Applied probability is a broad research area that is of interest to scientists in diverse disciplines in science and technology, including: anthropology, biology, communication theory, economics, epidemiology, finance, geography, linguistics, medicine, meteorology, operations research, psychology, quality control, sociology, and statistics. Recent Advances in Applied Probability is a collection of survey articles that bring together the work of leading researchers in applied probability to present current research advances in this important area.
This volume will be of interest to graduate students and researchers whose research is closely connected to probability modelling and their applications. It is suitable for one semester graduate level research seminar in applied probability.
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Modeling Text Databases.- An Overview of Probabilistic and Time Series Models in Finance.- Stereological Estimation of the Rose of Directions from the Rose of Intersections.- Approximations for Multiple Scan Statistics.- Krawtchouk Polynomials and Krawtchouk Matrices.- An Elementary Rigorous Introduction to Exact Sampling.- On the Different Extensions of the Ergodic Theorem of Information Theory.- Dynamic Stochastic Models for Indexes and Thesauri, Identification Clouds, and Information Retrieval and Storage.- Stability and Optimal Control for Semi-Markov Jump Parameter Linear Systems.- Statistical Distances Based on Euclidean Graphs.- Implied Volatility: Statics, Dynamics, and Probabilistic Interpretation.- On the Increments of the Brownian Sheet.- Compound Poisson Approximation with Drift for Stochastic Additive Functionals with Markov and Semi-Markov Switching.- Penalized Model Selection for Ill-Posed Linear Problems.- The Arov-Grossman Model and Burg’s Entropy.- Recent Results in Geometric Analysis Involving Probability.- Dependence or Independence of the Sample Mean and Variance In Non-IID or Non-Normal Cases and the Role of Some Tests of Independence.- Optimal Stopping Problems for Time-Homogeneous Diffusions: A Review.- Criticality in Epidemics: The Mathematics of Sandpiles Explains Uncertainty in Epidemic Outbreaks.