SCGoptim {tigre} | R Documentation |
Optimise the given function using (scaled) conjugate gradients.
optimiDefaultOptions() SCGoptim(x, fn, grad, options, ...) CGoptim(x, fn, grad, options, ...) modelOptimise(model, options, ...)
model |
the model to be optimised. |
x |
initial parameter values. |
fn |
objective function to minimise |
grad |
gradient function of the objective |
options |
options structure like one returned by
|
... |
extra arguments to pass to fn and grad |
options |
an options structure |
newParams |
optimised parameter values |
model |
the optimised model. |
## Not run to speed up package checks # model <- GPLearn(..., dontOptimise=TRUE) # options <- optimiDefaultOptions() # model <- modelOptimise(model, options)