makeSmart: makeSmart Function

In esmail-abdulfattah/smartGrad: Optimization using Smart Numerical Differentiation

makeSmart Function

Description

This function allows you to convert a non-smart numerical gradient to a SMART Gradient

Usage

makeSmart(fn, gr, ..., gr.args = list())

Arguments

fn	A function to be minimized (or maximized),
gr	is an optional generic gradient function of type: gr(fun, x, ...) and it returns the gradient for the "BFGS"
...	Further arguments to be passed to fn and gr.
gr.args	Specific arguments to 'gr' needs to be passed.

Examples

library(lbfgs)
library(stats)

myfun <- function(x) { 100 * (x[2] - x[1]^2)^2 + (1 - x[1])^2}

mygrad  <- function(fun,x) {
  h = 0.001
  grad <- numeric(2)
  grad[1] <- (fun(x + c(h,0)) - fun(x - c(h,0))) / (2 * h)
  grad[2] <- (fun(x + c(0,h)) - fun(x - c(0,h))) / (2 * h)
  return (grad)
}

mySmartgrad = smartGrad::makeSmart(fn = myfun,
                                   gr = mygrad)

x_initial = rnorm(2)
result1 <- stats::optim(par = x_initial,
                        fn = myfun,
                        gr = mySmartgrad,
                        method = c("BFGS"),
                        hessian = FALSE)

result2 <- lbfgs::lbfgs(myfun, mySmartgrad, vars = x_initial)

esmail-abdulfattah/smartGrad documentation built on March 19, 2022, 3:01 p.m.