Description

Book Synopsis
There have been major developments in the field of statistics over the last quarter century, spurred by the rapid advances in computing and data-measurement technologies. These developments have revolutionized the field and have greatly influenced research directions in theory and methodology. Increased computing power has spawned entirely new areas of research in computationally-intensive methods, allowing us to move away from narrowly applicable parametric techniques based on restrictive assumptions to much more flexible and realistic models and methods. These computational advances have also led to the extensive use of simulation and Monte Carlo techniques in statistical inference. All of these developments have, in turn, stimulated new research in theoretical statistics.This volume provides an up-to-date overview of recent advances in statistical modeling and inference. Written by renowned researchers from across the world, it discusses flexible models, semi-parametric methods and transformation models, nonparametric regression and mixture models, survival and reliability analysis, and re-sampling techniques. With its coverage of methodology and theory as well as applications, the book is an essential reference for researchers, graduate students, and practitioners.

Table of Contents
Statistics and Soccer; Survival Analysis; Reliability Techniques; Semiparametric Methods; Transformation Models; Nonparametric Regression; Clustering and Mixture Models; Bayesian Nonparametric Inference; Rank-Based Methods; Monte Carlo and Resampling Methods; Constrained Inference.

Advances In Statistical Modeling And Inference:

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A Hardback by Vijay Nair

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    View other formats and editions of Advances In Statistical Modeling And Inference: by Vijay Nair

    Publisher: World Scientific Publishing Co Pte Ltd
    Publication Date: 16/03/2007
    ISBN13: 9789812703699, 978-9812703699
    ISBN10: 9812703691

    Description

    Book Synopsis
    There have been major developments in the field of statistics over the last quarter century, spurred by the rapid advances in computing and data-measurement technologies. These developments have revolutionized the field and have greatly influenced research directions in theory and methodology. Increased computing power has spawned entirely new areas of research in computationally-intensive methods, allowing us to move away from narrowly applicable parametric techniques based on restrictive assumptions to much more flexible and realistic models and methods. These computational advances have also led to the extensive use of simulation and Monte Carlo techniques in statistical inference. All of these developments have, in turn, stimulated new research in theoretical statistics.This volume provides an up-to-date overview of recent advances in statistical modeling and inference. Written by renowned researchers from across the world, it discusses flexible models, semi-parametric methods and transformation models, nonparametric regression and mixture models, survival and reliability analysis, and re-sampling techniques. With its coverage of methodology and theory as well as applications, the book is an essential reference for researchers, graduate students, and practitioners.

    Table of Contents
    Statistics and Soccer; Survival Analysis; Reliability Techniques; Semiparametric Methods; Transformation Models; Nonparametric Regression; Clustering and Mixture Models; Bayesian Nonparametric Inference; Rank-Based Methods; Monte Carlo and Resampling Methods; Constrained Inference.

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