Density estimation applications for outlier detection.

Abstract

Nonparametric estimates of joint, conditional and marginal probability densities can be used to estimate the relative probability of a data point's recurrence. Outlier, unusual or abnormal values of a random variate tend to be those which are unlikely to recur. As part of an interactive graphical system, a procedure has been implemented which enables a biomedical researcher to view both the estimated probability and the numerical value of a data point's coordinates. This display circumvents the problem of interpreting a normal range in two or more dimensions and can thus be more easily generalized than most alternative outlier detection procedures.