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Statistical Analysis of Stochastic P...
~
Stein, M.
Statistical Analysis of Stochastic Processes in Time.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Statistical Analysis of Stochastic Processes in Time./
Author:
Lindsey, J. K.
other author:
Gill, R.
Published:
Cambridge :Cambridge University Press, : 2004.,
Description:
354 p.
Subject:
Stochastic processes. -
Online resource:
Click here to view book
ISBN:
9780511617164 (electronic bk.)
Statistical Analysis of Stochastic Processes in Time.
Lindsey, J. K.
Statistical Analysis of Stochastic Processes in Time.
[electronic resource]. - Cambridge :Cambridge University Press,2004. - 354 p.
Cover; Half-title; Series-title; Title; Copyright; Contents; Preface; Notation and symbols; 1 What is a stochastic process?; 2 Basics of statistical modelling; 3 Survival processes; 4 Recurrent events; 5 Discrete-time Markov chains; 6 Event histories; 7 Dynamic models; 8 More complex dependencies; 9 Time series; 10 Diffusion and volatility; 11 Dynamic models; 12 Growth curves; 13 Compartment models; 14 Repeated measurements; References; Author index; Subject index
This introduction to ways of modelling phenomena that occur over time is accessible to anyone with a basic knowledge of statistical ideas. Examples from physical, biological and social sciences show how the principles can be put into practice: data sets and R code for these are supplied on author's website.
Electronic reproduction.
Available via World Wide Web.
Mode of access: World Wide Web.
ISBN: 9780511617164 (electronic bk.)Subjects--Topical Terms:
121454
Stochastic processes.
Index Terms--Genre/Form:
96803
Electronic books.
LC Class. No.: QA274 .L54 2004eb
Dewey Class. No.: 519.23
Statistical Analysis of Stochastic Processes in Time.
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Statistical Analysis of Stochastic Processes in Time.
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[electronic resource].
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2004.
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Cambridge University Press,
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354 p.
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Cover; Half-title; Series-title; Title; Copyright; Contents; Preface; Notation and symbols; 1 What is a stochastic process?; 2 Basics of statistical modelling; 3 Survival processes; 4 Recurrent events; 5 Discrete-time Markov chains; 6 Event histories; 7 Dynamic models; 8 More complex dependencies; 9 Time series; 10 Diffusion and volatility; 11 Dynamic models; 12 Growth curves; 13 Compartment models; 14 Repeated measurements; References; Author index; Subject index
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This introduction to ways of modelling phenomena that occur over time is accessible to anyone with a basic knowledge of statistical ideas. Examples from physical, biological and social sciences show how the principles can be put into practice: data sets and R code for these are supplied on author's website.
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Electronic reproduction.
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Available via World Wide Web.
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Ripley, B. D.
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Ross, S.
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Click here to view book
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http://ebooks.cambridge.org/ebook.jsf?bid=CBO9780511617164
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