The np Package - NexTag Supports Open Source Initiatives

npudens 37Author(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 (2003), “Nonparametric estimation of distributions with categorical andcontinuous data,” Journal of Multivariate Analysis, 86, 266-292.Ouyang, D. and Q. Li and J.S. Racine (2006), “Cross-validation and the estimation of probabilitydistributions with categorical data,” Journal of Nonparametric Statistics, 18, 69-100.Pagan, A. and A. Ullah (1999), Nonparametric Econometrics, Cambridge University Press.Scott, D.W. (1992), Multivariate Density Estimation. Theory, Practice and Visualization, NewYork: Wiley.Silverman, B.W. (1986), Density Estimation, London: Chapman and Hall.Wang, M.C. and J. van Ryzin (1981), “A class of smooth estimators for discrete distributions,”Biometrika, 68, 301-309.See Alsonpudensbw , densityExamples# EXAMPLE 1 (INTERFACE=FORMULA): For this example, we load Giovanni# Baiocchi's Italian GDP panel (see Italy for details), then create a# data frame in which year is an ordered factor, GDP is continuous,# compute bandwidths using likelihood cross-validation, then create a# grid of data on which the density will be evaluated for plotting# purposes.data("Italy")attach(Italy)# Compute bandwidths using likelihood cross-validation (default), but we# override the default search tolerances to speed things up as this is a# well-behaved dataset (don't of course do this in general).bw