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].
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 1-α at which to compute critical values |
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