Conditional confidence intervals for classification error rate

An observation is to be classified into one of several multivariate normal populations with equal covariance matrix. When the parameters are unknown, independent training samples are taken from the populations. We consider the construction of confidence intervals for the conditional error rate. The cases of two populations and three populations are studied in detail. We propose the conditional jackknife confidence interval and the conditional bootstrap confidence intervals of the conditional error rate. A Monte Carlo study is conducted to compare the confidence intervals.