MLAD: Stata module to perform maximum likelihood using automatic differentiation
Paul Christopher Lambert · RePEc: Research Papers in Economics · 2021
mlad maximizes a log-likelihood function where the likelihood function is programmed in Python. This enables the gradients and Hessian matrix to be obtained using automatic differentiation and to take advantage of using multiple CPUs. With large datasets mlad tends to be substantially faster than ml and has the important advantage that you don't have to derive the gradients and the Hessian matrix analytically as these are obtained using automatic differentiation.