A collection of chapters from leading scholars on the subject of stochastic geometry, laying the foundations for future research and providing fresh perspectives, ideas and interdisciplinary connections now arising from stochastic geometry.
"Ross's classic bestseller, Introduction to Probability Models, has been used extensively by professors as the primary text for a first undergraduate course in applied probability. It provides an Introduction to elementary probability theory and stochastic processes, and shows h…
"Intended for upper level undergraduate students in mathematics or similar quantitative sciences, A Course in Mathematical Biology: Quantitative Modeling with Mathematical and Computational Methods is also appropriate for beginning graduate students in biology, medicine, ecology…
'Probabilistic Graphical Models' discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data.
