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Stochastic processes. --- Random processes --- Probabilities
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Stochastic Processes and their Applications illustrates the theoretical knowledge of random variables along with some practical skills to analyze various stochastic dynamical systems in economics, engineering and other fields. It includes the most appropriate process for modelling in particular situations arising in economics, engineering and other fields. Provide the readers with the insights into the development of different processes and theories like Poisson processes and the application of stochastic processes in biology.
Stochastic processes. --- Random processes --- Probabilities
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An introduction to stochastic processes through the use of R Introduction to Stochastic Processes with R is an accessible and well-balanced presentation of the theory of stochastic processes, with an emphasis on real-world applications of probability theory in the natural and social sciences. The use of simulation, by means of the popular statistical software R, makes theoretical results come alive with practical, hands-on demonstrations. Written by a highly-qualified expert in the field, the author presents numerous examples from a wide array of disciplines, which are used to illustrate concepts and highlight computational and theoretical results. Developing readers'problem-solving skills and mathematical maturity, Introduction to Stochastic Processes with R features: More than 200 examples and 600 end-of-chapter exercises A tutorial for getting started with R, and appendices that contain review material in probability and matrix algebra Discussions of many timely and stimulating topics including Markov chain Monte Carlo, random walk on graphs, card shuffling, Black–Scholes options pricing, applications in biology and genetics, cryptography, martingales, and stochastic calculus Introductions to mathematics as needed in order to suit readers at many mathematical levels A companion web site that includes relevant data files as well as all R code and scripts used throughout the book Introduction to Stochastic Processes with R is an ideal textbook for an introductory course in stochastic processes. The book is aimed at undergraduate and beginning graduate-level students in the science, technology, engineering, and mathematics disciplines. The book is also an excellent reference for applied mathematicians and statisticians who are interested in a review of the topic.
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Weak convergence of stochastic processes is one of most important theories in probability theory. Not only probability experts but also more and more statisticians are interested in it. In the study of statistics and econometrics, some problems cannot be solved by the classical method. In this book, we will introduce some recent development of modern weak convergence theory to overcome defects of classical theory.
Stochastic processes. --- Convergence. --- Functions --- Random processes --- Probabilities
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Stochastic processes --- Random processes --- Probabilities --- Stochastic processes.
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Algebras, linear --- Global positioning system --- Random processes
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Stochastic processes --- Stochastic processes. --- 519.2 --- Random processes --- Probabilities
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