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Author : W. Karwowski
Publisher : Unknown
Page : 128 pages
File Size : 47,5 Mb
Release : 1990-06-01
Category : Science
ISBN : 9810201338
Author : Wacław Kasprzak,A. Weron
Publisher : World Scientific Publishing Company
Page : 496 pages
File Size : 41,7 Mb
Release : 1990
Category : Mathematics
ISBN : UCAL:B4405388
This volume, containing selected papers presented during the COSMEX '89 meeting, provides readers with integrative and innovative articles on many aspects on many aspects of stochastic methods and their applications to experimental sciences. Offering an interdisciplinary presentation on the uses of stochastic methods, this publication discusses the practical applications of stochastic methods to such diverse areas as biology, chemistry, physics, mechanics and engineering. It also discusses computer implementation of theoretically derived algorithms especially for experimental designs.
Author : Waclaw Kasprzak,Aleksander Weron
Publisher : World Scientific
Page : 490 pages
File Size : 51,8 Mb
Release : 1990-08-23
Category : Electronic
ISBN : 9789814611947
This volume, containing selected papers presented during the COSMEX '89 meeting, provides readers with integrative and innovative articles on many aspects on many aspects of stochastic methods and their applications to experimental sciences. Offering an interdisciplinary presentation on the uses of stochastic methods, this publication discusses the practical applications of stochastic methods to such diverse areas as biology, chemistry, physics, mechanics and engineering. It also discusses computer implementation of theoretically derived algorithms especially for experimental designs.
Author : Waclaw Kasprzak
Publisher : Unknown
Page : 490 pages
File Size : 46,9 Mb
Release : 1990
Category : MATHEMATICS
ISBN : 9814540730
Author : Aleksand Janicki,A. Weron
Publisher : CRC Press
Page : 378 pages
File Size : 49,8 Mb
Release : 2021-07-29
Category : Mathematics
ISBN : 9781000447804
Presents new computer methods in approximation, simulation, and visualization for a host of alpha-stable stochastic processes.
Author : Stamatis Cambanis,Jayanta K. Ghosh,Rajeeva L. Karandikar,Pranab K. Sen
Publisher : Springer Science & Business Media
Page : 373 pages
File Size : 47,9 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461579090
This volume celebrates the many contributions which Gopinath Kallianpur has made to probability and statistics. It comprises 40 chapters which taken together survey the wide sweep of ideas which have been influenced by Professor Kallianpur's writing and research.
Author : Crispin W. Gardiner
Publisher : Unknown
Page : 442 pages
File Size : 41,5 Mb
Release : 1983
Category : Processus stochastiques
ISBN : 3540113576
Author : Peter Watts Jones,Peter Smith
Publisher : CRC Press
Page : 255 pages
File Size : 44,9 Mb
Release : 2017-10-30
Category : Mathematics
ISBN : 9781498778121
Based on a well-established and popular course taught by the authors over many years, Stochastic Processes: An Introduction, Third Edition, discusses the modelling and analysis of random experiments, where processes evolve over time. The text begins with a review of relevant fundamental probability. It then covers gambling problems, random walks, and Markov chains. The authors go on to discuss random processes continuous in time, including Poisson, birth and death processes, and general population models, and present an extended discussion on the analysis of associated stationary processes in queues. The book also explores reliability and other random processes, such as branching, martingales, and simple epidemics. A new chapter describing Brownian motion, where the outcomes are continuously observed over continuous time, is included. Further applications, worked examples and problems, and biographical details have been added to this edition. Much of the text has been reworked. The appendix contains key results in probability for reference. This concise, updated book makes the material accessible, highlighting simple applications and examples. A solutions manual with fully worked answers of all end-of-chapter problems, and Mathematica® and R programs illustrating many processes discussed in the book, can be downloaded from crcpress.com.
Author : Crispin Gardiner
Publisher : Springer
Page : 0 pages
File Size : 43,6 Mb
Release : 2010-10-19
Category : Science
ISBN : 3642089623
In the third edition of this classic the chapter on quantum Marcov processes has been replaced by a chapter on numerical treatment of stochastic differential equations to make the book even more valuable for practitioners.
