The np Package - NexTag Supports Open Source Initiatives

80 npplregbwCaution: multivariate data-driven bandwidth selection methods are, by their nature, computationallyintensive. Virtually all methods require dropping the ith observation from the data set, computingan object, repeating this for all observations in the sample, then averaging each of these leave-oneoutestimates for a given value of the bandwidth vector, and only then repeating this a large numberof times in order to conduct multivariate numerical minimization/maximization. Furthermore, dueto the potential for local minima/maxima, restarting this procedure a large number of times mayoften be necessary. This can be frustrating for users possessing large datasets. For exploratorypurposes, you may wish to override the default search tolerances, say, setting ftol=.01 and tol=.01and conduct multistarting (the default is to restart min(5, ncol(zdat)) times) as is done for a numberof examples. Once the procedure terminates, you can restart search with default tolerances usingthose bandwidths obtained from the less rigorous search (i.e., set bws=bw on subsequent calls tothis routine where bw is the initial bandwidth object). A version of this package using the Rmpiwrapper is under development that allows one to deploy this software in a clustered computingenvironment to facilitate computation involving large datasets.Author(s)Tristen Hayfield 〈hayfield@phys.ethz.ch〉, Jeffrey S. Racine 〈racinej@mcmaster.ca〉ReferencesAitchison, J. and C.G.G. Aitken (1976), “Multivariate binary discrimination by the kernel method,”Biometrika, 63, 413-420.Li, Q. and J.S. Racine (2007), Nonparametric Econometrics: Theory and Practice, Princeton UniversityPress.Li, Q. and J.S. Racine (2004), “Cross-validated local linear nonparametric regression,” StatisticaSinica, 14, 485-512.Racine, J.S. and L. Liu (2006), “A partially linear kernel estimator for categorical data,” manuscript.Pagan, A. and A. Ullah (1999), Nonparametric Econometrics, Cambridge University Press.Racine, J.S. and Q. Li (2004), “Nonparametric estimation of regression functions with both categoricaland continuous Data,” Journal of Econometrics, 119, 99-130.Robinson, P.M. (1988), “Root-n-consistent semiparametric regression,” Econometrica, 56, 931-954.Wang, M.C. and J. van Ryzin (1981), “A class of smooth estimators for discrete distributions,”Biometrika, 68, 301-309.See Alsonpregbw, npregExamples# EXAMPLE 1 (INTERFACE=FORMULA): For this example, we simulate an# example for a partially linear model and perform bandwidth selectionset.seed(123)n