Applied Stochastic Modelling PDF ePub eBook

Books Info:

Applied Stochastic Modelling free 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 improved figures, this edition offers numerous updates throughout. New to the Second Edition An extended discussion on Bayesian methods A large number of new exercises A new appendix on computational methods The book covers both contemporary and classical aspects of statistics, including survival analysis, Kernel density estimation, Markov chain Monte Carlo, hypothesis testing, regression, bootstrap, and generalised linear models. Although the book can be used without reference to computational programs, the author provides the option of using powerful computational tools for stochastic modelling. All of the data sets and MATLAB(R) and R programs found in the text as well as lecture slides and other ancillary material are available for download at www.crcpress.com Continuing in the bestselling tradition of its predecessor, this textbook remains an excellent resource for teaching students how to fit stochastic models to data.

About Byron J. T. Morgan

University of Kent, UK University of Minnesota, Minneapolis, Minnesota, USA Northwestern University, Evanston, Illinois, USA University of British Columbia, Vancouver, Canada

Details Book

Author : Byron J. T. Morgan
Publisher : Chapman
Data Published : 19 November 2008
ISBN : 1584886668
EAN : 9781584886662
Format Book : PDF, Epub, DOCx, TXT
Number of Pages : 368 pages
Age + : 15 years
Language : English
Rating :

Reviews Applied Stochastic Modelling



17 Comments Add a comment




Related eBooks Download


  • Elementary Stochastic Calculus, with Finance in View free pdfElementary Stochastic Calculus, with Finance in View

    Modelling with the Ito integral or stochastic differential equations has become increasingly important in various applied fields. including physics. biology. chemistry and finance. However. stochastic calculus is based on a deep mathematical theory..


  • Applied Probability Models with Optimization Applications free pdfApplied Probability Models with Optimization Applications

    Concise advanced-level introduction to stochastic processes that frequently arise in applied probability. Largely self-contained text covers Poisson process. renewal theory. Markov chains. inventory theory..


  • Stochastic Approximation Methods for Constrained and Unconstrained Systems free pdfStochastic Approximation Methods for Constrained and Unconstrained Systems

    The book deals with a powerful and convenient approach to a great variety of types of problems of the recursive monte-carlo or stochastic approximation type. Such recu- sive algorithms occur frequently in stochastic and adaptive control and optimization theory and in statistical esti- tion theory..


  • Economic Growth free pdfEconomic Growth

    This is a book on deterministic and stochastic Growth Theory and the computational methods needed to produce numerical solutions. Exogenous and endogenous growth models are thoroughly reviewed. Special attention is paid to the use of these models for fiscal and monetary policy analysis..


  • An Introduction to Stochastic Processes with Applications to Biology free pdfAn Introduction to Stochastic Processes with Applications to Biology

    An Introduction to Stochastic Processes with Applications to Biology. Second Edition presents the basic theory of stochastic processes necessary in understanding and applying stochastic methods to biological problems in areas such as population growth and extinction..


  • Applied Stochastic Modelling free pdfApplied Stochastic Modelling

    Books Online To Read For Free. Highlighting modern computational methods, Applied Stochastic Modelling, Second Edition provides students with the practical experience of scientific computing in applie