• Communications for Statistical Applications and Methods
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• v.21 no.3
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• pp.253-260
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• 2014

The intraclass correlation model has a long history of applications in several fields of research. Case deletion diagnostic methods for the intraclass correlation model are proposed. Based on the likelihood equations, we derive a formula for a case deletion diagnostic method which enables us to investigate the influence of observations on the maximum likelihood estimates of the model parameters. Using the Taylor series expansion we develop an approximation to the likelihood distance. Numerical examples are provided for illustration.

• Bulletin of the Korean Mathematical Society
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• v.52 no.1
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• pp.85-103
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• 2015

We prove some sharp extremal distance results for functions in various spaces of analytic functions on bounded strictly pseudoconvex domains with smooth boundary. Also, we obtain atomic decompositions in multifunctional Bloch and weighted Bergman spaces of analytic functions on strictly pseudoconvex domains with smooth boundary, which extend known results in the classical case of a single function.

• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.349-360
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• 1995

This paper deals with the robustness properties of the minimum disparity estimation in linear regression models. The estimators defined as statistical quantities whcih minimize the blended weight Hellinger distance between a weighted kernel density estimator of the residuals and a smoothed model density of the residuals. It is shown that if the weights of the density estimator are appropriately chosen, the estimates of the regression parameters are robust.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.4
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• pp.339-346
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• 2009

The objectives of this study were to introduce spatial interpolation methods which have been applied in recent papers, to apply three methods (nearest monitor, inverse distance weighting, kriging) to domestic data (Ulsan cohort) as an example of estimating the personal exposure levels. We predicted the personal exposure estimates of 2,102 participants in Ulsan cohort using spatial interpolation methods based on information of their residential address. We found that there was a similar tendency among the estimates of each method. The correlation coefficients between predictions from pairs of interpolation methods (except for the correlation coefficient between nearest montitor and kriging of CO and $SO_2$) were generally high (r=0.84 to 0.96). Even if there are some limitations such as location and density of monitoring station, spatial interpolation methods can reflect spatial aspects of air pollutant and spatial heterogeneity in individual level so that they provide more accurate estimates than monitor data alone. But they may still result in misclassification of exposure. To minimize misclassification for better estimates, we need to consider individual characteristics such as daily activity pattern.

• Journal of Korea Technology Innovation Society
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• v.1 no.3
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• pp.374-385
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• 1998

This study is estimates telephone service demand based on empirical studies of telecommunication service demand model. First, the telephone charge(call price index) by each location and subscription fee bring about a negative effect to telephone distribution rate: while the other explanatory variables bring about a positive effect. Second, the flexibility of telephone charge in A location(relevant location) and the flexibility between the distance of A location and B location are negative values, while the flexibility of other explanatory variables is represented in a positive value. This means that the long distance call numbers from A location to B location are in inverse proportion against the phone charge(call price index) of A location and against the distance between A location and the distance of other locations except A location, while they are in direct proportion with an average call number per minute from A location to other locations except A location, and also with subscription numbers of A location, other subscribers in locations other than A location, and the total expenditures of A location.

• Asian-Australasian Journal of Animal Sciences
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• v.22 no.1
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• pp.13-19
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• 2009

In the present study, genetic analyses of diversity and differentiation were performed on four breeds of Indian zebu cattle (Bos indicus). In total, 181 animals belonging to Ponwar, Kherigarh, Gangatiri and Kenkatha breeds were genotyped for 20 cattle specific microsatellite markers. Mean number of alleles observed per locus (MNA) varied between 5.75 (Kenkatha) to 6.05 (Kherigarh). The observed and expected heterozygosity for the breeds varied from 0.48 (Gangatiri) to 0.58 (Kherigarh) and 0.65 (Kenkatha) to 0.70 (Kherigarh), respectively. $F_{IS}$ estimates of all the breeds indicated significant deficit of heterozygotes being 28.8%, 25.9%, 17.7% and 17.7% for Gangatiri, Ponwar, Kherigarh and Kenkatha, respectively. The $F_{ST}$ estimates demonstrated that 10.6% was the average genetic differentiation among the breeds. Nei's genetic distance DA and Cavalli- Sforza and Edwards Chord distance ($D_C$) and the phylogenetic tree constructed from these reflected the close genetic relationship of Gangatiri and Kenkatha, whereas Ponwar appears to be more distant.

• Journal of information and communication convergence engineering
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• v.12 no.4
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• pp.215-220
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• 2014

We consider quantization optimized for distributed estimation, where a set of sensors at different sites collect measurements on the parameter of interest, quantize them, and transmit the quantized data to a fusion node, which then estimates the parameter. Here, we propose an iterative quantizer design algorithm with a weighted distance rule that allows us to reduce a system-wide metric such as the estimation error by constructing quantization partitions with their optimal weights. We show that the search for the weights, the most expensive computational step in the algorithm, can be conducted in a sequential manner without deviating from convergence, leading to a significant reduction in design complexity. Our experments demonstrate that the proposed algorithm achieves improved performance over traditional quantizer designs. The benefit of the proposed technique is further illustrated by the experiments providing similar estimation performance with much lower complexity as compared to the recently published novel algorithms.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.2
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• pp.50.4-51
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• 2015

Current and planned deep multicolor wide-area cosmological surveys will map in detail the spatial distribution of galaxies and quasars over unprecedented volumes, and provide a number of objects with photometric redshifts more than an order of magnitude bigger than that of spectroscopic redshifts. Photometric information is statistically more significant for studying cosmological evolution, dark energy, and the expansion history of the universe at a fraction of the cost of a full spectroscopic survey, but intrinsically carries a bias due to noise in the distance estimates. We provide convolution- and deconvolution-based algorithms capable of removing this bias -- thus able to exploit the full cosmological information -- in order to reconstruct intrinsic distributions and correlations between distance-dependent quantities. We then show some direct applications of our techniques to the VIMOS Public Extragalactic Redshift Survey (VIPERS) and the Sloan Digital Sky Survey (SDSS) datasets. Our methods impact a broader range of studies, when at least one distance-dependent quantity is involved; hence, they will be useful for upcoming large-volume surveys, some of which will only have photometric information.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.371-383
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• 2000

Lindsay (1994) and Basu et al (1997) show that another density-based distance called the negative exponential disparity (NED) is an excellent competitor to the Hellinger distance (HD) in generating an asymptotically fully efficient and robust estimator. Bhattacharya and Basu (1996) consider estimation of the locations of several normal populations when an order relation between them is known to be true. They empirically show that the robust HD based weighted likelihood estimators compare favorably with the M-estimators based on Huber's $\psi$ function, the Gastworth estimator, and the trimmed mean estimator. In this paper we investigate the performance of the weighted likelihood estimator based on the NED as a robust alternative relative to that based on the HD. The NED based estimator is found to be quite competitive in the settings considered by Bhattacharya and Basu.

• The Journal of Korea Robotics Society
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• v.7 no.1
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• pp.45-56
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• 2012

This paper proposes how to improve the performance of CSS-based indoor localization system. CSS based localization utilizes signal flight time between anchors and tag to estimate distance. From the distances, the 3-dimensional position is calculated through trilateration. However the error in distance caused from multi-path effect transfers to the position error especially in indoor environment. This paper handles a problem of reducing error in raw distance information. And, we propose the new localization method by pattern matching instead of the conventional localization method based on trilateration that is affected heavily on multi-path error. The pattern matching method estimates the position by using the fact that the measured data of near positions possesses a high similarity. In order to gain better performance of localization, we use EKF(Extended Kalman Filter) to fuse the result of CSS based localization and robot model.