear regression model. Also, we propose a goodness-of-fit measure for variable selection. A real data set are used for illustration.

• Journal of the Korean Data and Information Science Society
• /
• v.25 no.1
• /
• pp.87-95
• /
• 2014

In the regression model, Kang and Huh (2006) studied the estimation of the discontinuous variance function using the Nadaraya-Watson estimator with the squared residuals. The local linear estimator of the log-variance function, which may have the whole real number, was proposed by Huh (2013) based on the kernel weighted local-likelihood of the ${\chi}^2$-distribution. Chen et al. (2009) estimated the continuous variance function using the local linear fit with the log-squared residuals. In this paper, the estimator of the discontinuous log-variance function itself or its derivative using Chen et al. (2009)'s estimator. Numerical works investigate the performances of the estimators with simulated examples.

• Journal of the Korean Data and Information Science Society
• /
• v.24 no.2
• /
• pp.211-222
• /
• 2013

We consider the problem of nonparametrically estimating the conditional quantile function from censored data and propose new estimators here. They are based on local logistic regression technique of Lee et al. (2006) and "double-kernel" technique of Yu and Jones (1998) respectively, which are modified versions under random censoring. We compare those with two existing estimators based on a local linear fits using the check function approach. The comparison is done by a simulation study.

• Proceedings of the Korean Statistical Society Conference
• /
• 2003.10a
• /
• pp.179-182
• /
• 2003

This study describes a new graphical method for assessing and characterizing effect modification by a matching covariate in matched case-control studies. This method to understand effect modification is based on a semiparametric model using a varying coefficient model. The method allows for nonparametric relationships between effect modification and other covariates, or can be useful in suggesting parametric models. This method can be applied to examining effect modification by any ordered categorical or continuous covariates for which cases have been matched with controls. The method applies to effect modification when causality might be reasonably assumed. An example from veterinary medicine is used to demonstrate our approach. The simulation results show that this method, when based on linear, quadratic and nonparametric effect modification, can be more powerful than both a parametric multiplicative model fit and a fully nonparametric generalized additive model fit.

• Journal of radiological science and technology
• /
• v.22 no.1
• /
• pp.61-66
• /
• 1999

The use of multileaf collimator(MLC) to replace conventional field-shaping techniques is not in itself expected to improve the local control of malignancy. The purpose for using MLCs in conventional radiation oncology is to improve the efficiency of treatment delivery. For effective clinical application of MLCs to shaped radiation field, field outline must be translated into MLC leaf position tables. The intended leaf positions contained in these tables must then be communicated to the control computer that drives the MLC. There are currently at least three techniques utilized by manufacturers of MLCs and treatment planning systems for doing this. The Varian series use a workstation employing a manual digitizer and light box especially. It has a third level MLC configuration and also has the option of placing the wedges above or below the block tray. The C language are used for development of software and three leaf coverage have been used for positioning MLC loaves at the nominal field boundary. The fit of the leaf shape to treatment target volumes are optimized by the rotation of the direction in leaf travel. The clinical application of this software are investigated for Varian MLCs used in linear accelerator of Yonsei Cancer Center. The advantage of the results with using this software is to prescribe and calculate exposed and blocked area in MLCs field.

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