Displaying 2 results from an estimated 2 matches for "newtonraphson".
2010 Oct 27
0
Introducing the futile.paradigm, a package for functional dispatching in R
...<- 0
old.x <- x0
while (step < max.steps)
{
# Calls abstract function 'iterate' with definitions below
new.x <- iterate(old.x, algo)
if (converged(new.x, old.x)) break
old.x <- new.x
}
new.x
}
# Implement Newton-Raphson
iterate.nr %when% (algo %isa% NewtonRaphson)
iterate.nr <- function(x, algo) x - algo$f1(x) / algo$f2(x)
# Implement Gradient Descent
iterate.gd %when% (algo %isa% GradientDescent)
iterate.gd <- function(x, algo) x - algo$step * algo$f1(x)
# Create a custom type constructor
create.GradientDescent <- function(T, f1, step=0.01) list...
2010 Oct 27
0
Introducing the futile.paradigm, a package for functional dispatching in R
...<- 0
old.x <- x0
while (step < max.steps)
{
# Calls abstract function 'iterate' with definitions below
new.x <- iterate(old.x, algo)
if (converged(new.x, old.x)) break
old.x <- new.x
}
new.x
}
# Implement Newton-Raphson
iterate.nr %when% (algo %isa% NewtonRaphson)
iterate.nr <- function(x, algo) x - algo$f1(x) / algo$f2(x)
# Implement Gradient Descent
iterate.gd %when% (algo %isa% GradientDescent)
iterate.gd <- function(x, algo) x - algo$step * algo$f1(x)
# Create a custom type constructor
create.GradientDescent <- function(T, f1, step=0.01) list...