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Foundations and Methods of Stochastic Simulation

This graduate-level textbook covers modelling, programming and analysis of stochastic computer simulation experiments, including the;

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Foundations and Methods of Stochastic Simulation

This graduate-level textbook covers modelling, programming and analysis of stochastic computer simulation experiments, including the;

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Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology

of modelling and simulation of biological processes at the molecular scale. Following an overview of deterministic chemical kinetics and the stochastic;

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Monte-carlo Methods and Stochastic Processes

focuses on the simulation of stochastic processes in continuous time and their link with partial differential equations (PDEs). It covers linear;

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Monte-Carlo Methods and Stochastic Processes

focuses on the simulation of stochastic processes in continuous time and their link with partial differential equations (PDEs). It covers linear;

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Simulation and Chaotic Behavior of Alpha-stable Stochastic Processes

Presents new computer methods in approximation, simulation, and visualization for a host of alpha-stable stochastic processes.;

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Simulation and Chaotic Behavior of Alpha-stable Stochastic Processes

Presents new computer methods in approximation, simulation, and visualization for a host of alpha-stable stochastic processes.;

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Simulation of Stochastic Processes with Given Accuracy and Reliability

the new approaches and modern methods of simulation of stochastic processes, this book provides methods and tools in measuring accuracy and;

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Numerical Methods For Stochastic Processes

new methods. Topics presented include Monte Carlo and quasi-Monte Carlo methods, the simulation of major stochastic processes and;

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Stochastic Optimization with Simulation Based Optimization

Stochastic optimization is vital to making sound engineering and business decisions under uncertainty. While the limited capability;

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Introduction to Computational Earthquake Engineering

numerical simulation of strong ground motion and faulting, respectively. Stochastic modeling is used for uncertain underground structures, and;

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Stochastic Processes: Modeling and Simulation

This sequel to volume 19 of Handbook on Statistics on Stochastic Processes: Modelling and Simulation is concerned mainly with the theme;

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Advances in Linear Stochastic Programming

Benders decompositions, and L-shaped method. Moreover, approximation methods such as Monte Carlo simulation, as well as combinatorial heuristics;

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Stochastic Processes for Physicists

Stochastic processes are an essential part of numerous branches of physics, as well as in biology, chemistry, and finance. This textbook;

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Numerical Probability

covered include the Monte Carlo simulation (including simulation of random variables, variance reduction, quasi-Monte Carlo simulation, and more;

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Mean Field Simulation for Monte Carlo Integration

applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally;

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Mean Field Simulation for Monte Carlo Integration

applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally;

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Stochastic Methods in Subsurface Contaminant Hydrology

dispersion are discussed. Examples from field and laboratory experiments and simulation exercises illustrate several of these concepts. Stochastic;

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Comparison Methods for Stochastic Models and Risks

Stochastic order relations prprovide a valuable insight into the behaviour of complex stochastic (random) systems and enable the user to;

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Stochastic Modelling of Reactionâ Diffusion Processes

reactions, introducing stochastic simulation algorithms and mathematical methods for analysis of stochastic models. Different stochastic spatio;

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Stochastic Modelling of Reaction-Diffusion Processes

reactions, introducing stochastic simulation algorithms and mathematical methods for analysis of stochastic models. Different stochastic spatio;

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Simulation and Inference for Stochastic Differential Equations

. The introductory material on simulation and stochastic differential equation is very accessible and will prove popular with many readers;

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Monte Carlo Methods and Models in Finance and Insurance

and the simulation of stochastic processes with continuous and discontinuous paths. It also covers a wide selection of popular models;

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Stochastic Simulation

recommendations on the methods [make] this book an excellent reference for anyone interested in simulation. With its compact structure and good coverage;

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Stochastic Dynamics of Marine Structures

Stochastic Dynamics of Marine Structures is a text for students and a reference for professionals on the basic theory and methods used for;

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Simulation and Inference for Stochastic Processes with Yuima: A Comprehensive R Framework for Sdes and Other Stochastic Processes

The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stochastic;

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Numerical Solution of Stochastic Differential Equations with Jumps in Finance

In financial and actuarial modeling and other areas of application, stochastic differential equations with jumps have been employed to;

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