Maximum Likelihood Estimation Of Varma Models Using A State Space Em Algorithm

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Maximum Likelihood Estimation of VARMA Models Using a State-Space EM Algorithm

Author : Konstantinos Metaxoglou
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)

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Book Synopsis Maximum Likelihood Estimation of VARMA Models Using a State-Space EM Algorithm by : Konstantinos Metaxoglou

Download or read book Maximum Likelihood Estimation of VARMA Models Using a State-Space EM Algorithm written by Konstantinos Metaxoglou and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We introduce a state-space representation for vector autoregressive moving-average models that enables maximum likelihood estimation using the EM algorithm. We obtain closed-form expressions for both the E- and M-steps; the former requires the Kalman filter and a fixed-interval smoother, and the latter requires least squares-type regression. We show via simulations that our algorithm converges reliably to the maximum, whereas gradient-based methods often fail because of the highly nonlinear nature of the likelihood function. Moreover, our algorithm converges in a smaller number of function evaluations than commonly used direct-search routines. Overall, our approach achieves its largest performance gains when applied to models of high dimension. We illustrate our technique by estimating a high-dimensional vector moving-average model for an efficiency test of California's wholesale electricity market.

A Generalization of the EM Algorithm for Maximum Likelihood Estimation in Mallows' Model Using Partially Ranked Data and Asymptotic Relative Efficiencies for Some Ranking Tests of The K-Sample Problem

Download A Generalization of the EM Algorithm for Maximum Likelihood Estimation in Mallows' Model Using Partially Ranked Data and Asymptotic Relative Efficiencies for Some Ranking Tests of The K-Sample Problem PDF Online Free

Author : Laura Jean Adkins
Publisher :
ISBN 13 :
Total Pages : 426 pages
Book Rating : 4.:/5 (355 download)

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Book Synopsis A Generalization of the EM Algorithm for Maximum Likelihood Estimation in Mallows' Model Using Partially Ranked Data and Asymptotic Relative Efficiencies for Some Ranking Tests of The K-Sample Problem by : Laura Jean Adkins

Download or read book A Generalization of the EM Algorithm for Maximum Likelihood Estimation in Mallows' Model Using Partially Ranked Data and Asymptotic Relative Efficiencies for Some Ranking Tests of The K-Sample Problem written by Laura Jean Adkins and published by . This book was released on 1996 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Pseudo Maximum Likelihood Estimation of Cointegrated Multiple Frequency I(1) VARMA Processes Using the State Space Framework

Author : Patrick de Matos Ribeiro
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (124 download)

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Book Synopsis Pseudo Maximum Likelihood Estimation of Cointegrated Multiple Frequency I(1) VARMA Processes Using the State Space Framework by : Patrick de Matos Ribeiro

Download or read book Pseudo Maximum Likelihood Estimation of Cointegrated Multiple Frequency I(1) VARMA Processes Using the State Space Framework written by Patrick de Matos Ribeiro and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

The EM Algorithm and Related Statistical Models

Author : Michiko Watanabe
Publisher : CRC Press
ISBN 13 : 9780203913055
Total Pages : 226 pages
Book Rating : 4.9/5 (13 download)

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Book Synopsis The EM Algorithm and Related Statistical Models by : Michiko Watanabe

Download or read book The EM Algorithm and Related Statistical Models written by Michiko Watanabe and published by CRC Press. This book was released on 2003-10-15 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploring the application and formulation of the EM algorithm, The EM Algorithm and Related Statistical Models offers a valuable method for constructing statistical models when only incomplete information is available, and proposes specific estimation algorithms for solutions to incomplete data problems. The text covers current topics including sta

State-Space Methods for Time Series Analysis

Author : Jose Casals
Publisher : CRC Press
ISBN 13 : 1315362600
Total Pages : 270 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis State-Space Methods for Time Series Analysis by : Jose Casals

