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BAYESIAN IMAGE-RECONSTRUCTION FOR EMISSION TOMOGRAPHY INCORPORATING GOOD ROUGHNESS PRIOR ON MASSIVELY PARALLEL PROCESSORS

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 1991年第8期88卷 3223-3227页

作者： MILLER, MI ROYSAM, B WASHINGTON UNIV INST BIOMED COMPST LOUISMO 63130 RENSSELAER POLYTECH INST DEPT ELECT COMP & SYST ENGNTROYNY 12180

Since the introduction by Shepp and Vardi [Shepp, L. A. & Vardi, Y. (1982) IEEE Trans. Med. Imaging 1, 113-121] of the expectation-maximization algorithm for the generation of maximum-likelihood images in emission tomography, a number of investigators have applied the maximum-likelihood method to imaging problems. Though this approach is promising, it is now well known that the unconstrained maximum-likelihood approach has two major drawbacks: (i) the algorithm is computationally demanding, resulting in reconstruction times that are not acceptable for routine clinical application, and (ii) the unconstrained maximum-likelihood estimator has a fundamental noise artifact that worsens as the iterative algorithm climbs the likelihood hill. In this paper the computation issue is addressed by proposing an implementation on the class of massively parallel single-instruction, multiple-data architectures. By restructuring the superposition integrals required for the expectation-maximization algorithm as the solutions of partial differential equations, the local data passage required for efficient computation on this class of machines is satisfied. For dealing with the "noise artifact" a Markov random field prior determined by Good's rotationally invariant roughness penalty is incorporated. These methods are demonstrated on the single-instruction multiple-data class of parallel processors, with the computation times compared with those on conventional and hypercube architectures.

关键词： PENALIZED LIKELIHOOD expectation-maximization algorithm PARALLEL COMPUTERS

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Reliability analysis for multi-component systems considering stochastic dependency based on factor analysis

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2022年 169卷 108754-108754页

作者： Kong, Xuefeng Yang, Jun Li, Lei Beihang Univ Sch Reliabil & Syst Engn Beijing 100191 Peoples R China

Reliability analysis for engineering systems with multiple components has gained increasing interest in recent. Most existing works assume that components follow identical degradation models and preset joint distributions or link functions to characterize the degradation interactions. However, distinct degradation characteristics of components are commonly observed in practice. Besides, the degradation interactions are usually complex and diverse, making the preset dependency structures not applicable. Confronted with the diverse degradation characteristics and complex degradation interactions, this paper offers a flexible reliability analysis framework for multi-component systems. First, a stochastic process-based general degradation model combining the Wiener process, Gamma process, and inverse Gaussian process is adopted to describe component degradation processes, and the factor analysis is employed to characterize the degradation interactions by seeking the latent common factors that dominate their interdependency. Thus the assumption of the identical degradation process and preset dependency structure can be relaxed, which enhances the robustness of the method. On this basis, we derive the explicit form of the system reliability function. An efficient expectation-maximization algorithm is then utilized for statistical inference to enable a fast computation. Finally, the superiority of the proposed method is demonstrated by two real case studies on lithium-ion battery packs.

关键词： Reliability analysis Multi-component systems Stochastic process Stochastic dependency Factor analysis expectation-maximization algorithm

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A hidden Markov model for continuous longitudinal data with missing responses and dropout

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BIOMETRICAL JOURNAL 2023年第5期65卷 2200016-2200016页

作者： Pandolfi, Silvia Bartolucci, Francesco Pennoni, Fulvia Univ Perugia Dept Econ Perugia Italy Univ Milano Bicocca Dept Stat & Quantitat Methods Milan Italy Univ Perugia Dept ofEcon Via A Pascoli 20 I-06123 Perugia Italy

We propose a hidden Markov model for multivariate continuous longitudinal responses with covariates that accounts for three different types of missing pattern: (I) partially missing outcomes at a given time occasion, (II) completely missing outcomes at a given time occasion (intermittent pattern), and (III) dropout before the end of the period of observation (monotone pattern). The missing-at-random (MAR) assumption is formulated to deal with the first two types of missingness, while to account for the informative dropout, we rely on an extra absorbing state. Estimation of the model parameters is based on the maximum likelihood method that is implemented by an expectation-maximization (EM) algorithm relying on suitable recursions. The proposal is illustrated by a Monte Carlo simulation study and an application based on historical data on primary biliary cholangitis.

