Computes a confidence interval for a specified linear combination of
the regression parameters in a linear regression model with iid normal
errors with unknown variance when there is uncertain prior information
that a distinct specified linear combination of the regression
parameters takes a specified number. This confidence interval, found by
numerical nonlinear constrained optimization, has the required minimum coverage
and utilizes this uncertain prior information through desirable
expected length properties. This confidence interval is proposed by
Kabaila, P. and Giri, K. (2009)
The goal of ciuupi2 is to compute the Kabaila and Giri (2009) confidence interval that utilizes the uncertain prior information in linear regression with unknown error variance. These confidence intervals have desirable coverage and expected length properties.
You can install the released version of ciuupi2 from CRAN with:
install.packages("ciuupi2")