• Title/Summary/Keyword: weighted Monte Carlo method

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Projections of the high-school graduate in Daegu·Gyoungbook (대구·경북지역의 고등학교 3학년 학생수 추계)

  • Kim, Jongtae
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.4
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    • pp.907-914
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    • 2015
  • Reduction in the number of students due to the low birth rate has notice very many changes in the national education policies. The purpose of this study is to propose a method for estimation of the number of students (the population) by age or grade promotion rate of progression rate to estimate the exact number of students (the population) by 2032. It was suggested the nth moving average proportional method and the weighted proportional moving average method as the method of population projections. It presents the means and standard deviations of the measurement errors of the suggested methods by Monte Carlo simulation. Measured in this study are predicted result was a phenomenon is estimated lower than the actual value.

The model of the weighted proportion estimation for forecasting the number of population (인구추계를 위한 가중비례추정모형)

  • Yoon, Yong Hwa;Kim, Jong Tae
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.2
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    • pp.311-320
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    • 2013
  • The purpose of this paper is to suggest the methods of forecasting the numbers of students. The generalized weighted proportion estimation models are suggested and used for forecasting the numbers of student until 2029. The results of the Monte Carlo simulation show that the suggested method is powerful for the forecasting. In conclusion, the numbers of the third grade high-school students will be less than the numbers of college admission quota from 2019.

Exposure and Risk Assessment of Benzene and PM10 for Sub-populations using Monte-Carlo Simulations (Monte-Carlo 모의실험을 통한 부분 인구집단별 벤젠 및 PM10의 노출 및 위해성 평가)

  • Park, Jinhyeon;Yang, So Young;Park, Yunkyung;Ryu, Hyeonsu;Kim, Eunchae;Choe, Youngtae;Heo, Jung;Cho, Mansu;Yang, Wonho
    • Journal of Environmental Health Sciences
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    • v.45 no.3
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    • pp.247-257
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    • 2019
  • Objectives: The Korea Ministry of Environment regulates concentrations of hazardous air pollutants (HAPs) through Atmosphere Environmental Standards to protect public health from HAPs. However, simply determining the exceedance of HAP concentrations has several limitations and more comprehensive assessment is required. In addition, integrated risk assessment is needed considering exposure in all microenvironments, including outdoor as well as indoor environments. The purpose of this study was to assess the differences in risk by sub-population groups according to time-activity patterns and reported concentrations, as well as the lifetime risk for Koreans. Methods: In this study, we calculated time-weighted average exposure concentrations for benzene and $PM_{10}$ among preschool-age children, students, housewifes, workers, and the elderly using residential time and concentrations for indoor (house, school or workplace, other), outdoor, and transport by the meta-analysis method. The risk assessments were conducted by excess cancer risk and disease death risk using 1,000,000 Monte-Carlo simulations for probabilistic analysis. Results: Preschool-age children, students, housewifes, workers, and the elderly spent 91.9, 86.0, 79.8, 82.2, and 77.3% of their day in their house, workplace, or school, respectively. The more than 99% excess cancer risk for benzene exceed 1.0E-06 in all sub-populations and lifetime. The acute disease death risk for $PM_{10}$ for housewifes and workers for lifetime were 3.35E-04 and 3.18E-04, and chronic disease death risks were 2.84E-03 and 2.70E-03, respectively. Conclusions: The risk of benzene and $PM_{10}$ by sub-population group and for the lifetime of housewifes and workers were assessed. Benzene showed risky results for this study. All disease death risks of $PM_{10}$ were higher than 1.0E-04 and showed different risks by sub-population. This study can be used as a basis for lifetime exposure and risk assessment to benzene and $PM_{10}$.

Exposure and Risk Assessment of Nitrogen Dioxide and Ozone for Sub-population Groups using Monte-Carlo Simulations (Monte-Carlo 모의실험을 통한 부분 인구집단별 이산화질소와 오존의 노출 및 위해성 평가)

