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Author: Michael R. Kosorok
Publisher: Springer Science & Business Media
ISBN: 0387749780
Category : Mathematics
Languages : en
Pages : 482
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Book Description
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.
Author: Michael R. Kosorok
Publisher: Springer Science & Business Media
ISBN: 0387749780
Category : Mathematics
Languages : en
Pages : 482
Get Book Here
Book Description
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.
Author: Cram101 Textbook Reviews
Publisher: Academic Internet Pub Incorporated
ISBN: 9781617441158
Category : Education
Languages : en
Pages : 64
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Book Description
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 .
Author: David F. Andrews
Publisher: Springer Science & Business Media
ISBN: 1461250986
Category : Mathematics
Languages : en
Pages : 463
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Book Description
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.
Author: Masanobu Taniguchi
Publisher: Springer Science & Business Media
ISBN: 146121162X
Category : Mathematics
Languages : en
Pages : 671
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Book Description
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.
Author: Petar Todorovic
Publisher: Springer Science & Business Media
ISBN: 1461397421
Category : Mathematics
Languages : en
Pages : 302
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Book Description
This text on stochastic processes and their applications is based on a set of lectures given during the past several years at the University of California, Santa Barbara (UCSB). It is an introductory graduate course designed for classroom purposes. Its objective is to provide graduate students of statistics with an overview of some basic methods and techniques in the theory of stochastic processes. The only prerequisites are some rudiments of measure and integration theory and an intermediate course in probability theory. There are more than 50 examples and applications and 243 problems and complements which appear at the end of each chapter. The book consists of 10 chapters. Basic concepts and definitions are pro vided in Chapter 1. This chapter also contains a number of motivating ex amples and applications illustrating the practical use of the concepts. The last five sections are devoted to topics such as separability, continuity, and measurability of random processes, which are discussed in some detail. The concept of a simple point process on R+ is introduced in Chapter 2. Using the coupling inequality and Le Cam's lemma, it is shown that if its counting function is stochastically continuous and has independent increments, the point process is Poisson. When the counting function is Markovian, the sequence of arrival times is also a Markov process. Some related topics such as independent thinning and marked point processes are also discussed. In the final section, an application of these results to flood modeling is presented.
Author: Jian-Xin Pan
Publisher: Springer Science & Business Media
ISBN: 9780387950532
Category : Mathematics
Languages : en
Pages : 500
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Book Description
This book systematically introduces the theory of the GCM with particular emphasis on their multivariate statistical diagnostics, which are based mainly on recent developments made by the authors and their collaborators. Provided are complete proofs of theorems as well as practical data sets and MATLAB code.
Author: William J. Anderson
Publisher: Springer Science & Business Media
ISBN: 1461230381
Category : Mathematics
Languages : en
Pages : 367
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Book Description
Continuous time parameter Markov chains have been useful for modeling various random phenomena occurring in queueing theory, genetics, demography, epidemiology, and competing populations. This is the first book about those aspects of the theory of continuous time Markov chains which are useful in applications to such areas. It studies continuous time Markov chains through the transition function and corresponding q-matrix, rather than sample paths. An extensive discussion of birth and death processes, including the Stieltjes moment problem, and the Karlin-McGregor method of solution of the birth and death processes and multidimensional population processes is included, and there is an extensive bibliography. Virtually all of this material is appearing in book form for the first time.
Author: Karen C. Fuson
Publisher: Springer Science & Business Media
ISBN: 1461237548
Category : Psychology
Languages : en
Pages : 448
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Book Description
For some time now, the study of cognitive development has been far and away the most active discipline within developmental psychology. Although there would be much disagreement as to the exact proportion of papers published in developmental journals that could be considered cognitive, 50% seems like a conservative estimate. Hence, a series of scholary books to be devoted to work in cognitive development is especially appropriate at this time. The Springer Series in Cognitive Development contains two basic types of books, namely, edited collections of original chapters by several authors, and original volumes written by one author or a small group of authors. The flagship for the Springer Series is a serial publication of the "advances" type, carrying the subtitle Progress in Cognitive Development Research. Volumes in the Progress sequence are strongly thematic, in that each is limited to some well-defined domain of cognitive developmental research (e. g. , logical and mathematical development, semantic development). All Progress volumes are edited collections. Editors of such books, upon consultation with the Series Editor, may elect to have their works published either as contributions to the Progress sequence or as separate volumes. All books written by one author or a small group of authors will be published as separate volumes within the series. is being used in the selec A fairly broad definition of cognitive development tion of books for this series.
Author: Rolf-Dieter Reiss
Publisher: Springer Science & Business Media
ISBN: 1461396204
Category : Mathematics
Languages : en
Pages : 363
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Book Description
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.
Author: Alexander Meister
Publisher: Springer Science & Business Media
ISBN: 3540875573
Category : Mathematics
Languages : en
Pages : 211
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Book Description
Deconvolution problems occur in many ?elds of nonparametric statistics, for example, density estimation based on contaminated data, nonparametric - gression with errors-in-variables, image and signal deblurring. During the last two decades, those topics have received more and more attention. As appli- tions of deconvolution procedures concern many real-life problems in eco- metrics, biometrics, medical statistics, image reconstruction, one can realize an increasing number of applied statisticians who are interested in nonpa- metric deconvolution methods; on the other hand, some deep results from Fourier analysis, functional analysis, and probability theory are required to understand the construction of deconvolution techniques and their properties so that deconvolution is also particularly challenging for mathematicians. Thegeneraldeconvolutionprobleminstatisticscanbedescribedasfollows: Our goal is estimating a function f while any empirical access is restricted to some quantity h = f?G = f(x?y)dG(y), (1. 1) that is, the convolution of f and some probability distribution G. Therefore, f can be estimated from some observations only indirectly. The strategy is ˆ estimating h ?rst; this means producing an empirical version h of h and, then, ˆ applying a deconvolution procedure to h to estimate f. In the mathematical context, we have to invert the convolution operator with G where some reg- ˆ ularization is required to guarantee that h is contained in the invertibility ˆ domain of the convolution operator. The estimator h has to be chosen with respect to the speci?c statistical experiment.
