Dissertation Abstracts International PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Dissertation Abstracts International PDF full book. Access full book title Dissertation Abstracts International by . Download full books in PDF and EPUB format.
Author:
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 946
Get Book Here
Book Description
Author:
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 946
Get Book Here
Book Description
Author: Wolfgang Karl Härdle
Publisher: Springer Science & Business Media
ISBN: 364217146X
Category : Mathematics
Languages : en
Pages : 317
Get Book Here
Book Description
The statistical and mathematical principles of smoothing with a focus on applicable techniques are presented in this book. It naturally splits into two parts: The first part is intended for undergraduate students majoring in mathematics, statistics, econometrics or biometrics whereas the second part is intended to be used by master and PhD students or researchers. The material is easy to accomplish since the e-book character of the text gives a maximum of flexibility in learning (and teaching) intensity.
Author: Vijay Nair
Publisher: World Scientific
ISBN: 9812708294
Category : Mathematics
Languages : en
Pages : 698
Get Book Here
Book Description
There have been major developments in the field of statistics over the last quarter century, spurred by the rapid advances in computing and data-measurement technologies. These developments have revolutionized the field and have greatly influenced research directions in theory and methodology. Increased computing power has spawned entirely new areas of research in computationally-intensive methods, allowing us to move away from narrowly applicable parametric techniques based on restrictive assumptions to much more flexible and realistic models and methods. These computational advances have also led to the extensive use of simulation and Monte Carlo techniques in statistical inference. All of these developments have, in turn, stimulated new research in theoretical statistics. This volume provides an up-to-date overview of recent advances in statistical modeling and inference. Written by renowned researchers from across the world, it discusses flexible models, semi-parametric methods and transformation models, nonparametric regression and mixture models, survival and reliability analysis, and re-sampling techniques. With its coverage of methodology and theory as well as applications, the book is an essential reference for researchers, graduate students, and practitioners.
Author:
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 750
Get Book Here
Book Description
Author: P. Groeneboom
Publisher: Springer Science & Business Media
ISBN: 9783764327941
Category : Mathematics
Languages : en
Pages : 140
Get Book Here
Book Description
This book contains the lecture notes for a DMV course presented by the authors at Gunzburg, Germany, in September, 1990. In the course we sketched the theory of information bounds for non parametric and semiparametric models, and developed the theory of non parametric maximum likelihood estimation in several particular inverse problems: interval censoring and deconvolution models. Part I, based on Jon Wellner's lectures, gives a brief sketch of information lower bound theory: Hajek's convolution theorem and extensions, useful minimax bounds for parametric problems due to Ibragimov and Has'minskii, and a recent result characterizing differentiable functionals due to van der Vaart (1991). The differentiability theorem is illustrated with the examples of interval censoring and deconvolution (which are pursued from the estimation perspective in part II). The differentiability theorem gives a way of clearly distinguishing situations in which 1 2 the parameter of interest can be estimated at rate n / and situations in which this is not the case. However it says nothing about which rates to expect when the functional is not differentiable. Even the casual reader will notice that several models are introduced, but not pursued in any detail; many problems remain. Part II, based on Piet Groeneboom's lectures, focuses on non parametric maximum likelihood estimates (NPMLE's) for certain inverse problems. The first chapter deals with the interval censoring problem.
Author: Michael G. Schimek
Publisher: John Wiley & Sons
ISBN: 1118763300
Category : Mathematics
Languages : en
Pages : 682
Get Book Here
Book Description
A comprehensive introduction to a wide variety of univariate and multivariate smoothing techniques for regression Smoothing and Regression: Approaches, Computation, and Application bridges the many gaps that exist among competing univariate and multivariate smoothing techniques. It introduces, describes, and in some cases compares a large number of the latest and most advanced techniques for regression modeling. Unlike many other volumes on this topic, which are highly technical and specialized, this book discusses all methods in light of both computational efficiency and their applicability for real data analysis. Using examples of applications from the biosciences, environmental sciences, engineering, and economics, as well as medical research and marketing, this volume addresses the theory, computation, and application of each approach. A number of the techniques discussed, such as smoothing under shape restrictions or of dependent data, are presented for the first time in book form. Special features of this book include: * Comprehensive coverage of smoothing and regression with software hints and applications from a wide variety of disciplines * A unified, easy-to-follow format * Contributions from more than 25 leading researchers from around the world * More than 150 illustrations also covering new graphical techniques important for exploratory data analysis and visualization of high-dimensional problems * Extensive end-of-chapter references For professionals and aspiring professionals in statistics, applied mathematics, computer science, and econometrics, as well as for researchers in the applied and social sciences, Smoothing and Regression is a unique and important new resource destined to become one the most frequently consulted references in the field.
