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Author : Lung-Fei Lee
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (32 download)
Download or read book Simulated Maximum Likelihood Estimation of Discrete Models with Group Data written by Lung-Fei Lee and published by . This book was released on 1993 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Kenneth Train
Publisher : Cambridge University Press
ISBN 13 : 0521766559
Total Pages : 399 pages
Book Rating : 4.5/5 (217 download)
Download or read book Discrete Choice Methods with Simulation written by Kenneth Train and published by Cambridge University Press. This book was released on 2009-07-06 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
Author : Philipp Eisenhauer
Publisher :
ISBN 13 :
Total Pages : 47 pages
Book Rating : 4.:/5 (92 download)
Download or read book Estimation Od Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments written by Philipp Eisenhauer and published by . This book was released on 2014 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : T. Fomby
Publisher : Elsevier
ISBN 13 : 0762310758
Total Pages : 266 pages
Book Rating : 4.7/5 (623 download)
Download or read book Maximum Likelihood Estimation of Misspecified Models written by T. Fomby and published by Elsevier. This book was released on 2003-12-12 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comparative study of pure and pretest estimators for a possibly misspecified two-way error component model / Badi H. Baltagi, Georges Bresson, Alain Pirotte -- Estimation, inference, and specification testing for possibly misspecified quantile regression / Tae-Hwan Kim, Halbert White -- Quasimaximum likelihood estimation with bounded symmetric errors / Douglas Miller, James Eales, Paul Preckel -- Consistent quasi-maximum likelihood estimation with limited information / Douglas Miller, Sang-Hak Lee -- An examination of the sign and volatility switching arch models under alternative distributional assumptions / Mohamed F. Omran, Florin Avram -- estimating a linear exponential density when the weighting matrix and mean parameter vector are functionally related / Chor-yiu Sin -- Testing in GMM models without truncation / Timothy J. Vogelsang -- Bayesian analysis of misspecified models with fixed effects / Tiemen Woutersen -- Tests of common deterministic trend slopes applied to quarterly global temperature data / Thomas B. Fomby, Timothy J. Vogelsang -- The sandwich estimate of variance / James W. Hardin -- Test statistics and critical values in selectivity models / R. Carter Hill, Lee C. Adkins, Keith A. Bender -- Introduction / Thomas B Fomby, R. Carter Hill.
Author : Yanhua Tian
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (136 download)
Download or read book Maximum Likelihood Estimation of Discrete Log-Concave Distributions with Applications written by Yanhua Tian and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Shape-constrained methods specify a class of distributions instead of a single parametric family. The approach increases the robustness of the estimation without much loss of efficiency. Among these, log-concavity is an appealing shape constraint in distribution modeling, because it falls into the popular unimodal shape-constraint and many parametric models are log-concave. This is, therefore, the focus of our work. First, we propose a maximum likelihood estimator of discrete log-concave distributions in higher dimensions. We define a new class of log-concave distributions in multiple dimensional spaces and study its properties. We show how to compute the maximum likelihood estimator from an independent and identically distributed sample, and establish consistency of the estimator, even if the class has been incorrectly specified. For finite sample sizes, the proposed estimator outperforms a purely nonparametric approach (the empirical distribution), but is able to remain comparable to the correct parametric approach. Furthermore, the new class has a natural relationship with log-concave densities when data has been grouped or discretized. We show how this property can be used in a real data example. Secondly, we apply the discrete log-concave maximum likelihood estimator in one-dimensional space to a clustering problem. Our work mainly focuses on the categorical nominal data. We develop a log-concave mixture model using the discrete log-concave maximum likelihood estimator. We then apply the log-concave mixture model to our clustering algorithm. We compare our proposed clustering algorithm with the other two clustering methods. Comparing results show that our proposed algorithm has a good performance.
