The package npbr is the first free specialized software for data edge and frontier analysis in the statistical literature. It provides a variety of functions for the best known and most innovative approaches to nonparametric boundary estimation. The selected methods are concerned with empirical, smoothed, unrestricted as well as constrained fits under both single and multiple shape constraints. They also cover data envelopment techniques as well as robust approaches to outliers. The routines included in npbr are user friendly and afford a large degree of flexibility in the estimation specifications. They provide smoothing parameter selection for the modern local linear and polynomial spline methods as well as for some promising extreme value techniques. Also, they seamlessly allow for Monte Carlo comparisons among the implemented estimation procedures. This package will be very useful for statisticians and applied researchers interested in employing nonparametric boundary regression models. Its use is illustrated with a number of empirical applications and simulated examples
boundary curve; concavity; extreme-values; kernel smoothing; linear programming; local linear fitting; monotonicity; multiple shape constraints; piecewise polynomials; spline smoothing; R;
- C14: Semiparametric and Nonparametric Methods: General
- C61: Optimization Techniques • Programming Models • Dynamic Analysis
- C63: Computational Techniques • Simulation Modeling
- C87: Econometric Software
Abdelaati Daouia, Thibault Laurent, and Hohsuk Noh, “npbr: A Package for Nonparametric Boundary Regression in R”, TSE Working Paper, n. 15-576, May 2015.
Abdelaati Daouia, Thibault Laurent, and Hohsuk Noh, “npbr: A Package for Nonparametric Boundary Regression in R”, Journal of Statistical Software, vol. 79, n. 9, August 2017, pp. 1–43.
Journal of Statistical Software, vol. 79, n. 9, August 2017, pp. 1–43