optimsimplex.gradientfv determines the simplex gradient of the function
which is computed by the secondary functions optimsimplex.gradcenter
and optimsimplex.gradforward.
optimsimplex.gradientfv(this = NULL, fun = NULL, method = "forward",
data = NULL)
optimsimplex.gradcenter(this = NULL, fun = NULL, data = NULL)
optimsimplex.gradforward(this = NULL)An simplex object
The function to compute at vertices. The function is expected to have the following input and output arguments:
| myfunction <- function(x, this){ |
| ... |
| return(list(f=f,this=this)) |
where x is a row vector and this a user-defined data, i.e. the data
argument.
The method used to compute the simplex gradient. Two methods
are available: 'forward' and 'centered'. The 'forward' method uses the
current simplex to compute the gradient (using optimsimplex.dirmat
and optimsimplex.deltafv). The 'centered' method creates an
intermediate simplex and computes the average.
A user-defined data passed to the function. If data is provided,
it is passed to the callback function both as an input and output argument.
data may be used if the function uses some additionnal parameters. It
is returned as an output parameter because the function may modify the data
while computing the function value. This feature may be used, for example,
to count the number of times that the function has been called.
optimsimplex.gradientfv returns a list with the following elements:
A column vector of function gradient (with length this$n).
The updated user-defined data.
optimsimplex.gradcenter returns a list with the following elements:
A column vector of function gradient (with length this$n).
The updated user-defined data.
optimsimplex.gradforward returns a column vector of function gradient
(with length this$n).