• Title/Summary/Keyword: random components

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On Optimal Estimates of System Reliability (시스템 신뢰성(信賴性)의 최적추정(最適推定))

  • Kim, Jae-Ju
    • Journal of Korean Society for Quality Management
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    • v.7 no.2
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    • pp.7-10
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    • 1979
  • In this paper the Rao-Blackwell and Lehmann-$Scheff{\acute{e}}$ Theorem are used to drive the minimum variance unbiased estimators of system reliability for a number of distributions when a system consists of n Components whose random life times are assumed to be independent and identically distributed. For the case of a negative exponential life time, we obtain the maximum likelihood estimator of the system reliability and compair it with minimum variance unbiased estimator of the system reliability.

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Improved Algorithm for Case-Deletion Diagnostic in Mixed Linear Models

  • Lee, Jang-Teak
    • Communications for Statistical Applications and Methods
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    • v.7 no.3
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    • pp.677-686
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    • 2000
  • Outliers may occur with respect to any of the random components in mixed linear models. We develop a use of simple, inexpensive updating formulas to consider the effect of case-deletion for mixed linear models. The method described here requires inversions of an n x n matrix, where n is the number of nonempty cells. A numerical example illustrates the use of computational formulas.

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Semiparametric Bayesian Regression Model for Multiple Event Time Data

  • Kim, Yongdai
    • Journal of the Korean Statistical Society
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    • v.31 no.4
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    • pp.509-518
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    • 2002
  • This paper is concerned with semiparametric Bayesian analysis of the proportional intensity regression model of the Poisson process for multiple event time data. A nonparametric prior distribution is put on the baseline cumulative intensity function and a usual parametric prior distribution is given to the regression parameter. Also we allow heterogeneity among the intensity processes in different subjects by using unobserved random frailty components. Gibbs sampling approach with the Metropolis-Hastings algorithm is used to explore the posterior distributions. Finally, the results are applied to a real data set.

Reliability Analysis of Auto-Connector in Use-condition (사용 조건하에서의 자동차용 커넥터 신뢰성 분석)

  • 김종걸;김진환
    • Proceedings of the Safety Management and Science Conference
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    • 2004.05a
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    • pp.129-136
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    • 2004
  • Environmental factors for automotive consist of temperature, humidity, vibration(sine & random), gas, an electrical load and so on. These environmental factors are impressed in a automotive. Dependability is essential requirement in many electronic parts. Among components of automotive, the connector connecting electrical signals is one of the most important parts. Automotive -connector is inspected according to each manufacturer's test standard in which dependability should be considered. This paper aims to verify that current test standard is suitable for dependability, and present an inductive life test for automotive connector based on the field data in use-condition.

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THE MINIMUM VARIANCE UNBIASED ESTIMATION OF SYSTEM RELIABILITY

  • Park, C.J.;Kim, Jae-Joo
    • Journal of Korean Institute of Industrial Engineers
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    • v.4 no.1
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    • pp.29-32
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    • 1978
  • We obtain the minimum variance unbiased estimate of system reliability when a system consists of n components whose life times are assumed to be independent and identically distributed either negative exponential or geometric random variables. For the case of a negative exponential life time, we obtain the minimum variance unbiased estimate of the probability density function of the i-th order statistic.

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Dynamic Modeling and Verification of Litton's Space Inertial Reference Unit(SIRU) (ICCAS 2003)

  • Choi, Hong-Taek;Oh, Shi-Hwan;Rhee, Seung-Wu
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1211-1215
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    • 2003
  • Accurate mathematical models of spacecraft components are an essential of spacecraft attitude control system design, analysis and simulation. Gyro is one of the most important spacecraft components used for attitude propagation and control. Gyro errors may seriously degrade the accuracy of the calculated spacecraft angular rate and of attitude estimates due to inherent drift and bias errors. In order to validate this model, nominal case simulation has been performed and compared for the low range mode and high range mode, respectively. In this paper, a mathematical model of gyro containing the relationships for predicting spacecraft angular rate and disturbances is proposed.

