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Introduction to Empirical Processes and Semiparametric Inference

Introduction to Empirical Processes and Semiparametric Inference
Author: Michael R. Kosorok
Publisher: Springer Science & Business Media
Total Pages: 482
Release: 2007-12-29
Genre: Mathematics
ISBN: 0387749780

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Kosorok’s brilliant text provides a self-contained introduction to empirical processes and semiparametric inference. These powerful research techniques are surprisingly useful for developing methods of statistical inference for complex models and in understanding the properties of such methods. This is an authoritative text that covers all the bases, and also a friendly and gradual introduction to the area. The book can be used as research reference and textbook.


Semiparametric Methods in Econometrics

Semiparametric Methods in Econometrics
Author: Joel L. Horowitz
Publisher: Springer Science & Business Media
Total Pages: 211
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461206219

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Many econometric models contain unknown functions as well as finite- dimensional parameters. Examples of such unknown functions are the distribution function of an unobserved random variable or a transformation of an observed variable. Econometric methods for estimating population parameters in the presence of unknown functions are called "semiparametric." During the past 15 years, much research has been carried out on semiparametric econometric models that are relevant to empirical economics. This book synthesizes the results that have been achieved for five important classes of models. The book is aimed at graduate students in econometrics and statistics as well as professionals who are not experts in semiparametic methods. The usefulness of the methods will be illustrated with applications that use real data.


Data

Data
Author: David F. Andrews
Publisher: Springer Science & Business Media
Total Pages: 463
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461250986

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Statistics provides tools and strategies for the analysis of data. While much has been written about the methodology, sometimes without reference to data, little has been said about the data. In this volume we present sets of data obtained from many situations without any direct reference to a particular type of analysis. Our view of the usefulness of bringing together a broad collection of sets of data has been shared by many friends and contributors. Students of statistics need to gain facility with their art by applying their knowledge to many sets of data. Textbook examples tend to be small and selected primarily to illustrate a particular technique, thus failing to demonstrate the questioning, iterative nature of statistical analysis. The situations which gave rise to the more extensive sets of data given in this volume are colourful and interesting, and can be readily understood by laymen, students and research workers with diverse interests. These sets were often chosen for their perverse reluctance to yield under the naive application of standard procedures. They do not have correct solutions. They describe situations where the statisti cian can develop skills and learn the limitations of statistical methods.


Principles and Theory for Data Mining and Machine Learning

Principles and Theory for Data Mining and Machine Learning
Author: Bertrand Clarke
Publisher: Springer Science & Business Media
Total Pages: 786
Release: 2009-07-21
Genre: Computers
ISBN: 0387981357

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Extensive treatment of the most up-to-date topics Provides the theory and concepts behind popular and emerging methods Range of topics drawn from Statistics, Computer Science, and Electrical Engineering


Introductory Lectures on Fluctuations of Lévy Processes with Applications

Introductory Lectures on Fluctuations of Lévy Processes with Applications
Author: Andreas E. Kyprianou
Publisher: Springer Science & Business Media
Total Pages: 382
Release: 2006-12-18
Genre: Mathematics
ISBN: 3540313435

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This textbook forms the basis of a graduate course on the theory and applications of Lévy processes, from the perspective of their path fluctuations. The book aims to be mathematically rigorous while still providing an intuitive feel for underlying principles. The results and applications often focus on the case of Lévy processes with jumps in only one direction, for which recent theoretical advances have yielded a higher degree of mathematical transparency and explicitness.


Semi-Markov Chains and Hidden Semi-Markov Models toward Applications

Semi-Markov Chains and Hidden Semi-Markov Models toward Applications
Author: Vlad Stefan Barbu
Publisher: Springer Science & Business Media
Total Pages: 233
Release: 2009-01-07
Genre: Mathematics
ISBN: 0387731733

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Here is a work that adds much to the sum of our knowledge in a key area of science today. It is concerned with the estimation of discrete-time semi-Markov and hidden semi-Markov processes. A unique feature of the book is the use of discrete time, especially useful in some specific applications where the time scale is intrinsically discrete. The models presented in the book are specifically adapted to reliability studies and DNA analysis. The book is mainly intended for applied probabilists and statisticians interested in semi-Markov chains theory, reliability and DNA analysis, and for theoretical oriented reliability and bioinformatics engineers.


