The np Package - NexTag Supports Open Source Initiatives

npplreg 73residR2MSEMAEMAPECORRSIGNif residuals = TRUE, in-sample or out-of-sample residuals where appropriate(or possible)coefficient of determinationmean squared errormean absolute errormean absolute percentage errorabsolute value of Pearson’s correlation coefficientfraction of observations where fitted and observed values agree in signUsage IssuesIf you are using data of mixed types, then it is advisable to use the data.frame function toconstruct your input data and not cbind, since cbind will typically not work as intended onmixed data types and will coerce the data to the same type.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 compare the coefficient# estimates from the partially linear model with those from a correctly# specified parametric model...