print.summary.sfplsim {fsemipar} | R Documentation |
Summarise information from SFPLSIM estimation
Description
summary
and print
functions for sfplsim.kNN.fit
and sfplsim.kernel.fit
.
Usage
## S3 method for class 'sfplsim.kernel'
print(x, ...)
## S3 method for class 'sfplsim.kNN'
print(x, ...)
## S3 method for class 'sfplsim.kernel'
summary(object, ...)
## S3 method for class 'sfplsim.kNN'
summary(object, ...)
Arguments
x |
Output of the |
... |
Further arguments. |
object |
Output of the |
Value
The matched call.
The optimal value of the tunning parameter (
h.opt
ork.opt
).Coefficients of
\hat{\theta}
in the B-spline basis (theta.est
): a vector oflength(order.Bspline+nknot.theta).
The estimated vector of linear coefficients (
beta.est
).The number of non-zero components in
beta.est
.The indexes of the non-zero components in
beta.est
.The optimal value of the penalisation parameter (
lambda.opt
).The optimal value of the criterion function, i.e. the value obtained with
lambda.opt
,vn.opt
andh.opt
/k.opt
Minimum value of the penalised least-squares function. That is, the value obtained using
theta.est
,beta.est
andlambda.opt
.The penalty function used.
The criterion used to select the tuning parameter, the penalisation parameter and
vn
.The optimal value of
vn
.
Author(s)
German Aneiros Perez german.aneiros@udc.es
Silvia Novo Diaz snovo@est-econ.uc3m.es
See Also
sfplsim.kernel.fit
and sfplsim.kNN.fit
.