Topic
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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TL;DR: In this article, the authors derived the maximum likelihood predictive densities (MLPD) for the inverse Gaussian distribution for the cases of one or both parameters unknown and applied them to obtain estimators of the reliability function and prediction or shortest prediction intervals for a future observation.
10 citations
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TL;DR: A simulation study based on one of the populations used by Gregoire and Schabenberger shows that the resulting adjusted intervals have more balanced noncoverage probabilities and often higher coverage probability than the standard intervals in cases of substantial correlation.
Abstract: In a 1999 Ecology article, T. G. Gregoire and O. Schabenberger addressed the problem of obtaining truly symmetric confidence intervals for the total of a positively skewed biological population under simple random sampling. Their simulation study revealed that the skewness induced a substantial positive correlation between the estimator of the total and the estimator of its variance. This caused the standard nominally symmetric t-based intervals, based on approximate normality of the estimator of the total, to be highly unbalanced, i.e., intervals much more often missed from below than from above. To better cope with this situation I suggest an alternative confidence interval procedure that takes into account and adjusts for the induced correlation. A simulation study based on one of the populations used by Gregoire and Schabenberger shows that the resulting adjusted intervals have more balanced noncoverage probabilities and often higher coverage probability than the standard intervals in cases of substantial correlation. I also provide an example of an unequal probability design using auxiliary information, where there is much less need for an adjustment.
10 citations
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TL;DR: In this article, an empirical likelihood ratio statistic for the parametric components is proposed and the nonparametric version of Wilk's theorem is proved for a semivarying coefficient partially linear model with longitudinal data.
10 citations
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TL;DR: Improved confidence intervals for the one-parameter model with desirable coverage probability are proposed in this article and a numerical calculation shows the substantial improvement of the new confidence intervals over the conventional confidence intervals.
10 citations
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18 Nov 2015TL;DR: A closed-form expression for the network coverage probability in composite Rayleigh-Lognormal for both low and high SNR is derived and it is shown that the coverage probability is proportional to path loss exponent coefficient, and inversely proportional to exponential function of 1 over SNR.
Abstract: Poisson point process (PPP) network model in which base stations (BSs) and users have Poisson distributions has been recently used to replace grid model for analyzing the performance of cellular networks. The closed-form for the coverage probability of a typical user that connects to the closest base station (BS), however, is only found in case of high transmission signal-to-noise (SNR) and only in Rayleigh fading. This paper derives a closed-form expression for the network coverage probability in composite Rayleigh-Lognormal for both low and high SNR. The analytical results show that the coverage probability is proportional to path loss exponent coefficient, and inversely proportional to exponential function of 1 over SNR. The analytical results are also verified by Monte Carlo simulations.
10 citations