Stochastic Modeling Of Scientific Data

Author : Peter Guttorp
Publisher : CRC Press
Page : 384 pages
File Size : 47,5 Mb
Release : 2018-03-29
Category : Mathematics
ISBN : 9781351413664

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Stochastic Modeling of Scientific Data by Peter Guttorp Pdf

Stochastic Modeling of Scientific Data combines stochastic modeling and statistical inference in a variety of standard and less common models, such as point processes, Markov random fields and hidden Markov models in a clear, thoughtful and succinct manner. The distinguishing feature of this work is that, in addition to probability theory, it contains statistical aspects of model fitting and a variety of data sets that are either analyzed in the text or used as exercises. Markov chain Monte Carlo methods are introduced for evaluating likelihoods in complicated models and the forward backward algorithm for analyzing hidden Markov models is presented. The strength of this text lies in the use of informal language that makes the topic more accessible to non-mathematicians. The combinations of hard science topics with stochastic processes and their statistical inference puts it in a new category of probability textbooks. The numerous examples and exercises are drawn from astronomy, geology, genetics, hydrology, neurophysiology and physics.

Author : Peter Guttorp,Vladimir N. Minin
Publisher : Chapman & Hall
Page : 384 pages
File Size : 45,5 Mb
Release : 2014-02-15
Category : Mathematics
ISBN : 1439875642

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Stochastic Modeling of Scientific Data by Peter Guttorp,Vladimir N. Minin Pdf

Stochastic Modeling of Scientific Data combines stochastic modeling and statistical inference in a variety of standard and less common models, such as point processes, Markov random fields and hidden Markov models in a clear, thoughtful and succinct manner. The distinguishing feature of this work is that, in addition to probability theory, it contains statistical aspects of model fitting and a variety of data sets that are either analyzed in the text or used as exercises. Markov chain Monte Carlo methods are introduced for evaluating likelihoods in complicated models and the forward backward algorithm for analyzing hidden Markov models is presented. The strength of this text lies in the use of informal language that makes the topic more accessible to non-mathematicians. The combinations of hard science topics with stochastic processes and their statistical inference puts it in a new category of probability textbooks. The numerous examples and exercises are drawn from astronomy, geology, genetics,hydrology, neurophysiology and physics.

Author : Mariano J Valderrama Bonnet,Ramon Gutierrez
Publisher : World Scientific
Page : 326 pages
File Size : 40,8 Mb
Release : 1994-09-30
Category : Electronic
ISBN : 9789814550703

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Selected Topics On Stochastic Modelling by Mariano J Valderrama Bonnet,Ramon Gutierrez Pdf

This volume contains a selection of papers on recent developments in fields such as stochastic processes, multivariate data analysis and stochastic models in operations research, earth and life sciences and information theory, from an applicative perspective. Some of them have been extracted from lectures given at the Department of Statistics and Operations Research at the University of Granada for the past two years (Kai Lai Chung and Marcel F Neuts, among others). All the papers have been carefully selected and revised.

Author : Christos H Skiadas
Publisher : World Scientific
Page : 668 pages
File Size : 40,5 Mb
Release : 2007-11-16
Category : Mathematics
ISBN : 9789814474474

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Recent Advances In Stochastic Modeling And Data Analysis by Christos H Skiadas Pdf

This volume presents the most recent applied and methodological issues in stochastic modeling and data analysis. The contributions cover various fields such as stochastic processes and applications, data analysis methods and techniques, Bayesian methods, biostatistics, econometrics, sampling, linear and nonlinear models, networks and queues, survival analysis, and time series. The volume presents new results with potential for solving real-life problems and provides novel methods for solving these problems by analyzing the relevant data. The use of recent advances in different fields is emphasized, especially new optimization and statistical methods, data warehouse, data mining and knowledge systems, neural computing, and bioinformatics.

Author : Howard M. Taylor,Samuel Karlin
Publisher : Academic Press
Page : 410 pages
File Size : 49,8 Mb
Release : 2014-05-10
Category : Mathematics
ISBN : 9781483269276

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An Introduction to Stochastic Modeling by Howard M. Taylor,Samuel Karlin Pdf

An Introduction to Stochastic Modeling 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.

