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Probability for Statistics and Machine Learning - Fundamentals and Advanced Topics_Anirban DasGupta(Springer 2011 803s).pdf

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Probability for Statistics and Machine Learning - Fundamentals and Advanced Topics_Anirban DasGupta(Springer 2011 803s).pdf

文档介绍

文档介绍:Springer Texts in Statistics
Series Editors:
G. Casella
S. Fienberg
I. Olkin
For further volumes:
ies/417
Anirban DasGupta
Probability for Statistics
and Machine Learning
Fundamentals and Advanced Topics
ABC
Anirban DasGupta
Department of Statistics
Purdue University
150 N. University Street
West Lafayette, IN 47907, USA
******@
MathematicaR is a registered trademark of Wolfram Research, Inc.
ISBN 978-1-4419-9633-6 e-ISBN 978-1-4419-9634-3
DOI -1-4419-9634-3
Springer New York Dordrecht Heidelberg London
Library of Congress Control Number: 2011924777
c Springer Science+Business Media, LLC 2011
All rights reserved. This work may not be translated or copied in whole or in part without the written
permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York,
NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in
connection with any form of information storage and retrieval, electronic adaptation, computer software,
or by similar or dissimilar methodology now known or hereafter developed is forbidden.
The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are
not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject
to proprietary rights.
Printed on acid-free paper
Springer is part of Springer Science+Business Media ()
To Persi Diaconis, Peter Hall, Ashok Maitra,
and my mother, with affection
Preface
This is panion second volume to my undergraduate text Fundamentals of
Probability: A First Course. The purpose of my writing this book is to give gradu-
ate students, instructors, and researchers in statistics, mathematics, puter
science a lucidly written unique text at the confluence of probability, advanced
stochastic processes, statistics, and key tools for machine learning. Numerous top-
ics in probability and stochastic process

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