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Cambridge: Statistische Analyse stochastischer Prozesse in der Zeit, Lindsey, HC

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ISBN
9780521837415

Über dieses Produkt

Product Identifiers

Publisher
Cambridge University Press
ISBN-10
0521837413
ISBN-13
9780521837415
eBay Product ID (ePID)
30202303

Product Key Features

Number of Pages
354 Pages
Publication Name
Statistical Analysis of Stochastic Processes in Time
Language
English
Subject
Probability & Statistics / General, Probability & Statistics / Multivariate Analysis
Publication Year
2004
Type
Textbook
Subject Area
Mathematics
Author
J. K. Lindsey
Series
Cambridge Series in Statistical and Probabilistic Mathematics Ser.
Format
Hardcover

Dimensions

Item Height
0.8 in
Item Weight
29.3 Oz
Item Length
10 in
Item Width
7 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
2004-045684
Dewey Edition
22
Reviews
'This book is an extraordinary piece of literature ... It is simply a masterpiece and even the most experienced statistician will learn a thing or two from this text. ... It is more than a mere cookery book type of statistical commands, output and interpretation but, rather, a deep understanding and appreciation of the statistical thinking process. ... The book is well written and would be good reading for applied statisticians as well as all post-graduate and faculty members who interact with data. Libraries should purchase a copy.' Journal of the Royal Statistical Society, Series A, 'This book is an extraordinary piece of literature … It is simply a masterpiece and even the most experienced statistician will learn a thing or two from this text. … It is more than a mere cookery book type of statistical commands, output and interpretation but, rather, a deep understanding and appreciation of the statistical thinking process. … The book is well written and would be good reading for applied statisticians as well as all post-graduate and faculty members who interact with data. Libraries should purchase a copy.' Journal of the Royal Statistical Society, Series A, 'This book is an extraordinary piece of literature ... It is simply a masterpiece and even the most experienced statistician will learn a thing or two from this text. ... It is more than a mere cookery book type of statistical commands, output and interpretation but, rather, a deep understanding and appreciation of the statistical thinking process. ... The book is well written and would be good reading for applied statisticians as well as all post-graduate and faculty members who interact with data. Libraries should purchase a copy.' Journal of the Royal Statistical Society, "The text is aimed at scientists looking for realistic statistical models to help in understanding and explaining the specific conditions of their empirical data." Quarterly of Applied Mathematics, "This book is an extraordinary piece of literature which gives the non-fluent statistician the ability to model random events. It is simply a masterpiece and even the most experienced statistician will learn a thing or two from this text...Examples in this text not only use real data but also carry the reader through the entire statistical thinking process...The book is well written and would be good reading for applied statisticians as well as all post-graduate and faculty members who interact with data. Libraries should purchase a copy." Journal of the Royal Statistical Society, '... the book fills a gap between the more fundamental, topical volumes around, and more popular texts on these matters. it is very well readable, and it provides both an excellent introduction and a good overview over much of stochastic methods applicable in longitudinal data.' Environmental and Ecological Statistics, '… the book fills a gap between the more fundamental, topical volumes around, and more popular texts on these matters. it is very well readable, and it provides both an excellent introduction and a good overview over much of stochastic methods applicable in longitudinal data.' Environmental and Ecological Statistics, "...I envision an audience of masters-and doctoral-level epidemiology and biostatistics students who could benefit from a course from this text. Students with a fear of the technical mathematics of stochastics, but with a need for practical analyses of time-correlated data, may find this text useful before a formal course in stochastics." Robert Lund, Journal of the American Statistical Association
Series Volume Number
Series Number 14
Illustrated
Yes
Dewey Decimal
519.2/3
Table Of Content
Preface; Part I. Basic Principles: 1. What is a stochastic process?; 2. Normal theory models and extensions; Part II. Categorical State Space: 3. Survival processes; 4. Recurrent events; 5. Discrete-time Markov chains; 6. Event histories; 7. Dynamics models; 8. More complex dependencies; Part III. Continuous State Space: 9. Time series; 10. Growth curves; 11. Dynamic models; 12. Repeated measurements; Bibliography; Author index; Subject index.
Synopsis
This introduction to ways of modelling a wide variety of phenomena that occur over time is accessible to anyone with a basic knowledge of statistical ideas. J.K. Lindsey concentrates on tractable models involving simple processes for which explicit probability models, hence likelihood functions, can be specified. (These models are the most useful in statistical applications modelling empirical data.) Examples are drawn from physical, biological and social sciences, to show how the book's underlying ideas can be applied, and data sets and R code are supplied for them. Author resource page: http: //popgen.unimaas.nl/~jlindsey/books.html, This introduction to ways of modelling a wide variety of phenomena that occur over time is accessible to anyone with a basic knowledge of statistical ideas. J.K. Lindsey concentrates on tractable models involving simple processes for which explicit probability models, hence likelihood functions, can be specified. (These models are the most useful in statistical applications modelling empirical data.) Examples are drawn from physical, biological and social sciences, to show how the book's underlying ideas can be applied, and data sets and R code are supplied for them. Author resource page: http: //popgen.unimaas.nl/ jlindsey/books.html, This 2004 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., This book was first published in 2004. Many observed phenomena, from the changing health of a patient to values on the stock market, are characterised by quantities that vary over time: stochastic processes are designed to study them. This book introduces practical methods of applying stochastic processes to an audience knowledgeable only in basic statistics. It covers almost all aspects of the subject and presents the theory in an easily accessible form that is highlighted by application to many examples. These examples arise from dozens of areas, from sociology through medicine to engineering. Complementing these are exercise sets making the book suited for introductory courses in stochastic processes. Software (available from www.cambridge.org) is provided for the freely available R system for the reader to apply to all the models presented.
LC Classification Number
QA274 .L54 2004

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