# Statistical Inference: The Minimum Distance Approach (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)

## Ayanendranath Basu; Hiroyuki Shioya; Chanseok Park

4 valoración promedio
( 1 valoraciones por Goodreads )

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Críticas:

"The book is an excellent and thorough outline of work in the area. It would provide an ideal volume for someone who plans to undertake research in the area."
International Statistical Review, 2013

"The book provides a comprehensive overview of the theory of density-based minimum distance methods and it is well written and easy to read and understand. The book is well suited for graduate students, professionals and researchers not only in statistics but also in biosciences, engineering and various other fields where statistical inference plays a fundamental role."
―Alex Karagrigoriou, Journal of Applied Statistics, 2012

Reseña del editor:

In many ways, estimation by an appropriate minimum distance method is one of the most natural ideas in statistics. However, there are many different ways of constructing an appropriate distance between the data and the model: the scope of study referred to by "Minimum Distance Estimation" is literally huge. Filling a statistical resource gap, Statistical Inference: The Minimum Distance Approach comprehensively overviews developments in density-based minimum distance inference for independently and identically distributed data. Extensions to other more complex models are also discussed.

Comprehensively covering the basics and applications of minimum distance inference, this book introduces and discusses:

• The estimation and hypothesis testing problems for both discrete and continuous models
• The robustness properties and the structural geometry of the minimum distance methods
• The inlier problem and its possible solutions, and the weighted likelihood estimation problem
• The extension of the minimum distance methodology in interdisciplinary areas, such as neural networks and fuzzy sets, as well as specialized models and problems, including semi-parametric problems, mixture models, grouped data problems, and survival analysis.

Statistical Inference: The Minimum Distance Approach gives a thorough account of density-based minimum distance methods and their use in statistical inference. It covers statistical distances, density-based minimum distance methods, discrete and continuous models, asymptotic distributions, robustness, computational issues, residual adjustment functions, graphical descriptions of robustness, penalized and combined distances, weighted likelihood, and multinomial goodness-of-fit tests. This carefully crafted resource is useful to researchers and scientists within and outside the statistics arena.

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## 1.Statistical Inference

Publicado por Chapman and Hall/CRC (2011)
ISBN 10: 1420099655 ISBN 13: 9781420099652
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Books2Anywhere
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Descripción Chapman and Hall/CRC, 2011. HRD. Condición: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Nº de ref. del artículo: F9-9781420099652

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## 2.Statistical Inference: The Minimum Distance Approach

ISBN 10: 1420099655 ISBN 13: 9781420099652
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Descripción 2011. HRD. Condición: New. New Book. Shipped from US within 10 to 14 business days. Established seller since 2000. Nº de ref. del artículo: VT-9781420099652

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## 3.Statistical Inference: The Minimum Distance Approach (Hardback)

Publicado por Taylor Francis Ltd, United States (2011)
ISBN 10: 1420099655 ISBN 13: 9781420099652
Nuevo Tapa dura Cantidad disponible: 1
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(London, Reino Unido)
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Descripción Taylor Francis Ltd, United States, 2011. Hardback. Condición: New. Language: English . Brand New Book. In many ways, estimation by an appropriate minimum distance method is one of the most natural ideas in statistics. However, there are many different ways of constructing an appropriate distance between the data and the model: the scope of study referred to by Minimum Distance Estimation is literally huge. Filling a statistical resource gap, Statistical Inference: The Minimum Distance Approach comprehensively overviews developments in density-based minimum distance inference for independently and identically distributed data. Extensions to other more complex models are also discussed. Comprehensively covering the basics and applications of minimum distance inference, this book introduces and discusses: * The estimation and hypothesis testing problems for both discrete and continuous models * The robustness properties and the structural geometry of the minimum distance methods * The inlier problem and its possible solutions, and the weighted likelihood estimation problem * The extension of the minimum distance methodology in interdisciplinary areas, such as neural networks and fuzzy sets, as well as specialized models and problems, including semi-parametric problems, mixture models, grouped data problems, and survival analysis. Statistical Inference: The Minimum Distance Approach gives a thorough account of density-based minimum distance methods and their use in statistical inference. It covers statistical distances, density-based minimum distance methods, discrete and continuous models, asymptotic distributions, robustness, computational issues, residual adjustment functions, graphical descriptions of robustness, penalized and combined distances, weighted likelihood, and multinomial goodness-of-fit tests. This carefully crafted resource is useful to researchers and scientists within and outside the statistics arena. Nº de ref. del artículo: AAC9781420099652

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## 4.Statistical Inference: The Minimum Distance Approach (Hardback)

Publicado por Taylor Francis Ltd, United States (2011)
ISBN 10: 1420099655 ISBN 13: 9781420099652
Nuevo Tapa dura Cantidad disponible: 1
Librería
The Book Depository
(London, Reino Unido)
Valoración

