Abstract
In Chapter 3, the Monte Carlo method was introduced (and discussed) as a simulation-based approach to the approximation of complex integrals. There has been a considerable body of work in this area and, while not all of it is completely relevant for this book, in this chapter we discuss the specifics of variance estimation and control. These are fundamental concepts, and we will see connections with similar developments in the realm of MCMC algorithms that are discussed in Chapters 7–12.
The others regarded him uncertainly, none of them sure how he had arrived at such a conclusion or on how to refute it.
—Susanna Gregory, A Deadly Brew
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Notes
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© 2004 Springer Science+Business Media New York
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Robert, C.P., Casella, G. (2004). Controling Monte Carlo Variance. In: Monte Carlo Statistical Methods. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-4145-2_4
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DOI: https://doi.org/10.1007/978-1-4757-4145-2_4
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-1939-7
Online ISBN: 978-1-4757-4145-2
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