A heteroscedastic linear regression model is developed from plausible assumptions that describe the time evolution of performance metrics for equipment. The inherited motivation for the related weighted least squares analysis of the model is an essential and attractive selling point to engineers with interest in equipment surveillance methodologies. A simple test for the significance of the heteroscedasticity suggested by a data set is derived and a simulation study is used to evaluate the power of the test and compare it with several other applicable tests that were designed under different contexts. Tolerance intervals within the context of the model are derived, thus generalizing well-known tolerance intervals for ordinary least squares regression. Use of the model and its associated analyses is illustrated with an aerospace application where hundreds of electronic components are continuously monitored by an automated system that flags components that are suspected of unusual degradation patterns.

20. ADi'nAcT Cts a' m peven id i f nmweeaay and Identify by block nuaber) This report examines the combination of two ellipses associated wit fixing the same emitter. Extreme cases are analyzed while intermediate cases are simulated. The effect of combination on the confidence level is examined. The meaning of acceptance or rejecti n-of _th U elipses .z dci6ussea in detail 1 .

20. AUSNACT (cmt"a reverae m-b it nmc.ea md ider tio by block n.umber) This report discusses limitations of algorithms with respect to operator training. Operators can improve algorithm performance thru use of unmodeled data (weather. history of variance, etc.). As an example fixing bias is discussed in detail. OD l 1473 EDITION OF I NOV aS IS OBSOLETE SECURITY CLASSIFICATION OF THIS PAIIE (When Dete Entered) g& LAA ggN

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