Author : Jan C. Willems
Publisher : Springer Science & Business Media
ISBN 13 : 3642750079
Total Pages : 254 pages
Book Rating : 4.6/5 (427 download)
Download or read book From Data to Model written by Jan C. Willems and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problem of obtaining dynamical models directly from an observed time-series occurs in many fields of application. There are a number of possible approaches to this problem. In this volume a number of such points of view are exposed: the statistical time series approach, a theory of guaranted performance, and finally a deterministic approximation approach. This volume is an out-growth of a number of get-togethers sponsered by the Systems and Decision Sciences group of the International Institute of Applied Systems Analysis (IIASA) in Laxenburg, Austria. The hospitality and support of this organization is gratefully acknowledged. Jan Willems Groningen, the Netherlands May 1989 TABLE OF CONTENTS Linear System Identification- A Survey page 1 M. Deistler A Tutorial on Hankel-Norm Approximation 26 K. Glover A Deterministic Approach to Approximate Modelling 49 C. Heij and J. C. Willems Identification - a Theory of Guaranteed Estimates 135 A. B. Kurzhanski Statistical Aspects of Model Selection 215 R. Shibata Index 241 Addresses of Authors 246 LINEAR SYSTEM IDENTIFICATION· A SURVEY M. DEISTLER Abstract In this paper we give an introductory survey on the theory of identification of (in general MIMO) linear systems from (discrete) time series data. The main parts are: Structure theory for linear systems, asymptotic properties of maximum likelihood type estimators, estimation of the dynamic specification by methods based on information criteria and finally, extensions and alternative approaches such as identification of unstable systems and errors-in-variables. Keywords Linear systems, parametrization, maximum likelihood estimation, information criteria, errors-in-variables.
Author : Riccardo Scarpa
Publisher : Springer Science & Business Media
ISBN 13 : 9781402036835
Total Pages : 456 pages
Book Rating : 4.0/5 (368 download)
Download or read book Applications of Simulation Methods in Environmental and Resource Economics written by Riccardo Scarpa and published by Springer Science & Business Media. This book was released on 2005-08-12 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simulation methods are revolutionizing the practice of applied economic analysis. In this book, leading researchers from around the world discuss interpretation issues, similarities and differences across alternative models, and propose practical solutions for the choice of the model and programming. Case studies show the practical use and the results brought forth by the different methods.
Author : Vinh Quang Nguyen
Publisher :
ISBN 13 : 9781124951140
Total Pages : 204 pages
Book Rating : 4.9/5 (511 download)
Download or read book Robust Inference and Group Sequential Methods in Discrete Hazard Models written by Vinh Quang Nguyen and published by . This book was released on 2011 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: The current research focuses on the analysis of discrete-time data arising from periodic follow-up using discrete-time hazard models (analogs to the Cox proportional hazards model) when the model is misspecified. We begin by providing scientific examples that motivate the present research and provide some background and notation that lays the foundation for the remainder of the dissertation. We then describe methods for analyzing grouped proportional hazards data, and present simulation results to convey their relative performances. Focusing on discrete hazard models for analyzing grouped survival data, we then explore the impact of model misspecification, namely a time-varying treatment effect, on the maximum likelihood (ML) estimator of commonly used discrete-time models in the two-sample setting (e.g., clinical trials). We show that the ML estimator is consistent to a quantity that depends on the censoring pattern of the observations and the maximum follow-up time of the study. We propose a censoring-robust estimator that removes the influence of censoring by re-weighing observations based on the inverse of the Kaplan-Meier estimator of the censoring times for each group and derive its asymptotic distribution. Simulation is used to compare the two estimators in different scenarios and the proposed estimator is applied to data from clinical trial in HIV/AIDS. Next, we describe how robust inference can be extended to the observational study setting where multiple (possibly continuous) covariates are involved. In this setting, we rely on survival trees to identify group-specific censoring to aid in the estimation of the censoring distribution. Finally, we explore the use of the censoring-robust estimator in an interim testing context that is typical of late stage clinical trials. To that end, we derive the joint asymptotic distribution of the censoring-robust estimator calculated over time. We note that the estimating equation of the censoring-robust estimator lacks an independent increments structure, rendering standard group sequential methods inapplicable. We then propose a strategy for designing and evaluating group sequential trials based on the censoring-robust estimator using existing pilot data.
