We show that a simple, general, and easily reproducible method for generating non-uniform sampling (NUS) schedules preserves the benefits of random sampling, including inherently reduced sampling artifacts, while removing the pitfalls associated with choosing an arbitrary seed. Sampling schedules are generated from a discrete cumulative distribution function (CDF) that closely fits the continuo...

This chapter is a comprehensive overview of sampling methods for web and e-mail (‘Internetbased’) surveys. It reviews the various types of sampling method – both probability and nonprobability – and examines their applicability to Internet-based surveys. Issues related to Internetbased survey sampling are discussed, including difficulties assembling sampling frames for probability sampling, cov...

The use of profiling by ethnicity or nationality to trigger secondary security screening is a controversial social and political issue. Overlooked is the question of whether such actuarial methods are in fact mathematically justified, even under the most idealized assumptions of completely accurate prior probabilities, and secondary screenings concentrated on the highest-probability individuals...

Belief updating in Bayes nets, a well known computationally hard problem, has recently been approximated by several deterministic algorithms, and by various randomized approximation algorithms. Deterministic algorithms usually provide probability bounds, but have an exponential runtime. Some randomized schemes have a polynomial runtime, but provide only probability estimates. Randomized algorit...

The fidelity of surrogate models remains one of the primary concerns in their application to represent complex system behavior. Appropriate sampling of training points is one of the primary factors affecting the fidelity of surrogate models. This paper investigates the relative advantage of probability-based uniform sampling over distance-based uniform sampling, in training surrogate models who...

In ecology, as in other research fields, efficient sampling for population estimation often drives sample designs toward unequal probability sampling, such as in stratified sampling. Design based statistical analysis tools are appropriate for seamless integration of sample design into the statistical analysis. However, it is also common and necessary, after a sampling design has been implemente...

In this paper, we introduce a novel, general purpose, technique for faster sampling of nodes over an online social network. Specifically, unlike traditional random walks which wait for the convergence of sampling distribution to a predetermined target distribution a waiting process that incurs a high query cost we develop WALK-ESTIMATE, which starts with a much shorter random walk, and then pro...

The number of weighted random patterns depends on the sampling probability of the corresponding deterministic test pattern . Therefore if the weight set is extracted from the deterministic pattern set with high sampling probabilities, the test length can be shortened. In this paper we present a new multiple weight set generation algorithm that generates high performance weight sets by removing ...