Coverage probability

About: Coverage probability is a research topic. Over the lifetime, 2479 publications have been published within this topic receiving 53259 citations.

Coverage Aspects of Indoor VLC Networks

Abstract: Achieving both illumination and data reception with probability almost one inside a specific indoor environment is not an effortless task in visible light communication (VLC) networks. Several factors such as error probability, transmitted power, dimming factor, or node failure affect coverage probability to a large extent. To assure reliable signal reception, a dense transmitting network is required on the ceiling. In this paper, we investigate how the key factors contribute to a network deployment with a reliable degree of coverage at a specific horizontal plane. Considering that VLC is set to be one of the most challenging technologies for domestic applications in 5G networks, the analysis on coverage issues discussed herein is of particular interest in practical scenarios.

Performance of Skart: A Skewness-and Autoregression-Adjusted Batch Means Procedure for Simulation Analysis

Abstract: An analysis is given for an extensive experimental performance evaluation of Skart, an automated sequential batch means procedure for constructing an asymptotically valid confidence interval (CI) on the steady-state mean of a simulation output process. Skart is designed to deliver a CI satisfying user-specified requirements on absolute or relative precision as well as coverage probability. Skart exploits separate adjustments to the half-length of the classical batch means CI so as to account for the effects on the distribution of the underlying Student's t-statistic that arise from skewness (nonnormality) and autocorrelation of the batch means. Skart also delivers a point estimator for the steady-state mean that is approximately free of initialization bias. In an experimental performance evaluation involving a wide range of test processes, Skart compared favorably with other steady-state simulation analysis methods---namely, its predecessors ASAP3, WASSP, and SBatch, as well as ABATCH, LBATCH, the Heidelberger--Welch procedure, and the Law--Carson procedure. Specifically, Skart exhibited competitive sampling efficiency and closer conformance to the given CI coverage probabilities than the other procedures, especially in the most difficult test processes.

Coverage probability bias, objective Bayes and the likelihood principle

Abstract: SUMMARY We review objective Bayes procedures based on both parametric and predictive coverage probability bias and explore the extent to which such procedures contravene the likelihood principle in the case of a scalar parameter. The discussion encompasses choice of objective priors, objective posterior probability statements and objective predictive probability statements. We conclude with some remarks concerning the future development and implementation of objective priors based on small coverage probability bias.

Adaptive Confidence Bands for Nonparametric Regression Functions

Abstract: This article proposes a new formulation for the construction of adaptive confidence bands (CBs) in nonparametric function estimation problems. CBs, which have size that adapts to the smoothness of the function while guaranteeing that both the relative excess mass of the function lying outside the band and the measure of the set of points where the function lies outside the band are small. It is shown that the bands adapt over a maximum range of Lipschitz classes. The adaptive CB can be easily implemented in standard statistical software with wavelet support. We investigate the numerical performance of the procedure using both simulated and real datasets. The numerical results agree well with the theoretical analysis. The procedure can be easily modified and used for other nonparametric function estimation models. Supplementary materials for this article are available online.