- Newton-like optimization methods. When using Newton-like methods, Newton-Raphson, Fisher Scoring [7], and Average-Information [4] methods are available. Math is done internally by the optimized linear algebra routines in the numpy [9] and scipy [5] software packages. To compare models a likelihood-ratio test is provided.
- This monograph is about a class of optimization algorithms called proximal algorithms. Much like Newton's method is a standard tool for solving unconstrained smooth optimization problems of modest size, proximal algorithms can be viewed as an analogous tool for nonsmooth, constrained, large-scale, or distributed versions of these problems.
- In numerical analysis, Newton's method, also known as the Newton–Raphson method, named after Isaac Newton and Joseph Raphson, is a root-finding algorithm which produces successively better approximations to the roots (or zeroes) of a real-valued function.

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