viii Preface
and Casella, 2004).) This book can also be viewed as a companion to, rather
than a competitor of, Jim Albert’s Use R! book Bayesian Computation with
R (Albert, 2009). Indeed, taken as a pair, these two books can provide a fairly
thorough introduction to Monte Carlo methods and Bayesian modeling.
We stress that, at a production level (that is, when using advanced Monte
Carlo techniques or analyzing large datasets), R cannot be recommended as
the default language, but the expertise gained from this book should make
the switch to another language seamless.
Contrary to usual practice, many exercises are interspersed within the
chapters rather than postponed until the end of each chapter. There are two
reasons for this stylistic choice. First, the results or developments contained in
those exercises are often relevant for upcoming points in the chapter. Second,
they signal to the student (or to any reader) that some pondering over the
previous pages may be useful before moving to the following topic and so may
act as self-checking gateways. Additional exercises are found at the end of
each chapter, with abridged solutions of the odd-numbered exercises provided
on our Webpages as well as Springer’s.
Thanks
We are immensely grateful to colleagues and friends for their help with this
book, in particular to the following people: Ed George for his comments on the
general purpose of the book and some exercises in particular; Jim Hobert and
Fernando Quintana for helpful discussions on the Monte Carlo EM; Alessandra
Iacobucci for signaling in due time a fatal blunder; Jean-Michel Marin for
letting us recycle the first chapter of Bayesian Core (Marin and Robert, 2007)
into our introduction to R and for numerous pieces of R advice, as well as
pedagogical suggestions; Antonietta Mira for pointing out mistakes during
a session of an MCMC conference in Warwick; Fran¸cois Perron for inviting
CPR to Montr´eal and thus providing him with a time window to complete
Chapter 8 (only shortened by an ice-climbing afternoon in Qu´eb´ec!), and also
Fran¸cois Perron and Cl´ementine Trimont for testing the whole book from
the perspectives of a professor and a student, respectively; Martyn Plummer
for answering queries about coda; Jeff Rosenthal for very helpful exchanges
on amcmc; Dimitris Rizopoulos for providing Exercise 7.21; and Phil Spector
from Berkeley for making available his detailed and helpful notes and slides
on R and C, now partly published as Spector (2009). Comments from both
reviewers were especially useful in finalizing the book. We are also grateful to
John Kimmel of Springer for his advice and efficiency, as well as for creating
the visionary Use R! series and supporting the development of the R language
that way. From a distance, we also wish to thank Professors Gentleman and
Ihaka for creating the R language and for doing it in open-source, as well as
the entire R community for contributing endlessly to its development.
Sceaux and Gainesville Christian P. Robert and George Casella
October 18, 2009
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