Decomposition and Invariance of Measures, and Statistical Transformation Models

Decomposition and Invariance of Measures, and Statistical Transformation Models PDF Author: Ole E Barndorff-Nielsen
Publisher: Springer Science & Business Media
ISBN: 1461236827
Category : Mathematics
Languages : en
Pages : 154

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Book Description

Decomposition and Invariance of Measures, and Statistical Transformation Models

Decomposition and Invariance of Measures, and Statistical Transformation Models PDF Author: Ole E Barndorff-Nielsen
Publisher: Springer Science & Business Media
ISBN: 1461236827
Category : Mathematics
Languages : en
Pages : 154

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Book Description


Invariant Measures on Groups and Their Use in Statistics

Invariant Measures on Groups and Their Use in Statistics PDF Author: Robert A. Wijsman
Publisher: IMS
ISBN: 9780940600195
Category : Mathematics
Languages : en
Pages : 264

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Book Description


Stochastic Models, Statistical Methods, and Algorithms in Image Analysis

Stochastic Models, Statistical Methods, and Algorithms in Image Analysis PDF Author: Piero Barone
Publisher: Springer Science & Business Media
ISBN: 1461229200
Category : Mathematics
Languages : en
Pages : 266

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Book Description
This volume comprises a collection of papers by world- renowned experts on image analysis. The papers range from survey articles to research papers, and from theoretical topics such as simulated annealing through to applied image reconstruction. It covers applications as diverse as biomedicine, astronomy, and geophysics. As a result, any researcher working on image analysis will find this book provides an up-to-date overview of the field and in addition, the extensive bibliographies will make this a useful reference.

Statistical Evaluation of Diagnostic Performance

Statistical Evaluation of Diagnostic Performance PDF Author: Kelly H. Zou
Publisher: CRC Press
ISBN: 1439812233
Category : Mathematics
Languages : en
Pages : 243

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Book Description
Statistical evaluation of diagnostic performance in general and Receiver Operating Characteristic (ROC) analysis in particular are important for assessing the performance of medical tests and statistical classifiers, as well as for evaluating predictive models or algorithms. This book presents innovative approaches in ROC analysis, which are releva

Model-Oriented Design of Experiments

Model-Oriented Design of Experiments PDF Author: Valerii V. Fedorov
Publisher: Springer Science & Business Media
ISBN: 9780387982151
Category : Mathematics
Languages : en
Pages : 136

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Book Description
Here, the authors explain the basic ideas so as to generate interest in modern problems of experimental design. The topics discussed include designs for inference based on nonlinear models, designs for models with random parameters and stochastic processes, designs for model discrimination and incorrectly specified (contaminated) models, as well as examples of designs in functional spaces. Since the authors avoid technical details, the book assumes only a moderate background in calculus, matrix algebra, and statistics. However, at many places, hints are given as to how readers may enhance and adopt the basic ideas for advanced problems or applications. This allows the book to be used for courses at different levels, as well as serving as a useful reference for graduate students and researchers in statistics and engineering.

A User's Guide to Measure Theoretic Probability

A User's Guide to Measure Theoretic Probability PDF Author: David Pollard
Publisher: Cambridge University Press
ISBN: 9780521002899
Category : Mathematics
Languages : en
Pages : 372

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Book Description
This book grew from a one-semester course offered for many years to a mixed audience of graduate and undergraduate students who have not had the luxury of taking a course in measure theory. The core of the book covers the basic topics of independence, conditioning, martingales, convergence in distribution, and Fourier transforms. In addition there are numerous sections treating topics traditionally thought of as more advanced, such as coupling and the KMT strong approximation, option pricing via the equivalent martingale measure, and the isoperimetric inequality for Gaussian processes. The book is not just a presentation of mathematical theory, but is also a discussion of why that theory takes its current form. It will be a secure starting point for anyone who needs to invoke rigorous probabilistic arguments and understand what they mean.

Optimum Designs for Multi-Factor Models

Optimum Designs for Multi-Factor Models PDF Author: Rainer Schwabe
Publisher: Springer Science & Business Media
ISBN: 1461240387
Category : Mathematics
Languages : en
Pages : 132

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Book Description
In real applications most experimental situations are influenced by a large number of different factors. In these settings the design of an experiment leads to challenging optimization problems, even if the underlying relationship can be described by a linear model. Based on recent research, this book introduces the theory of optimum designs for complex models and develops general methods of reduction to marginal problems for large classes of models with relevant interaction structures.

