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Simulation of Stochastic Processes with Given Accuracy and Reliability

variables and processes and Cox processes. Methods of simulation of stochastic processes and fields with given accuracy and reliability in some;

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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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Stochastic Processes

stochastic processes is indispensable. As well as providing readers with useful reliability studies and applications, Stochastic Processes also;

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Stochastic Dynamics

of stochastic variables and stochastic processes have been indicated. Chapter 4 deals with the stochastic response analysis of single degrees;

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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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Structural Reliability and Time-Dependent Reliability

This book provides structural reliability and design students with fundamental knowledge in structural reliability, as well as an overview;

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Applied Probability and Stochastic Processes

stochastic processes by focusing on techniques for the modelling and analysis of systems evolving with time. Further, it discusses the applications;

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Applied Probability and Stochastic Processes

stochastic processes by focusing on techniques for the modelling and analysis of systems evolving with time. Further, it discusses the applications;

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Introduction to Stochastic Analysis

is paid to simulation diffusion processes. The topics covered include Brownian motion; motivation of stochastic models with Brownian motion; Ito;

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Introduction to Stochastic Models

This book provides a pedagogical examination of the way in which stochastic models are encountered in applied sciences and techniques such;

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Introduction to Simulation Methods for Gas Discharge Plasmas: Accuracy, reliability and limitations

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Methods of Structural Safety

, providing a framework for evaluating, comparing, and combining stochastic effects.Starting with the general problem of consistent evaluation;

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

briefly the underlying theory for simulation and inference of several classes of stochastic processes and then presents both simulation;

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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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Degradation Processes in Reliability

Degradation process refers to many types of reliability models, which correspond to various kinds of stochastic processes used for;

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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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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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Elementary Applications of Probability Theory

simulation. Chapter six contains a lucid account of the convergence of sequences of random variables, with emphasis on the central limit theorem and;

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Elementary Applications of Probability Theory

simulation. Chapter six contains a lucid account of the convergence of sequences of random variables, with emphasis on the central limit theorem and;

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Parameter Estimation in Stochastic Volatility Models

well as nontraditional continuous time stochastic volatility models driven by fractional Levy processes. By incorporating jumps and long memory;

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Modeling and Simulation Based Analysis in Reliability Engineering

Recent developments in reliability engineering has become the most challenging and demanding area of research. Modeling and Simulation;

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Modeling and Simulation Based Analysis in Reliability Engineering

Recent developments in reliability engineering has become the most challenging and demanding area of research. Modeling and Simulation;

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Stochastic Analysis, Stochastic Systems, And Applications To Finance

with the analysis of stochastic dynamical systems, in terms of Gaussian processes, white noise theory, and diffusion processes. The second part;

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Random Summation

, information properties of probability distributions, and asymptotic behavior of doubly stochastic Poisson processes. Random Summation: Limit Theorems;

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