Adelchi Azzalini's Books

Statistical Inference Based on the likelihood

By: Adelchi Azzalini

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Statistical Inference Based on the likelihood

By: Adelchi Azzalini

The Likelihood plays a key role in both introducing general notions of statistical theory, and in developing specific methods. This book introduces likelihood-based statistical theory and related methods from a classical viewpoint, and demonstrates how the main body of currently used statistical techniques can be generated from a few key concepts, in particular the likelihood. Focusing on those methods, which have both a solid theoretical background and practical relevance, the author gives formal justification of the methods used and provides numerical examples with real data.

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Page Count

356

Publisher

Routledge

Published Date

ISBN 10

1351414461

ISBN 13

9781351414463

Data Analysis and Data Mining

An Introduction

By: Adelchi Azzalini,Bruno Scarpa

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Data Analysis and Data Mining

An Introduction

By: Adelchi Azzalini,Bruno Scarpa

An introduction to statistical data mining, Data Analysis and Data Mining is both textbook and professional resource. Assuming only a basic knowledge of statistical reasoning, it presents core concepts in data mining and exploratory statistical models to students and professional statisticians-both those working in communications and those working in a technological or scientific capacity-who have a limited knowledge of data mining. This book presents key statistical concepts by way of case studies, giving readers the benefit of learning from real problems and real data. Aided by a diverse range of statistical methods and techniques, readers will move from simple problems to complex problems. Through these case studies, authors Adelchi Azzalini and Bruno Scarpa explain exactly how statistical methods work; rather than relying on the "push the button" philosophy, they demonstrate how to use statistical tools to find the best solution to any given problem. Case studies feature current topics highly relevant to data mining, such web page traffic; the segmentation of customers; selection of customers for direct mail commercial campaigns; fraud detection; and measurements of customer satisfaction. Appropriate for both advanced undergraduate and graduate students, this much-needed book will fill a gap between higher level books, which emphasize technical explanations, and lower level books, which assume no prior knowledge and do not explain the methodology behind the statistical operations.

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Page Count

289

Publisher

Oxford University Press

Published Date

ISBN 10

0199909288

ISBN 13

9780199909285

Applied Smoothing Techniques for Data Analysis

The Kernel Approach with S-Plus Illustrations

By: Adrian W. Bowman,Adelchi Azzalini

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Applied Smoothing Techniques for Data Analysis

The Kernel Approach with S-Plus Illustrations

By: Adrian W. Bowman,Adelchi Azzalini

The book describes the use of smoothing techniques in statistics, including both density estimation and nonparametric regression. Considerable advances in research in this area have been made in recent years. The aim of this text is to describe a variety of ways in which these methods can be applied to practical problems in statistics. The role of smoothing techniques in exploring data graphically is emphasised, but the use of nonparametric curves in drawing conclusions from data, as an extension of more standard parametric models, is also a major focus of the book. Examples are drawn from a wide range of applications. The book is intended for those who seek an introduction to the area, with an emphasis on applications rather than on detailed theory. It is therefore expected that the book will benefit those attending courses at an advanced undergraduate, or postgraduate, level, as well as researchers, both from statistics and from other disciplines, who wish to learn about and apply these techniques in practical data analysis. The text makes extensive reference to S-Plus, as a computing environment in which examples can be explored. S-Plus functions and example scripts are provided to implement many of the techniques described. These parts are, however, clearly separate from the main body of text, and can therefore easily be skipped by readers not interested in S-Plus.

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Page Count

205

Publisher

OUP Oxford

Published Date

ISBN 10

0191545694

ISBN 13

9780191545696

The Skew-Normal and Related Families

By: Adelchi Azzalini,Antonella Capitanio

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The Skew-Normal and Related Families

By: Adelchi Azzalini,Antonella Capitanio

The standard resource for statisticians and applied researchers. Accessible to the wide range of researchers who use statistical modelling techniques.

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Page Count

271

Publisher

Cambridge University Press

Published Date

ISBN 10

1107029279

ISBN 13

9781107029279

Applied Smoothing Techniques for Data Analysis

The Kernel Approach with S-Plus Illustrations

By: Adrian W. Bowman,Adelchi Azzalini

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Applied Smoothing Techniques for Data Analysis

The Kernel Approach with S-Plus Illustrations

By: Adrian W. Bowman,Adelchi Azzalini

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Solve jigsaw puzzle

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Page Count

205

Publisher

OUP Oxford

Published Date

ISBN 10

0191545694

ISBN 13

9780191545696

Statistical Inference Based on the likelihood

By: Adelchi Azzalini

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Statistical Inference Based on the likelihood

By: Adelchi Azzalini

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Page Count

356

Publisher

Routledge

Published Date

ISBN 10

1351414461

ISBN 13

9781351414463

Data Analysis and Data Mining

An Introduction

By: Adelchi Azzalini,Bruno Scarpa

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Data Analysis and Data Mining

An Introduction

By: Adelchi Azzalini,Bruno Scarpa

This book introduces the specific statistical methods and models involved in data mining, targeting students and professionals with a a basic knowledge of statistical reasoning.

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Page Count

289

Publisher

OUP USA

Published Date

ISBN 10

0199767106

ISBN 13

9780199767106

Book's by Adelchi Azzalini

Statistical Inference Based on the likelihood

Statistical Inference Based on the likelihood

Data Analysis and Data Mining

Data Analysis and Data Mining

Applied Smoothing Techniques for Data Analysis

Applied Smoothing Techniques for Data Analysis

The Skew-Normal and Related Families

The Skew-Normal and Related Families

Applied Smoothing Techniques for Data Analysis

Applied Smoothing Techniques for Data Analysis

Statistical Inference Based on the likelihood

Statistical Inference Based on the likelihood

Data Analysis and Data Mining

Data Analysis and Data Mining

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