Latent Variable Modeling and Applications to Causality

Latent Variable Modeling and Applications to Causality PDF Author: Maia Berkane
Publisher: Springer Science & Business Media
ISBN: 146121842X
Category : Mathematics
Languages : en
Pages : 285

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Book Description
This volume gathers refereed papers presented at the 1994 UCLA conference on "La tent Variable Modeling and Application to Causality. " The meeting was organized by the UCLA Interdivisional Program in Statistics with the purpose of bringing together a group of people who have done recent advanced work in this field. The papers in this volume are representative of a wide variety of disciplines in which the use of latent variable models is rapidly growing. The volume is divided into two broad sections. The first section covers Path Models and Causal Reasoning and the papers are innovations from contributors in disciplines not traditionally associated with behavioural sciences, (e. g. computer science with Judea Pearl and public health with James Robins). Also in this section are contri butions by Rod McDonald and Michael Sobel who have a more traditional approach to causal inference, generating from problems in behavioural sciences. The second section encompasses new approaches to questions of model selection with emphasis on factor analysis and time varying systems. Amemiya uses nonlinear factor analysis which has a higher order of complexity associated with the identifiability condi tions. Muthen studies longitudinal hierarchichal models with latent variables and treats the time vector as a variable rather than a level of hierarchy. Deleeuw extends exploratory factor analysis models by including time as a variable and allowing for discrete and ordi nal latent variables. Arminger looks at autoregressive structures and Bock treats factor analysis models for categorical data.

Applications of Computer Aided Time Series Modeling

Applications of Computer Aided Time Series Modeling PDF Author: Masanao Aoki
Publisher: Springer Science & Business Media
ISBN: 1461222524
Category : Mathematics
Languages : en
Pages : 335

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Book Description
This book consists of three parts: Part One is composed of two introductory chapters. The first chapter provides an instrumental varible interpretation of the state space time series algorithm originally proposed by Aoki (1983), and gives an introductory account for incorporating exogenous signals in state space models. The second chapter, by Havenner, gives practical guidance in apply ing this algorithm by one of the most experienced practitioners of the method. Havenner begins by summarizing six reasons state space methods are advanta geous, and then walks the reader through construction and evaluation of a state space model for four monthly macroeconomic series: industrial production in dex, consumer price index, six month commercial paper rate, and money stock (Ml). To single out one of the several important insights in modeling that he shares with the reader, he discusses in Section 2ii the effects of sampling er rors and model misspecification on successful modeling efforts. He argues that model misspecification is an important amplifier of the effects of sampling error that may cause symplectic matrices to have complex unit roots, a theoretical impossibility. Correct model specifications increase efficiency of estimators and often eliminate this finite sample problem. This is an important insight into the positive realness of covariance matrices; positivity has been emphasized by system engineers to the exclusion of other methods of reducing sampling error and alleviating what is simply a finite sample problem. The second and third parts collect papers that describe specific applications.

Wavelets, Approximation, and Statistical Applications

Wavelets, Approximation, and Statistical Applications PDF Author: Wolfgang Härdle
Publisher: Springer Science & Business Media
ISBN: 1461222222
Category : Mathematics
Languages : en
Pages : 276

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Book Description
The mathematical theory of ondelettes (wavelets) was developed by Yves Meyer and many collaborators about 10 years ago. It was designed for ap proximation of possibly irregular functions and surfaces and was successfully applied in data compression, turbulence analysis, image and signal process ing. Five years ago wavelet theory progressively appeared to be a power ful framework for nonparametric statistical problems. Efficient computa tional implementations are beginning to surface in this second lustrum of the nineties. This book brings together these three main streams of wavelet theory. It presents the theory, discusses approximations and gives a variety of statistical applications. It is the aim of this text to introduce the novice in this field into the various aspects of wavelets. Wavelets require a highly interactive computing interface. We present therefore all applications with software code from an interactive statistical computing environment. Readers interested in theory and construction of wavelets will find here in a condensed form results that are somewhat scattered around in the research literature. A practioner will be able to use wavelets via the available software code. We hope therefore to address both theory and practice with this book and thus help to construct bridges between the different groups of scientists. This te. xt grew out of a French-German cooperation (Seminaire Paris Berlin, Seminar Berlin-Paris). This seminar brings together theoretical and applied statisticians from Berlin and Paris. This work originates in the first of these seminars organized in Garchy, Burgundy in 1994.