fast_grad: Fast Numerical Gradient

In optimflex: Derivative-Based Optimization with User-Defined Convergence Criteria

Fast Numerical Gradient

Description

Provides a high-speed numerical gradient using forward or central differences.

Usage

fast_grad(f, x, diff_method = c("forward", "central"), ...)

Arguments

f	Function. The objective function.
x	Numeric vector. Parameters at which to evaluate the gradient.
diff_method	String. Differentiation method: "forward" or "central".
...	Additional arguments passed to f.

Value

A numeric vector of gradients.

optimflex documentation built on April 11, 2026, 5:06 p.m.