Author: Hengqing Tong
Publisher: John Wiley & Sons
ISBN: 0470681772
Category : Business & Economics
Languages : en
Pages : 489
Get Book Here
Book Description
Statistical Theories and Methods with Applications to Economics and Business highlights recent advances in statistical theory and methods that benefit econometric practice. It deals with exploratory data analysis, a prerequisite to statistical modelling and part of data mining. It provides recently developed computational tools useful for data mining, analysing the reasons to do data mining and the best techniques to use in a given situation. Provides a detailed description of computer algorithms. Provides recently developed computational tools useful for data mining Highlights recent advances in statistical theory and methods that benefit econometric practice. Features examples with real life data. Accompanying software featuring DASC (Data Analysis and Statistical Computing). Essential reading for practitioners in any area of econometrics; business analysts involved in economics and management; and Graduate students and researchers in economics and statistics.
Author: Joel L. Horowitz
Publisher: Springer Science & Business Media
ISBN: 0387928707
Category : Business & Economics
Languages : en
Pages : 278
Get Book Here
Book Description
Standard methods for estimating empirical models in economics and many other fields rely on strong assumptions about functional forms and the distributions of unobserved random variables. Often, it is assumed that functions of interest are linear or that unobserved random variables are normally distributed. Such assumptions simplify estimation and statistical inference but are rarely justified by economic theory or other a priori considerations. Inference based on convenient but incorrect assumptions about functional forms and distributions can be highly misleading. Nonparametric and semiparametric statistical methods provide a way to reduce the strength of the assumptions required for estimation and inference, thereby reducing the opportunities for obtaining misleading results. These methods are applicable to a wide variety of estimation problems in empirical economics and other fields, and they are being used in applied research with increasing frequency. The literature on nonparametric and semiparametric estimation is large and highly technical. This book presents the main ideas underlying a variety of nonparametric and semiparametric methods. It is accessible to graduate students and applied researchers who are familiar with econometric and statistical theory at the level taught in graduate-level courses in leading universities. The book emphasizes ideas instead of technical details and provides as intuitive an exposition as possible. Empirical examples illustrate the methods that are presented. This book updates and greatly expands the author’s previous book on semiparametric methods in econometrics. Nearly half of the material is new.
Author: Anatoly Lisnianski
Publisher: Springer Science & Business Media
ISBN: 1447122070
Category : Technology & Engineering
Languages : en
Pages : 323
Get Book Here
Book Description
Recent Advances in System Reliability discusses developments in modern reliability theory such as signatures, multi-state systems and statistical inference. It describes the latest achievements in these fields, and covers the application of these achievements to reliability engineering practice. The chapters cover a wide range of new theoretical subjects and have been written by leading experts in reliability theory and its applications. The topics include: concepts and different definitions of signatures (D-spectra), their properties and applications to reliability of coherent systems and network-type structures; Lz-transform of Markov stochastic process and its application to multi-state system reliability analysis; methods for cost-reliability and cost-availability analysis of multi-state systems; optimal replacement and protection strategy; and statistical inference. Recent Advances in System Reliability presents many examples to illustrate the theoretical results. Real world multi-state systems, such as power generation and transmission, refrigeration, and production systems, are considered in the form of case studies, making the book a useful resource for researchers and postgraduate students.
Author:
Publisher:
ISBN:
Category : Dissertation abstracts
Languages : en
Pages : 776
Get Book Here
Book Description