Author : Vlad Stefan Barbu,Nicolas Vergne
Publisher : John Wiley & Sons
Page : 288 pages
File Size : 43,5 Mb
Release : 2020-10-09
Category : Mathematics
ISBN : 9781119779414

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Statistical Topics and Stochastic Models for Dependent Data with Applications by Vlad Stefan Barbu,Nicolas Vergne Pdf

This book is a collective volume authored by leading scientists in the field of stochastic modelling, associated statistical topics and corresponding applications. The main classes of stochastic processes for dependent data investigated throughout this book are Markov, semi-Markov, autoregressive and piecewise deterministic Markov models. The material is divided into three parts corresponding to: (i) Markov and semi-Markov processes, (ii) autoregressive processes and (iii) techniques based on divergence measures and entropies. A special attention is payed to applications in reliability, survival analysis and related fields.

Author : Anonim
Publisher : Unknown
Page : 128 pages
File Size : 54,7 Mb
Release : 2010
Category : Actuarial science
ISBN : 098139681X

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Stochastic Modeling by Anonim Pdf

Author : Byron J.T. Morgan
Publisher : CRC Press
Page : 363 pages
File Size : 49,7 Mb
Release : 2008-12-02
Category : Mathematics
ISBN : 9781420011654

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Applied Stochastic Modelling by Byron J.T. Morgan Pdf

Highlighting modern computational methods, Applied Stochastic Modelling, Second Edition provides students with the practical experience of scientific computing in applied statistics through a range of interesting real-world applications. It also successfully revises standard probability and statistical theory. Along with an updated bibliography and

Author : Fred Espen Benth,Jurate Saltyte Benth,Steen Koekebakker
Publisher : World Scientific
Page : 352 pages
File Size : 45,5 Mb
Release : 2008
Category : Business & Economics
ISBN : 9789812812308

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Stochastic Modelling of Electricity and Related Markets by Fred Espen Benth,Jurate Saltyte Benth,Steen Koekebakker Pdf

The markets for electricity, gas and temperature have distinctive features, which provide the focus for countless studies. For instance, electricity and gas prices may soar several magnitudes above their normal levels within a short time due to imbalances in supply and demand, yielding what is known as spikes in the spot prices. The markets are also largely influenced by seasons, since power demand for heating and cooling varies over the year. The incompleteness of the markets, due to nonstorability of electricity and temperature as well as limited storage capacity of gas, makes spot-forward hedging impossible. Moreover, futures contracts are typically settled over a time period rather than at a fixed date. All these aspects of the markets create new challenges when analyzing price dynamics of spot, futures and other derivatives.This book provides a concise and rigorous treatment on the stochastic modeling of energy markets. Ornstein?Uhlenbeck processes are described as the basic modeling tool for spot price dynamics, where innovations are driven by time-inhomogeneous jump processes. Temperature futures are studied based on a continuous higher-order autoregressive model for the temperature dynamics. The theory presented here pays special attention to the seasonality of volatility and the Samuelson effect. Empirical studies using data from electricity, temperature and gas markets are given to link theory to practice.

Author : Fred Espen Benth,Jurate Saltyte Benth,Steen Koekebakker
Publisher : World Scientific
Page : 352 pages
File Size : 53,9 Mb
Release : 2008
Category : Technology & Engineering
ISBN : 9789812812315

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Stochastic Modelling of Electricity and Related Markets by Fred Espen Benth,Jurate Saltyte Benth,Steen Koekebakker Pdf

The markets for electricity, gas and temperature have distinctive features, which provide the focus for countless studies. For instance, electricity and gas prices may soar several magnitudes above their normal levels within a short time due to imbalances in supply and demand, yielding what is known as spikes in the spot prices. The markets are also largely influenced by seasons, since power demand for heating and cooling varies over the year. The incompleteness of the markets, due to nonstorability of electricity and temperature as well as limited storage capacity of gas, makes spot-forward hedging impossible. Moreover, futures contracts are typically settled over a time period rather than at a fixed date. All these aspects of the markets create new challenges when analyzing price dynamics of spot, futures and other derivatives. This book provides a concise and rigorous treatment on the stochastic modeling of energy markets. OrnsteinOCoUhlenbeck processes are described as the basic modeling tool for spot price dynamics, where innovations are driven by time-inhomogeneous jump processes. Temperature futures are studied based on a continuous higher-order autoregressive model for the temperature dynamics. The theory presented here pays special attention to the seasonality of volatility and the Samuelson effect. Empirical studies using data from electricity, temperature and gas markets are given to link theory to practice. Sample Chapter(s). A Survey of Electricity and Related Markets (331 KB). Contents: A Survey of Electricity and Related Markets; Stochastic Analysis for Independent Increment Processes; Stochastic Models for the Energy Spot Price Dynamics; Pricing of Forwards and Swaps Based on the Spot Price; Applications to the Gas Markets; Modeling Forwards and Swaps Using the HeathOCoJarrowOCoMorton Approach; Constructing Smooth Forward Curves in Electricity Markets; Modeling of the Electricity Futures Market; Pricing and Hedging of Energy Options; Analysis of Temperature Derivatives. Readership: Researchers in energy and commodity markets, and mathematical finance.

