summary method for class "ldblm".
# S3 method for ldblm
summary(object,...)A list of class summary.ldblm containing the following components:
number of observations.
the coefficient of determination R2.
Trace of smoother matrix .
the matched call.
the residuals (the response minus fitted values).
the family object used.
smoothing kernel function.
method used to decide the optimal bandwidth.
the optimal bandwidth h used in the fitting proces
(if method.h!=user.h).
value of criterion defined in method.h.
an object of class ldblm.
Result of ldblm.
arguments passed to or from other methods to the low level.
Boj, Eva <evaboj@ub.edu>, Caballe, Adria <adria.caballe@upc.edu>, Delicado, Pedro <pedro.delicado@upc.edu> and Fortiana, Josep <fortiana@ub.edu>
Boj E, Delicado P, Fortiana J (2010). Distance-based local linear regression for functional predictors. Computational Statistics and Data Analysis 54, 429-437.
Boj E, Grane A, Fortiana J, Claramunt MM (2007). Selection of predictors in distance-based regression. Communications in Statistics B - Simulation and Computation 36, 87-98.
Cuadras CM, Arenas C, Fortiana J (1996). Some computational aspects of a distance-based model for prediction. Communications in Statistics B - Simulation and Computation 25, 593-609.
Cuadras C, Arenas C (1990). A distance-based regression model for prediction with mixed data. Communications in Statistics A - Theory and Methods 19, 2261-2279.
Cuadras CM (1989). Distance analysis in discrimination and classification using both continuous and categorical variables. In: Y. Dodge (ed.), Statistical Data Analysis and Inference. Amsterdam, The Netherlands: North-Holland Publishing Co., pp. 459-473.
ldblm for local distance-based linear models.