  • Park, Jinhyeon;Ryu, Hyeonsu;Yang, So Young;Park, Yunkyung;Heo, Jung;Kim, Eunchae;Choe, Youngtae;Cho, Mansu;Yang, Wonho
    • Journal of Environmental Health Sciences
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    • v.45 no.2
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    • pp.113-125
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    • 2019
  • Objectives: Although the risk assessments for nitrogen dioxide ($NO_2$) and ozone ($O_3$) have been extensively studied, most of the existing risk assessments were limited mainly to indoor environments such as workplaces, schools, and multi-use facilities. Therefore, integrated risk assessment is needed to consider exposure in all microenvironments, including outdoors. The purpose of this study was to assess the differences in risk among sub-population groups according to time-activity patterns and reported concentrations, as well as the lifetime risk of Koreans. Methods: In this study, we estimated time-weighted average exposure concentrations of $NO_2$ and $O_3$ for preschool children, students, housewives, workers, and seniors using residential time and indoor concentrations (house, school or workplace, other), outdoors, and transport by meta-analysis method. The risk for $NO_2$ and $O_3$ were assessed by hazard quotient using reference concentrations 30 and 60 ppb, respectively. The risk assessments were conducted through 1,000,000 Monte-Carlo simulations for probabilistic analysis. Results: Preschool children, students, housewives, workers, and seniors spent 91.9, 86.0, 79.8, 82.2, and 77.3% of their day in a house, school, or workplace, respectively. The risk assessment for the lifetime of a housewife and a worker showed that 33.8 and 28.4% of hazard quotients of $NO_2$ exceed 1, respectively, and more than 99% of hazard quotient of $O_3$ were less than 1. Conclusions: The risk of $NO_2$ and $O_3$ by sub-population group and for the lifetime of housewives and workers were assessed. The risk for $NO_2$ was higher than for $O_3$ and showed a different risk by sub-population group. Both $NO_2$ and $O_3$ showed a higher risk for housewives than for workers. This study can be used as a basis for lifetime exposure and risk assessment for $NO_2$ and $O_3$.

New approach for analysis of progressive Type-II censored data from the Pareto distribution

  • Seo, Jung-In;Kang, Suk-Bok;Kim, Ho-Yong
    • Communications for Statistical Applications and Methods
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    • v.25 no.5
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    • pp.569-575
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    • 2018
  • Pareto distribution is important to analyze data in actuarial sciences, reliability, finance, and climatology. In general, unknown parameters of the Pareto distribution are estimated based on the maximum likelihood method that may yield inadequate inference results for small sample sizes and high percent censored data. In this paper, a new approach based on the regression framework is proposed to estimate unknown parameters of the Pareto distribution under the progressive Type-II censoring scheme. The proposed method provides a new regression type estimator that employs the spacings of exponential progressive Type-II censored samples. In addition, the provided estimator is a consistent estimator with superior performance compared to maximum likelihood estimators in terms of the mean squared error and bias. The validity of the proposed method is assessed through Monte Carlo simulations and real data analysis.

Estimation of Drought Rainfall by Regional Frequency Analysis using L and LH-Moments(I) - On the Method of L-Moments - (L 및 LH-모멘트법과 지역빈도분석에 의한 가뭄우량의 추정(I) - L-모멘트법을 중심으로 -)

  • 이순혁;윤성수;맹승진;류경식;주호길
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.45 no.5
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    • pp.97-109
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    • 2003
  • This study is mainly conducted to derive the design drought rainfall by the consecutive duration using probability weighted moments with rainfall in the regional drought frequency analysis. It is anticipated to suggest optimal design drought rainfall of hydraulic structures for the water requirement and drought frequency of occurrence for the safety of water utilization through this study. Preferentially, this study was conducted to derive the optimal regionalization of the precipitation data that can be classified by the climatologically and geographically homogeneous regions all over the regions except Cheju and Ulreung islands in Korea. Five homogeneous regions in view of topographical and climatological aspects were accomplished by K-means clustering method. Using the L-moment ratio diagram and Kolmogorov-Smirnov test, generalized extreme value distribution was confirmed as the best fitting one among applied distributions. At-site and regional parameters of the generalized extreme value distribution were estimated by the method of L-moments. Design drought rainfalls using L-moments following the consecutive duration were derived by the at-site and regional analysis using the observed and simulated data resulted from Monte Carlo techniques. Relative root-mean-square error (RRMSE), relative bias (RBIAS) and relative reduction (RR) in RRMSE for the design drought rainfall derived by at-site and regional analysis in the observed an simulated data were computed and compared. In has shown that the regional frequency analysis procedure can substantially more reduce the RRMSE. RBIAS and RR in RRMSE than those of at-site analysis in the prediction of design drought rainfall. Consequently, optimal design drought rainfalls following the regions and consecutive durations were derived by the regional frequency analysis.

