rosen | R Documentation |
Test function 1 from the More', Garbow and Hillstrom paper.
rosen()
The objective function is the sum of m
functions, each of n
parameters.
Dimensions: Number of parameters n = 2
, number of summand
functions m = 2
.
Minima: f = 0
at (1, 1)
A list containing:
fn
Objective function which calculates the value given input
parameter vector.
gr
Gradient function which calculates the gradient vector
given input parameter vector.
fg
A function which, given the parameter vector, calculates
both the objective value and gradient, returning a list with members
fn
and gr
, respectively.
x0
Standard starting point.
More', J. J., Garbow, B. S., & Hillstrom, K. E. (1981). Testing unconstrained optimization software. ACM Transactions on Mathematical Software (TOMS), 7(1), 17-41. \Sexpr[results=rd]{tools:::Rd_expr_doi("doi.org/10.1145/355934.355936")}
Rosenbrock, H. (1960). An automatic method for finding the greatest or least value of a function. The Computer Journal, 3(3), 175-184. \Sexpr[results=rd]{tools:::Rd_expr_doi("doi.org/10.1093/comjnl/3.3.175")}
fun <- rosen()
# Optimize using the standard starting point
x0 <- fun$x0
res_x0 <- stats::optim(par = x0, fn = fun$fn, gr = fun$gr, method =
"L-BFGS-B")
# Use your own starting point
res <- stats::optim(c(0.1, 0.2), fun$fn, fun$gr, method = "L-BFGS-B")
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