Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Download Rapid Maximum Likelihood Estimation Of Stable Distribution Parameters full books in PDF, epub, and Kindle. Read online Rapid Maximum Likelihood Estimation Of Stable Distribution Parameters ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author : Timothy Masters
Publisher :
ISBN 13 :
Total Pages : 64 pages
Book Rating : 4.:/5 (376 download)
Download or read book Rapid Maximum Likelihood Estimation of Stable Distribution Parameters written by Timothy Masters and published by . This book was released on 1977 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Michael Grabchak
Publisher :
ISBN 13 :
Total Pages : 254 pages
Book Rating : 4.E/5 ( download)
Download or read book Maximum Likelihood Estimation of Parametric Tempered Stable Distributions on the Real Line with Applications to Finance written by Michael Grabchak and published by . This book was released on 2008 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : John Nolan
Publisher : Birkhauser
ISBN 13 : 9780817641597
Total Pages : 352 pages
Book Rating : 4.6/5 (415 download)
Download or read book Stable Distributions written by John Nolan and published by Birkhauser. This book was released on 2007-03-01 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stable distributions model phenomena in a wide range of applications in real systems. Their intriguing mathematical properties have long been of interest, but the lack of computational tools has prevented their practical application. This book, the first to deal with stable distributions as a practical tool, develops an intuition for stable distributions by giving a complete, self-contained derivation of their properties and describing accurate numerical methods for computing stable laws.
Author : John P. Nolan
Publisher : Springer Nature
ISBN 13 : 3030529150
Total Pages : 342 pages
Book Rating : 4.0/5 (35 download)
Download or read book Univariate Stable Distributions written by John P. Nolan and published by Springer Nature. This book was released on 2020-09-13 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook highlights the many practical uses of stable distributions, exploring the theory, numerical algorithms, and statistical methods used to work with stable laws. Because of the author’s accessible and comprehensive approach, readers will be able to understand and use these methods. Both mathematicians and non-mathematicians will find this a valuable resource for more accurately modelling and predicting large values in a number of real-world scenarios. Beginning with an introductory chapter that explains key ideas about stable laws, readers will be prepared for the more advanced topics that appear later. The following chapters present the theory of stable distributions, a wide range of applications, and statistical methods, with the final chapters focusing on regression, signal processing, and related distributions. Each chapter ends with a number of carefully chosen exercises. Links to free software are included as well, where readers can put these methods into practice. Univariate Stable Distributions is ideal for advanced undergraduate or graduate students in mathematics, as well as many other fields, such as statistics, economics, engineering, physics, and more. It will also appeal to researchers in probability theory who seek an authoritative reference on stable distributions.
Author : Marc S. Paolella
Publisher : John Wiley & Sons
ISBN 13 : 1119417872
Total Pages : 584 pages
Book Rating : 4.1/5 (194 download)
Download or read book Fundamental Statistical Inference written by Marc S. Paolella and published by John Wiley & Sons. This book was released on 2018-06-19 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on approach to statistical inference that addresses the latest developments in this ever-growing field This clear and accessible book for beginning graduate students offers a practical and detailed approach to the field of statistical inference, providing complete derivations of results, discussions, and MATLAB programs for computation. It emphasizes details of the relevance of the material, intuition, and discussions with a view towards very modern statistical inference. In addition to classic subjects associated with mathematical statistics, topics include an intuitive presentation of the (single and double) bootstrap for confidence interval calculations, shrinkage estimation, tail (maximal moment) estimation, and a variety of methods of point estimation besides maximum likelihood, including use of characteristic functions, and indirect inference. Practical examples of all methods are given. Estimation issues associated with the discrete mixtures of normal distribution, and their solutions, are developed in detail. Much emphasis throughout is on non-Gaussian distributions, including details on working with the stable Paretian distribution and fast calculation of the noncentral Student's t. An entire chapter is dedicated to optimization, including development of Hessian-based methods, as well as heuristic/genetic algorithms that do not require continuity, with MATLAB codes provided. The book includes both theory and nontechnical discussions, along with a substantial reference to the literature, with an emphasis on alternative, more modern approaches. The recent literature on the misuse of hypothesis testing and p-values for model selection is discussed, and emphasis is given to alternative model selection methods, though hypothesis testing of distributional assumptions is covered in detail, notably for the normal distribution. Presented in three parts—Essential Concepts in Statistics; Further Fundamental Concepts in Statistics; and Additional Topics—Fundamental Statistical Inference: A Computational Approach offers comprehensive chapters on: Introducing Point and Interval Estimation; Goodness of Fit and Hypothesis Testing; Likelihood; Numerical Optimization; Methods of Point Estimation; Q-Q Plots and Distribution Testing; Unbiased Point Estimation and Bias Reduction; Analytic Interval Estimation; Inference in a Heavy-Tailed Context; The Method of Indirect Inference; and, as an appendix, A Review of Fundamental Concepts in Probability Theory, the latter to keep the book self-contained, and giving material on some advanced subjects such as saddlepoint approximations, expected shortfall in finance, calculation with the stable Paretian distribution, and convergence theorems and proofs.
