r - R 中的优化函数可以接受目标、梯度和粗麻布吗？

Question

我有一个想要优化的复杂目标函数。优化问题需要相当长的时间来优化。幸运的是，我确实有可用的函数的梯度和粗麻布。

R 中是否有一个优化包可以接受所有这三个输入？ “optim”类不接受 Hessian 矩阵。我扫描了CRAN task page for optimization没有任何弹出。

无论如何，我可以使用 ' fminunc 在 MATLAB 中执行优化' 带有 'GradObj' 和 'Hessian' 参数。

Answer 1

我认为包trust信任区域优化可以解决这个问题。来自trust的文档，你看到了

This function carries out a minimization or maximization of a function using a trust region algorithm... (it accepts) an R function that computes value, gradient, and Hessian of the function to be minimized or maximized and returns them as a list with components value, gradient, and hessian.

事实上，我认为它使用与 fminunc 相同的算法。

By default fminunc chooses the large-scale algorithm if you supply the gradient in fun and set GradObj to 'on' using optimset. This algorithm is a subspace trust-region method and is based on the interior-reflective Newton method described in [2] and [3]. Each iteration involves the approximate solution of a large linear system using the method of preconditioned conjugate gradients (PCG). See Large Scale fminunc Algorithm, Trust-Region Methods for Nonlinear Minimization and Preconditioned Conjugate Gradient Method.