Abstract
ABSTRACTThis paper explores the computation of Circular Error Probable from a bivariate regression model as well as upper confidence limits computed at covariate values of interest. Upper confidence limits were computed based on a bootstrap methodology and a bootstrap calibration of the delta method. The bootstrap calibration provided an improvement in the nominal coverage for the delta method at smaller sample sizes. An example is provided using munition data from an Army test event to show how these approaches can be applied to data sets from test events with small sample sizes.
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