Найти книгу: "Statistical Inference for Piecewise-deterministic Markov Processes"

Piecewise-deterministic Markov processes form a class of stochastic models with a sizeable scope of applications: biology, insurance, neuroscience, networks, finance… Such processes are defined by a deterministic motion punctuated by random jumps at random times, and offer simple yet challenging models to study. Nevertheless, the issue of statistical estimation of the parameters ruling the jump mechanism is far from trivial. Responding to new developments in the field as well as to current research interests and needs, Statistical inference for piecewise-deterministic Markov processes offers a detailed and comprehensive survey of state-of-the-art results. It covers a wide range of general processes as well as applied models. The present book also dwells on statistics in the context of Markov chains, since piecewise-deterministic Markov processes are characterized by an embedded Markov chain corresponding to the position of the process right after the jumps.

Учебное пособие предназначено для обучения магистров по направлению «Химическая технология» и его содержание соответствует ФГОС 3-го поколения для дисциплины «Процессы массопереноса в системах с участием твердой фазы». Изложенный в учебном пособии материал позволяет студентам восполнить и систематизировать знания по теории массообменных процессов, знакомит со спецификой массопереноса в системах с участием твердой фазы, а также с такими процессами, как адсорбция, ионный обмен, кристаллизация, растворение, мембранное разделение, конструкциями соответствующих аппаратов и методами их расчетов.

MIVAR: Transition from Productions to Bipartite Graphs MIVAR Nets and Practical Realization of Automated Constructor of Algorithms Handling More than Three Million Production Rules. The theoretical transition from the graphs of production systems to the bipartite graphs of the MIVAR nets is shown. Examples of the implementation of the MIVAR nets in the formalisms of matrixes and graphs are given. The linear computational complexity of algorithms for automated building of objects and rules of the MIVAR nets is theoretically proved. On the basis of the MIVAR nets the UDAV software complex is developed, handling more than 1.17 million objects and more than 3.5 million rules on ordinary computers. The results of experiments that confirm a linear computational complexity of the MIVAR method of information processing are given.