4. Parametric Inference (cont.) and Maximum Likelihood Estimation

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In this lecture, Prof. Rigollet talked about confidence intervals, total variation distance, and Kullback-Leibler divergence.

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Published 07/20/17

24. Generalized Linear Models (cont.)

In this lecture, Prof. Rigollet talked about Hessian, Fisher information, weighted least squares, and iteratively reweighed least squares.

Published 07/20/17

23. Generalized Linear Models (cont.)

In this lecture, Prof. Rigollet talked about strict concavity, optimization methods, quadratic approximation, Newton-Raphson method, and Fisher-scoring method.

Published 07/20/17