fastfun-class: Class for fast to compute objective.

Description

Class for fast to compute objective.

Usage

# S4 method for fastfun
predict(object, newdata, ...)
# S4 method for fastfun
update(object, newX, newy, ...)
# S4 method for fastfun
simulate(object, nsim, seed, newdata, cond, nugget.sim, checkNames, ...)

Arguments

object: fastfun object
newdata: an optional vector, matrix or data frame containing the points where to perform predictions. Default is NULL: simulation is performed at design points specified in object.
...: further arguments (not used)
newX: Matrix of the new location for the design
newy: Matrix of the responses at newX
nsim: an optional number specifying the number of response vectors to simulate. Default is 1.
seed: usual seed argument of method simulate. Not used.
cond: an optional boolean indicating the type of simulations. Not used.
nugget.sim: an optional number corresponding to a numerical nugget effect. Not used.
checkNames: an optional boolean. Not used.

Methods (by generic)

predict(fastfun): Predict(by evaluating fun) the result at a new observation.
update(fastfun): Update the X and y slots with a new design and observation.
simulate(fastfun): Simulate responses values (for compatibility with methods using [DiceKriging::simulate()])

Slots

d: spatial dimension,

n

observations number,

X

the design of experiments, size n x d,

y

the observations, size n x 1,

fun

the evaluator function.

Objects from the Class

To create a fastfun object, use fastfun. See also this function for more details and examples.