• Nuclear Engineering and Technology
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• 제55권11호
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• pp.4228-4237
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• 2023

The Improved Deterministic Truncation of Monte Carlo (iDTMC) is a powerful acceleration and variance reduction scheme in the Monte Carlo analysis. The concept of the iDTMC method and correlated sampling-based real variance estimation are briefly introduced. Moreover, the application of the iterative scheme to the correlated sampling is discussed. The iDTMC method is utilized in a 3-dimensional small modular reactor (SMR) model problem. The real variances of burnup-dependent criticality and power distribution are evaluated and compared with the ones obtained from 30 independent iDTMC calculations. The impact of the inactive cycles on the correlated sampling is also evaluated to investigate the consistency of the correlated sample scheme. In addition, numerical performances and sensitivity analysis on the real variance estimation are performed in view of the figure of merit of the iDTMC method. The numerical results show that the correlated sampling accurately estimates the real variances with high computational efficiencies.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.574-576
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• 2004

Since variance of noise is important parameter for a noise filter to reduce noise in image and the performance of noise filter is dependent on estimated variance. In this paper, we apply additive noise variance estimation method to estimate variance of speckle noise of synthetic aperture radar (SAR) imagery. Generally, speckle noise is in multiplicative model, logarithmic transformation is then used to transform multiplicative model into additive model. Here, speckle noise is generally modeled as Gamma distribution function with different looks. The additive noise variance estimation is processed in log domain. The synthesis image and real image of SAR are implemented to test and confirm results and show that more accurate estimation can be achieved.

• Communications for Statistical Applications and Methods
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• 제12권2호
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• pp.365-379
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• 2005

Balanced Repeated Replication(BRR) is widely used to estimate the variance of linear or nonlinear estimators from complex sampling surveys. Most of survey data sets include imputed missing values and treat the imputed values as observed data. But applying the standard BRR variance estimation formula for imputed data does not produce valid variance estimators. Shao, Chen and Chen(1998) proposed an adjusted BRR method by adjusting the imputed data to produce more accurate variance estimators. In this paper, another adjusted BRR method is proposed with examples of real data.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2005년도 한국컴퓨터종합학술대회 논문집 Vol.32 No.1 (A)
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• pp.820-822
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• 2005

The current paper is on a study of the performance estimation fer data processing time and CPU utilization to efficiently develop the real-time system. The analytical modeling and OPNET modeling and benchmarking tests are applied to perform the estimation for data processing time and CPU utilization in real-time system. We demonstrate that the estimation results can be predicted fairly and accurately through the benchmarking test results although there is a small variance between the estimation results and the benchmarking test results.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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• pp.2082-2084
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• 2003

A practical real-time LOS rate estimator is proposed to handle the time-varying measurement noise statistics. To calculate the optimal Kalman gain, the algebraic transformation method is taken into account. By using the algebraic transformation, the differential algebraic Riccati equation(DARE) regarding estimation error covariance is replaced by the simple algebraic Riccati equation(ARE). The proposed LOS estimation filter gain is only a function of relative range. Consequently, the proposed method is computationally very efficient and suitable for embedded environment.

• Journal of the Korean Data Analysis Society
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• 제20권6호
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• pp.2733-2746
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• 2018

The two inverse regression estimation methods, SIR and SAVE to estimate the central space are computationally easy and are widely used. However, SIR and SAVE may have poor performance in finite samples and need strong assumptions (linearity and/or constant covariance conditions) on predictors. The two non-parametric estimation methods, MAVE and dMAVE have much better performance for finite samples than SIR and SAVE. MAVE and dMAVE need no strong requirements on predictors or on the response variable. MAVE is focused on estimating the central mean subspace, but dMAVE is to estimate the central space. This paper explores and compares four methods to explain the dimension reduction. Each algorithm of these four methods is reviewed. Empirical study for simulated data shows that MAVE and dMAVE has relatively better performance than SIR and SAVE, regardless of not only different models but also different distributional assumptions of predictors. However, real data example with the binary response demonstrates that SAVE is better than other methods.

