• Title/Summary/Keyword: approximate variance

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Confidence Interval For Sum Of Variance Components In A Simple Linear Regression Model With Unbalanced Nested Error Structure

  • Park, Dong-Joon
    • Proceedings of the Korean Statistical Society Conference
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    • 2003.05a
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    • pp.75-78
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    • 2003
  • Those who are interested in making inferences concerning linear combination of variance components in a simple linear regression model with unbalanced nested error structure can use the confidence intervals proposed in this paper. Two approximate confidence intervals for the sum of two variance components in the model are proposed. Simulation study is peformed to compare the methods.

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Variance estimation of a double expanded estimator for two-phase sampling

  • Mingue Park
    • Communications for Statistical Applications and Methods
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    • v.30 no.4
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    • pp.403-410
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    • 2023
  • Two-Phase sampling, which was first introduced by Neyman (1938), has various applications in different forms. Variance estimation for two-phase sampling has been an important research topic because conventional variance estimators used in most softwares are not working. In this paper, we considered a variance estimation for two-phase sampling in which stratified two-stage cluster sampling designs are used in both phases. By defining a conditionally unbiased estimator of an approximate variance estimator, which is calculable when all elements in the first phase sample are observed, we propose an explicit form of variance estimator of the double expanded estimator for a two-phase sample. A small simulation study shows the proposed variance estimator has a negligible bias with small variance. The suggested variance estimator is also applicable to other linear estimators of the population total or mean if appropriate residuals are defined.

A Standard Section-Based Approximate Cost Estimating Model on Tunnel (II) - Cost Variance Index Table and Test - (표준단면을 이용한 터널 공사비 예측모델 개발 (II) - 공사비 변동 모델 및 검증 -)

  • Cho, Jeongyeon;Kim, Sang-Kwi;Kim, Kyoungmin;Kim, Kyong Ju
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.5D
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    • pp.677-684
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    • 2008
  • The paper provides an approximate cost estimating model that can be used for tunnel. Based on the previous study analyzed critical factors that have impact on tunnel construction cost, this paper establishes a cost variance index table that reflects the cost impacts due to the change of the critical cost factors. An estimating procedure is described utilizing the index table. For the verification of the suggested model, the comparison of the estimated construction cost with real project cost is performed. The estimated results range from 95%~111% of the real project costs. As an approximate tunnel cost estimating model, the model can be utilized to quickly estimate tunnel construction costs based on the conceptual information at the planning stage and to efficiently make a decision on design alternatives.

A Fuzzy-Neural Network-Based IMM Method Tracking System (퍼지 뉴럴 네트워크 기반 다중모델 기법 추적 시스템)

  • Son Hyun-Seung;Joo Young-Hoon;Park Jin-Bae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.4
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    • pp.472-478
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    • 2006
  • This paper presents a new fuzzy-neural-network based interacting multiple model (FNNBIMM) algorithm for tracking a maneuvering target. To effectively handle the unknown target acceleration, this paper regards it as additional noise, time-varying variance to target model. Each sub model characterized by the variance of the overall process noise, which is obtained on the basis of each acceleration interval. Since it is hard to approximate this time-varying variance adaptively owing to the unknown acceleration, the FNN is utilized to precisely approximate this time-varying variance. The error back-propagation method is utilized to optimize each FNN. To show the feasibility of the proposed algorithm, a numerical example is provided.

Interval Estimation for Sum of Variance Components in a Simple Linear Regression Model with Unbalanced Nested Error Structure

  • Park, Dong-Joon
    • Communications for Statistical Applications and Methods
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    • v.10 no.2
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    • pp.361-370
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    • 2003
  • Those who are interested in making inferences concerning linear combination of valiance components in a simple linear regression model with unbalanced nested error structure can use the confidence intervals proposed in this paper. Two approximate confidence intervals for the sum of two variance components in the model are proposed. Simulation study is peformed to compare the methods. The methods are applied to a numerical example and recommendations are given for choosing a proper interval.

Comparison of Confidence Intervals on Variance Component In a Simple Linear Regression Model with Unbalanced Nested Error Structure

  • Park, Dong Joon;Park, Sun-Young;Han, Man-Ho
    • Communications for Statistical Applications and Methods
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    • v.9 no.2
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    • pp.459-471
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    • 2002
  • In applications using a linear regression model with nested error structure, one might be interested in making inferences concerning variance components. This article proposes approximate confidence intervals on the variance component of the primary level in a simple linear regression model with an unbalanced nested error structure. The intervals are compared using computer simulation and recommendations are provided for selecting an appropriate interval.

Confidence Intervals in Three-Factor-Nested Variance Component Model

  • Kang, Kwan-Joong
    • Journal of the Korean Statistical Society
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    • v.22 no.1
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    • pp.39-54
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    • 1993
  • In the three-factor nested variance component model with equal numbers in the cells given by $y_{ijkm} = \mu + A_i + B_{ij} + C_{ijk} + \varepsilon_{ijkm}$, the exact confidence intervals of the variance component of $\sigma^2_A, \sigma^2_B, \sigma^2_C, \sigma^2_{\varepsilon}, \sigma^2_A/\sigma^2_{\varepsilon}, \sigma^2_B/\sigma^2_{\varepsilon}, \sigma^2_C/\sigma^2_{\varepsilon}, \sigma^2_A/\sigma^2_C, \sigma^2_B/\sigma^2_C$ and $\sigma^2_A/\sigma^2_B$ are not found out yet. In this paper approximate lower and upper confidence intervals are presented.

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Approximate MLE for the Scale Parameter of the Weibull Distribution with Type-II Censoring

  • Kang, Suk-Bok;Kim, Mi-Hwa
    • Journal of the Korean Data and Information Science Society
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    • v.5 no.2
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    • pp.19-27
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    • 1994
  • It is known that the maximum likelihood method does not provide explicit estimator for the scale parameter of the Weibull distribution based on Type-II censored samples. In this paper we provide an approximate maximum likelihood estimator (AMLE) of the scale parameter of the Weibull distribution with Type-II censoring. We obtain the asymptotic variance and simulate the values of the bias and the variance of this estimator based on 3000 Monte Carlo runs for n = 10(10)30 and r,s = 0(1)4. We also simulate the absolute biases of the MLE and the proposed AMLE for complete samples. It is found that the absolute bias of the AMLE is smaller than the absolute bias of the MLE.

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Percetiles for the distributions belonging to the natural exponential families having power variance functions (파워(>2)분산함수를 가진 자연지수계열군에 속하는 분포들의 백분위수)

  • 서의훈
    • The Korean Journal of Applied Statistics
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    • v.8 no.1
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    • pp.133-149
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    • 1995
  • Since probability density functions for the distributions belonging to the natural exponential families having power(>2) variance functions are expressed as infinite series, it is very difficult to deal with the distributins in spite of their usefulness. Therefore, tables for the percentiles of the distributions are obtained, and approximate percentiles are also obtained in this thesis. It is shown that the approximate percentiles can replace exact percentlies well for some distributions.

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