• Title/Summary/Keyword: method of moments estimation

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RC Tree Delay Estimation (RC tree의 지연시간 예측)

  • 유승주;최기영
    • Journal of the Korean Institute of Telematics and Electronics A
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    • v.32A no.12
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    • pp.209-219
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    • 1995
  • As a new algorithm for RC tree delay estimation, we propose a $\tau$-model of the driver and a moment propagation method. The $\tau$-model represents the driver as a Thevenin equivalent circuit which has a one-time-constant voltage source and a linear resistor. The new driver model estimates the input voltage waveform applied to the RC more accurately than the k-factor model or the 2-piece waveform model. Compared with Elmore method, which is a lst-order approximation, the moment propagation method, which uses $\pi$-model loads to calculate the moments of the voltage waveform on each node of RC trees, gives more accurate results by performing higher-order approximations with the same simple tree walking algorithm. In addition, for the instability problem which is common to all the approximation methods using the moment matching technique, we propose a heuristic method which guarantees a stable and accureate 2nd order approximation. The proposed driver model and the moment propagation method give an accureacy close to SPICE results and more than 1000 times speedup over circuit level simulations for RC trees and FPGA interconnects in which the interconnect delay is dominant.

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Length-biased Rayleigh distribution: reliability analysis, estimation of the parameter, and applications

  • Kayid, M.;Alshingiti, Arwa M.;Aldossary, H.
    • International Journal of Reliability and Applications
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    • v.14 no.1
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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.

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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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    • v.26 no.4
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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.

On the Numerical Procedure for Estimating Structural Stress of Welded Structures (수치해석을 통한 용접구조물의 구조응력 추정에 관한 연구)

  • Kang, Sung-Won;Kim, Myung-Hyun
    • Journal of the Society of Naval Architects of Korea
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    • v.42 no.4 s.142
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    • pp.388-395
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    • 2005
  • A numerical procedure is proposed as a mesh-size insensitive structural stress definition that gives a stress state at a weld toe with relatively large mesh size. The structural stress values obtained using different finite element types, i.e. shell element and solid element, are examined for typical weld structures. The calculation procedures are performed using the balanced nodal forces and moments obtained from finite element solutions. A consistent formulation based on work equivalent argument has been implemented to transform the balanced nodal forces and moments from shell to line force and line moments at each nodal position. The mesh-insensitivity, the effect of distance $\delta$(where the stress is calculated) and the potential limitations of the structural stress method are examined for various types of weldments. Based on the results from this study, it is expected to develop a more precise stress estimation technique for fatigue strength assessment of welded structures.

Estimation of Design Rainfall by the Regional Frequency Analysis using Higher Probability Weighted Moments and GIS Techniques(l ) - On the method of L-moments- (고차확률가중모멘트법에 의한 지역화빈도분석과 GIS기법에 의한 설계강우량 추정(II) - L-모멘트법을 중심으로 -)

  • 이순혁;박종화;류경식
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.43 no.5
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    • pp.70-82
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    • 2001
  • This study was conducted to derive the regional design rainfall by the regional frequency analysis based on the regionalization of the precipitation suggested by the first report of this project. Using the L-moment ratios and Kolmogorov-Smirnov test, the underlying regional probability distribution was identified to be the Generalized extreme value distribution among applied distributions. Regional and at-site parameters of the generalized extreme value distribution were estimated by the linear combination of the probability weighted moments, L-moment. The regional and at-site analysis for the design rainfall were tested by Monte Carlo simulation. Relative root-mean-square error(RRMSE), relative bias(RBIAS) and relative reduction(RR) in RRMSE were computed and compared with those resulting from at-site Monte Carlo simulation. All show that the regional analysis procedure can substantially reduce the RRMSE, RBIAS and RR in RRMSE in the prediction of design rainfall. Consequently, optimal design rainfalls following the legions and consecutive durations were derived by the regional frequency analysis.

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Regional flood frequency analysis of extreme rainfall in Thailand, based on L-moments

  • Thanawan Prahadchai;Piyapatr Busababodhin;Jeong-Soo Park
    • Communications for Statistical Applications and Methods
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    • v.31 no.1
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    • pp.37-53
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    • 2024
  • In this study, flood records from 79 sites across Thailand were analyzed to estimate flood indices using the regional frequency analysis based on the L-moments method. Observation sites were grouped into homogeneous regions using k-means and Ward's clustering techniques. Among various distributions evaluated, the generalized extreme value distribution emerged as the most appropriate for certain regions. Regional growth curves were subsequently established for each delineated region. Furthermore, 20- and 100-year return values were derived to illustrate the recurrence intervals of maximum rainfall across Thailand. The predicted return values tend to increase at each site, which is associated with growth curves that could describe an increasing long-term predictive pattern. The findings of this study hold significant implications for water management strategies and the design of flood mitigation structures in the country.