Download or read book State-Space Methods for Time Series Analysis written by Jose Casals and published by CRC Press. This book was released on 2018-09-03 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: The state-space approach provides a formal framework where any result or procedure developed for a basic model can be seamlessly applied to a standard formulation written in state-space form. Moreover, it can accommodate with a reasonable effort nonstandard situations, such as observation errors, aggregation constraints, or missing in-sample values. Exploring the advantages of this approach, State-Space Methods for Time Series Analysis: Theory, Applications and Software presents many computational procedures that can be applied to a previously specified linear model in state-space form. After discussing the formulation of the state-space model, the book illustrates the flexibility of the state-space representation and covers the main state estimation algorithms: filtering and smoothing. It then shows how to compute the Gaussian likelihood for unknown coefficients in the state-space matrices of a given model before introducing subspace methods and their application. It also discusses signal extraction, describes two algorithms to obtain the VARMAX matrices corresponding to any linear state-space model, and addresses several issues relating to the aggregation and disaggregation of time series. The book concludes with a cross-sectional extension to the classical state-space formulation in order to accommodate longitudinal or panel data. Missing data is a common occurrence here, and the book explains imputation procedures necessary to treat missingness in both exogenous and endogenous variables. Web Resource The authors’ E4 MATLAB® toolbox offers all the computational procedures, administrative and analytical functions, and related materials for time series analysis. This flexible, powerful, and free software tool enables readers to replicate the practical examples in the text and apply the procedures to their own work.

Safety and Reliability. Theory and Applications

Author : Marko Cepin
Publisher : CRC Press
ISBN 13 : 1351809733
Total Pages : 3668 pages
Book Rating : 4.3/5 (518 download)

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Book Synopsis Safety and Reliability. Theory and Applications by : Marko Cepin

Download or read book Safety and Reliability. Theory and Applications written by Marko Cepin and published by CRC Press. This book was released on 2017-06-14 with total page 3668 pages. Available in PDF, EPUB and Kindle. Book excerpt: Safety and Reliability – Theory and Applications contains the contributions presented at the 27th European Safety and Reliability Conference (ESREL 2017, Portorož, Slovenia, June 18-22, 2017). The book covers a wide range of topics, including: • Accident and Incident modelling • Economic Analysis in Risk Management • Foundational Issues in Risk Assessment and Management • Human Factors and Human Reliability • Maintenance Modeling and Applications • Mathematical Methods in Reliability and Safety • Prognostics and System Health Management • Resilience Engineering • Risk Assessment • Risk Management • Simulation for Safety and Reliability Analysis • Structural Reliability • System Reliability, and • Uncertainty Analysis. Selected special sessions include contributions on: the Marie Skłodowska-Curie innovative training network in structural safety; risk approaches in insurance and fi nance sectors; dynamic reliability and probabilistic safety assessment; Bayesian and statistical methods, reliability data and testing; oganizational factors and safety culture; software reliability and safety; probabilistic methods applied to power systems; socio-technical-economic systems; advanced safety assessment methodologies: extended Probabilistic Safety Assessment; reliability; availability; maintainability and safety in railways: theory & practice; big data risk analysis and management, and model-based reliability and safety engineering. Safety and Reliability – Theory and Applications will be of interest to professionals and academics working in a wide range of industrial and governmental sectors including: Aeronautics and Aerospace, Automotive Engineering, Civil Engineering, Electrical and Electronic Engineering, Energy Production and Distribution, Environmental Engineering, Information Technology and Telecommunications, Critical Infrastructures, Insurance and Finance, Manufacturing, Marine Industry, Mechanical Engineering, Natural Hazards, Nuclear Engineering, Offshore Oil and Gas, Security and Protection, Transportation, and Policy Making.

Approximate EM Algorithms for State Space Models with Markov Regime Changes

Author : Tianni Zhou
Publisher :
ISBN 13 :
Total Pages : 192 pages
Book Rating : 4.:/5 (65 download)

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Book Synopsis Approximate EM Algorithms for State Space Models with Markov Regime Changes by : Tianni Zhou

Download or read book Approximate EM Algorithms for State Space Models with Markov Regime Changes written by Tianni Zhou and published by . This book was released on 2002 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt:

The EM Algorithm in Multivariate Gaussian Mixture Models Using Anderson Acceleration

Author : Joshua H. Plasse
Publisher :
ISBN 13 :
Total Pages : 102 pages
Book Rating : 4.:/5 (851 download)

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Book Synopsis The EM Algorithm in Multivariate Gaussian Mixture Models Using Anderson Acceleration by : Joshua H. Plasse

