The random geometric graph is obtained by sampling n points from the unit square (uniformly at random and independently), and connecting two points whenever their distance is at most r, for some given r = r(n). We consider the following variation on the random geometric graph: in each of n rounds in total, a player is offered two random points from the unit square, and has to select exactly one...

When conducting simulation for evaluating complex system reliability or availability, method of random sampling is applied to simulate fault occasion of complex system. Current research of fault sampling generally assumes maintenance activity restores systems to “good-as-new” and “bad-as-old” without considering “partly good” situation. However, system usually keeps its function through imperfe...

Abstract Simple random-sampling resolutions of the raven paradox relevantly diverge from scientific practice. We develop a stratified model, yielding better fit and apparently rehabilitating simple random sampling as legitimate idealization. However, neither accommodates second concern, objection potential bias. third model that crucially invokes causal considerations, novel resolution handles ...

Sequential sample selection methods are distinguished from conventional methods in the manner in which random numbers are used to determine the sample. Conventionally, a sample of size n is selected from a sampling frame of N sampling units by selecting n random numbers and mapping then into n of the labels in the sampling frame. Sequential methods require each sampling unit in the sampling fra...

This paper presents a stochastic iteration algorithm solving the global illumination problem, where the random sampling is governed by classical importance sampling and also by the Metropolis method. Point pairs where radiance transfer takes place are obtained with random ray shooting. Ray shooting can mimic the source radiance and the geometric factor, but not the receiving capability of the t...

This paper presents a stochastic iteration algorithm solving the global illumination problem, where the random sampling is governed by classical importance sampling and also by the Metropolis method. Point pairs where radiance transfer takes place are obtained with random ray shooting. Ray shooting can mimic the source radiance and the geometric factor, but not the receiving capability of the t...

We propose a jackknife variance estimator for the population average from two, two-phase samples after imputation. The jackknife method has long been used to estimate and reduce bias, but has now become a valuable tool for variance estimation. We apply two different sampling methods, (simple random sampling and stratified random sampling) to derive jackknife variance estimators for the twosampl...

Particle filtering is a very popular technique for sequential state estimation. However, in high-dimensional cases where the state dynamics are complex or poorly modeled, thousands of particles are usually required for real applications. This paper presents a hybrid sampling solution that combines RANSAC and particle filtering. In this approach, RANSAC provides proposal particles that, with hig...