Description Usage Arguments Details Value Author(s) See Also
Allow the user to set some characteristics of the optimisation algorithm
1 2 3 4 5 6 | kspmControl(interval.upper = NA, interval.lower = NA, trace = FALSE,
optimize.tol = .Machine$double.eps^0.25, NP = NA, itermax = 500,
CR = 0.5, F = 0.8, initialpop = NULL, storepopfrom = itermax + 1,
storepopfreq = 1, p = 0.2, c = 0,
reltol = sqrt(.Machine$double.eps), steptol = itermax,
parallel = FALSE)
|
interval.upper |
integer or vetor of initial maximum value(s) allowed for parameter(s) |
interval.lower |
integer or vetor of initial maximum value(s) allowed for parameter(s) |
trace |
boolean. If TRUE parameters value at each iteration are displayed. |
optimize.tol |
if optimize function is used. See optimize |
NP |
if DEoptim function is used. See DEoptim.control |
itermax |
if DEoptim function is used. See DEoptim.control |
CR |
if DEoptim function is used. See DEoptim.control |
F |
if DEoptim function is used. See DEoptim.control |
initialpop |
if DEoptim function is used. See DEoptim.control |
storepopfrom |
if DEoptim function is used. See DEoptim.control |
storepopfreq |
if DEoptim function is used. See DEoptim.control |
p |
if DEoptim function is used. See DEoptim.control |
c |
if DEoptim function is used. See DEoptim.control |
reltol |
if DEoptim function is used. See DEoptim.control |
steptol |
if DEoptim function is used. See DEoptim.control |
parallel |
if DEoptim function is used. See DEoptim.control |
When only one hyperparameter should be estimated, the optimisation problem calls the optimize function from stats
basic package. Otherwise, it calls the DEoptim function from the package DEoptim
. In both case, the parameters are choosen among the initial interval defined by interval.lower
and interval.upper
.
search.parameters
is an iterative algorithm estimating model parameters and returns the following components:
lambda |
tuning parameters for penalization. |
beta |
vector of coefficients associated with linear part of the model, the size being the number of variable in linear part (including an intercept term). |
alpha |
vector of coefficients associated with kernel part of the model, the size being the sample size. |
Ginv |
a matrix used in several calculations. Ginv = (lambda I + K)^(-1). |
Catherine Schramm, Aurelie Labbe, Celia Greenwood
link get.parameters for computation of parameters at each iteration
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