A comprehensive account of the statistical theory of exponential
families of stochastic processes. The book reviews the progress in
the field made over the last ten years or so by the authors - two
of the leading experts in the field - and several other
researchers. The theory is applied to a broad spectrum of examples,
covering a large number of frequently applied stochastic process
models with discrete as well as continuous time. To make the
reading even easier for statisticians with only a basic background
in the theory of stochastic process, the first part of the book is
based on classical theory of stochastic processes only, while
stochastic calculus is used later. Most of the concepts and tools
from stochastic calculus needed when working with inference for
stochastic processes are introduced and explained without proof in
an appendix. This appendix can also be used independently as an
introduction to stochastic calculus for statisticians. Numerous
exercises are also included.
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