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Geometrical Foundations of Asymptotic Inference

: Basic properties of curved exponential families Elements of second-order, asymptotic theory The Fisher-Efron-Amari theory of information loss;

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Asymptotic Theory Of Quantum Statistical Inference

made remarkable progress since 1990. In particular, its asymptotic theory has been developed during this period. However, there has hitherto;

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Inference and Asymptotics

This book provides a systematic account of some developments in asymptotic parametric inference from a likelihood-based perspective. It;

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Theory of Shells

provides, without any recourse to any a priori assumptions of a geometrical or mechanical nature, a mathematical justification of two-dimensional;

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Methods for Estimation and Inference in Modern Econometrics

as generalized empirical likelihood estimation and alternative asymptotics under drifting parameterizations, which have not been discussed;

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Methods for Estimation and Inference in Modern Econometrics

as generalized empirical likelihood estimation and alternative asymptotics under drifting parameterizations, which have not been discussed;

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From Finite Sample To Asymptotic Methods In Statistics

justified by asymptotic arguments but are still based on the concepts and principles that underlie exact statistical inference. With this;

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Semimartingales and their Statistical Inference

modeling. Until now, however, researchers have had no single reference that collected the research conducted on the asymptotic theory for;

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Semimartingales and Their Statistical Inference

modeling. Until now, however, researchers have had no single reference that collected the research conducted on the asymptotic theory for;

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Exact Statistical Inference for Categorical Data

Exact Statistical Inference for Categorical Data discusses the way asymptotic approaches have been often used in practice to make;

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Inference for Functional Data with Applications

supported by a complete asymptotic theory. The book can be read at two levels. Readers interested primarily in methodology will find detailed;

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Nonparametric Statistical Methods And Related Topics

, linear model theory, Bayesian nonparametrics, change point problems, time series analysis and asymptotic theory.This volume presents state-of-the;

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Empirical Bayes and Likelihood Inference

Bayesian and such approaches to inference have a number of points of close contact, especially from an asymptotic point of view. Both;

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Simulation-based Inference in Econometrics

of problems and estimators, the asymptotic properties of these estimators, as well as descriptions of the different simulators in use. Second, the;

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Simulation-based Inference in Econometrics

of problems and estimators, the asymptotic properties of these estimators, as well as descriptions of the different simulators in use. Second, the;

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Foundations of Measurement Volume II: Geometrical, Threshold, and Probabilistic Representationsvolume 2

. Volume II extends the subject in the direction of geometrical, threshold, and probabilistic representations, and Volume III examines;

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Asymptotic Statistical Inference

The book presents the fundamental concepts from asymptotic statistical inference theory, elaborating on some basic large sample optimality;

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Asymptotic Statistical Inference

The book presents the fundamental concepts from asymptotic statistical inference theory, elaborating on some basic large sample optimality;

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Statistical Inference for Spatial Processes

pseudo-likelihood. Professor Ripley also stresses the importance of edge effects and of lack of a unique asymptotic setting in spatial problems;

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Inference, Asymptotics, and Applications

of the field of asymptotic theory and inference as it was being pushed forward during an exceptionally fruitful time. It provides students and;

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Asymptotic Statistics

This book is an introduction to the field of asymptotic statistics. The treatment is both practical and mathematically rigorous;

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Essential Statistical Inference

likelihood, Bayesian, and permutation inference; an introduction to basic asymptotic distribution theory; and modern topics like M-estimation, the;

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Mathematical Methods of Classical Mechanics

theory of oscillations and the Hamiltonian formalism. The author emphasizes geometrical considerations and includes phase spaces and flows;

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Mathematical Methods of Classical Mechanics

theory of oscillations and the Hamiltonian formalism. The author emphasizes geometrical considerations and includes phase spaces and flows;

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Mathematical Foundations of Infinite-Dimensional Statistical Models

This book develops the theory of statistical inference in statistical models with an infinite-dimens;...

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A Graduate Course on Statistical Inference

in statistical research. It draws from three main themes throughout: the finite-sample theory, the asymptotic theory, and Bayesian statistics. The;

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Nonlinear Econometric Modeling in Time Series Analysis

, consistency and asymptotic normality, asymptotic inference and error-correction models. With a world-class panel of contributors, this volume;

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