Random variation is a fact of life that provides substance to a
wide range of problems in the sciences, engineering, and economics.
There is a growing need in diverse disciplines to model complex
patterns of variation and interdependence using random fields, as
both deterministic treatment and conventional statistics are often
insufficient. An ideal random field model will capture key features
of complex random phenomena in terms of a minimum number of
physically meaningful and experimentally accessible parameters.
This volume, a revised and expanded edition of an acclaimed book
first published by the M I T Press, offers a synthesis of methods
to describe and analyze and, where appropriate, predict and control
random fields. There is much new material, covering both theory and
applications, notably on a class of probability distributions
derived from quantum mechanics, relevant to stochastic modeling in
fields such as cosmology, biology and system reliability, and on
discrete-unit or agent-based random processes. Random Fields is
self-contained and unified in presentation. The first edition was
found, in a review in EOS (American Geophysical Union) to be "both
technically interesting and a pleasure to read ... the presentation
is clear and the book should be useful to almost anyone who uses
random processes to solve problems in engineering or science ...
and (there is) continued emphasis on describing the mathematics in
physical terms."
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