[下载]经典probability series系列丛书

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初级系列，适合本科

Fundamental Probability: A Computational Approach (Hardcover)~ Marc Paolella (Author)


Amazon link
http://www.amazon.com/Fundamental-Probability-Computational-Marc-Paolella/dp/0470025948/ref=sr_1_2?ie=UTF8&s=books&qid=1259889430&sr=8-2




Editorial Reviews        Review    "The collection is sure to be a set of remarkable references for students and teachers alike." (The American Statistician, May 2008)        "Very enjoyable and instructive reading." (CHOICE, November 2006)   
    "...a very good book which might, I hope, be standard for introductory courses in probability theory during next years." (Zentralbatt MATH, 11th March 2007)      

  


      Product Description    Probabilityis a vital measure in numerous disciplines, from bioinformatics andeconometrics to finance/insurance and computer science. Developed froma successful course, Fundamental Probability provides anengaging and hands-on introduction to this important topic. Whilst thetheory is explored in detail, this book also emphasises practicalapplications, with the presentation of a large variety of examples andexercises, along with generous use of computational tools.  Basedon international teaching experience with students of statistics,mathematics, finance and econometrics, the book:

• Presents new, innovative material alongside the classic theory.
• Goesbeyond standard presentations by carefully introducing and discussingmore complex subject matter, including a richer use of combinatorics,runs and occupancy distributions, various multivariate samplingschemes, fat-tailed distributions, and several basic concepts used infinance.
• Emphasises computational matters and programming methods via generous use of examples in MATLAB.
• Includesa large, self-contained Calculus/Analysis appendix with derivations ofall required tools, such as Leibniz’ rule, exchange of derivative andintegral, Fubini’s theorem, and univariate and multivariate Taylorseries.
• Presents over 150 end-of-chapter exercises, graded interms of their difficulty, and accompanied by a full set of solutionsonline.

     This book is intended as an introduction tothe theory of probability for students in biology, mathematics,statistics, economics, engineering, finance, and computer science whopossess the prerequisite knowledge of basic calculus and linearalgebra.

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关键词：Probability bability Ability Series Serie 下载 经典 Probability 丛书 Series

中级系列，高年级本科和硕士

Intermediate Probability: A Computational Approach (Hardcover)
Author: Marc Paolella,

Amazon link,
http://www.amazon.com/Intermediate-Probability-Computational-Marc-Paolella/dp/0470026375/ref=sr_1_1?ie=UTF8&s=books&qid=1259889430&sr=8-1



Editorial Reviews        Review    "The reader-friendly style of the text itself would make the book appropriate for self-study or classroom adoption…" (MAA Reviews, December 28, 2007)      
  


      Product Description  Intermediate Probability is the natural extension of the author'sFundamental Probability. It details several highly important topics,from standard ones such as order statistics, multivariate normal, andconvergence concepts, to more advanced ones which are usually notaddressed at this mathematical level, or have never previously appearedin textbook form. The author adopts a computational approachthroughout, allowing the reader to directly implement the methods, thusgreatly enhancing the learning experience and clearly illustrating theapplicability, strengths, and weaknesses of the theory.     The book:      

• Placesgreat emphasis on the numeric computation of convolutions of randomvariables, via numeric integration, inversion theorems, fast Fouriertransforms, saddlepoint approximations, and simulation.
• Providesintroductory material to required mathematical topics such as complexnumbers, Laplace and Fourier transforms, matrix algebra, confluenthypergeometric functions, digamma functions, and Bessel functions.
• Presentsfull derivation and numerous computational methods of the stableParetian and the singly and doubly non-central distributions.
• Awhole chapter is dedicated to mean-variance mixtures, NIG, GIG,generalized hyperbolic and numerous related distributions.
• Awhole chapter is dedicated to nesting, generalizing, and asymmetricextensions of popular distributions, as have become popular inempirical finance and other applications.
• Provides all essential programming code in Matlab and R.

    The user-friendly style of writing and attention to detail means thatself-study is easily possible, making the book ideal for seniorundergraduate and graduate students of mathematics, statistics,econometrics, finance, insurance, and computer science, as well asresearchers and professional statisticians working in these fields.

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