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Stochastic Processes and Applications in Biology and Medicine II: Models

mathematicians and biologists with a strong mathematical background to the study of stochastic processes and their applications in biological sciences;

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Statistical Topics and Stochastic Models for Dependent Data with Applications

, (ii) autoregressive processes and (iii) techniques based on divergence measures and entropies. A special attention is payed to applications;

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Stochastic Processes in Cell Biology

This book develops the theory of continuous and discrete stochastic processes within the context of cell biology. In the second edition the;

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Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology

of Markov jump processes and stochastic differential equations. Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational;

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Stochastic Processes in Cell Biology

This book develops the theory of continuous and discrete stochastic processes within the context of cell biology. A wide range;

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An Introduction to Continuous-Time Stochastic Processes

processes, stochastic integrals, and stochastic differential equations. Expertly balancing theory and applications, the work features concrete;

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Stochastic Processes and their Applications

processes and theories like Poisson processes and the application of stochastic processes in biology.;

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Branching Processes in Biology

, cellular biology, human evolution and medicine. The branching processes discussed include Galton-Watson, Markov, Bellman-Harris, Multitype, and;

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Stochastic Dynamics for Systems Biology

in systems biology. The book shows how the mathematical models are used as technical tools for simulating biological processes and how the models;

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Stochastic Modelling For Systems Biology

Although stochastic kinetic models are increasingly accepted as the best way to represent and simulate genetic and biochemical networks;

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Stochastic Chemical Reaction Systems in Biology

This book provides an introduction to the analysis of stochastic dynamic models in biology and medicine. The main aim is to offer a;

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Stochastic Models, Statistics and Their Applications

analysis and reliability, statistics for stochastic processes, big data in technology and the sciences, statistical genetics, experiment design;

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An Introduction to Stochastic Processes with Applications to Biology

An Introduction to Stochastic Processes with Applications to Biology, Second Edition presents the basic theory of stochastic processes;

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Stochastic Processes: Modeling and Simulation

, biology, astronomy and chemistry. particular with modelling, simulation techniques and numerical methods concerned with stochastic processes. The;

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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 Stochastic Calculus With Applications (3rd Edition)

This book presents a concise and rigorous treatment of stochastic calculus. It also gives its main applications in finance, biology and;

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Theory and Statistical Applications of Stochastic Processes

This book is concerned with the theory of stochastic processes and the theoretical aspects of statistics for stochastic processes. It;

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Flowgraph Models For Multistate Time-To-Event Data

in fields that use stochastic processes, including anthropology, biology, psychology, computer science, and engineering.;

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Markov Processes and Applications

, Professor at Universite de Paris-Orsay, France. Markov processes is the class of stochastic processes whose past and future are conditionally;

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Probability

on the Axioms Probability Laws II: Results of Conditioning Random Variables and Stochastic Processes Discrete Random Variables and;

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Advanced Mathematical Tools for Automatic Control Engineers: Volume 2

time processes, including the concepts of random sequences, martingales, and limit theorems. Part III covers continuous time stochastic;

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Bayesian Analysis of Stochastic Process Models

Bayesian analysis of complex models based on stochastic processes has in recent years become a growing area. This book provides a unified;

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Stochastic Modelling of Reactionâ Diffusion Processes

mathematics and computations with biology and chemistry. The book can be used both for self-study and as a supporting text for advanced undergraduate;

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Stochastic Modelling of Reaction-Diffusion Processes

mathematics and computations with biology and chemistry. The book can be used both for self-study and as a supporting text for advanced undergraduate;

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Probability Theory and Stochastic Processes

study of stochastic processes gives an opportunity to apply the main theoretical results of probability theory beyond classroom examples and;

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Stochastic Exponential Growth and Lattice Gases

volatility models and stochastic interest rates models such as the Black-Derman-Toy and Black-Karasinski models. These processes can be mapped to;

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Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology

of biochemical and biological networks. Deterministic versus stochastic modelling in biochemistry and systems biology introduces and critically reviews;

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