Simplex gradient {optimsimplex} | R Documentation |
Simplex Gradient
Description
optimsimplex.gradientfv
determines the simplex gradient of the function
which is computed by the secondary functions optimsimplex.gradcenter
and optimsimplex.gradforward
.
Usage
optimsimplex.gradientfv(this = NULL, fun = NULL, method = "forward",
data = NULL)
optimsimplex.gradcenter(this = NULL, fun = NULL, data = NULL)
optimsimplex.gradforward(this = NULL)
Arguments
this |
An simplex object | ||||
fun |
The function to compute at vertices. The function is expected to have the following input and output arguments:
where x is a row vector and this a user-defined data, i.e. the | ||||
method |
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 | ||||
data |
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.
|
Value
optimsimplex.gradientfv
returns a list with the following elements:
- g
A column vector of function gradient (with length
this$n
).- data
The updated user-defined data.
optimsimplex.gradcenter
returns a list with the following elements:
- g
A column vector of function gradient (with length
this$n
).- data
The updated user-defined data.
optimsimplex.gradforward
returns a column vector of function gradient
(with length this$n
).
Author(s)
Author of Scilab optimsimplex module: Michael Baudin (INRIA - Digiteo)
Author of R adaptation: Sebastien Bihorel (sb.pmlab@gmail.com)
See Also
optimsimplex
,
optimsimplex.dirmat
,
optimsimplex.deltafv