This lecture covers the concept of likelihood ratio test for detection and estimation, focusing on decision functions, notation, and the importance of likelihood in statistical analysis.
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Covers Likelihood Ratio Tests, their optimality, and extensions in hypothesis testing, including Wilks' Theorem and the relationship with Confidence Intervals.
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