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Optimum Nonseparable Filter Bank Design in Multidimensional M-Band Subband Structure

  • Park, Kyu-Sik;Lee, Won-Cheol
    • The Journal of the Acoustical Society of Korea
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    • v.15 no.2E
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    • pp.24-32
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    • 1996
  • A rigorous theory for modeling, analysis, optimum nonseparable filter bank in multidimensional M-band quantized subband codec are developed in this paper. Each pdf-optimized quantizer is modeled by a nonlinear gain-plus-additive uncorrelated noise and embedded into the subband structure. We then decompose the analysis/synthesis filter banks into their polyphase components and shift the down-and up-samplers to the right and left of the analysis/synthesis polyphase matrices respectively. Focusing on the slow clock rate signal between the samplers, we derive the exact expression for the output mean square quantization error by using spatial-invariant analysis. We show that this error can be represented by two uncorrelated components : a distortion component due to the quantizer gain, and a random noise component due to fictitious uncorrelated noise at the uantizer. This mean square error is then minimized subject to perfect reconstruction (PR) constraints and the total bit allocation for the entire filter bank. The algorithm gives filter coefficients and subband bit allocations. Numerical design example for the optimum nonseparable orthonormal filter bank is given with a quincunx subsampling lattice.

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A Heuristic Methodology for Fault Diagnosis using Statistical Patterns

  • Kwon, Young-il;Song, Suh-ill
    • Journal of Korean Society for Quality Management
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    • v.21 no.2
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    • pp.17-26
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    • 1993
  • Process fault diagnosis is a complicated matter because quality control problems can result from a variety of causes. These causes include problems with electrical components, mechanical components, human errors, job justification errors, and air conditioning influences. In order to make the system run smoothly with minimum delay, it is necessary to suggest heuristic remedies for the detected faults. Hence, this paper describes a heuristic methodology of fault diagnosis that is performed using statistical patterns generated by quality characteristics The proposed methodology is described briefly as follows: If a sample pattern generated by random variables is similar to the number of prototype patterns, the sample pattern may be matched by any prototype pattern among them to be resembled. This concept is based on the similarity between a sample pattern and the matched prototype pattern. The similarity is calculated as the weighted average of squared deviation, which is expressed as the difference between the relative values of standard normal distribution to be transformed by the observed values of quality characteristics in a sample pattern and the critical values of the corresponding ones in a matched prototype pattern.

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A Fuzzy Impulse Noise Filter Based on Boundary Discriminative Noise Detection

  • Verma, Om Prakash;Singh, Shweta
    • Journal of Information Processing Systems
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    • v.9 no.1
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    • pp.89-102
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    • 2013
  • The paper presents a fuzzy based impulse noise filter for both gray scale and color images. The proposed approach is based on the technique of boundary discriminative noise detection. The algorithm is a multi-step process comprising detection, filtering and color correction stages. The detection procedure classifies the pixels as corrupted and uncorrupted by computing decision boundaries, which are fuzzified to improve the outputs obtained. In the case of color images, a correction term is added by examining the interactions between the color components for further improvement. Quantitative and qualitative analysis, performed on standard gray scale and color image, shows improved performance of the proposed technique over existing state-of-the-art algorithms in terms of Peak Signal to Noise Ratio (PSNR) and color difference metrics. The analysis proves the applicability of the proposed algorithm to random valued impulse noise.

Bayesian Analysis of Multivariate Threshold Animal Models Using Gibbs Sampling

  • Lee, Seung-Chun;Lee, Deukhwan
    • Journal of the Korean Statistical Society
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    • v.31 no.2
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    • pp.177-198
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    • 2002
  • The estimation of variance components or variance ratios in linear model is an important issue in plant or animal breeding fields, and various estimation methods have been devised to estimate variance components or variance ratios. However, many traits of economic importance in those fields are observed as dichotomous or polychotomous outcomes. The usual estimation methods might not be appropriate for these cases. Recently threshold linear model is considered as an important tool to analyze discrete traits specially in animal breeding field. In this note, we consider a hierarchical Bayesian method for the threshold animal model. Gibbs sampler for making full Bayesian inferences about random effects as well as fixed effects is described to analyze jointly discrete traits and continuous traits. Numerical example of the model with two discrete ordered categorical traits, calving ease of calves from born by heifer and calving ease of calf from born by cow, and one normally distributed trait, birth weight, is provided.