• 응용통계연구
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• 제29권4호
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• pp.595-611
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• 2016

일반적으로 독성학 또는 약리학에서는 자료를 분석할 때 Hill Model과 같은 비선형 회귀모형을 사용한다. 비선형 회귀모형에서 모수의 추정량과 그것의 불확실성(uncertainty)에 대한 측도의 추정은 오차의 분산 구조에 영향을 받게 된다. 따라서 자료가 등분산인지 혹은 이분산인지에 따라 사용하여야 할 추정 방법이 달라져야 한다. 그러나 일반적으로 자료를 실제로 분석하기 전에는 오차의 분산구조에 대해서 잘 알 수 없다. 그러므로 오차의 분산구조에 로버스트한 추정 방법을 개발하는 것은 중요한 문제이다. 본 논문에서는 예비검정 방법을 기반으로 한 비선형 회귀모형에서의 모수 추정 방법을 제안하였다. 오차 분산의 등분산성에 대한 간단한 예비검정의 결과에 따라 보통 최소제곱 추정(ordinary Least Square Estimation) 방법과 반복 가중 최소제곱 추정(iterative weighted least square estimation) 방법을 사용하는 추정량을 정의하였다. 제안된 추정량은 모의실험 연구를 통하여 기존의 표준적인 추정량들과 그 성능을 비교하였다. 또한 미국의 National Toxicology Program으로부터 얻어진 실제자료를 사용하여 추정 방법들을 비교하였다.

• 응용통계연구
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• 제30권2호
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• pp.259-269
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• 2017

분산함수가 불연속점을 가지는 경우, 대부분의 비모수적 함수 추정 연구에서 분산함수가 음수 값을 갖지 않기에 잔차제곱을 이용한 Nadaraya-Watson 추정량인 국소상수항추정량을 이용하였다. 한편, Huh (2014, 2016a)는 Chen 등 (2009)과 Yu와 Jones (2004)의 연구를 바탕으로 불연속 분산함수를 로그 변환한 로그분산함수를 추정 대상으로 삼아 잔차제곱이나 로그잔차제곱으로 경계점 문제를 가지지 않는 국소선형추정량을 이용하여 비모수적으로 추정하였다. Huh (2016b)는 불연속점에서 점프크기추정량을 활용하여 잔차제곱을 분산함수가 연속인 회귀모형에서 얻어진 잔차제곱인 것처럼 수정한 후 이들을 이용하여 불연속 분산함수의 추정을 연구하였다. 본 연구에서는 불연속 로그분산함수의 점프크기추정량을 이용하여 로그잔차제곱을 수정하고 불연속 로그분산함수를 국소선형추정량을 이용하여 추정하고자 한다. 제안된 추정량의 우수성을 모의실험을 통하여 Chen 등 (2009)의 로그분산함수 추정량을 이용한 Huh (2014)의 불연속 로그분산함수 추정량과 비교하고 실제자료에 적용하고자 한다.

• 한국자동차공학회논문집
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• 제21권3호
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• pp.142-147
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• 2013

Over the past few years, intelligent tire is developed very actively for more accurate measurement of real-time tire forces generated during vehicle driving situation. Information on the force of intelligent tire could be used very usefully to chassis control systems of a vehicle. Intelligent tire is based on deformation of tire's inner surface from the waveform of a SAW, or Surface Acoustic Wave. The tire vertical force is estimated by using variance analysis of sensor signals. The estimated tire vertical force is compared with the tire vertical force generated during vehicle driving situation in real-time environment. The scope of this paper is a correlation study between the measured sensor signals and the tire vertical force generated during vehicle driving situation.

• International Journal of Reliability and Applications
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• 제14권1호
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• pp.27-39
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• 2013

In this article, a new model based on the Rayleigh distribution is introduced. This model is useful and practical in physics, reliability, and life testing. The statistical and reliability properties of this model are presented, including moments, the hazard rate, the reversed hazard rate, and mean residual life functions, among others. In addition, it is shown that the distributions of the new model are ordered regarding the strongest likelihood ratio ordering. Four estimating methods, namely, method of moment, maximum likelihood method, Bayes estimation, and uniformly minimum variance unbiased, are used to estimate the parameters of this model. Simulation is used to calculate the estimates and to study their properties. Finally, the appropriateness of this model for real data sets is shown by using the chi-square goodness of fit test and the Kolmogorov-Smirnov statistic.