Author : Aliakbar Montazer Haghighi,Indika Wickramasinghe
Publisher : CRC Press
Page : 635 pages
File Size : 50,5 Mb
Release : 2020-07-14
Category : Mathematics
ISBN : 9781351238397
2020 Taylor & Francis Award Winner for Outstanding New Textbook! Featuring recent advances in the field, this new textbook presents probability and statistics, and their applications in stochastic processes. This book presents key information for understanding the essential aspects of basic probability theory and concepts of reliability as an application. The purpose of this book is to provide an option in this field that combines these areas in one book, balances both theory and practical applications, and also keeps the practitioners in mind. Features Includes numerous examples using current technologies with applications in various fields of study Offers many practical applications of probability in queueing models, all of which are related to the appropriate stochastic processes (continuous time such as waiting time, and fuzzy and discrete time like the classic Gambler’s Ruin Problem) Presents different current topics like probability distributions used in real-world applications of statistics such as climate control and pollution Different types of computer software such as MATLAB®, Minitab, MS Excel, and R as options for illustration, programing and calculation purposes and data analysis Covers reliability and its application in network queues
Author : Frank Beichelt
Publisher : CRC Press
Page : 438 pages
File Size : 46,6 Mb
Release : 2006-02-22
Category : Mathematics
ISBN : 142001045X
This book presents a self-contained introduction to stochastic processes with emphasis on their applications in science, engineering, finance, computer science, and operations research. It provides theoretical foundations for modeling time-dependent random phenomena in these areas and illustrates their application by analyzing numerous practical examples. The treatment assumes few prerequisites, requiring only the standard mathematical maturity acquired by undergraduate applied science students. It includes an introductory chapter that summarizes the basic probability theory needed as background. Numerous exercises reinforce the concepts and techniques discussed and allow readers to assess their grasp of the subject. Solutions to most of the exercises are provided in an appendix. While focused primarily on practical aspects, the presentation includes some important proofs along with more challenging examples and exercises for those more theoretically inclined. Mastering the contents of this book prepares readers to apply stochastic modeling in their own fields and enables them to work more creatively with software designed for dealing with the data analysis aspects of stochastic processes.
Author : Georg Lindgren,Holger Rootzen,Maria Sandsten
Publisher : CRC Press
Page : 316 pages
File Size : 40,5 Mb
Release : 2013-10-11
Category : Mathematics
ISBN : 9781466586192
Suitable for a one-semester course, this text teaches students how to use stochastic processes efficiently. Carefully balancing mathematical rigor and ease of exposition, the book provides students with a sufficient understanding of the theory and a practical appreciation of how it is used in real-life situations. Special emphasis is on the interpretation of various statistical models and concepts as well as the types of questions statistical analysis can answer. To enable hands-on practice, MATLAB code is available online.
Author : Carlo Laing,Gabriel J Lord
Publisher : Oxford University Press
Page : 399 pages
File Size : 46,7 Mb
Release : 2010
Category : Mathematics
ISBN : 9780199235070
Computational or mathematical neuroscience is a research area currently of great interest, due to, amongst other factors, rapid increases in computing power, increases in the ability to record large amounts of neurophysiological data, and a realisation amongst both neuroscientists and mathematicians that each can benefit from collaborating with the other. Suitable for graduates and researchers in computational neuroscience, stochastic systems, and neuroscientists seeking to learn more about recent advances in the modelling and analysis of noisy neural systems, this text presents an overview of neuroscience and the role of noise via a series of self-contained chapters on major aspects, written by experts in their particular field. These range over Markov chain models for ion channel release, stochastically forced single neurons and population of neurons, statistical methods for parameter estimation, and the numerical approximation these models. Each chapter will give an overview of a particular topic, including its history, important results in the area, and future challenges.
Author : Andrei Kramer
Publisher : Logos Verlag Berlin GmbH
Page : 161 pages
File Size : 45,9 Mb
Release : 2016-02-11
Category : Biological systems
ISBN : 9783832541958
Markov Chain Monte Carlo (MCMC) methods are sampling based techniques, which use random numbers to approximate deterministic but unknown values. They can be used to obtain expected values, estimate parameters or to simply inspect the properties of a non-standard, high dimensional probability distribution. Bayesian analysis of model parameters provides the mathematical foundation for parameter estimation using such probabilistic sampling. The strengths of these stochastic methods are their robustness and relative simplicity even for nonlinear problems with dozens of parameters as well as a built-in uncertainty analysis. Because Bayesian model analysis necessarily involves the notion of prior knowledge, the estimation of unidentifiable parameters can be regularised (by priors) in a straight forward way. This work draws the focus on typical cases in systems biology: relative data, nonlinear ordinary differential equation models and few data points. It also investigates the consequences of parameter estimation from steady state data; consequences such as performance benefits. In biology the data is almost exclusively relative, the raw measurements (e.g. western blot intensities) are normalised by control experiments or a reference value within a series and require the model to do the same when comparing its output to the data. Several sampling algorithms are compared in terms of effective sampling speed and necessary adaptations to relative and steady state data are explained.
