• Journal of applied mathematics & informatics
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• 제8권2호
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• pp.627-634
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• 2001

Under contamination, Bahadur representations with a strong remainder term are derived for random central order statistics with a prescribed limiting rank, and asymptotic normalities for these statistics of truncated and contaminated data are proved, with a suitable limiting rank. From these results, an application to the fixed-width confidence interval problem is available.

• Journal of Multimedia Information System
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• 제1권2호
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• pp.127-132
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• 2014

The transverse electromagnetic (TEM) cells are widely used for electromagnetic compatibility (EMC) testing and field probe calibrations. We propose the verification of TEM mode with statistical method using a four-port TEM cell. The verification results are compared with Normal, Rayleigh, and Gamma distribution. As a result, the 75 % quantile of the Rayleigh distribution is excellent agreement with the true quantiles for a number of calibration points.

• Journal of the Korean Data and Information Science Society
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• 제21권5호
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• pp.973-981
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• 2010

Quantile regression investigates the quantiles of the conditional distribution of a response variable given a set of covariates. M-quantile regression extends this idea by a "quantile-like" generalization of regression based on influence functions. In this paper we propose a new method of estimating M-quantile regression functions, which uses kernel machine technique. Simulation studies are presented that show the finite sample properties of the proposed M-quantile regression.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -2
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• pp.1343-1345
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• 2002

In this paper, we introduce the MC-CDMA (Multi-Carrier CDMA) system with MD (multi-detector). Due to unknown functional form of noise in wireless channel environments, it is not easy to design the detector through estimating the functional form of noise. Instead, we design the MD, which is constructed based on DGT (Data Grouping Technique) and quantiles estimated through RMSA (Robbins-Monro Stochastic Approximation) algorithm.

• Communications for Statistical Applications and Methods
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• 제9권2호
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• pp.325-335
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• 2002

In this paper we introduce some adaptive M-estimators using selector statistics to estimate the center of symmetric and continuous underlying distributions. This selector statistics is based on the idea of Hogg(1983) and Hogg et. al. (1988) who used averages of some order statistics to discriminate underlying distributions. In this paper, we use the functions of sample quantiles as selector statistics and determine the suitable quantile points based on maximizing the distance index to discriminate distributions under consideration. In Monte Carlo study, this robust estimation method works pretty good in wide range of underlying distributions.

• Journal of the Korean Data and Information Science Society
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• 제11권2호
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• pp.139-155
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• 2000

An exclusive simulation study is conducted in computing means for order statistics in standard normal variate. Monte Carlo moments are used in Shapiro-Francia W' statistic computation. Finally, quantiles for Shapiro-Francia W' are generated. The study shows that in computing means for order statistics in standard normal variate, complicated distributions and intensive numerical integrations can be avoided by using Monte Carlo simulation. Lack of accuracy is minimal and computation simplicity is noteworthy.

• Journal of the Korean Data and Information Science Society
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• 제19권4호
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• pp.1027-1036
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• 2008

Value at Risk(VaR) is a fundamental tool for managing market risks. It measures the worst loss to be expected of a portfolio over a given time horizon under normal market conditions at a given confidence level. Calculation of VaR frequently involves estimating the volatility of return processes and quantiles of standardized returns. In this paper, we introduced and applied the CreditMetrics model to estimate the credit VaR of Korean Property and Casuality insurers.

• Communications for Statistical Applications and Methods
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• 제12권2호
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• pp.395-411
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• 2005

In this paper, we develop the Jeffreys' prior, reference prior and the the probability matching priors for the difference of intraclass correlation coefficients in familial data. e prove the sufficient condition for propriety of posterior distributions. Using marginal posterior distributions under those noninformative priors, we compare posterior quantiles and frequentist coverage probability.

• 한국수자원학회논문집
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• 제45권3호
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• pp.253-262
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• 2012

본 연구에서는 스케일 특성을 이용하여 기후변화에 따른 일단위 이하의 극한강우를 평가할 수 있는 방법을 제안하였으며, 서울을 비롯한 6개 주요 기상관측소 지점을 대상으로 적용성을 평가하였다. 우선, 과거 관측자료를 이용하여 스케일 특성을 이용한 확률강우량 산정기법의 적용성을 평가하였으며, 평가 결과 빈도분석과 스케일특성으로 산정된 확률강우량의 절대상대오차가 10% 내외의 범위를 보였다. 또한 기준기간의 기후시나리오를 이용하여 적용성 평가를 수행한 결과 100년 빈도이내에서 20% 내의 절대상대오차를 보였다. 평가 결과를 통해 본 연구에서 적용한 스케일 특성 기법은 미래 확률강우량 산정 시 신뢰성 있는 결과를 도출할 수 있을 것으로 판단된다.

• Journal of the Korean Data and Information Science Society
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• 제28권1호
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• pp.119-130
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• 2017

다변량 분포에서의 VaR (Value at Risk)와 CTE (Conditional Tail Expectation)에 관한 많은 연구문헌에서는 특정한 포트폴리오 구성비를 이용하여 일변량 분포로 변환하여 추정하였다. 다변량 분포에서 분위수에 관한 많은 연구가 존재한다. 그러나 분위수가 유일하게 존재하지 않으므로, VaR와 CTE의 추정에 어려움이 있다. 본 연구에서는 다변량 분위 벡터를 이용한 대안적인 VaR와 통합적인 다변량 CTE의 연구를 확장하여, 여러 종류의 포트폴리오로 구성된 다양한 비율 조합에 따른 가중 CTE 벡터들을 제안한다. 일변량에 대한 CTE 관계식을 다차원의 관계식으로 확장하고, 일변량의 관계식과의 특징과 차이점에 대하여 토론한다. 정규분포로부터 추출한 자료와 실증 예제를 통하여 본 연구에서 제안한 가중 CTE를 탐색하면서 가중 CTE의 활용성과 장점을 유도한다.