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Sinopsis
This 2006 graduate text introduces some of the most common computer-intensive methods, including Maximum Likelihood, Monte Carlo and Bayesian methods. Examples of their application using biological data are provided, along with a series of software instructions for the statistical software package S-PLUS and problems and solutions are included to aid understanding.
"Sinopsis" puede pertenecer a otra edición de este libro.
Críticas
"The strength of the work is its coverage of contemporary, computer-intensive methods and the detailed templates provided for implementing each one. Many people learn most quickly by working through an example that resembles a problem of their own, and so I think this aspect of the book will be widely appreciated."
N. Thompson Hobbs for Ecology
"The author's presentation of the material is meticulous in terms of organization and the use of well-defined notation. Nearly every method presented in the text has accompanying code in S-PLUS. Examples are interesting and most always involve real data. The topics are presented in a delightfully simple and intuitive fashion."
David H. Annis for The American Statistician
Biografía del autor
Derek A. Roff is a Professor in the Department of Biology at the University of California, Riverside.
"Sobre este título" puede pertenecer a otra edición de este libro.
- EditorialCambridge University Press
- Año de publicación2006
- ISBN 10 0521846285
- ISBN 13 9780521846288
- EncuadernaciónTapa dura
- IdiomaInglés
- Número de páginas378
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Introduction to Computer-Intensive Methods of Data Analysis in Biology
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Introduction to Computer-Intensive Methods of Data Analysis in Biology (Hardcover)
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Hardcover. Condición: new. Hardcover. This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter. This 2006 graduate text introduces some of the most common computer-intensive methods, including Maximum Likelihood, Monte Carlo and Bayesian methods. Examples of their application using biological data are provided, along with a series of software instructions for the statistical software package S-PLUS and problems and solutions are included to aid understanding. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9780521846288
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Hardcover. Condición: new. Hardcover. This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter. This 2006 graduate text introduces some of the most common computer-intensive methods, including Maximum Likelihood, Monte Carlo and Bayesian methods. Examples of their application using biological data are provided, along with a series of software instructions for the statistical software package S-PLUS and problems and solutions are included to aid understanding. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9780521846288
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Introduction to Computer-Intensive Methods of Data Analysis in Biology
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Cambridge University Press, 2006
ISBN 10: 0521846285
ISBN 13: 9780521846288
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This 2006 graduate text introduces some of the most common computer-intensive methods, including Maximum Likelihood, Monte Carlo and Bayesian methods. Examples of their application using biological data are provided, along with a series of software instruct. Nº de ref. del artículo: 594764618
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