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Principles of Statistical Inference: Likelihood and the Bayesian Paradigm
Published online by Cambridge University Press: 21 July 2017
Abstract
We review two foundations of statistical inference, the theory of likelihood and the Bayesian paradigm. We begin by applying principles of likelihood to generate point estimators (maximum likelihood estimators) and hypothesis tests (likelihood ratio tests). We then describe the Bayesian approach, focusing on two controversial aspects: the use of prior information and subjective probability. We illustrate these analyses using simple examples.
- Type
- General Toolkit
- Information
- The Paleontological Society Papers , Volume 16: Quantitative Methods in Paleobiology , October 2010 , pp. 1 - 18
- Copyright
- Copyright © 2010 by the Paleontological Society
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