Confidence intervals for the conditional probability of misallocation in discriminant analysis.
In this study we are concerned with the construction of confidence intervals for the conditional probability of misallocation associated with Anderson's classification statistics, W. The available methods of computing confidence intervals for the conditional probability are not satisfactory in practice, mainly because the intervals obtained are fairly inaccurate. A new method is presented which enables intervals with almost the desired level of confidence to be easily computed from the initial samples on which W is based.
D009010:Monte Carlo Method; D012494:Sampling Studies; D013223:Statistics as Topic