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Stochastic Modeling And Mathematical Statistics


Stochastic Modeling And Mathematical Statistics
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Stochastic Modeling And Mathematical Statistics


Stochastic Modeling And Mathematical Statistics
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Author : Francisco J. Samaniego
language : en
Publisher: CRC Press
Release Date : 2014-01-14

Stochastic Modeling And Mathematical Statistics written by Francisco J. Samaniego and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-14 with Mathematics categories.


Provides a Solid Foundation for Statistical Modeling and Inference and Demonstrates Its Breadth of Applicability Stochastic Modeling and Mathematical Statistics: A Text for Statisticians and Quantitative Scientists addresses core issues in post-calculus probability and statistics in a way that is useful for statistics and mathematics majors as well



Stochastic Modeling And Mathematical Statistics


Stochastic Modeling And Mathematical Statistics
DOWNLOAD
Author : Francisco J. Samaniego
language : en
Publisher: CRC Press
Release Date : 2014-01-14

Stochastic Modeling And Mathematical Statistics written by Francisco J. Samaniego and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-14 with Mathematics categories.


Provides a Solid Foundation for Statistical Modeling and Inference and Demonstrates Its Breadth of Applicability Stochastic Modeling and Mathematical Statistics: A Text for Statisticians and Quantitative Scientists addresses core issues in post-calculus probability and statistics in a way that is useful for statistics and mathematics majors as well as students in the quantitative sciences. The book’s conversational tone, which provides the mathematical justification behind widely used statistical methods in a reader-friendly manner, and the book’s many examples, tutorials, exercises and problems for solution, together constitute an effective resource that students can read and learn from and instructors can count on as a worthy complement to their lectures. Using classroom-tested approaches that engage students in active learning, the text offers instructors the flexibility to control the mathematical level of their course. It contains the mathematical detail that is expected in a course for "majors" but is written in a way that emphasizes the intuitive content in statistical theory and the way theoretical results are used in practice. More than 1000 exercises and problems at varying levels of difficulty and with a broad range of topical focus give instructors many options in assigning homework and provide students with many problems on which to practice and from which to learn.



Stochastic Modeling


Stochastic Modeling
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Author : Barry L. Nelson
language : en
Publisher: Courier Corporation
Release Date : 2012-10-11

Stochastic Modeling written by Barry L. Nelson and has been published by Courier Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-11 with Mathematics categories.


Coherent introduction to techniques also offers a guide to the mathematical, numerical, and simulation tools of systems analysis. Includes formulation of models, analysis, and interpretation of results. 1995 edition.



Probability And Stochastic Modeling


Probability And Stochastic Modeling
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Author : Vladimir I. Rotar
language : en
Publisher: CRC Press
Release Date : 2006-09-20

Probability And Stochastic Modeling written by Vladimir I. Rotar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-20 with Mathematics categories.


A First Course in Probability with an Emphasis on Stochastic ModelingProbability and Stochastic Modeling not only covers all the topics found in a traditional introductory probability course, but also emphasizes stochastic modeling, including Markov chains, birth-death processes, and reliability models. Unlike most undergraduate-level probability t



An Introduction To Stochastic Modeling


An Introduction To Stochastic Modeling
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Author : Howard M. Taylor
language : en
Publisher: Academic Press
Release Date : 2014-05-10

An Introduction To Stochastic Modeling written by Howard M. Taylor and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-10 with Mathematics categories.


An Introduction to Stochastic Modeling, Revised Edition provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.



Foundations Of Stochastic Analysis


Foundations Of Stochastic Analysis
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Author : M. M. Rao
language : en
Publisher: Courier Corporation
Release Date : 2011-01-01

Foundations Of Stochastic Analysis written by M. M. Rao and has been published by Courier Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-01 with Mathematics categories.


Stochastic analysis involves the study of a process involving a randomly determined sequence of observations, each of which represents a sample of one element of probability distribution. This volume considers fundamental theories and contrasts the natural interplay between real and abstract methods. Starting with the introduction of the basic Kolmogorov-Bochner existence theorem, the text explores conditional expectations and probabilities as well as projective and direct limits. Subsequent chapters examine several aspects of discrete martingale theory, including applications to ergodic theory, likelihood ratios, and the Gaussian dichotomy theorem. Prerequisites include a standard measure theory course. No prior knowledge of probability is assumed; therefore, most of the results are proved in detail. Each chapter concludes with a problem section that features many hints and facts, including the most important results in information theory.



