IDENTIFICATION OF THE LARGEST INDIVIDUAL-SAMPLE VALUE USING COMPOSITESAMPLE DATA AND CERTAIN MODIFICATIONS OF THE SWEEP-OUT METHOD

Cost-effective hotspot identification is an important issue in hazardo us waste site characterization and evaluation. Composite sampling tech niques are known to be cost effective when the cost of measurement is substantially higher than the cost of sampling. Although compositing i ncurs no loss of information on the means, information on individual s ample values is lost due to compositing. In particular, if the interes t is in identifying the largest individual sample value, the composite sampling techniques are not able to do so. Under certain assumptions, it may be possible to satisfactorily predict individual sample values using the composite sample data, but it is not generally possible to identify the largest individual sample value. In this paper, we propos e two methods of identifying the largest individual sample value with some additional measurement effort. Both methods are modifications of the simple sweep-out method proposed earlier. Since analytical results do not seem to be feasible, performance of the proposed methods is as sessed via simulation. The simulation results show that both the propo sed methods, namely the locally sequential sweep-out and the globally sequential sweep-out, are better than the simple sweep-out method.