JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.. Biometrika Trust is collaborating with JSTOR to digitize, preserve and extend access to Biometrika. SUMMARY Designs for estimating the slope of a response surface are considered. Minimization of the variance of the estimated slope maximized over all points in the factor space is taken as the optimality criterion. Optimal designs under the minimax criterion are derived for second-and third-order polynomial regression over spherical regions.Some key words: Optimal design; Rotatable design; Second-order design; Slope of a response surface; Thirdorder design.
Radar rainfall estimates has become an indispensable complementary to rain gauge data as input to flood prediction model though the use of traditional rain gages at a series of point has been improved with the application of spatial interpolation techniques such as Kriging. The paper presents Kriging interpolation for a network of rain gauges in Klang River Basin. The kriged rain values are compared with radar rainfall estimates to assess the advantages of both methods. Three types of semivariogram functions namely Spherical, Exponential and Gaussian have been applied in the interpolation. The results show that the Spherical semivariogram model performs the best in the interpolation. It is also found that Kriging interpolation of rain gauges data can provide useful comparative values to the radar rainfall estimates
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