cva {ebci} | R Documentation |
Computes the critical value cva_{\alpha}(m_{2}, \kappa)
from Armstrong, Kolesár, and Plagborg-Møller (2020).
cva(m2, kappa = Inf, alpha = 0.05, check = TRUE)
m2 |
Bound on second moment of the normalized bias, |
kappa |
Bound on the kurtosis of the normalized bias,
|
alpha |
Determines confidence level, |
check |
If |
Returns a list with 4 components:
cv
Critical value for constructing two-sided confidence intervals.
alpha
The argument alpha
.
x
Support points for the least favorable distribution for the
squared normalized bias, b^2
.
p
Probabilities associated with the support points.
Armstrong, Timothy B., Kolesár, Michal, and Plagborg-Møller, Mikkel (2020): Robust Empirical Bayes Confidence Intervals, https://arxiv.org/abs/2004.03448
# Usual critical value
cva(m2=0, kappa=Inf, alpha=0.05)
# Larger critical value that takes bias into account. Only uses second moment
# constraint on normalized bias.
cva(m2=4, kappa=Inf, alpha=0.05)
# Add a constraint on kurtosis. This tightens the critical value.
cva(m2=4, kappa=3, alpha=0.05)