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Coverage probability

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


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Journal Article
TL;DR: In this paper, the asymptotic distribution for the ratio of the sample correlations in two independent populations is established and the presented method can be used to derive the confidence interval and hypothesis testing for the ratios of population correlations.
Abstract: The asymptotic distribution for the ratio of the sample correlations in two independent populations is established. The presented method can be used to derive the asymptotic confidence interval and hypothesis testing for the ratio of population correlations. The performance of the new interval is comparable with similar method. Then the simulation study is provided to compare our confidence interval with Fisher Z-transform and Cauchy-transform methods. The proposed confidence set has a good coverage probability with a larger power.

22 citations

Journal ArticleDOI
TL;DR: The simulation study shows that, for estimating extreme quantiles, both the standard Bayesian and the maximum likelihood approaches can lead to an over-confident result, and Bayesian model averaging provides a -credibility interval with a wider average length, but a more accurate coverage probability.
Abstract: In an accelerated life test, inferences on extreme quantiles of the lifetime distribution at the use condition are obtained via extrapolation in two directions: in time, and in stress levels. Extrapolation is known to highly depend on the working model, and ignoring model uncertainty can result in over-confidence. This paper explores the use of Bayesian model averaging for estimating quantiles in an accelerated life test. Two of the most commonly used lifetime regression models, lognormal, and Weibull log-location-scale regression models, are considered in this paper as candidate models. To illustrate, we analyse complementary metal-oxide semiconductor integrated circuit data. We also construct a simulation study to compare the performance of the Bayesian model averaging -credibility intervals with other exiting interval estimators. The simulation study shows that, for estimating extreme quantiles, both the standard Bayesian and the maximum likelihood approaches can lead to an over-confident result, and Bayesian model averaging provides a -credibility interval with a wider average length, but a more accurate coverage probability.

22 citations

Journal ArticleDOI
TL;DR: In this article, several procedures for using path control variates to improve the accuracy of simulation-based point and confidence-interval estimators of the mean completion time of a stochastic activity network (SAN) are described.
Abstract: This article details several procedures for using path control variates to improve the accuracy of simulation-based point and confidence-interval estimators of the mean completion time of a stochastic activity network (SAN). Because each path control variate is the duration of the corresponding directed path in the network from the source to the sink, the vector of selected path controls has both a known mean and a known covariance matrix. This information is incorporated into estimation procedures for both normal and nonnormal responses. To evaluate the performance of these procedures experimentally, we examine the bias, variance, and mean square error of the controlled point estimators as well as the average half-length and coverage probability of the corresponding confidence-interval estimators for a set of SANs in which the following characteristics are systematically varied: (a) the size of the network (number of nodes and arcs); (b) the topology of the network; (c) the percentage of activities with exponentially distributed durations; and (d) the relative dominance of the critical path. The experimental results show that although large improvements in accuracy can be achieved with some of these procedures, the confidence-interval estimators for normal responses may suffer serious loss of coverage probability in some applications.

22 citations

Journal ArticleDOI
TL;DR: In this paper, an empirical likelihood (EL) inference procedure of the mean residual life (MRL) function is proposed and the limiting distribution of the EL ratio for MRL function is derived.
Abstract: In addition to the distribution function, the mean residual life (MRL) function is the other important function which can be used to characterize a lifetime in survival analysis and reliability. For inference on the MRL function, some procedures have been proposed in the literature. However, the coverage accuracy of such procedures may be low when the sample size is small. In this article, an empirical likelihood (EL) inference procedure of MRL function is proposed and the limiting distribution of the EL ratio for MRL function is derived. Based on the result, we obtain confidence interval/band for the MRL function. The proposed method is compared with the normal approximation based method through simulation study in terms of coverage probability.

22 citations

Journal ArticleDOI
TL;DR: Approaches to address possible inefficiency in estimation resulting from survey weighting are reviewed, including methods derived from both the design and modelbased perspectives.
Abstract: In sample surveys, the sample units are typically chosen using a complex design. This may lead to a selection effect and, if uncorrected in the analysis, may lead to biased inferences. To mitigate the effect on inferences of deviations from a simple random sample a common technique is to use survey weights in the analysis. This article reviews approaches to address possible inefficiency in estimation resulting from such weighting. To improve inferences we emphasize modifications of the basic designbased weight, that is, the inverse of a unit’s inclusion probability. These techniques include weight trimming, weight modelling and incorporating weights via models for survey variables.We start with an introduction to survey weighting, including methods derived from both the design and modelbased perspectives. Then we present the rationale and a taxonomy of methods for modifying the weights. We next describe an extensive numerical study to compare these methods. Using as the criteria relative bias, relative mean square error, confidence or credible interval width and coverage probability, we compare the alternative methods and summarize our findings. To supplement this numerical study we use Texas school data to compare the distributions of the weights for several methods.We also make general recommendations, describe limitations of our numerical study and make suggestions for further investigation.

22 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20241
202363
2022153
2021142
2020151
2019142