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• Amazon Sales Rank: #429340 in Books
• Published on: 1988-05-08
• Ingredients: Example Ingredients
• Original language: English
• Number of items: 1
• Binding: Hardcover
• 220 pages

From Publishers Weekly A shy, sensitive Jew who grew up in Fascist Italy, the author overcame anti-Semitic repression and her country's relative scientific immaturity, winning the 1986 Nobel Prize in medicine for her work on the nervous system. After Mussolini's racial laws stripped Levi-Montalcini of her academic post, she set up a small, clandestine laboratory in a Piedmont farmhouse where she carried out her fruitful research. Her firsthand account of her country's knuckling under to Hitler is calm and courageous. In 1946, she left Italy for St. Louis, and this earnest, talkative autobiography offers a detailed picture of the growth of modern experimental neurobiology. In 1963, Levi-Montalcini returned to Rome to live with her twin sister and continue her research. Mirroring her scientific credo that imperfection and unpredictability are the yeast of human evolution, her story unfolds a rich, unpredictable life. Copyright 1988 Reed Business Information, Inc.

From Library Journal The title bespeaks an unwarranted modesty as Levi-Montalcini, co-winner of the 1986 Nobel Prize in medicine, reviews her life and work. An elegant writer, she highlights events and personalities that have altered her life. She examines her family and youth, neither Catholic nor Jewish, but dynamic and creative; her schooling and attempts at research in anguished war-torn Italy; her successful research in the United States; and finally, her work in establishing the Laboratory of Cell Biology of the National Research Council of Italy. She does not reveal her soul, but rather a spirit of determination against social and political forces. Inspiring. Recommended for academic and larger public libraries. Mary Hemmings, McGill Univ. Medical Lib., MontrealCopyright 1988 Reed Business Information, Inc.

Language Notes Text: English Introduction: Italian

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Ebook Stochastic Simulation: Algorithms and Analysis (Stochastic Modelling and Applied Probability)By Søren Asmussen, Peter W. Glynn

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Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods, as well as accompanying mathematical analysis of the convergence properties of the methods discussed. The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first half of the book focuses on general methods; the second half discusses model-specific algorithms. Exercises and illustrations are included.

• Sales Rank: #2393099 in Books
• Published on: 2009-12-28
• Original language: English
• Number of items: 1
• Dimensions: 9.00" h x 1.11" w x 6.00" l, 1.50 pounds
• Binding: Paperback
• 476 pages

Review

From the reviews:

"The adequate statistical simulation of random quantities is one of the challenges of this century. Therefore, sampling-based computational methods have become a fundamental part of the numerical toolset of both practitioners and researchers … . This book provides a descriptive treatment of a variety of such sampling-based methods. Some steps to the mathematical analysis of their convergence properties and diverse applications are sketched as well. … this book is of potential interest to many researchers, students and instructors." (Henri Schurz, Zentralblatt MATH, Vol. 1126 (3), 2008)

"This is a very interesting book for all who are interested in stochastic simulations. … the book is designed as a potential teaching and learning tool for use in a wide variety of courses. … it is a book that should be on the bookshelf of everybody who is seriously interested in stochastic simulations." (EMS Newsletter, September, 2008)

"The present book provides a broad treatment of sampling-based computational methods, as well as accompanying mathematical analysis of the convergence properties of these methods for a wide range of stochastic application problems. … A set of exercises … is also given at the end of each chapter. This book will be a reference of great value for researchers in probability, statistics, operations research, economics, finance, and engineering … . It would also be perfect as a textbook for graduate seminars or courses in stochastic simulation." (Mou-Hsiung Chang, Siam Review, Vol. 51 (1), 2009)

"This book is intended to provide a broad treatment of the basic ideas and algorithms associated with sampling-based methods, often referred to as Monte Carlo algorithms or stochastic simulation. … the book will be very useful to students and researchers from a wide range of disciplines." (John P. Lehoczky, Mathematical Reviews, Issue 2009 c)

"Stochastic Simulation, written by two prominent researchers in applied probability, is an outgrowth of that maturation. The authors’ goal is not to tell the reader everything known about simulation, nor is it to give a collection of recipes, but rather to provide insight into analyzing problems via simulation. … The book would make an excellent text for a graduate course in simulation, especially in a mathematical sciences department." (Peter C. Kiessler, Journal of the American Statistical Association, Vol. 104 (486), June, 2009)

From the Back Cover

Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods, as well as accompanying mathematical analysis of the convergence properties of the methods discussed. The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first half of the book focuses on general methods, whereas the second half discusses model-specific algorithms.

Given the wide range of examples, exercises and applications students, practitioners and researchers in probability, statistics, operations research, economics, finance, engineering as well as biology and chemistry and physics will find the book of value.

Søren Asmussen is a professor of Applied Probability at Aarhus University, Denmark and Peter Glynn is the Thomas Ford professor of Engineering at Stanford University.

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Stochastic Simulation: Algorithms and Analysis (Stochastic Modelling and Applied Probability)By Søren Asmussen, Peter W. Glynn PDF

Stochastic Simulation: Algorithms and Analysis (Stochastic Modelling and Applied Probability)By Søren Asmussen, Peter W. Glynn PDF