关键词： expectation-maximization algorithm forward-backward recursion latent Markov model missing values prediction

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Maximum-likelihood direction of arrival estimation under intermittent jamming

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DIGITAL SIGNAL PROCESSING 2021年 113卷 103028-103028页

作者： Akdemir, Safak Bilgi Candan, Cagatay Middle East Tech Univ METU Dept Elect & Elect Engn TR-06800 Ankara Turkey

Multiple-snapshot maximum-likelihood (ML) direction of arrival (DOA) estimation problem is studied for the intermittent jamming scenario. The intermittent jamming modality is based on the assumption that only a subset of the collected snapshots are contaminated by the jammer while the others are jammer free;but the receiver does not know which is which. This type of jamming is frequently encountered in practice either inadvertently, say due to the sporadic activity of a non-hostile system;or intentionally, say due to the activity of an adversary sweeping the operational bandwidth of the receiver. Exact maximum likelihood solution for the problem is analytically intractable and an expectation maximization (EM) method based solution is developed for coherent and non-coherent signal models. Coherent signal model assumes that the phase difference between the coefficients of two consecutive snapshots are known a-priori which is an assumption compatible with the Swerling-1/3 target models in the radar signal processing literature. Non-coherent signal model does not have such an assumption and it is suitable for Swerling-2/4 targets. The suggested EM based solution is shown to yield an important estimation accuracy improvement over conventional maximum-likelihood solution which ignores the intermittency of jammer and also over the atomic norm based high resolution estimation techniques. Cramer-Rao type performance lower bounds for the problem is also provided to illustrate the efficacy of the suggested estimator. (C) 2021 Elsevier Inc. All rights reserved.

关键词： Direction of arrival estimation Jamming Intermittent interference expectation-maximization algorithm Cramer-Rao bound Modified Cramer-Rao bound

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Iterative Channel Estimation for Higher Order Modulated STBC-OFDM Systems with Reduced Complexity

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KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 2016年第6期10卷 2446-2462页

作者： Basturk, Ilhan Ozbek, Berna Adnan Menderes Univ Dept Elect & Elect Engn Aydin Turkey Izmir Inst Technol Dept Elect & Elect Engn Izmir Turkey

In this paper, a frequency domain expectation-maximization (EM)-based channel estimation algorithm for Space Time Block Coded-Orthogonal Frequency Division Multiplexing (STBC-OFDM) systems is investigated to support higher data rate applications in wireless communications. The computational complexity of the frequency domain EM-based channel estimation is increased when higher order constellations are used because of the ascending size of the search set space. Thus, a search set reduction algorithm is proposed to decrease the complexity without sacrificing the system performance. The performance results of the proposed algorithm is obtained in terms of Bit Error Rate (BER) and Mean Square Error (MSE) for 16QAM and 64QAM modulation schemes.

关键词： Channel estimation space-time block codes OFDM expectation-maximization algorithm

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Deconvolution of a Distribution Function

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Journal of the American Statistical Association 1997年第440期92卷 1459-1465页

作者： Cordy, Clifford B. Thomas, David R. Software Engineer Accu-Fab Systems Inc. Corvallis OR 97330. Professor Department of Statistics Oregon State University Corvallis OR 97331

We consider the estimation of a distribution function when observations from this distribution are contaminated by measurement error. The unknown distribution is modeled as a mixture of a finite number of known distributions. Model parameters can be estimated and confidence intervals constructed using well-known likelihood theory. We show that it is also possible to apply this approach to estimation of a unimodal distribution. An application is presented using data from a dietary survey. Simulation results are given to indicate the performance of the estimators and the confidence interval procedures. [ABSTRACT FROM AUTHOR]

关键词： expectation-maximization algorithm Mixture of distributions Profile likelihood Unimodal distribution

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Estimation, diagnostics, and extensions of nonparametric Hawkes processes with kernel functions

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JAPANESE JOURNAL OF STATISTICS AND DATA SCIENCE 2020年第1期3卷 391-412页

作者： Zhuang, Jiancang Inst Stat Math 10-3 Midori Cho Tachikawa Tokyo 1908562 Japan Grad Univ Adv Studies SOKENDAI Dept Stat Sci 10-3 Midori Cho Tachikawa Tokyo 1908562 Japan London Math Lab 8 Margravine Gardens London W6 8RH England

The Hawkes self-exciting model has become one of the most popular point-process models in many research areas in the natural and social sciences because of its capacity for investigating the clustering effect and positive interactions among individual events/particles. This article discusses a general nonparametric framework for the estimation, extensions, and post-estimation diagnostics of Hawkes models, in which we use the kernel functions as the basic smoothing tool.

