In this paper some resampling methods for the extrema of certain conditional functions, including delta method along with jackkniing and bootstrapping, are examined, and the properties of the resulted statistics are discussed.

Sampling of large datasets for data mining is important for at least two reasons. The processing of large amounts of data results in increased computational complexity. The cost of this additional complexity may not be justifiable. On the other hand, the use of small samples results in fast and efficient computation for data mining algorithms. Statistical methods for obtaining sufficient sample...

This paper discusses the statistical principles, methods, and software programs used to calculate sample size. In addition, it reviews the practical challenges faced in calculating sample size. We show that because of such challenges, statistical calculations often do not provide us with a clear-cut number for the study sample size; rather they suggest a range of reasonable numbers. The paper a...

There has been a great deal of progress in developing probabilistically complete methods that move beyond motion planning to multi-modal problems including various forms of task planning. This paper presents a general-purpose formulation of a large class of discrete-time planning problems, with hybrid state and action spaces. The formulation characterizes conditions on the submanifolds in which...

OBJECTIVES: The goal of this project was to evaluate nucleic acid extraction techniques to detect different microbial pathogens (e.g., pathogenic viruses, bacteria, bacterial spores, and protozoan parasites) in drinking water using molecular techniques. While numerous nucleic acid extraction kits are commercially available, the composition of these kits is largely proprietary, making it difficu...