• Communications for Statistical Applications and Methods
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• v.2 no.1
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• pp.99-111
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• 1995

It is shown that the adaptive kernel methods can potentially produce superior density estimates to the fixed one. In using the adaptive estimates, problems pertain to the initial choice of the estimate can be solved by iteration. Also, simultaneous recommended for variety of distributions. Some data-based method for the choice of the parameters are suggested based on simulation study.

• Journal of applied mathematics & informatics
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• v.6 no.1
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• pp.163-174
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• 1999

The purpose of this paper is to obtain the solution of Fredholm-Volterra integral equation with singular kernel in the space $L_2(-1, 1)\times C(0,T), 0 \leq t \leq T< \infty$, under certain conditions,. The numerical method is used to solve the Fredholm integral equation of the second kind with weak singular kernel using the Toeplitz matrices. Also the error estimate is computed and some numerical examples are computed using the MathCad package.

• Journal of the Korean Statistical Society
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• v.33 no.1
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• pp.59-78
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• 2004

A regression function in generalized linear model may have a discontinuity/change point at unknown location. In order to estimate the location of the discontinuity point and its jump size, the strategy is to use a nonparametric approach based on one-sided kernel weighted local-likelihood functions. Weak convergences of the proposed estimators are established. The finite-sample performances of the proposed estimators with practical aspects are illustrated by simulated examples.

• Journal of the Korean Data and Information Science Society
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• v.6 no.1
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• pp.31-37
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• 1995

We consider density estimates of the usual type generated by a kernel function. By using the limit theorems for the maximum of normalized deviation of the estimate from its expected value, we propose to use data dependent bandwidth in the tests of goodness of fit based on these statistics. Also a small sample Monte Carlo simulation is conducted and proposed method is compared with Kolmogorov-Smirnov test.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.645-650
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• 2015

Image restoration is required when the image is blurred due to out of focus or motion during the image acquisition. This type of image restoration is known as ill-posed inverse problem because the estimate of an original image should be derived from only one blurred image. This paper introduces a reference image to facilitate the restoration process. The experimental result shows that computation time is significantly reduced, compared with other methods. The proposed method obtains the estimate of the kernel used in blurring processing. New cost function is defined to update both the image and the kernel alternately. In the last stage, Wiener filter produces the estimate of an original image using the kernel and the reference image.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.987-994
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• 2011

From the point view of credit evaluation whose population is divided into the default and non-default state, two methods are considered to estimate conditional distribution functions: one is to estimate under the assumption that the data is followed the mixture normal distribution and the other is to use the kernel density estimation. The parameters of normal mixture are estimated using the EM algorithm. For the kernel density estimation, five kinds of well known kernel functions and four kinds of the bandwidths are explored. In addition, the corresponding ROC functions are obtained based on the estimated distribution functions. The goodness-of-fit of the estimated distribution functions are discussed and the performance of the ROC functions are compared. In this work, it is found that the kernel distribution functions shows better fit, and the ROC function obtained under the assumption of normal mixture shows better performance.

• Journal of Ecology and Environment
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• v.29 no.3
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• pp.253-257
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• 2006

The objectives of this paper are to estimate home range and core habitat area of wild bores in Jirisan National Park of Korea. A radio-telemetry study was carried out on 5 wild boar individuals (3 females and 2 males). Except one individual whose enough data could not be collected, the mean home range size of 4 individuals was $5.13km^2$ (95% kernel) and mean core habitat area was $1.18{\pm}0.31km^2$ (50% kernel). Home-range sizes of 2 females were $6.21km^2\;and\;5.45km^2$ each, and that of 2 males were $5.15km^2\;and\;3.72km^2$ each, which means home-ranges of female boars were larger than those of male boars in this research. This result is presumed to have been caused by the fact that the males were sub adult individuals weighing 40 kg and 19 kg when they were captured for this research.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.454-459
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• 2012

A kernel function of apparent earth resistivity can be estimated using the apparent earth resistivity measured with Wenner's 4 point method. It becomes to solve a nonlinear system to estimate the kernel function of apparent earth resistivity. However it is not simple to get solution of nonlinear system with many unknown variables. This paper suggests the method of estimating kernel function by linearizing this nonlinear system. Finally, various examples of earth structure have been simulated to evaluate the proposed method in this paper.

• Journal of the Korean Statistical Society
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• v.27 no.4
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• pp.515-529
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• 1998

Burman (1987) and Hall and Titterington (1987) studied kernel smoothing for sparse multinomial data in detail. Both of their estimators for cell probabilities are sparse asymptotic consistent under some restrictive conditions on the true cell probabilities. Dong and Simonoff (1994) adopted boundary kernels to relieve the restrictive conditions. We propose a local linear kernel estimator which is popular in nonparametric regression to estimate cell probabilities. No boundary adjustment is necessary for this estimator since it adapts automatically to estimation at the boundaries. It is shown that our estimator attains the optimal rate of convergence in mean sum of squared error under sparseness. Some simulation results and a real data application are presented to see the performance of the estimator.

• International Journal of Reliability and Applications
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• v.6 no.1
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• pp.1-12
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• 2005

A new test for testing that a life distribution is exponential against the alternative that it is harmonic new better (worse) than used in expectation upper tail HNBUET (HNWUET), but not exponential is presented based on the highly popular 'Kernel methods' of curve fitting. This new procedure is competitive with old one in the sense of Pitman's asymptotic relative efficiency, easy to compute and does not depend on the choice of either the band width or kernel. It also enjoys good power.