DFSnoopingCV: Data frame of snooping-adjusted critical values for common...

In kolesarm/BWSnooping: Confidence invervals robust to bandwidth snooping

Description

Calculates a data frame of snooping-adjusted critical values for uniform, triangular, and epanechnikov kernels and local constant, linear, and quadratic regression in the interior and on the boundary. Also calculates coverage of confidence intervals without snooping adjustment.

Usage

DFSnoopingCV(S, T, ngr)

Arguments

S	number of draws of the Gaussian process \hat{\mathbb{H}}(h)
T	number of draws from a normal distribution in each draw of the Gaussian process
ngr	number of grid points on which to evaluate the Gaussian process \hat{\mathbb{H}}(s), or else a vector of grid points

Value

data frame in the same format as the snoopingcvs data frame, which was generated using this funcion.

kolesarm/BWSnooping documentation built on May 20, 2019, 12:54 p.m.