cov_prob_nobias: Unbiased Half-oracle Average Coverage Probability Estimator
In koohyun-kwon/OptACI: Methods to Construct Optimal Average Coverage Confidence Intervals
Description
Usage
Arguments
Value
Examples
Description
Estimates average coverage probability with the same series approximation
procedure as gnB, and then removes the truncation bias.
Usage
1
cov_prob_nobias(chi, lam, th_vec, Jn, xvec)
Arguments
chi
a scalar half-length value χ.
lam
a scalar shrinkage factor λ.
th_vec
a normalized mean vector.
Jn
the order of polynomial approximation.
xvec
normalized observed outcome vector,
corresponding to z_i in the paper.
Value
average coverage probability.
Examples
1
2
3
th_vec <- stats::rnorm(50)
xvec <- stats::rnorm(50, th_vec)
cov_prob_nobias(1, 0.5, th_vec, 2, xvec)
koohyun-kwon/OptACI documentation built on Oct. 6, 2020, 8:09 a.m.
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Description Usage Arguments Value Examples
Description
Estimates average coverage probability with the same series approximation
procedure as gnB, and then removes the truncation bias.
Usage
1 | cov_prob_nobias(chi, lam, th_vec, Jn, xvec)
|
Arguments
chi |
a scalar half-length value χ. |
lam |
a scalar shrinkage factor λ. |
th_vec |
a normalized mean vector. |
Jn |
the order of polynomial approximation. |
xvec |
normalized observed outcome vector, corresponding to z_i in the paper. |
Value
average coverage probability.
Examples
1 2 3 | th_vec <- stats::rnorm(50)
xvec <- stats::rnorm(50, th_vec)
cov_prob_nobias(1, 0.5, th_vec, 2, xvec)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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