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- Author:
-
Clayton Scott,
Rob Nowak
- Subject:
- Mathematics and Statistics, Science and Technology
- Institution Name:
- Connexions
- Collection:
-
Connexions
- Grade Level:
- Post-secondary
- Abstract:
This module introduces the maximum likelihood estimator. We show how the MLE implements the likelihood principle. Methods for computing the MLE are covered. Properties of the MLE are discussed including asymptotic efficiency and invariance under reparameterization.
- Course Type:
- Learning Module
- Languages:
- English
- Material Type:
- Readings, Syllabi
- Media Format:
- Text/HTML
- Conditions of Use:
-
Creative Commons Attribution 1.0
No restrictions on your remixing, redistributing, or making derivative works.
Give credit to the author, as required.
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restrictions, including how it is shared.
Your redistributing comes with some restrictions. Do not remix or make
derivative works.
Copyrighted materials, available under Fair Use and the TEACH Act for US-based
educators, or other custom arrangements. Go to the resource provider to see
their individual restrictions.
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