Abstract
Linear regression modeling is an extremely powerful data analysis tool, useful for a variety of inferential tasks such as prediction, parameter estimation and data description. In this section we give a very brief introduction to the linear regression model and the corresponding Bayesian approach to estimation. Additionally, we discuss the relationship between Bayesian and ordinary least squares regression estimates.
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© 2009 Springer Science+Business Media, LLC
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Hoff, P.D. (2009). Linear regression. In: A First Course in Bayesian Statistical Methods. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-92407-6_9
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DOI: https://doi.org/10.1007/978-0-387-92407-6_9
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Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-92299-7
Online ISBN: 978-0-387-92407-6
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