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This book covers a highly relevant and timely topic that is of wide interest, especially in finance, engineering and computational biology. The introductory material on simulation and stochastic differential equation is very accessible and will prove popular with many readers. While there are several recent texts available that cover stochastic differential equations, the concentration here on inference makes this book stand out. No other direct competitors are known to date. With an emphasis on the practical implementation of the simulation and estimation methods presented, the text will be useful to practitioners and students with minimal mathematical background. What’s more, because of the many R programs, the information here is appropriate for many mathematically well educated practitioners, too.
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| | Fuzzy Systems Engineering: Toward Human-Centric ComputingA self-contained treatment of fuzzy systems engineering, offering conceptual fundamentals, design methodologies, development guidelines, and carefully selected illustrative material
Forty years have passed since the birth of fuzzy sets, in which time a wealth of theoretical developments, conceptual pursuits, algorithmic... | | Learning DCOM
DCOM -- the Distributed Component Object Model -- is a recent upgrade of a time-honored and well-tested technology promoted by Microsoft for distributed object programming. Now that components are playing a larger and larger part in Windows 98, Windows NT 4.0, and Windows 2000, every Windows programmer will want to understand the... |
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