Author : Alan Paul Fenech
Publisher :
ISBN 13 :
Total Pages : 246 pages
Book Rating : 4.E/5 ( download)
Download or read book Asymptotically Maximum Probability Estimators for Parameters of Symmetric Stable Distributions written by Alan Paul Fenech and published by . This book was released on 1973 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ole E. Barndorff-Nielsen
Publisher : Springer Science & Business Media
ISBN 13 : 9780817641672
Total Pages : 436 pages
Book Rating : 4.6/5 (416 download)
Download or read book Lévy Processes written by Ole E. Barndorff-Nielsen and published by Springer Science & Business Media. This book was released on 2001-03-30 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Lévy process is a continuous-time analogue of a random walk, and as such, is at the cradle of modern theories of stochastic processes. Martingales, Markov processes, and diffusions are extensions and generalizations of these processes. In the past, representatives of the Lévy class were considered most useful for applications to either Brownian motion or the Poisson process. Nowadays the need for modeling jumps, bursts, extremes and other irregular behavior of phenomena in nature and society has led to a renaissance of the theory of general Lévy processes. Researchers and practitioners in fields as diverse as physics, meteorology, statistics, insurance, and finance have rediscovered the simplicity of Lévy processes and their enormous flexibility in modeling tails, dependence and path behavior. This volume, with an excellent introductory preface, describes the state-of-the-art of this rapidly evolving subject with special emphasis on the non-Brownian world. Leading experts present surveys of recent developments, or focus on some most promising applications. Despite its special character, every topic is aimed at the non- specialist, keen on learning about the new exciting face of a rather aged class of processes. An extensive bibliography at the end of each article makes this an invaluable comprehensive reference text. For the researcher and graduate student, every article contains open problems and points out directions for futurearch. The accessible nature of the work makes this an ideal introductory text for graduate seminars in applied probability, stochastic processes, physics, finance, and telecommunications, and a unique guide to the world of Lévy processes.
Author : Gaoyuan Tian
Publisher :
ISBN 13 : 9781339671680
Total Pages : 94 pages
Book Rating : 4.6/5 (716 download)
Download or read book Parameter Estimation for Stable Distributions written by Gaoyuan Tian and published by . This book was released on 2016 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stable distributions are important family of parametric distributions widely used in signal processing as well as in mathematical finance. Estimation of the parameters of this model, is not quite straightforward due to the fact that there is no closed-form expression for their probability density function. Besides the computationally intensive maximum likelihood method where the density has to be evaluated numerically, there are some existing adhoc methods such as the quantile method, and a regression based method. These are introduced in Chapter 2. In this thesis, we introduce two new approaches: One, a spacing based estimation method introduced in Chapter 3 and two, an indirect inference method considered in Chapter 4. Simulation studies show that both these methods are very robust and efficient and do as well or better than the existing methods in most cases. Finally in Chapter 5, we use indirect inference approach to estimate the best fitting income distribution based on limited information that is often available.
Author : José-Francisco Rodrigues
Publisher : Birkhauser
ISBN 13 : 9780817671655
Total Pages : 282 pages
Book Rating : 4.6/5 (716 download)
Download or read book Trends in Partial Differential Equations of Mathematical Physics written by José-Francisco Rodrigues and published by Birkhauser. This book was released on 2005-01-01 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consists of contributions originating from a conference in Obedo, Portugal, which honoured the 70th birthday of V.A. Solonnikov. A broad variety of topics centering on nonlinear problems is presented, particularly Navier-Stokes equations, viscosity problems, diffusion-absorption equations, free boundaries, and Euler equations.