Stochastic Models Statistics And Their Applications


Stochastic Models Statistics And Their Applications
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Author : Ansgar Steland
language : en
Publisher: Springer Nature
Release Date : 2019-10-15

Stochastic Models Statistics And Their Applications written by Ansgar Steland and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-15 with Mathematics categories.


This volume presents selected and peer-reviewed contributions from the 14th Workshop on Stochastic Models, Statistics and Their Applications, held in Dresden, Germany, on March 6-8, 2019. Addressing the needs of theoretical and applied researchers alike, the contributions provide an overview of the latest advances and trends in the areas of mathematical statistics and applied probability, and their applications to high-dimensional statistics, econometrics and time series analysis, statistics for stochastic processes, statistical machine learning, big data and data science, random matrix theory, quality control, change-point analysis and detection, finance, copulas, survival analysis and reliability, sequential experiments, empirical processes, and microsimulations. As the book demonstrates, stochastic models and related statistical procedures and algorithms are essential to more comprehensively understanding and solving present-day problems arising in e.g. the natural sciences, machine learning, data science, engineering, image analysis, genetics, econometrics and finance.



Applied Stochastic Differential Equations


Applied Stochastic Differential Equations
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Author : Simo Särkkä
language : en
Publisher: Cambridge University Press
Release Date : 2019-05-02

Applied Stochastic Differential Equations written by Simo Särkkä and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-02 with Business & Economics categories.


With this hands-on introduction readers will learn what SDEs are all about and how they should use them in practice.



Stochastic Biomathematical Models


Stochastic Biomathematical Models
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Author : Mostafa Bachar
language : en
Publisher: Springer
Release Date : 2012-10-19

Stochastic Biomathematical Models written by Mostafa Bachar and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-19 with Mathematics categories.


Stochastic biomathematical models are becoming increasingly important as new light is shed on the role of noise in living systems. In certain biological systems, stochastic effects may even enhance a signal, thus providing a biological motivation for the noise observed in living systems. Recent advances in stochastic analysis and increasing computing power facilitate the analysis of more biophysically realistic models, and this book provides researchers in computational neuroscience and stochastic systems with an overview of recent developments. Key concepts are developed in chapters written by experts in their respective fields. Topics include: one-dimensional homogeneous diffusions and their boundary behavior, large deviation theory and its application in stochastic neurobiological models, a review of mathematical methods for stochastic neuronal integrate-and-fire models, stochastic partial differential equation models in neurobiology, and stochastic modeling of spreading cortical depression.



Algebraic Structures And Applications


Algebraic Structures And Applications
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Author : Sergei Silvestrov
language : en
Publisher: Springer Nature
Release Date : 2020-06-18

Algebraic Structures And Applications written by Sergei Silvestrov and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-18 with Mathematics categories.


This book explores the latest advances in algebraic structures and applications, and focuses on mathematical concepts, methods, structures, problems, algorithms and computational methods important in the natural sciences, engineering and modern technologies. In particular, it features mathematical methods and models of non-commutative and non-associative algebras, hom-algebra structures, generalizations of differential calculus, quantum deformations of algebras, Lie algebras and their generalizations, semi-groups and groups, constructive algebra, matrix analysis and its interplay with topology, knot theory, dynamical systems, functional analysis, stochastic processes, perturbation analysis of Markov chains, and applications in network analysis, financial mathematics and engineering mathematics. The book addresses both theory and applications, which are illustrated with a wealth of ideas, proofs and examples to help readers understand the material and develop new mathematical methods and concepts of their own. The high-quality chapters share a wealth of new methods and results, review cutting-edge research and discuss open problems and directions for future research. Taken together, they offer a source of inspiration for a broad range of researchers and research students whose work involves algebraic structures and their applications, probability theory and mathematical statistics, applied mathematics, engineering mathematics and related areas.