Comparison of Three Parameter Estimation Methods for Mixture Distributions (혼합분포모형의 매개변수 추정방법 비교)

  • Shin, Ju-Young;Kim, Sooyoung;Kim, Taereem;Heo, Jun-Haeng
    • Proceedings of the Korea Water Resources Association Conference
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    • 2017.05a
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    • pp.45-45
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    • 2017
  • 상이한 자연현상으로 발생된 자료들은 때때로 통계적으로 다른 특성을 가지는 경우가 있다. 이런 자료들은 다른 두 개 이상의 모집단에서 자료가 발생한 것으로 가정할 수 가 있다. 기존에 널리 사용되어온 분포형 모형의 경우 단일한 모집단으로부터 자료가 발생한다는 가정하에서 개발된 모형들로 위에서 언급한 자료들을 적절히 모의할 수 없다. 이런 상이한 모집단에서 발생된 자료를 모형화 하기 위해서 혼합분포모형(mixture distribution)이 개발되었다. 홍수나 가뭄 등과 같은 극치 사상의 경우 다양한 자연현상들로부터 발생하기에 혼합분포모형을 적용할 경우 보다 정확한 모의가 가능하다. 혼합분포모형은 두 개 이상의 비혼합분포모형들을 가중합하여 만들어진다. 혼합 분포모형의 형태로 인하여 기존의 분포형 모형의 매개변수 추정 모형으로 널리 사용되던 최우도법 (maximum likelihood method), 모멘트법(method of moment), 확률가중모멘트법 (probability weighted moment method) 등을 이용하여 혼합분포모형의 매개변수를 추정하는 것이 용이 하지 않다. 혼합분포모형의 매개변수 추정 방법으로는 Expectation-Maximization (EM) 알고리즘, Meta-Heuristic Maximum Likelihood (MHML) 방법, Markov Chain Monte Carlo (MCMC) 방법 등이 적용되고 있다. 현재까지 수자원 분야에서 사용되는 극치 자료를 혼합분포모형을 이용하여 모의할 때 매개변수 추정방법에 따른 특성에 대한 연구가 진행되지 않았다. 본 연구에서는 우리나라 연최대강우량 자료를 이용하여 혼합분포모형의 매개변수 추정방법 (EM 알고리즘, MHML 방법, MCMC 방법) 들의 특성들을 비교 분석하였다. 혼합분포모형으로는 Gumbel-Gumbel 혼합분포 모형을 적용하였다. 본 연구의 결과는 향후 혼합분포모형을 이용한 연구에 좋은 기초자료로 사용될 수 있을 것으로 판단된다.

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On Confidence Intervals of Robust Regression Estimators (로버스트 회귀추정에 의한 신뢰구간 구축)

  • Lee Dong-Hee;Park You-Sung;Kim Kee-Whan
    • The Korean Journal of Applied Statistics
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    • v.19 no.1
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    • pp.97-110
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    • 2006
  • Since it is well-established that even high quality data tend to contain outliers, one would expect fat? greater reliance on robust regression techniques than is actually observed. But most of all robust regression estimators suffers from the computational difficulties and the lower efficiency than the least squares under the normal error model. The weighted self-tuning estimator (WSTE) recently suggested by Lee (2004) has no more computational difficulty and it has the asymptotic normality and the high break-down point simultaneously. Although it has better properties than the other robust estimators, WSTE does not have full efficiency under the normal error model through the weighted least squares which is widely used. This paper introduces a new approach as called the reweighted WSTE (RWSTE), whose scale estimator is adaptively estimated by the self-tuning constant. A Monte Carlo study shows that new approach has better behavior than the general weighted least squares method under the normal model and the large data.

Probabilistic Behavior of Laminated Composite Plates with Random Material Properties (재료 물성치의 불확실성에 의한 복합적층판 변위의 확률적 거동)

  • Noh, Hyuk-Chun
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2008.04a
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    • pp.27-32
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    • 2008
  • The laminated composite materials have been applied to various mechanical structures due to their high performance to weight ratios. In this study, we suggest a stochastic finite element scheme for the probabilistic analysis of the composite laminated plates. The composite materials consist of two different materials which constitute the matrix and fiber. The material properties in the major and minor directions are determined depending on the volume fraction of these two materials. In this study, the elastic modulus and shear modulus are considered as random and the effect of these random properties on the behavior of the composite plate is investigated. We adopt the weighted integral scheme in the formulation, which has been recognized as the most accurate method in the statistical methodologies. For verification of the proposed scheme, Monte Carlo analysis is also performed for the comparison with the proposed scheme.

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An Empirical Characteristic Function Approach to Selecting a Transformation to Normality

  • Yeo, In-Kwon;Johnson, Richard A.;Deng, XinWei
    • Communications for Statistical Applications and Methods
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    • v.21 no.3
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    • pp.213-224
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    • 2014
  • In this paper, we study the problem of transforming to normality. We propose to estimate the transformation parameter by minimizing a weighted squared distance between the empirical characteristic function of transformed data and the characteristic function of the normal distribution. Our approach also allows for other symmetric target characteristic functions. Asymptotics are established for a random sample selected from an unknown distribution. The proofs show that the weight function $t^{-2}$ needs to be modified to have thinner tails. We also propose the method to compute the influence function for M-equation taking the form of U-statistics. The influence function calculations and a small Monte Carlo simulation show that our estimates are less sensitive to a few outliers than the maximum likelihood estimates.