Lecture

Maximum Likelihood Estimation: Theory

Description

This lecture covers the theory behind Maximum Likelihood Estimation (MLE), discussing properties such as consistency, asymptotic normality, and efficiency. It delves into the information matrix, asymptotic covariance matrix, and the use of MLE in various applications like binary choice models and ordered multiresponse models.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_3uiac2zr

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Ontological neighbourhood

Statistics

Data analysis: Regression analysis

Statistical inference: Mathematical statistics

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