On a classification rule for multiple measurements

✍ Scribed by A.K. Gupta

• Publisher: Elsevier Science
• Year: 1986
• Tongue: English
• Weight: 377 KB
• Volume: 12
• Category: Article
• ISSN: 0898-1221
• DOI: 10.1016/0898-1221(86)90082-9

✦ Synopsis

In this paper an optimum procedure, based on the maximum-likelihood criterion, for classification into one of two populations has been studied when multiple observations are available on the same variable for each individual. The distribution of the classification statistic, which turns out to be a nonlinear function of the mean and variance of the observations of the individual, are derived, and formulae (exact and approximate) for the computation of the conditional probability of misclassification are given when the parameters are known, as well as when the parameters are unknown. This procedure is further extended to more than two populations.