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This is the first book on the maximum entropy and Bayesian methods aimed at senior undergraduates in science and engineering. It takes the mystery out of statistics by showing how a few fundamental rules can be used to tackle a wide variety of problems in data analysis. After explaining thebasic principles of Bayesian probability theory, their use is illustrated with a variety of examples ranging from elementary parameter estimation to image processing. Other topics covered include reliability analysis, multivariate optimization, least squares and maximum likelihood,error-propagation, hypothesis testing, maximum entropy, and experimental design. As a logical and unified approach to the subject of data analysis, with a self-contained tutorial approach, this work will be valued by instructors and students alike.
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Data Analysis, Devinderjit Singh Sivia
- Taal
- Jaar van publicatie
- 1996
- Bindwijze
- (Paperback),
- Staat van het boek
- Goed
- Prijs
- € 5,99
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- Titel
- Data Analysis
- Ondertitel
- A Bayesian Tutorial
- Taal
- Engels
- Auteurs
- Devinderjit Singh Sivia
- Uitgever
- Oxford University Press
- Jaar van publicatie
- 1996
- Formaat
- Paperback
- Aantal pagina's
- 200
- ISBN10
- 0198518897
- ISBN13
- 9780198518891
- Reeks
- Aantekening
- This is the first book on the maximum entropy and Bayesian methods aimed at senior undergraduates in science and engineering. It takes the mystery out of statistics by showing how a few fundamental rules can be used to tackle a wide variety of problems in data analysis. After explaining thebasic principles of Bayesian probability theory, their use is illustrated with a variety of examples ranging from elementary parameter estimation to image processing. Other topics covered include reliability analysis, multivariate optimization, least squares and maximum likelihood,error-propagation, hypothesis testing, maximum entropy, and experimental design. As a logical and unified approach to the subject of data analysis, with a self-contained tutorial approach, this work will be valued by instructors and students alike.