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A Second Course in Stochastic Processes

>A First Course. We emphasize a careful treatment of basic structures in stochastic processes in symbiosis with the analysis of natural;

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Stochastic Processes - Inference Theory

in econometrics. The first three chapters can be used for a quarter or semester graduate course on inference on stochastic processes. The remaining;

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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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XIII Symposium on Probability and Stochastic Processes

This volume features a collection of contributed articles and lecture notes from the XIII Symposium on Probability and Stochastic Processes;

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A First Course in Stochastic Processes

of several classes of stochastic processes not dealt with in the first edition, notably martingales, renewal and fluctuation phenomena associated;

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Generalized Stochastic Processes

This textbook shall serve a double purpose: first of all, it is a book about generalized stochastic processes, a very important but highly;

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An Introduction To Stochastic Modeling

Serving as the foundation for a one-semester course in stochastic processes for students familiar with elementary probability theory and;

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Essentials of Stochastic Processes

Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students;

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Essentials of Stochastic Processes

Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students;

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Probability Theory and Stochastic Processes

The ultimate objective of this book is to present a panoramic view of the main stochastic processes which have an impact on applications;

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Monte-carlo Methods and Stochastic Processes

Developed from the author's course at the Ecole Polytechnique, Monte-Carlo Methods and Stochastic Processes: From Linear to Non-Linear;

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Monte-Carlo Methods and Stochastic Processes

Developed from the author's course at the Ecole Polytechnique, Monte-Carlo Methods and Stochastic Processes: From Linear to Non-Linear;

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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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Classical and Spatial Stochastic Processes

: An appetizing textbook for a first course in stochastic processes. It guides the reader in a very clever manner from classical ideas to some;

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Discrete Stochastic Processes

Stochastic processes are found in probabilistic systems that evolve with time. Discrete stochastic processes change by only integer time;

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Stochastic Processes in Cell Biology

processes. A wide range of biological topics are covered in the new edition, including stochastic ion channels and excitable systems, molecular;

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An Introduction to Stochastic Modeling

Serving as the foundation for a one-semester course in stochastic processes for students familiar with elementary probability theory;

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Markov Processes

Clear, rigorous, and intuitive, Markov Processes provides a bridge from an undergraduate probability course to a course in stochastic;

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Stochastic Dynamics and Control

graduate course. It provides a systematic review of theory of probability, stochastic processes, and stochastic calculus. The feedback control;

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Probability and Stochastic Processes

This text introduces engineering students to probability theory and stochastic processes. Along with thorough mathematical development;

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Stationary Stochastic Processes

Intended for a second course in stationary processes, Stationary Stochastic Processes: Theory and Applications presents the theory behind;

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Almost Periodic Stochastic Processes

This book lays the foundations for a theory on almost periodic stochastic processes and their applications to various stochastic;

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Probability and Stochastic Modeling

Probability and Stochastic Modeling not only covers all the topics found in a traditional introductory probability course, but also;

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Probability and Stochastic Modeling

Probability and Stochastic Modeling not only covers all the topics found in a traditional introductory probability course, but also;

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Introduction to the Theory of Random Processes

of infinitely divisible processes, stochastic integration allows for obtaining a representation of trajectories through jump measures. The Ito;

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Stochastic Processes

This comprehensive guide to stochastic processes gives a complete overview of the theory and addresses the most important applications;

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Stationary Stochastic Processes for Scientists and Engineers

concepts, this classroom-tested book conveys a broad understanding of the mechanisms that generate stationary stochastic processes. By combining;

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