Surveys of people's opinions are fraught with difficulties. It is easier to obtain information from those who respond to text messages or to emails than to attempt to obtain a representative sample. Samples of the population that are selected non-randomly in this way are termed convenience samples as they are easy to recruit. This introduces a sampling bias. Such non-probability samples have me...

traditional survey methods may cause refusals to respond or untruthful replies when encounter the sensitive questions. the randomized response technique (rrt) is designed to decrease social desirability bias and obtain reliable estimates. this study aimed to apply these new methods on the sensitive questions survey.simmons model was applied in the survey of issues relevant to commercial sex amo...

Compressive sensing (CS) theory demonstrates that by using uniformly-random sampling, rather than uniformly-spaced sampling, higher quality image reconstructions are often achievable. Considering that the structure of sampling protocols has such a profound impact on the quality of image reconstructions, we formulate a new sampling scheme motivated by physiological receptive field structure, loc...

This paper presents a sampling-based method for path planning in robotic systems without known cost-to-go information. It uses trajectories generated from random search to heuristically learn the cost-to-go of regions within the configuration space. Gradually, the search is increasingly directed towards lower cost regions of the configuration space, thereby producing paths that converge towards...

primary information about different methods of vegetation sampling is important to researchers to decide about their sampling. in this study we applied five distance methods (closest individual, nearest neighbor, random pairs, point-centered quarter and angle orderd) to estimate plant density in three vegetation types including artemisia sieberi, juncus littoralis and punica granatum in mazanda...

Born from empirical observations in nonuniformly sampled multidimensional NMR data relating to gaps between sampled points, the Poisson-gap sampling method has enjoyed widespread use in biomolecular NMR. While the majority of nonuniform sampling schemes are fully randomly drawn from probability densities that vary over a Nyquist grid, the Poisson-gap scheme employs constrained random deviates t...

We look at the benefits of using a kind of quasi-random numbers to obtain more accurate results for a given number of simulation runs. We explore a sampling method with enhanced independence in multidimensional simulations by combining the ideas of stratified sampling and Latin Hypercube sampling. We test the new sampling method by comparing it with traditional stratified sampling and Latin Hyp...

A method based on multicanonical Monte Carlo is applied to the calculation of large deviations in the largest eigenvalue of random matrices. The method is successfully tested with the Gaussian orthogonal ensemble, sparse random matrices, and matrices whose components are subject to uniform density. Specifically, the probability that all eigenvalues of a matrix are negative is estimated in these...