Download or read book The EM Algorithm in Multivariate Gaussian Mixture Models Using Anderson Acceleration written by Joshua H. Plasse and published by . This book was released on 2013 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Over the years analysts have used the EM algorithm to obtain maximum likelihood estimates from incomplete data for various models. The general algorithm admits several appealing properties such as strong global convergence; however, the rate of convergence is linear which in some cases may be unacceptably slow. This work is primarily concerned with applying Anderson acceleration to the EM algorithm for Gaussian mixture models (GMM) in hopes of alleviating slow convergence. As preamble we provide a review of maximum likelihood estimation and derive the EM algorithm in detail. The iterates that correspond to the GMM are then formulated and examples are provided. These examples show how faster convergence is experienced when the data are well separated, whereas much slower convergence is seen whenever the sample is poorly separated. The Anderson acceleration method is then presented, and its connection to the EM algorithm is discussed. The work is then concluded by applying Anderson acceleration to the EM algorithm which results in reducing the number of iterations required to obtain convergence.

State-space Models with Exogenous Variables and Missing Data

Author : Arlene Hortensia Naranjo
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (663 download)

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Book Synopsis State-space Models with Exogenous Variables and Missing Data by : Arlene Hortensia Naranjo

Download or read book State-space Models with Exogenous Variables and Missing Data written by Arlene Hortensia Naranjo and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT: We describe a method to calculate parameter estimates in the state-space model with exogenous variables, with and without missing observations. Exogenous variables are independent of the system and affect the response, but not vice versa. The EM algorithm and the Kalman smoother equations are used in combination to derive maximum likelihood estimates for the model parameters. In the missing data case, two state-space models are proposed to represent the unobserved information that can occur in both the response and exogenous variables. In addition, analytic recursive formulas are derived for calculating parameter estimate standard errors. Simulation studies are performed to determine the effects of varying the number of subjects and time points, differing missing data percentages, and mismatched observations in time. It seems that the exogenous variables are superfluous in the complete case since the previous responses in time appear to be sufficient in predicting future outcomes. However, the exogenous variables add considerable information to the analysis when data are missing and there is strong evidence in favor of including these in the model. The new procedure appears to be relatively robust to moderate percentages of missing data and mismatched observations in time, even with fewer subjects and time points, although several of the variance parameters are being overestimated. The methodology is applied to a data set from an observational study on patients with autoimmune diseases.

Data-based Techniques to Improve State Estimation in Model Predictive Control

Author : Murali R. Rajamani
Publisher :
ISBN 13 :
Total Pages : 264 pages
Book Rating : 4.:/5 (891 download)

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Book Synopsis Data-based Techniques to Improve State Estimation in Model Predictive Control by : Murali R. Rajamani

Download or read book Data-based Techniques to Improve State Estimation in Model Predictive Control written by Murali R. Rajamani and published by . This book was released on 2007 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Theory and Use of the EM Algorithm

Author : Maya R. Gupta
Publisher : Now Publishers Inc
ISBN 13 : 1601984308
Total Pages : 87 pages
Book Rating : 4.6/5 (19 download)

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Book Synopsis Theory and Use of the EM Algorithm by : Maya R. Gupta

Download or read book Theory and Use of the EM Algorithm written by Maya R. Gupta and published by Now Publishers Inc. This book was released on 2011 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces the expectation-maximization (EM) algorithm and provides an intuitive and mathematically rigorous understanding of this method. Theory and Use of the EM Algorithm is designed to be useful to both the EM novice and the experienced EM user looking to better understand the method and its use.

Multivariate Time Series With Linear State Space Structure

Author : Víctor Gómez
Publisher : Springer
ISBN 13 : 3319285998
Total Pages : 553 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Multivariate Time Series With Linear State Space Structure by : Víctor Gómez

Download or read book Multivariate Time Series With Linear State Space Structure written by Víctor Gómez and published by Springer. This book was released on 2016-05-09 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive study of multivariate time series with linear state space structure. The emphasis is put on both the clarity of the theoretical concepts and on efficient algorithms for implementing the theory. In particular, it investigates the relationship between VARMA and state space models, including canonical forms. It also highlights the relationship between Wiener-Kolmogorov and Kalman filtering both with an infinite and a finite sample. The strength of the book also lies in the numerous algorithms included for state space models that take advantage of the recursive nature of the models. Many of these algorithms can be made robust, fast, reliable and efficient. The book is accompanied by a MATLAB package called SSMMATLAB and a webpage presenting implemented algorithms with many examples and case studies. Though it lays a solid theoretical foundation, the book also focuses on practical application, and includes exercises in each chapter. It is intended for researchers and students working with linear state space models, and who are familiar with linear algebra and possess some knowledge of statistics.

