This second edition of Daniel W. Stroock's text is suitable for first-year graduate students with a good grasp of introductory, undergraduate probability theory and a sound grounding in analysis. It is intended to provide readers with an introduction to probability theory and the analytic ideas and [...]
Kiyosi It's greatest contribution to probability theory may be his introduction of stochastic differential equations to explain the Kolmogorov-Feller theory of Markov processes. Starting with the geometric ideas that guided him, this book gives an account of It's program. The modern theory of Markov[...]
Designed for the full-time analyst, physicist, engineer, or economist, this book attempts to provide its readers with most of the measure theory they will ever need. The author has consistently developed the concrete rather than the abstract aspects of topics treated. The major new feature of this t[...]
Explains the theory of linear and second order PDEs of parabolic and elliptic type.