NR: Newton-Raphson method

Description Usage Arguments Details Examples

View source: R/optims.R

Description

Newton-Raphson method

Usage

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NR(
  start,
  objective = NULL,
  gradient = NULL,
  hessian = NULL,
  control,
  args = NULL,
  ...
)

Arguments

start

Starting value

objective

Optional objective function (used for selecting step length)

gradient

gradient

hessian

hessian (if NULL a numerical derivative is used)

control

optimization arguments (see details)

args

Optional list of arguments parsed to objective, gradient and hessian

...

additional arguments parsed to lower level functions

Details

control should be a list with one or more of the following components:

Examples

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# Objective function with gradient and hessian as attributes
f <- function(z) {
   x <- z[1]; y <- z[2]
   val <- x^2 + x*y^2 + x + y
   structure(val, gradient=c(2*x+y^2+1, 2*y*x+1),
             hessian=rbind(c(2,2*y),c(2*y,2*x)))
}
NR(c(0,0),f)

# Parsing arguments to the function and
g <- function(x,y) (x*y+1)^2
NR(0, gradient=g, args=list(y=2), control=list(trace=1,tol=1e-20))

kkholst/lava documentation built on Sept. 27, 2020, 2:34 p.m.