Descripción Taylor Francis Ltd, United States, 2011. Hardback. Condición: New. Language: English . Brand New Book. In many ways, estimation by an appropriate minimum distance method is one of the most natural ideas in statistics. However, there are many different ways of constructing an appropriate distance between the data and the model: the scope of study referred to by Minimum Distance Estimation is literally huge. Filling a statistical resource gap, Statistical Inference: The Minimum Distance Approach comprehensively overviews developments in density-based minimum distance inference for independently and identically distributed data. Extensions to other more complex models are also discussed. Comprehensively covering the basics and applications of minimum distance inference, this book introduces and discusses: * The estimation and hypothesis testing problems for both discrete and continuous models * The robustness properties and the structural geometry of the minimum distance methods * The inlier problem and its possible solutions, and the weighted likelihood estimation problem * The extension of the minimum distance methodology in interdisciplinary areas, such as neural networks and fuzzy sets, as well as specialized models and problems, including semi-parametric problems, mixture models, grouped data problems, and survival analysis. Statistical Inference: The Minimum Distance Approach gives a thorough account of density-based minimum distance methods and their use in statistical inference. It covers statistical distances, density-based minimum distance methods, discrete and continuous models, asymptotic distributions, robustness, computational issues, residual adjustment functions, graphical descriptions of robustness, penalized and combined distances, weighted likelihood, and multinomial goodness-of-fit tests. This carefully crafted resource is useful to researchers and scientists within and outside the statistics arena. Nº de ref. del artículo: AAC9781420099652

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## 5.Statistical Inference

Publicado por Chapman and Hall/CRC (2018)
ISBN 10: 1420099655 ISBN 13: 9781420099652
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Descripción Chapman and Hall/CRC, 2018. Hardback. Condición: NEW. 9781420099652 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Print on Demand title, produced to the highest standard, and there would be a delay in dispatch of around 10 working days. For all enquiries, please contact Herb Tandree Philosophy Books directly - customer service is our primary goal. Nº de ref. del artículo: HTANDREE0191704

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## 6.Statistical Inference: The Minimum Distance Approach (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)

Publicado por Chapman and Hall/CRC (2011)
ISBN 10: 1420099655 ISBN 13: 9781420099652
Nuevo Tapa dura Cantidad disponible: 1
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Descripción Chapman and Hall/CRC, 2011. Hardcover. Condición: New. 1. Nº de ref. del artículo: DADAX1420099655

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## 7.Statistical Inference: The Minimum Distance Approach (Hardback)

Publicado por Taylor Francis Ltd, United States (2011)
ISBN 10: 1420099655 ISBN 13: 9781420099652
Nuevo Tapa dura Cantidad disponible: 1
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Book Depository hard to find
(London, Reino Unido)
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Descripción Taylor Francis Ltd, United States, 2011. Hardback. Condición: New. Language: English . This book usually ship within 10-15 business days and we will endeavor to dispatch orders quicker than this where possible. Brand New Book. In many ways, estimation by an appropriate minimum distance method is one of the most natural ideas in statistics. However, there are many different ways of constructing an appropriate distance between the data and the model: the scope of study referred to by Minimum Distance Estimation is literally huge. Filling a statistical resource gap, Statistical Inference: The Minimum Distance Approach comprehensively overviews developments in density-based minimum distance inference for independently and identically distributed data. Extensions to other more complex models are also discussed. Comprehensively covering the basics and applications of minimum distance inference, this book introduces and discusses: * The estimation and hypothesis testing problems for both discrete and continuous models * The robustness properties and the structural geometry of the minimum distance methods * The inlier problem and its possible solutions, and the weighted likelihood estimation problem * The extension of the minimum distance methodology in interdisciplinary areas, such as neural networks and fuzzy sets, as well as specialized models and problems, including semi-parametric problems, mixture models, grouped data problems, and survival analysis. Statistical Inference: The Minimum Distance Approach gives a thorough account of density-based minimum distance methods and their use in statistical inference. It covers statistical distances, density-based minimum distance methods, discrete and continuous models, asymptotic distributions, robustness, computational issues, residual adjustment functions, graphical descriptions of robustness, penalized and combined distances, weighted likelihood, and multinomial goodness-of-fit tests. This carefully crafted resource is useful to researchers and scientists within and outside the statistics arena. Nº de ref. del artículo: BTE9781420099652

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## 8.Statistical Inference: The Minimum Distance Approach (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)

Publicado por Chapman and Hall/CRC (2011)
ISBN 10: 1420099655 ISBN 13: 9781420099652
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Descripción Chapman and Hall/CRC, 2011. Hardcover. Condición: New. Never used!. Nº de ref. del artículo: 1420099655

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## 9.Statistical Inference: The Minimum Distance Approach

Publicado por Chapman & Hall (2010)
ISBN 10: 1420099655 ISBN 13: 9781420099652
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Descripción Chapman & Hall, 2010. Hardcover. Condición: Brand New. 1st edition. 320 pages. 9.30x6.30x1.10 inches. In Stock. Nº de ref. del artículo: __1420099655

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## 10.Statistical Inference: The Minimum Distance Approach (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)

ISBN 10: 1420099655 ISBN 13: 9781420099652
Nuevo Tapa dura Cantidad disponible: 1
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Descripción Chapman and Hall/CRC. Condición: New. Hardcover. Worldwide shipping. FREE fast shipping inside USA (express 2-3 day delivery also available). Tracking service included. Ships from United States of America. Nº de ref. del artículo: 1420099655

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