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Books > Business & Economics > Economics > Econometrics > Economic statistics

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Approximating Integrals via Monte Carlo and Deterministic Methods (Hardcover) Loot Price: R4,259

Discovery Miles 42 590

Repayment Terms: R399 pm x 12*

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Approximating Integrals via Monte Carlo and Deterministic Methods (Hardcover): Michael Evans, Timothy Swartz

Approximating Integrals via Monte Carlo and Deterministic Methods (Hardcover)

Michael Evans, Timothy Swartz

Series: Oxford Statistical Science Series, 20

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Loot Price R4,259 Discovery Miles 42 590 | Repayment Terms: R399 pm x 12*

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This book is designed to introduce graduate students and researchers to the primary methods useful for approximating integrals. The emphasis is on those methods that have been found to be of practical use, and although the focus is on approximating higher-dimensional integrals the lower-dimensional case is also covered. This book covers all the most useful approximation techniques so far discovered; the first time that all such techniques have been included in a single book and at a level accessible for students. In particular, it includes a complete development of the material needed to construct the highly popular Markov Chain Monte Carlo (MCMC) methods.

General

Imprint:	Oxford UniversityPress
Country of origin:	United Kingdom
Series:	Oxford Statistical Science Series, 20
Release date:	March 2000
First published:	March 2000
Authors:	Michael Evans (Professor of Statistics) • Timothy Swartz (Associate Professor of Statistics)
Dimensions:	241 x 161 x 21mm (L x W x T)
Format:	Hardcover
Pages:	298
ISBN-13:	978-0-19-850278-4
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Computing & IT > General theory of computing > General Books > Computing & IT > Applications of computing > General Books > Business & Economics > Economics > Econometrics > Economic statistics Books > Professional & Technical > Mechanical engineering & materials > Production engineering > Reliability engineering Promotions
LSN:	0-19-850278-8
Barcode:	9780198502784