# Maximum Likelihood Estimation with Stata, Fifth Edition

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## Beschreibung

**Book Highlights**

- Learn about maximum likelihood estimation and how to write your own maximum likelihood estimator in Stata using the
**ml**command.

- See how to easily incorporate robust and cluster–robust standard errors, constraints, support for survey data, and other features that are common to many official Stata commands.

- Learn how to write a complete estimation command.

- Find out how to take advantage of Mata, Stata's matrix programming language, either to write your own likelihood evaluator that is used with the
**ml**command or to implement a maximum likelihood estimator fully within Mata with the**moptimize()**suite of functions.

**New in the fifth edition**

- Updates for modern syntax and features

- A new chapter on the
**mlexp**command, which allows you to specify a likelihood and perform estimation without any programming

- A new chapter on Mata's
**moptimize()**suite of functions, which allows you to implement maximum likelihood estimators entirely within Mata

- Updated examples, including a new example of implementing a bivariate Poisson model that takes the researcher through the entire process of deriving a likelihood through writing a full-fledged estimation command