Simulation of Stochastic Processes with Given Accuracy and Reliability

Simulation has now become an integral part of research and development across many fields of study. Despite the large amounts of literature in the field of simulation and modeling, one recurring problem is the issue of accuracy and confidence level of constructed models. By outlining the new approaches and modern methods of simulation of stochastic processes, this book provides methods and tools in measuring accuracy and reliability in functional spaces. The authors explore analysis of the theory of Sub-Gaussian (including Gaussian one) and Square Gaussian random variables and processes and Cox processes.  Methods of simulation of stochastic processes and fields with given accuracy and reliability in some Banach spaces are also considered. Provides an analysis of the theory of Sub-Gaussian (including Gaussian one) and Square Gaussian random variables and processesContains information on the study of the issue of accuracy and confidence level of constructed models not found in other books on the topicProvides methods and tools in measuring accuracy and reliability in functional spaces

Yuriy Kozachenko is Professor at Taras Shevchenko National University of Kyiv, Ukraine.Doctor of Sciences in Physics and Mathematics, Laureate of the State Prize of Ukraine in Science and Technology
Main scientific research interests relate to the study of the properties of random processes in various functional spaces, simulation and statistics of random processes, the theory of wavelet expansions of random processes. One of the founders of the theory of sub-Gaussian and f-subGaussian random processes, random processes from Orlicz spaces. Determination of accuracy and reliability of computer simulation of random processes.
Author of over 300 scientific papers, several textbooks and seven monographs.