Author : Daniel Zelterman
Publisher : Oxford University Press
ISBN 13 : 9780198524366
Total Pages : 233 pages
Book Rating : 4.5/5 (243 download)
Download or read book Models for Discrete Data written by Daniel Zelterman and published by Oxford University Press. This book was released on 1999 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discrete or count data arise in experiments where the outcome variables are the numbers of individuals classified into unique, non-overlapping categories. This book describes the statistical models used in the analysis and summary of such data, and provides an introduction to the subject for graduate students and practitioners needing a review of the methodology. It includes topics not covered in depth elsewhere, such as the negative multinomial distribution; the many forms of the hypergeometric distribution; and coordinate free models.
Author : Henghsiu Tsai
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)
Download or read book Quasi-Maximum Likelihood Estimation for a Class of Continuous-Time Long-Memory Processes written by Henghsiu Tsai and published by . This book was released on 2005 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tsai and Chan (2003) has recently introduced the Continuous-time Auto-Regressive Fractionally Integrated Moving-Average (CARFIMA) models useful for studying long-memory data. We consider the estimation of the CARFIMA models with discrete-time data by maximizing the Whittle likelihood. We show that the quasi-maximum likelihood estimator is asymptotically normal and efficient. Finite-sample properties of the quasi-maximum likelihood estimator and those of the exact maximum likelihood estimator are compared by simulations. Simulations suggest that for finite samples, the quasi-maximum likelihood estimator of the Hurst parameter is less biased but more variable than the exact maximum likelihood estimator. We illustrate the method with a real application.
Author : Scott R. Eliason
Publisher : SAGE Publications
ISBN 13 : 1506315909
Total Pages : 100 pages
Book Rating : 4.5/5 (63 download)
Download or read book Maximum Likelihood Estimation written by Scott R. Eliason and published by SAGE Publications. This book was released on 1993-08-09 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Maximum Likelihood Estimation. . . provides a useful introduction. . . it is clear and easy to follow with applications and graphs. . . . I consider this a very useful book. . . . well-written, with a wealth of explanation. . ." --Dougal Hutchison in Educational Research Eliason reveals to the reader the underlying logic and practice of maximum likelihood (ML) estimation by providing a general modeling framework that utilizes the tools of ML methods. This framework offers readers a flexible modeling strategy since it accommodates cases from the simplest linear models (such as the normal error regression model) to the most complex nonlinear models that link a system of endogenous and exogenous variables with non-normal distributions. Using examples to illustrate the techniques of finding ML estimators and estimates, Eliason discusses what properties are desirable in an estimator, basic techniques for finding maximum likelihood solutions, the general form of the covariance matrix for ML estimates, the sampling distribution of ML estimators; the use of ML in the normal as well as other distributions, and some useful illustrations of likelihoods.
Author : Christian Gouriéroux
Publisher : OUP Oxford
ISBN 13 : 019152509X
Total Pages : 190 pages
Book Rating : 4.1/5 (915 download)
Download or read book Simulation-based Econometric Methods written by Christian Gouriéroux and published by OUP Oxford. This book was released on 1997-01-09 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces a new generation of statistical econometrics. After linear models leading to analytical expressions for estimators, and non-linear models using numerical optimization algorithms, the availability of high- speed computing has enabled econometricians to consider econometric models without simple analytical expressions. The previous difficulties presented by the presence of integrals of large dimensions in the probability density functions or in the moments can be circumvented by a simulation-based approach. After a brief survey of classical parametric and semi-parametric non-linear estimation methods and a description of problems in which criterion functions contain integrals, the authors present a general form of the model where it is possible to simulate the observations. They then move to calibration problems and the simulated analogue of the method of moments, before considering simulated versions of maximum likelihood, pseudo-maximum likelihood, or non-linear least squares. The general principle of indirect inference is presented and is then applied to limited dependent variable models and to financial series.
