Designing an efficient sampling scheme for a rare and clustered population is a challenging area of research. Adaptive cluster sampling, which has been shown to be viable for such a population, is based on sampling a neighborhood of units around a unit that meets a specified condition. However, the edge units produced by sampling neighborhoods have proven to limit the efficiency and applicabili...

We present a method that directs sampling and reconstruction for image generation. This method reduces the cost of the sampling stage, allows a reconstruction of the scene to be progressively reened during the sampling process, and produces a representation of the scene that permits exibility in the generation of images. The method employs a set of region estimators to model and evaluate the sa...

nigeria represents one of the paradoxes of development in which case the nation is rich but her people are poor. this study examines the rate of poverty among rural households in south western, nigeria. a random multistage sampling was employed for the study. ekiti and osun states were randomly selected from the six states in south-western nigeria. this was followed by random selection of two l...

We compared the effectiveness of light traps and plankton tows for sampling brachyuran crab larvae in Bartlett Cove, Glacier Bay, Alaska, U.S.A. during three nights each in July and August 2001 and June, August, and September 2002. Proportions of species and stages were used to compare larvae caught by light traps and plankton tows. Absolute numbers of larvae are difficult to compare because of...

Multi-structure model fitting has traditionally taken a two-stage approach: First, sample a (large) number of model hypotheses, then select the subset of hypotheses that optimise a joint fitting and model selection criterion. This disjoint two-stage approach is arguably suboptimal and inefficient — if the random sampling did not retrieve a good set of hypotheses, the optimised outcome will not ...