SnoopingCVNearBd: Snooping-adjusted critical values for estimation near a...

Description Usage Arguments

View source: R/cv_near_boundary.R

Description

Calculate one- and two-sided critical values c_{1-α}(t;k) for values of t in bwratios based on evaluating the Gaussian process \hat{\mathbb{H}}(h) at ngr values of h in the interval [1/t,1].

Usage

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SnoopingCVNearBd(S, T, bwratios, kernel, order, db, ngr, alpha = c(0.1, 0.05,
  0.01))

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

bwratios

Bandwidth ratios of maximum to minimum bandwidth for which to compute critical values

kernel

Kernel function k(u) supported on [-1,1] that takes a vector or a matrix as an argument u.

order

Order of local linear regression

db

Local distance to boundary, equal to x_{0}/\underline{h}, where x_{0} is point of interest.

ngr

number of grid points at which to evaluate the Gaussian process

alpha

A vector of values determining the confidence level 1-α at which to compute critical values


kolesarm/BWSnooping documentation built on June 20, 2018, 3:44 p.m.