Author : B. R. Bhat
Publisher : New Age International
Page : 412 pages
File Size : 53,6 Mb
Release : 2004
Category : Mathematical statistics
ISBN : 8122412289

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Stochastic Models: Analysis and Applications by B. R. Bhat Pdf

The Book Presents A Systematic Exposition Of The Basic Theory And Applications Of Stochastic Models.Emphasising The Modelling Rather Than Mathematical Aspects Of Stochastic Processes, The Book Bridges The Gap Between The Theory And Applications Of These Processes.The Basic Building Blocks Of Model Construction Are Explained In A Step By Step Manner, Starting From The Simplest Model Of Random Walk And Proceeding Gradually To More Complicated Models. Several Examples Are Given Throughout The Text To Illustrate Important Analytical Properties As Well As To Provide Applications.The Book Also Includes A Detailed Chapter On Inference For Stochastic Processes. This Chapter Highlights Some Of The Recent Developments In The Subject And Explains Them Through Illustrative Examples.An Important Feature Of The Book Is The Complements And Problems Section At The End Of Each Chapter Which Presents (I) Additional Properties Of The Model, (Ii) Extensions Of The Model, And (Iii) Applications Of The Model To Different Areas.With All These Features, This Is An Invaluable Text For Post-Graduate Students Of Statistics, Mathematics And Operation Research.

Author : Vladimir I. Rotar
Publisher : CRC Press
Page : 510 pages
File Size : 54,7 Mb
Release : 2012-08-25
Category : Mathematics
ISBN : 9781439872062

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Probability and Stochastic Modeling by Vladimir I. Rotar Pdf

A First Course in Probability with an Emphasis on Stochastic Modeling Probability 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 texts, the book also focuses on increasingly important areas, such as martingales, classification of dependency structures, and risk evaluation. Numerous examples, exercises, and models using real-world data demonstrate the practical possibilities and restrictions of different approaches and help students grasp general concepts and theoretical results. The text is suitable for majors in mathematics and statistics as well as majors in computer science, economics, finance, and physics. The author offers two explicit options to teaching the material, which is reflected in "routes" designated by special "roadside" markers. The first route contains basic, self-contained material for a one-semester course. The second provides a more complete exposition for a two-semester course or self-study.

Author : Mostafa Bachar,Jerry J. Batzel,Susanne Ditlevsen
Publisher : Springer
Page : 206 pages
File Size : 41,6 Mb
Release : 2012-10-19
Category : Mathematics
ISBN : 9783642321573

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Stochastic Biomathematical Models by Mostafa Bachar,Jerry J. Batzel,Susanne Ditlevsen Pdf

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.

Author : Timothy C. Coburn,Jeffrey M. Yarus,R. L. Chambers
Publisher : AAPG
Page : 406 pages
File Size : 40,6 Mb
Release : 2005-12-10
Category : Petroleum
ISBN : 9780891817048

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Stochastic Modeling and Geostatistics by Timothy C. Coburn,Jeffrey M. Yarus,R. L. Chambers Pdf

Author : Valderrama M J,Gutierrez Ramon
Publisher : #N/A
Page : 672 pages
File Size : 47,7 Mb
Release : 1991-03-29
Category : Electronic
ISBN : 9789814556293

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Applied Stochastic Models And Data Analysis - Proceedings Of The Fifth International Symposium On Asmda by Valderrama M J,Gutierrez Ramon Pdf

As with previous symposiums, the main objective of the Sixth International Symposium is to publish papers (of both technical and practical nature) to present new findings uncovered by theoretical results which may have the potential to contribute solutions to real-life problems. With this objective in mind, this collection of papers aims to serve as an interface between stochastic modeling and data analysis as well as their applications to the problems we face in the various fields. The papers first focused on the theory, application and interaction between stochastic models and data analysis. The results and their applications to the problems we face in the fields of economics, finance and insurance, management, marketing, health sciences, production and engineering are then explored.