• 제목/요약/키워드: variance approximation

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시뮬레이션을 이용한 대기행렬 네트워크 도착과정의 변동성함수에 관한 연구 (A Simulation Study on the Variability Function of the Arrival Process in Queueing Networks)

  • 김선교
    • 한국시뮬레이션학회논문지
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    • 제20권2호
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    • pp.1-10
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    • 2011
  • 본 연구에서는 대기행렬네트워크 성과측정 방법 중의 한 가지로서 널리 이용되는 분해법의 구성요소로 제안된 변동성 함수 의 이론적 근거를 살펴보고 성과척도 측정의 정확도 제고를 위하여 회귀분석을 통한 변동성 함수의 모수추정 개선방안을 제안하고자 한다. 이를 위하여 변동성이 높은 도착과정과 서비스 과정이 포함된 직렬 대기행렬 네트워크에서의 이탈과정의 자동상관계수 함수를 추정하여 분해법에 사용할 수 있는 방안을 알아본다.

평균 벡터의 평활함수모형에 대한 안부점근사 -스튜던트화 분산을 중심으로- (Saddlepoint Approximation to the Smooth Functions of Means Model)

  • 나종화;김주성
    • 응용통계연구
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    • 제14권2호
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    • pp.333-344
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    • 2001
  • 통계적 추론에 사용되는 많은 통계량들은 평균벡터의 평활함수의 형태로 표현이 가능하다. 본 연구에서는 이들 통계량들의 분포함수에 대한 안부점근사법을 제시하였다. 이 방법은 Na(1998)에서 제시된 일반적 통계량의 분포함수에 대한 안부점근사법이 평균벡터의 평활함수모형에 특히 유용하게 사용될 수 있음을 보인 것이다. 이 근사법은 정규근사에 비해 근사의 정도가 뛰어나며, 특히 통계량의 꼬리부분의 확률에 대해서도 정확도가 그대로 유지되는 장점이 있어 정밀한 추론이 요구되는 많은 문제에 효과적으로 사용될 수 있다. 모의 실험에 사용할 평균벡터의 평활함수 모형으로는 스튜던트화 분산을 고려하였다.

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Exchange Rate Pass-through, Nominal Wage Rigidities, and Monetary Policy in a Small Open Economy

  • Rhee, Hyuk-Jae;Song, Jeongseok
    • East Asian Economic Review
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    • 제22권3호
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    • pp.337-370
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    • 2018
  • This paper discusses the design of monetary policy in a New Keynesian small open economy framework by introducing nominal wage rigidities and incomplete exchange rate pass-through on import prices. Three main findings are summarized. First, with the existence of an incomplete exchange rate pass-through and nominal wage rigidities, the optimal policy is to seek to minimize the output gap, the variance of domestic price and wage inflation, as well as deviations from the law of one price. Second, the CPI inflation targeting Taylor rule is welfare enhancing when there is a technological shock to the economy. The exception occurs when there is a foreign income shock, which minimizes welfare losses under the domestic inflation targeting Taylor rule. Last, two stylized Taylor rules turn out to be a bad approximation, but the modified Taylor rules that respond to the unemployment gap rather than the output gap are a closer approximation to the optimal policy.

Restricted maximum likelihood estimation of a censored random effects panel regression model

  • Lee, Minah;Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
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    • 제26권4호
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    • pp.371-383
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    • 2019
  • Panel data sets have been developed in various areas, and many recent studies have analyzed panel, or longitudinal data sets. Maximum likelihood (ML) may be the most common statistical method for analyzing panel data models; however, the inference based on the ML estimate will have an inflated Type I error because the ML method tends to give a downwardly biased estimate of variance components when the sample size is small. The under estimation could be severe when data is incomplete. This paper proposes the restricted maximum likelihood (REML) method for a random effects panel data model with a censored dependent variable. Note that the likelihood function of the model is complex in that it includes a multidimensional integral. Many authors proposed to use integral approximation methods for the computation of likelihood function; however, it is well known that integral approximation methods are inadequate for high dimensional integrals in practice. This paper introduces to use the moments of truncated multivariate normal random vector for the calculation of multidimensional integral. In addition, a proper asymptotic standard error of REML estimate is given.

ROBUST PORTFOLIO OPTIMIZATION UNDER HYBRID CEV AND STOCHASTIC VOLATILITY

  • Cao, Jiling;Peng, Beidi;Zhang, Wenjun
    • 대한수학회지
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    • 제59권6호
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    • pp.1153-1170
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    • 2022
  • In this paper, we investigate the portfolio optimization problem under the SVCEV model, which is a hybrid model of constant elasticity of variance (CEV) and stochastic volatility, by taking into account of minimum-entropy robustness. The Hamilton-Jacobi-Bellman (HJB) equation is derived and the first two orders of optimal strategies are obtained by utilizing an asymptotic approximation approach. We also derive the first two orders of practical optimal strategies by knowing that the underlying Ornstein-Uhlenbeck process is not observable. Finally, we conduct numerical experiments and sensitivity analysis on the leading optimal strategy and the first correction term with respect to various values of the model parameters.