Finite Mixture and Markov Switching Models

Finite Mixture and Markov Switching Models
Author: Sylvia Frühwirth-Schnatter
Publisher: Springer Science & Business Media
Total Pages: 506
Release: 2006-11-24
Genre: Mathematics
ISBN: 0387357688

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The past decade has seen powerful new computational tools for modeling which combine a Bayesian approach with recent Monte simulation techniques based on Markov chains. This book is the first to offer a systematic presentation of the Bayesian perspective of finite mixture modelling. The book is designed to show finite mixture and Markov switching models are formulated, what structures they imply on the data, their potential uses, and how they are estimated. Presenting its concepts informally without sacrificing mathematical correctness, it will serve a wide readership including statisticians as well as biologists, economists, engineers, financial and market researchers.


Statistical Inference for Spatial Poisson Processes

Statistical Inference for Spatial Poisson Processes
Author: Yu A. Kutoyants
Publisher: Springer Science & Business Media
Total Pages: 282
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461217067

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This work is devoted to several problems of parametric (mainly) and nonparametric estimation through the observation of Poisson processes defined on general spaces. Poisson processes are quite popular in applied research and therefore they attract the attention of many statisticians. There are a lot of good books on point processes and many of them contain chapters devoted to statistical inference for general and partic ular models of processes. There are even chapters on statistical estimation problems for inhomogeneous Poisson processes in asymptotic statements. Nevertheless it seems that the asymptotic theory of estimation for nonlinear models of Poisson processes needs some development. Here nonlinear means the models of inhomogeneous Pois son processes with intensity function nonlinearly depending on unknown parameters. In such situations the estimators usually cannot be written in exact form and are given as solutions of some equations. However the models can be quite fruitful in en gineering problems and the existing computing algorithms are sufficiently powerful to calculate these estimators. Therefore the properties of estimators can be interesting too.


Topics in Applied Statistics

Topics in Applied Statistics
Author: Mingxiu Hu
Publisher: Springer Science & Business Media
Total Pages: 340
Release: 2013-09-14
Genre: Medical
ISBN: 1461478464

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This volume presents 27 selected papers in topics that range from statistical applications in business and finance to applications in clinical trials and biomarker analysis. All papers feature original, peer-reviewed content. The editors intentionally selected papers that cover many topics so that the volume will serve the whole statistical community and a variety of research interests. The papers represent select contributions to the 21st ICSA Applied Statistics Symposium. The International Chinese Statistical Association (ICSA) Symposium took place between the 23rd and 26th of June, 2012 in Boston, Massachusetts. It was co-sponsored by the International Society for Biopharmaceutical Statistics (ISBS) and American Statistical Association (ASA). This is the inaugural proceedings volume to share research from the ICSA Applied Statistics Symposium.


Exponential Families of Stochastic Processes

Exponential Families of Stochastic Processes
Author: Uwe Küchler
Publisher: Springer Science & Business Media
Total Pages: 322
Release: 2006-05-09
Genre: Mathematics
ISBN: 0387227652

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A comprehensive account of the statistical theory of exponential families of stochastic processes. The book reviews the progress in the field made over the last ten years or so by the authors - two of the leading experts in the field - and several other researchers. The theory is applied to a broad spectrum of examples, covering a large number of frequently applied stochastic process models with discrete as well as continuous time. To make the reading even easier for statisticians with only a basic background in the theory of stochastic process, the first part of the book is based on classical theory of stochastic processes only, while stochastic calculus is used later. Most of the concepts and tools from stochastic calculus needed when working with inference for stochastic processes are introduced and explained without proof in an appendix. This appendix can also be used independently as an introduction to stochastic calculus for statisticians. Numerous exercises are also included.