View source: R/cv_near_boundary.R
Calculate one and twosided critical values c_{1α}(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].
1 2  SnoopingCVNearBd(S, T, bwratios, kernel, order, db, ngr, alpha = c(0.1, 0.05,
0.01))

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 1α at which to compute critical values 
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