关键词： Hawkes process Kernel estimate ETAS model Earthquake Crime expectation-maximization algorithm Stochastic reconstruction

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A spatio-temporal model for the analysis and prediction of fine particulate matter concentration in Beijing

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ENVIRONMETRICS 2021年第1期32卷 e2648-e2648页

作者： Wan, Yating Xu, Minya Huang, Hui Chen, Song Xi Peking Univ Guanghua Sch Management Beijing Peoples R China Sun Yat Sen Univ Sch Math Guangzhou Peoples R China

Effective air quality management and forecasting in Beijing is urgently needed as the region suffers from the worst air pollution in any standards. However, the statistical mechanism of the PM(2.5)formation with respect to various factors is underexplored in this region and China in general. Through an elaborate application with refinement of a spatio-temporal model with varying coefficients to the dynamics of PM(2.5)around Beijing based on a large dataset, we provide a comprehensive interpretation for the dynamics of PM(2.5)concentration with respect to its gaseous precursors, meteorological conditions and geographical variables. Furthermore, we conduct multistep temporal forecasts on a rolling basis for both the PM(2.5)concentration and the pollution levels. With the help of the expectation-maximization algorithm, the proposed models estimated for eight seasons from March 2015 to February 2017 around Beijing provide satisfactory in-sample fits and generate more accurate out-of-sample forecasts, compared with Finazzi and Fasso's original model as well as other alternative models. Valuable insights in tackling the excessive air pollution in Beijing are suggested from the comprehensive application of our model.

关键词： air pollution expectation-maximization algorithm random effects rolling prediction

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RETRACTED: Development of censored data-based robust design for pharmaceutical quality by design (Retracted Article)

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2010年第9-12期49卷 839-851页

作者： Cho, Byung Rae Choi, Yongsun Shin, Sangmun Clemson Univ Dept Ind Engn Clemson SC 29634 USA Inje Univ Dept Syst Management & Engn Gimhae 621749 Gyeong Nam South Korea

Robust design techniques, which are based on the concept of building quality into products or processes, are increasingly popular in many manufacturing industries. In this paper, we propose a new robust design model in the context of pharmaceutical production research and development. Traditional robust design principles have often been applied to situations in which the quality characteristics of interest are typically time insensitive. In pharmaceutical manufacturing processes, time-oriented quality characteristics, such as the degradation of a drug, are often of interest. As a result, current robust design models for quality improvement which have been studied in the literature may not be effective in finding robust design solutions. To address such practical needs, this paper develops a robust design model using censored data, which is perhaps the first attempt in the robust design field. We then study estimation methods, such as the expectation-maximization algorithm and the maximum likelihood method, in the robust design context. Finally, comparative studies are discussed for model verification via a numerical example.

关键词： Robust design Mixture experiments Pharmaceutical formulations Censored data expectation-maximization algorithm Maximum likelihood estimation

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Transmission Based Conditional Logistic Model for Testing Main and Interaction Effects

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Open Journal of Statistics 2021年第5期11卷 713-719页

作者： Caixia Li Peixing Li School of Mathematics Sun Yat-sen University Guangzhou China Guangdong Province Key Laboratory of Computational Science Sun Yat-sen University Guangzhou China

Transmission disequilibrium test (TDT) is a popular family based genetic association method. Under multiplicative assumption, a conditional logistic regression for matched pair, affected offspring with allele transmitted from parents and pseudo-offspring (control) with allele non-transmitted from parents, was built to detect the main effects of genes and gene-covariate interactions. When there exist genotype uncertainties, expectation-maximization (EM) algorithm was adopted to estimate the coefficients. The transmission model was applied to detect the association between M235T polymorphism in AGT gene and essential hypertension (ESH). Most of parents are not available in the 126 families from HongKong Chinese population. The results showed M235T is associated with hypertension and there is interaction between M235T and the case’s sex. The allele T is higher risk for male than female.

关键词： Transmission Disequilibrium Test Gene-Covariate Interaction Conditional Logistic Model expectation-maximization algorithm

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