Perform point estimation of statistical parameters using maximum likelihood estimation (MLE) applying criteria such as consistency, unbiasedness, sufficiency, efficiency, minimum variance, and mean square error (including censoring and truncation).
Free CAS MAS-I (Modern Actuarial Statistics I) lesson in Statistics. 9 min read, ~1,326 words.
MLE maximizes; solve and verify a maximum. Cramér-Rao lower bound is with; MLEs are asymptotically efficient. MLEs are consistent, asymptotically normal, asymptotically unbiased, and functions of any sufficient statistic, but often biased in finite samples. MSE variance bias; a biased estimator can still beat an unbiased one on MSE. Censored...
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What this lesson covers
- Content
- Example 1
- Example 2
- Common Mistakes
- Key Takeaways
- Exam Shortcuts
Learning objectives
- B8
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