I thought readers of sci.stat.edu might be interested in this book.  For
more information please visit http://mitpress.mit.edu/promotions/books/SPICHF00.

Best,
Jud

Causation, Prediction, and Search
second edition
Peter Spirtes, Clark Glymour, and Richard Scheines

What assumptions and methods allow us to turn observations into causal
knowledge, and how can even incomplete causal knowledge be used in
planning and prediction to influence and control our environment? In
this book Peter Spirtes, Clark Glymour, and Richard Scheines address
these questions using the formalism of Bayes networks, with results that
have been applied in diverse areas of research in the social,
behavioral, and physical sciences.
        
The authors show that although experimental and observational study
designs may not always permit the same inferences, they are subject to
uniform principles. They axiomatize the connection between causal
structure and probabilistic independence, explore several varieties of
causal indistinguishability, formulate a theory of manipulation, and
develop asymptotically reliable procedures for searching over
equivalence classes of causal models, including models of categorical
data and structural equation models with and without latent variables.
        
The authors show that the relationship between causality and probability
can also help to clarify such diverse topics in statistics as the
comparative power of experimentation versus observation, Simpson's
paradox, errors in regression models, retrospective versus prospective
sampling, and variable selection.
        
The second edition contains a new introduction and an extensive survey
of advances and applications that have appeared since the first edition
was published in 1993. 
        
Peter Spirtes is Professor of Philosophy at the Center for Automated
Learning and Discovery, Carnegie Mellon University. Clark Glymour is
Alumni University Professor of Philosophy at Carnegie Mellon University
and Valtz Family Professor of Philosophy at the University of
California, San Diego. He is also Distinguished External Member of the
Center for Human and Machine Cognition at the University of West
Florida, and Adjunct Professor of Philosophy of History and Philosophy
of Science at the University of Pittsburgh. Richard Scheines is
Associate Professor of Philosophy at the Center for Automated Learning
and Discovery, and at the Human Computer Interaction Institute, Carnegie
Mellon University.

7 x 9, 496 pp., 225 illus., cloth ISBN 0-262-19440-6
Adaptive Computation and Machine Learning series
A Bradford Book


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