Optimum Designs for Second Order Processes with General Linear Means.
GEORGIA TECH RESEARCH INST ATLANTA
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In the experimentation of any of the sciences, physical, biological, or social there arise situations in which the exact conduct of a specified experiment is under the control of an experimenter. The experimenter must therefore make a decision. Where the conduct of an individual experiment may be costly or where there are a large number of possible experiments a premium is placed upon the quality of this decision. This research was concerned with the selection of the proper experiments when the data are time recordings. Of special interest was data which arise as solutions to linear white noise random differential equations. Approximately optimal designs were effectively characterized for this case. Similar characterizations were shown to hold for partial differential operators and random fields. Work was also begun on the identification of experiments which are robust against departures from the assumed model. Results were obtained for both scalar and time recording data. Author
- Statistics and Probability