A Robust Optimization Using the Statistics Based on Kriging Metamodel

  • Lee Kwon-Hee;Kang Dong-Heon
    • Journal of Mechanical Science and Technology
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    • 제20권8호
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    • pp.1169-1182
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    • 2006
  • Robust design technology has been applied to versatile engineering problems to ensure consistency in product performance. Since 1980s, the concept of robust design has been introduced to numerical optimization field, which is called the robust optimization. The robustness in the robust optimization is determined by a measure of insensitiveness with respect to the variation of a response. However, there are significant difficulties associated with the calculation of variations represented as its mean and variance. To overcome the current limitation, this research presents an implementation of the approximate statistical moment method based on kriging metamodel. Two sampling methods are simultaneously utilized to obtain the sequential surrogate model of a response. The statistics such as mean and variance are obtained based on the reliable kriging model and the second-order statistical approximation method. Then, the simulated annealing algorithm of global optimization methods is adopted to find the global robust optimum. The mathematical problem and the two-bar design problem are investigated to show the validity of the proposed method.

An alternative method for estimating lognormal means

  • Kwon, Yeil
    • Communications for Statistical Applications and Methods
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    • 제28권4호
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    • pp.351-368
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    • 2021
  • For a probabilistic model with positively skewed data, a lognormal distribution is one of the key distributions that play a critical role. Several lognormal models can be found in various areas, such as medical science, engineering, and finance. In this paper, we propose a new estimator for a lognormal mean and depict the performance of the proposed estimator in terms of the relative mean squared error (RMSE) compared with Shen's estimator (Shen et al., 2006), which is considered the best estimator among the existing methods. The proposed estimator includes a tuning parameter. By finding the optimal value of the tuning parameter, we can improve the average performance of the proposed estimator over the typical range of σ2. The bias reduction of the proposed estimator tends to exceed the increased variance, and it results in a smaller RMSE than Shen's estimator. A numerical study reveals that the proposed estimator has performance comparable with Shen's estimator when σ2 is small and exhibits a meaningful decrease in the RMSE under moderate and large σ2 values.

The Limit Distribution of a Modified W-Test Statistic for Exponentiality

  • Kim, Namhyun
    • Communications for Statistical Applications and Methods
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    • 제8권2호
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    • pp.473-481
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    • 2001
  • Shapiro and Wilk (1972) developed a test for exponentiality with origin and scale unknown. The procedure consists of comparing the generalized least squares estimate of scale with the estimate of scale given by the sample variance. However the test statistic is inconsistent. Kim(2001) proposed a modified Shapiro-Wilk's test statistic based on the ratio of tow asymptotically efficient estimates of scale. In this paper, we study the asymptotic behavior of the statistic using the approximation of the quantile process by a sequence of Brownian bridges and represent the limit null distribution as an integral of a Brownian bridge.

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Higher-order solutions for generalized canonical correlation analysis

  • Kang, Hyuncheol
    • Communications for Statistical Applications and Methods
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    • 제26권3호
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    • pp.305-313
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    • 2019
  • Generalized canonical correlation analysis (GCCA) extends the canonical correlation analysis (CCA) to the case of more than two sets of variables and there have been many studies on how two-set canonical solutions can be generalized. In this paper, we derive certain stationary equations which can lead the higher-order solutions of several GCCA methods and suggest a type of iterative procedure to obtain the canonical coefficients. In addition, with some numerical examples we present the methods for graphical display, which are useful to interpret the GCCA results obtained.

의료영상의 화질개선을 위한 프랙탈 영상 부호화 (Fractal Image Coding for Improve the Quality of Medical Images)

  • 박재홍;박철우;양원석
    • 한국방사선학회논문지
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    • 제8권1호
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    • pp.19-26
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    • 2014
  • 본 논문에서는 프랙탈 부호화시 변환식의 계수를 찾는 과정에서 블럭의 탐색영역을 줄이기 위해 탐색영역인 도메인 블럭의 특성을 화소의 밝기의 평균에 의한 클래스와 분산에 의한 클래스로 분류하여 리스트를 구성한 후 레인지 블럭과 같은 클래스를 가지는 도메인 블럭만 검색하도록 하면서 도메인 블록 탐색시 1차 허용 오차 한계값을 제어하여 리스트 탐색시 RMS값에 일정 허용오차 이내의 값을 가지면 리스트를 끝까지 탐색하지 않고 변환값을 결정하도록 하여 부호화 시간을 향상시켰다. 또한 퀴드트리 분할법으로 레인지 블럭의 크기를 가변시켜 변환($w_i$)의 수를 줄임으로서 압축효율을 높이고 도메인 레인지 블럭의 크기에 따라 탐색 영역의 탐색 밀도와 허용오차를 변화시켰을 때 화질 개선 여부를 검토하였다. 제안된 방법으로 부호화한 결과 부호화 시간은 허용오차의 범위에 따라 향상되며 압축효과는 높아 졌고 PSNR값은 다소 떨어졌으나 거의 무시할 수 있을 정도의 변화가 있었다.