A Study of Estimation Method for Auto-Regressive Model with Non-Normal Error and Its Prediction Accuracy (비정규 오차를 고려한 자기회귀모형의 추정법 및 예측성능에 관한 연구)

  • Lim, Bo Mi;Park, Cheong-Sool;Kim, Jun Seok;Kim, Sung-Shick;Baek, Jun-Geol
    • Journal of Korean Institute of Industrial Engineers
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    • v.39 no.2
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    • pp.109-118
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    • 2013
  • We propose a method for estimating coefficients of AR (autoregressive) model which named MLPAR (Maximum Likelihood of Pearson system for Auto-Regressive model). In the present method for estimating coefficients of AR model, there is an assumption that residual or error term of the model follows the normal distribution. In common cases, we can observe that the error of AR model does not follow the normal distribution. So the normal assumption will cause decreasing prediction accuracy of AR model. In the paper, we propose the MLPAR which does not assume the normal distribution of error term. The MLPAR estimates coefficients of auto-regressive model and distribution moments of residual by using pearson distribution system and maximum likelihood estimation. Comparing proposed method to auto-regressive model, results are shown to verify improved performance of the MLPAR in terms of prediction accuracy.

RMS Current Estimation Technique for Reliability Analysis of Multiple Semiconductor Interconnects (신뢰성 해석을 위한 반도체 다중연결선의 RMS 전류 추정 기법)

  • Kim, Ki-Young;Kim, Deok-Min;Kim, Seok-Yoon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.8
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    • pp.1547-1554
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    • 2011
  • As process parameters scale, interconnect width are reduced rapidly while the current flowing through interconnects does not decrease in a proportional manner. This effect increases current density in metal interconnects which may result in poor reliability. Since RMS(root-mean-square) current limits are used to evaluate self-heating and short-time stress failures caused by high-current pluses, RMS current estimation is very important to guarantee the reliability of semiconductor systems. Hence, it is critical to estimate the current limits through interconnects earlier in semiconductor design stages. The purpose of this paper is to propose a fast, yet accurate RMS current estimation technique that can offer a relatively precise estimate by using closed-form equations. The efficiency and accuracy of the proposed method have been verified through simulations using HSPICE for a vast range of interconnect parameters.

Estimation of Automatic Video Captioning in Real Applications using Machine Learning Techniques and Convolutional Neural Network

  • Vaishnavi, J;Narmatha, V
    • International Journal of Computer Science & Network Security
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    • v.22 no.9
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    • pp.316-326
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    • 2022
  • The prompt development in the field of video is the outbreak of online services which replaces the television media within a shorter period in gaining popularity. The online videos are encouraged more in use due to the captions displayed along with the scenes for better understandability. Not only entertainment media but other marketing companies and organizations are utilizing videos along with captions for their product promotions. The need for captions is enabled for its usage in many ways for hearing impaired and non-native people. Research is continued in an automatic display of the appropriate messages for the videos uploaded in shows, movies, educational videos, online classes, websites, etc. This paper focuses on two concerns namely the first part dealing with the machine learning method for preprocessing the videos into frames and resizing, the resized frames are classified into multiple actions after feature extraction. For the feature extraction statistical method, GLCM and Hu moments are used. The second part deals with the deep learning method where the CNN architecture is used to acquire the results. Finally both the results are compared to find the best accuracy where CNN proves to give top accuracy of 96.10% in classification.

Statistical Inferences for Bivariare Exponential Distribution in Reliability and Life Testing Problems

  • PARK, BYUNG-GU
    • Journal of Korean Society for Quality Management
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    • v.13 no.1
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    • pp.31-40
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    • 1985
  • In this paper, statistical estimation of the parameters of the bivariate exponential distribution are studied. Bayes estimators of the parameters are obtained and compared with the maximum likelihood estimators which are introduced by Freund. We know that the method of moments estimators coincide with the maximum likelihood estimators and Bayes estimators are more efficient than the maximum likelihood estimators in moderate samples. The asymptotic distributions of the maximum likelihood estimators and the estimator of mean time to system failure are obtained.

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