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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.


Outlines and Highlights for Introduction to Empirical Processes and Semiparametric Inference by Michael R Kosorok, Isbn

Outlines and Highlights for Introduction to Empirical Processes and Semiparametric Inference by Michael R Kosorok, Isbn
Author: Cram101 Textbook Reviews
Publisher: Academic Internet Pub Incorporated
Total Pages: 64
Release: 2010-12
Genre: Education
ISBN: 9781617441158

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Never HIGHLIGHT a Book Again! Virtually all of the testable terms, concepts, persons, places, and events from the textbook are included. Cram101 Just the FACTS101 studyguides give all of the outlines, highlights, notes, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanys: 9780387749778 .


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.


Life Distributions

Life Distributions
Author: Albert W. Marshall
Publisher: Springer Science & Business Media
Total Pages: 785
Release: 2007-10-13
Genre: Technology & Engineering
ISBN: 0387684778

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This book is devoted to the study of univariate distributions appropriate for the analyses of data known to be nonnegative. The book includes much material from reliability theory in engineering and survival analysis in medicine.


Proceedings of the Second Seattle Symposium in Biostatistics

Proceedings of the Second Seattle Symposium in Biostatistics
Author: Danyu Lin
Publisher: Springer Science & Business Media
Total Pages: 332
Release: 2012-12-06
Genre: Medical
ISBN: 1441990763

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This volume contains a selection of papers presented at the Second Seattle Symposium in Biostatistics: Analysis of Correlated Data. The symposium was held in 2000 to celebrate the 30th anniversary of the University of Washington School of Public Health and Community Medicine. It featured keynote lectures by Norman Breslow, David Cox and Ross Prentice and 16 invited presentations by other prominent researchers. The papers contained in this volume encompass recent methodological advances in several important areas, such as longitudinal data, multivariate failure time data and genetic data, as well as innovative applications of the existing theory and methods. This volume is a valuable reference for researchers and practitioners in the field of correlated data analysis.


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.


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.


Asymptotic Theory of Statistical Inference for Time Series

Asymptotic Theory of Statistical Inference for Time Series
Author: Masanobu Taniguchi
Publisher: Springer Science & Business Media
Total Pages: 671
Release: 2012-12-06
Genre: Mathematics
ISBN: 146121162X

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The primary aim of this book is to provide modern statistical techniques and theory for stochastic processes. The stochastic processes mentioned here are not restricted to the usual AR, MA, and ARMA processes. A wide variety of stochastic processes, including non-Gaussian linear processes, long-memory processes, nonlinear processes, non-ergodic processes and diffusion processes are described. The authors discuss estimation and testing theory and many other relevant statistical methods and techniques.


Introduction to Nonparametric Estimation

Introduction to Nonparametric Estimation
Author: Alexandre B. Tsybakov
Publisher: Springer Science & Business Media
Total Pages: 222
Release: 2008-10-22
Genre: Mathematics
ISBN: 0387790527

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Developed from lecture notes and ready to be used for a course on the graduate level, this concise text aims to introduce the fundamental concepts of nonparametric estimation theory while maintaining the exposition suitable for a first approach in the field.


Approximate Distributions of Order Statistics

Approximate Distributions of Order Statistics
Author: Rolf-Dieter Reiss
Publisher: Springer Science & Business Media
Total Pages: 363
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461396204

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This book is designed as a unified and mathematically rigorous treatment of some recent developments of the asymptotic distribution theory of order statistics (including the extreme order statistics) that are relevant for statistical theory and its applications. Particular emphasis is placed on results concern ing the accuracy oflimit theorems, on higher order approximations, and other approximations in quite a general sense. Contrary to the classical limit theorems that primarily concern the weak convergence of distribution functions, our main results will be formulated in terms of the variational and the Hellinger distance. These results will form the proper springboard for the investigation of parametric approximations of nonparametric models of joint distributions of order statistics. The approxi mating models include normal as well as extreme value models. Several applications will show the usefulness of this approach. Other recent developments in statistics like nonparametric curve estima tion and the bootstrap method will be studied as far as order statistics are concerned. 1n connection with this, graphical methods will, to some extent, be explored.