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A Course in Mathematical Statistics and Large Sample Theory (Springer Texts in Statistics) - Tapa dura

Libro 76 de 103: Springer Texts in Statistics

Bhattacharya, Rabi; Lin, Lizhen; Patrangenaru, Victor

 
9781493940301: A Course in Mathematical Statistics and Large Sample Theory (Springer Texts in Statistics)
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ISBN 10: 1493940309 ISBN 13: 9781493940301
Editorial: Springer-Verlag GmbH, 2016

Sinopsis

This graduate-level textbook is primarily aimed at graduate students of statistics, mathematics, science, and engineering who have had an undergraduate course in statistics, an upper division course in analysis, and some acquaintance with measure theoretic probability. It provides a rigorous presentation of the core of mathematical statistics.
Part I of this book constitutes a one-semester course on basic parametric mathematical statistics. Part II deals with the large sample theory of statistics - parametric and nonparametric, and its contents may be covered in one semester as well. Part III provides brief accounts of a number of topics of current interest for practitioners and other disciplines whose work involves statistical methods.

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Acerca del autor

Rabi Bhattacharya, PhD, has held regular faculty positions at UC, Berkeley; Indiana University; and the University of Arizona.  He is a Fellow of the Institute of Mathematical Statistics and a recipient of the U.S. Senior Scientist Humboldt Award and of a Guggenheim Fellowship.  He has served on editorial boards of many international journals and has published several research monographs and graduate texts on probability and statistics, including Nonparametric Inference on Manifolds, co-authored with A. Bhattacharya.

Lizhen Lin, PhD, is Assistant Professor in the Department of Statistics and Data Science at the University of Texas at Austin.  She received a PhD in Mathematics from the University of Arizona and was a Postdoctoral Associate at Duke University.  Bayesian nonparametrics, shape constrained inference, and nonparametric inference on manifolds are among her areas of expertise. 

Vic Patrangenaru, PhD, is Professor of Statistics at Florida State University.  He received PhDs in Mathematics from Haifa, Israel, and from Indiana University in the fields of differential geometry and statistics, respectively.  He has many research publications on Riemannian geometry and especially on statistics on manifolds.  He is a co-author with L. Ellingson of Nonparametric Statistics on Manifolds and Their Applications to Object Data Analysis. 

De la contraportada

This graduate-level textbook is primarily aimed at graduate students of statistics, mathematics, science, and engineering who have had an undergraduate course in statistics, an upper division course in analysis, and some acquaintance with measure theoretic probability. It provides a rigorous presentation of the core of mathematical statistics.


Part I of this book constitutes a one-semester course on basic parametric mathematical statistics. Part II deals with the large sample theory of statistics parametric and nonparametric, and its contents may be covered in one semester as well. Part III provides brief accounts of a number of topics of current interest for practitioners and other disciplines whose work involves statistical methods.
  • Large Sample theory with many worked examples, numerical calculations, and simulations to illustrate theory
  • Appendices provide ready access to a number of standard results, with many proofs
  • Solutions given to a number of selected exercises from Part I
  • Part II exercises with a certain level of difficulty appear with detailed hints
Rabi Bhattacharya, PhD,has held regular faculty positions at UC, Berkeley; Indiana University; and the University of Arizona. He is a Fellow of the Institute of Mathematical Statistics and a recipient of the U.S. Senior Scientist Humboldt Award and of a Guggenheim Fellowship. He has served on editorial boards of many international journals and has published several research monographs and graduate texts on probability and statistics, including Nonparametric Inference on Manifolds, co-authored with A. Bhattacharya.

Lizhen Lin, PhD, is Assistant Professor in the Department of Statistics and Data Science at the University of Texas at Austin. She received a PhD in Mathematics from the University of Arizona and was a Postdoctoral Associate at Duke University. Bayesian nonparametrics, shape constrained inference, and nonparametric inference on manifolds are among her areas of expertise.

Vic Patrangenaru, PhD, is Professor of Statistics at Florida State University. He received PhDs in Mathematics from Haifa, Israel, and from Indiana University in the fields of differential geometry and statistics, respectively. He has many research publications on Riemannian geometry and especially on statistics on manifolds. He is a co-author with L. Ellingson of Nonparametric Statistics on Manifolds and Their Applications to Object Data Analysis. 

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Editorial
Springer-Verlag GmbH
Año de publicación
2016
Idioma
Inglés
ISBN 10 
1493940309
ISBN 13 
9781493940301
Encuadernación
Tapa dura
Número de edición
1
Número de páginas
400
Contacto del fabricante
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