Readme for Implementation of the BHHH algorithm in Python In order to find our code including examples and tests please follow the path src/algorithms. For the documentation as a pdf and html please follow bld/src/documentation.

Python implementation of the BHHH algorithm. Contribute to segsell/bhhh development by creating an account on GitHub.

Python implementation of the BHHH algorithm. Contribute to segsell/bhhh development by creating an account on GitHub.

2025年3月3日 · GitHub is where people build software. More than 150 million people use GitHub to discover, fork, and contribute to over 420 million projects.

This package contains a set of functions and tools for Maximum Likelihood (ML) estimation. The focus of the package is on non-linear optimization from the ML viewpoint, and it provides several convenience wrappers and tools, like BHHH algorithm, variance-covariance matrix, standard errors, and summary methods.

2023年10月16日 · BHHH is a second-order algorithm that (conceptually) uses the self-outer-product of the gradient to approximate the Hessian. This is justified by the information matrix equality in statistics, which states that E(x * x') = E(hessian(x)) , making the self-outer-product an unbiased and consistent estimator of the Hessian (that can usually be ...

Implementation of the Berndt-Hall-Hall-Hausman (BHHH) algorithm. - Pascalheid/BHHH

Implementation of the Berndt-Hall-Hall-Hausman (BHHH) algorithm. - Pascalheid/BHHH

2012年8月31日 · Can we get BHHH or something close to it almost for free? see also issue #429 "LikelihoodModel optimization needs to be generalized" and maybe we also need more flexibility in defining the Hessian that is used in the call to the optimization routines.

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