Author : Murat Khairzhanuly Munkin
Publisher :
ISBN 13 :
Total Pages : 374 pages
Book Rating : 4.3/5 ( download)
Download or read book Three Essays on Simulation-based Estimation of Multivariate Models with Unobserved Heterogeneity written by Murat Khairzhanuly Munkin and published by . This book was released on 2001 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : David Stadelmann
Publisher : GRIN Verlag
ISBN 13 : 3638720500
Total Pages : 18 pages
Book Rating : 4.6/5 (387 download)
Download or read book Discrete Choice Models written by David Stadelmann and published by GRIN Verlag. This book was released on 2007-05-29 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: Seminar paper from the year 2007 in the subject Mathematics - Statistics, grade: sehr gut (6.0), University of Fribourg (Departement für Mathematik), course: Freies Seminar des Departements für Mathematik, language: English, abstract: There are many settings in which the outcome we seek to model is a discrete choice among a set of alternatives. Almost non of these models can be consistently estimated with linear regression methods. Other methods have been devised for these cases such as the logistic regression model. This paper presents some basic principles of the logistic regression model and explains its estimation using the maximum likelihood method. An econometric application at the end highlights the importance of the theoretical issues discussed.
Author : Wim J. van der Linden
Publisher :
ISBN 13 :
Total Pages : 22 pages
Book Rating : 4.F/5 ( download)
Download or read book Likelihood-based Estimation Methods for Models for Concurrent Continuous and Discrete Responses with a Structure for the Item and Person Parameters written by Wim J. van der Linden and published by . This book was released on 2009 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Kenneth E. Train
Publisher : Cambridge University Press
ISBN 13 : 1139480375
Total Pages : 399 pages
Book Rating : 4.1/5 (394 download)
Download or read book Discrete Choice Methods with Simulation written by Kenneth E. Train and published by Cambridge University Press. This book was released on 2009-06-30 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. This second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
Author : Stuart A. Klugman
Publisher : John Wiley & Sons
ISBN 13 : 0470391332
Total Pages : 758 pages
Book Rating : 4.4/5 (73 download)
Download or read book Loss Models written by Stuart A. Klugman and published by John Wiley & Sons. This book was released on 2012-01-25 with total page 758 pages. Available in PDF, EPUB and Kindle. Book excerpt: An update of one of the most trusted books on constructing and analyzing actuarial models Written by three renowned authorities in the actuarial field, Loss Models, Third Edition upholds the reputation for excellence that has made this book required reading for the Society of Actuaries (SOA) and Casualty Actuarial Society (CAS) qualification examinations. This update serves as a complete presentation of statistical methods for measuring risk and building models to measure loss in real-world events. This book maintains an approach to modeling and forecasting that utilizes tools related to risk theory, loss distributions, and survival models. Random variables, basic distributional quantities, the recursive method, and techniques for classifying and creating distributions are also discussed. Both parametric and non-parametric estimation methods are thoroughly covered along with advice for choosing an appropriate model. Features of the Third Edition include: Extended discussion of risk management and risk measures, including Tail-Value-at-Risk (TVaR) New sections on extreme value distributions and their estimation Inclusion of homogeneous, nonhomogeneous, and mixed Poisson processes Expanded coverage of copula models and their estimation Additional treatment of methods for constructing confidence regions when there is more than one parameter The book continues to distinguish itself by providing over 400 exercises that have appeared on previous SOA and CAS examinations. Intriguing examples from the fields of insurance and business are discussed throughout, and all data sets are available on the book's FTP site, along with programs that assist with conducting loss model analysis. Loss Models, Third Edition is an essential resource for students and aspiring actuaries who are preparing to take the SOA and CAS preliminary examinations. It is also a must-have reference for professional actuaries, graduate students in the actuarial field, and anyone who works with loss and risk models in their everyday work. To explore our additional offerings in actuarial exam preparation visit www.wiley.com/go/actuarialexamprep.
