Maximum Likelihood: Basic Results

Charles A. Rohde
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Charles A. Rohde: Johns Hopkins University, Bloomberg School of Health

Chapter Chapter 7 in Introductory Statistical Inference with the Likelihood Function, 2014, pp 67-83 from Springer

Abstract: Abstract As we have seen once we have an estimator and its sampling distribution we can easily obtain confidence intervals and tests regarding the parameter. We now develop the theory of estimation focusing on the method of maximum likelihood, which for parametric models is the most widely used method. This will also supply us with a collection of statistical methods for important problems.

Keywords: Maximum Likelihood Estimate; Score Function; Maximum Likelihood Estimator; Fisher Information; Multivariate Normal Distribution (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-10461-4_7

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DOI: 10.1007/978-3-319-10461-4_7

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