Author : Charles J Mode,Candace K Sleeman
Publisher : World Scientific
Page : 696 pages
File Size : 43,6 Mb
Release : 2012-02-13
Category : Mathematics
ISBN : 9789814397070
The scope of this book is the field of evolutionary genetics. The book contains new methods for simulating evolution at the genomic level. It sets out applications using up to date Monte Carlo simulation methods applied in classical population genetics, and sets out new fields of quantifying mutation and selection at the Mendelian level. A serious limitation of Wright-Fisher process, the assumption that population size is constant, motivated the introduction of self regulating branching processes in this book. While providing a short review of the principles of probability and its application and using computer intensive methods whilst applying these principles, this book explains how it is possible to derive new formulas expressed in terms of matrix algebra providing new insights into the classical Wright-Fisher processes of evolutionary genetics. Also covered are the development of new methods for studying genetics and evolution, simulating nucleotide substitutions of a DNA molecule and on self regulating branching processes. Components of natural selection are studied in terms of reproductive success of each genotype whilst also studying the differential ability of genotypes to compete for resources and sexual selection. The concept of the gene is also reviewed in this book, and it provides a current definition of a gene based on very recent experiments with micro-array technologies. A development of stochastic models for simulating the evolution of model genomes concludes the studies in this book. Deserving of a place on the book shelves of workers in biomathematics, applied probability, stochastic processes and statistics, as well as in bioinformatics and phylogenetics, it will also be relevant to those interested in computer simulation, and evolutionary biologists interested in quantitative methods. Contents:An Introduction to Mathematical Probability with Applications in Mendelian GeneticsLinkage and Recombination at Multiple LociLinkage and Recombination in Large Random Mating Diploid Populations Random Mating Diploid PopulationsTwo Allele Wright-Fisher Process with Mutation and SelectionMultitype Gamete Sampling Processes, Generation of Random Numbers and Monte Carlo Simulation MethodsNucleotide Substitution Models Formulated as Markov Processes in Continuous TimeMixtures of Markov Processes as Models of Nucleotide Substitutions at Many SitesComputer Implementations and Applications of Nucleotide Substitution Models at Many Sites — Other Non-SNP Types of MutationGenealogies, Coalescence and Self-Regulating Branching ProcessesEmergence, Survival and Extinction of Mutant Types in Populations of Self Replicating Individuals Evolving From Small Founder PopulationsTwo Sex Multitype Self Regulating Branching Processes in Evolutionary GeneticsMultitype Self-Regulatory Branching Process and the Evolutionary Genetics of Age Structured Two Sex PopulationsAn Overview of the History of the Concept of a Gene and Selected Topics in Molecular GeneticsDetecting Genomic Signals of Selection and the Development of Models for Simulating the Evolution of GenomesSuggestions for Further Research, Reading and Viewing Readership: Professionals, researchers in mathematical and theoretical genetics and biology, graduate students in applied stochastic processes. Keywords:Mutation;Selection;Genes;Genomes;Stochastic Processes;Self Regulating Branching Processes;Models of GenomesKey Features:Provides many examples of applying Monte Carlo simulation methods to models that are not tractable mathematicallyRaises the study of evolution to new levels by using computer intensive methods when compared to classical and widely read population genetics books such as those by Ewens and Hartl and ClarkAll models, rooted within a formal framework of stochastic processes, enable any reader to write code in a programming language of his choice, to duplicate any of the experiments reported in the bookReviews: "Evolutionary biologists today need enough mathematical training to be able to assess the power and limits of evolutionary genetic models and to develop theories and models themselves. This book, based on very extensive—and impressive—research work, serves that purpose." Mathematical Reviews