Author : HUITIAN. XUE
Publisher :
ISBN 13 : 9781361292624
Total Pages : pages
Book Rating : 4.2/5 (926 download)
Download or read book Maximum Likelihood Estimation of Parameters with Constraints in Normal and Multinomial Distributions written by HUITIAN. XUE and published by . This book was released on 2017-01-26 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "Maximum Likelihood Estimation of Parameters With Constraints in Normal and Multinomial Distributions" by Huitian, Xue, 薛惠天, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Motivated by problems in medicine, biology, engineering and economics, con- strained parameter problems arise in a wide variety of applications. Among them the application to the dose-response of a certain drug in development has attracted much interest. To investigate such a relationship, we often need to conduct a dose- response experiment with multiple groups associated with multiple dose levels of the drug. The dose-response relationship can be modeled by a shape-restricted normal regression. We develop an iterative two-step ascent algorithm to estimate normal means and variances subject to simultaneous constraints. Each iteration consists of two parts: an expectation{maximization (EM) algorithm that is utilized in Step 1 to compute the maximum likelihood estimates (MLEs) of the restricted means when variances are given, and a newly developed restricted De Pierro algorithm that is used in Step 2 to find the MLEs of the restricted variances when means are given. These constraints include the simple order, tree order, umbrella order, and so on. A bootstrap approach is provided to calculate standard errors of the restricted MLEs. Applications to the analysis of two real datasets on radioim-munological assay of cortisol and bioassay of peptides are presented to illustrate the proposed methods. Liu (2000) discussed the maximum likelihood estimation and Bayesian estimation in a multinomial model with simplex constraints by formulating this constrained parameter problem into an unconstrained parameter problem in the framework of missing data. To utilize the EM and data augmentation (DA) algorithms, he introduced latent variables {Zil;Yil} (to be defined later). However, the proposed DA algorithm in his paper did not provide the necessary individual conditional distributions of Yil given (the observed data and) the updated parameter estimates. Indeed, the EM algorithm developed in his paper is based on the assumption that{ Yil} are fixed given values. Fortunately, the EM algorithm is invariant under any choice of the value of Yil, so the final result is always correct. We have derived the aforesaid conditional distributions and hence provide a valid DA algorithm. A real data set is used for illustration. DOI: 10.5353/th_b4785001 Subjects: Estimation theory Parameter estimation
Author : Raymond L. Chambers
Publisher : CRC Press
ISBN 13 : 1420011359
Total Pages : 374 pages
Book Rating : 4.4/5 (2 download)
Download or read book Maximum Likelihood Estimation for Sample Surveys written by Raymond L. Chambers and published by CRC Press. This book was released on 2012-05-02 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sample surveys provide data used by researchers in a large range of disciplines to analyze important relationships using well-established and widely used likelihood methods. The methods used to select samples often result in the sample differing in important ways from the target population and standard application of likelihood methods can lead to
Author : Edwin Joseph Hughes
Publisher :
ISBN 13 :
Total Pages : 174 pages
Book Rating : 4.:/5 (249 download)
Download or read book Maximum Likelihood Estimation of Distribution Parameters from Incomplete Data written by Edwin Joseph Hughes and published by . This book was released on 1962 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Gavin J.S. Ross
Publisher : Springer Science & Business Media
ISBN 13 : 1461234123
Total Pages : 198 pages
Book Rating : 4.4/5 (612 download)
Download or read book Nonlinear Estimation written by Gavin J.S. Ross and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: Non-Linear Estimation is a handbook for the practical statistician or modeller interested in fitting and interpreting non-linear models with the aid of a computer. A major theme of the book is the use of 'stable parameter systems'; these provide rapid convergence of optimization algorithms, more reliable dispersion matrices and confidence regions for parameters, and easier comparison of rival models. The book provides insights into why some models are difficult to fit, how to combine fits over different data sets, how to improve data collection to reduce prediction variance, and how to program particular models to handle a full range of data sets. The book combines an algebraic, a geometric and a computational approach, and is illustrated with practical examples. A final chapter shows how this approach is implemented in the author's Maximum Likelihood Program, MLP.
