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Semimartingales and their Statistical Inference

stochastic processes a well-recognized and important branch of statistics and probability. The class of semimartingales includes a large class;

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Semimartingales and Their Statistical Inference

stochastic processes a well-recognized and important branch of statistics and probability. The class of semimartingales includes a large class;

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Stochastic Processes - Inference Theory

fundamental memoir on stochastic processes and related inference theory. The present volume gives a substantial account of regression analysis, both;

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Optimal Statistical Inference in Financial Engineering

Until now, few systematic studies of optimal statistical inference for stochastic processes had existed in the financial engineering;

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Bayesian Inference for Stochastic Processes

This is the first book designed to introduce Bayesian inference procedures for stochastic processes. There are clear advantages to the;

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Bayesian Inference for Stochastic Processes

This is the first book designed to introduce Bayesian inference procedures for stochastic processes. There are clear advantages to the;

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Statistical Inference for Fractional Diffusion Processes

Stochastic processes are widely used for model building in the social, physical, engineering and life sciences as well as in financial;

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Statistical Inference in Stochastic Processes

Covering both theory and applications, this collection of eleven contributed papers surveys the role of probabilistic models and;

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Elements of Applied Stochastic Processes

statistical inference in stochastic processes. * Integration of theory and application offers improved teachability * Provides a comprehensive;

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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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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 Modeling of Scientific Data

of informal language that makes the topic more accessible to non-mathematicians. The combinations of hard science topics with stochastic processes;

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Stochastic Modeling of Scientific Data

of informal language that makes the topic more accessible to non-mathematicians. The combinations of hard science topics with stochastic processes;

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Stochastic Modelling For Systems Biology

, most researchers in the field have limited knowledge of stochastic process theory. The stochastic processes formalism provides a beautiful;

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Statistical Inference for Diffusion Type Processes

refinement of the model are the key steps or building blocks involved in any rational decision making process. Stochastic processes are widely used;

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Stochastic Processes

This definitive textbook provides a solid introduction to discrete and continuous stochastic processes, tackling a complex field in a way;

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Probability

development of distribution theory while also introducing the reader to basic statistical inference. In this way, the major stochastic processes are;

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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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Probability, Statistics, and Stochastic Processes

... Technometrics Thoroughly updated to showcase the interrelationships between probability, statistics, and stochastic processes, Probability, Statistics;

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Semimartingale Theory and Stochastic Calculus

Semimartingale Theory and Stochastic Calculus presents a systematic and detailed account of the general theory of stochastic processes, the;

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Combinatorial Stochastic Processes

of combinatorics and stochastic processes. There is particular focus on the theory of random combinatorial structures such as partitions, permutations;

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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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Theory of Stochastic Objects

areas; statistical inference, measure-theoretic probability theory and stochastic processes. This point of view has not been explored by;

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Theory of Stochastic Objects

areas; statistical inference, measure-theoretic probability theory and stochastic processes. This point of view has not been explored by;

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Stochastic Processes for Physicists

provides a solid understanding of stochastic processes and stochastic calculus in physics, without the need for measure theory. In avoiding measure;

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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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Limit Theorems for Stochastic Processes

. Coverage develops in detail useful parts of the general theory of stochastic processes, such as martingale problems and absolute continuity or;

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