Parameter Estimation of a Robust State-space Model Via Monte Carlo Methods and the EM Algorithm

Author : Amanda Halladay
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (437 download)

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Book Synopsis Parameter Estimation of a Robust State-space Model Via Monte Carlo Methods and the EM Algorithm by : Amanda Halladay

Download or read book Parameter Estimation of a Robust State-space Model Via Monte Carlo Methods and the EM Algorithm written by Amanda Halladay and published by . This book was released on 2007 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

The EM Algorithm for Maximum Likelihood Estimates of Multivariate Normal Parameters with Incomplete Data

Author : Richard A. Goodrum
Publisher :
ISBN 13 :
Total Pages : 42 pages
Book Rating : 4.:/5 (953 download)

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Book Synopsis The EM Algorithm for Maximum Likelihood Estimates of Multivariate Normal Parameters with Incomplete Data by : Richard A. Goodrum

Download or read book The EM Algorithm for Maximum Likelihood Estimates of Multivariate Normal Parameters with Incomplete Data written by Richard A. Goodrum and published by . This book was released on 1982 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt:

State Space and Unobserved Component Models

Author : James Durbin
Publisher : Cambridge University Press
ISBN 13 : 9780521835954
Total Pages : 398 pages
Book Rating : 4.8/5 (359 download)

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Book Synopsis State Space and Unobserved Component Models by : James Durbin

Download or read book State Space and Unobserved Component Models written by James Durbin and published by Cambridge University Press. This book was released on 2004-06-10 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive overview of developments in the theory and application of state space modeling, first published in 2004.

Conceptual Econometrics Using R

Author :
Publisher : Elsevier
ISBN 13 : 0444643125
Total Pages : 330 pages
Book Rating : 4.4/5 (446 download)

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Book Synopsis Conceptual Econometrics Using R by :

Download or read book Conceptual Econometrics Using R written by and published by Elsevier. This book was released on 2019-08-20 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Conceptual Econometrics Using R, Volume 41 provides state-of-the-art information on important topics in econometrics, including quantitative game theory, multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, productivity and financial market jumps and co-jumps, among others. Presents chapters authored by distinguished, honored researchers who have received awards from the Journal of Econometrics or the Econometric Society Includes descriptions and links to resources and free open source R, allowing readers to not only use the tools on their own data, but also jumpstart their understanding of the state-of-the-art

Essentials of Time Series for Financial Applications

Author : Massimo Guidolin
Publisher : Academic Press
ISBN 13 : 0128134100
Total Pages : 435 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Essentials of Time Series for Financial Applications by : Massimo Guidolin

Download or read book Essentials of Time Series for Financial Applications written by Massimo Guidolin and published by Academic Press. This book was released on 2018-05-29 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essentials of Time Series for Financial Applications serves as an agile reference for upper level students and practitioners who desire a formal, easy-to-follow introduction to the most important time series methods applied in financial applications (pricing, asset management, quant strategies, and risk management). Real-life data and examples developed with EViews illustrate the links between the formal apparatus and the applications. The examples either directly exploit the tools that EViews makes available or use programs that by employing EViews implement specific topics or techniques. The book balances a formal framework with as few proofs as possible against many examples that support its central ideas. Boxes are used throughout to remind readers of technical aspects and definitions and to present examples in a compact fashion, with full details (workout files) available in an on-line appendix. The more advanced chapters provide discussion sections that refer to more advanced textbooks or detailed proofs. Provides practical, hands-on examples in time-series econometrics Presents a more application-oriented, less technical book on financial econometrics Offers rigorous coverage, including technical aspects and references for the proofs, despite being an introduction Features examples worked out in EViews (9 or higher)