Author : Svetlozar T. Rachev
Publisher : Springer Science & Business Media
ISBN 13 : 0817681809
Total Pages : 438 pages
Book Rating : 4.8/5 (176 download)
Download or read book Handbook of Computational and Numerical Methods in Finance written by Svetlozar T. Rachev and published by Springer Science & Business Media. This book was released on 2011-06-28 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: The subject of numerical methods in finance has recently emerged as a new discipline at the intersection of probability theory, finance, and numerical analysis. The methods employed bridge the gap between financial theory and computational practice, and provide solutions for complex problems that are difficult to solve by traditional analytical methods. Although numerical methods in finance have been studied intensively in recent years, many theoretical and practical financial aspects have yet to be explored. This volume presents current research and survey articles focusing on various numerical methods in finance. The book is designed for the academic community and will also serve professional investors.
Author : N. L. Johnson
Publisher :
ISBN 13 :
Total Pages : 30 pages
Book Rating : 4.3/5 (91 download)
Download or read book The Folded Normal Distribution, Iii. Accuracy of Estimation by Maximum Likelihood written by N. L. Johnson and published by . This book was released on 1961 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: Formulae for the asymptotic variances and covariance of the maximum likelihood estimators of the parameters of the folded normal distribution are obtained. Numerical comparisons with the asymptotic variances of moments estimators are made. (Author).
Author : Brian Berkowitz
Publisher : Springer Science & Business Media
ISBN 13 : 9401712786
Total Pages : 261 pages
Book Rating : 4.4/5 (17 download)
Download or read book Dispersion in Heterogeneous Geological Formations written by Brian Berkowitz and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: In spite of many years of intensive study, our current abilities to quantify and predict contaminant migration in natural geological formations remain severely limited. The heterogeneity of these formations over a wide range of scales necessitates consideration of sophisticated transport theories. The evolution of such theories has escalated to the point that a review of the subject seems timely. While conceptual and mathematical developments were crucial to the introduction of these new approaches, there are now too many publications that contain theoretical abstractions without regard to real systems, or incremental improvements to existing theories which are known not to be applicable. This volume brings together articles representing a broad spectrum of state-of-the-art approaches for characterization and quantification of contaminant dispersion in heterogeneous porous media. Audience: The contributions are intended to be as accessible as possible to a wide readership of academics and professionals with diverse backgrounds such as earth sciences, subsurface hydrology, petroleum engineering, and soil physics.
Author : Dean G. Boerrigter
Publisher :
ISBN 13 : 9781423563013
Total Pages : 136 pages
Book Rating : 4.5/5 (63 download)
Download or read book Parameter Estimation of the Mixed Generalized Gamma Distribution Using Maximum Likelihood Estimation and Minimum Distance Estimation written by Dean G. Boerrigter and published by . This book was released on 1998-03-01 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Generalized Gamma is an extremely flexible distribution that is useful for reliability modeling. Among its many special cases are the Weibull and Exponential distributions. A mixture of Generalized Gamma Distributions is even more useful because multiple causes of failure can he simultaneously modeled. This research studied parameter estimation of the special cases of the Mixed Generalized Gamma Distribution and built upon them until the full nine- parameter distribution was being estimated. First, special cases of a single Generalized Gamma Distribution were estimated. Next, mixtures of Exponential distributions with both known and unknown location parameters were estimated. Next, mixtures of Weibull distributions with both known and unknown location parameters were estimated. Lastly, the full nine- parameter Mixed Generalized Gamma Distribution was estimated. Two techniques were used to estimate the parameters of each distribution. The first technique used was the Method of Maximum Likelihood. The log likelihood equation was maximized using a Genetic Algorithm. The second technique used was the Method of Minimum Distance. This technique takes the Maximum Likelihood parameter estimate as initial estimate. With this initial estimate, the mixture and the first location parameter are sequentially varied to minimize the Anderson-Darling statistic between the estimated cumulative distribution function and the empirical distribution function. These two parameters are then fixed at their Minimum Distance values and the remaining parameters are re-estimated using Maximum Likelihood. Minimum Distance Estimation was demonstrated to improve the parameter estimates from Maximum Likelihood for almost all of the special case distributions tested.
