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A Bayesian framework for the ratio of two Poisson rates in the context of vaccine efficacy trials∗

Stéphane Laurent, Catherine Legrand (2012)

ESAIM: Probability and Statistics

In many applications, we assume that two random observations x and y are generated according to independent Poisson distributions ( λ S ) 𝒫(λS) and ( μ T ) 𝒫(μT) and we are interested in performing statistical inference on the ratio φ = λ / μ of the two incidence rates. In vaccine efficacy trials, x and y are typically the numbers of cases in the vaccine and the control groups respectively, φ is called the relative risk...

A bayesian framework for the ratio of two Poisson rates in the context of vaccine efficacy trials

Stéphane Laurent, Catherine Legrand (2012)

ESAIM: Probability and Statistics

In many applications, we assume that two random observations x and yare generated according to independent Poisson distributions ( λ S ) x1d4ab;(λS) and ( μ T ) x1d4ab;(μT) and we are interested in performing statistical inference on the ratio φ = λ / μ of the two incidence rates. In vaccine efficacy trials, x and y are typically the numbers of cases in the vaccine and the control groups respectively, φ is called the relative risk and the statistical model is called ‘partial immunity model’. In this paper we...

A Bayesian significance test of change for correlated observations

Abdeldjalil Slama (2014)

Discussiones Mathematicae Probability and Statistics

This paper presents a Bayesian significance test for a change in mean when observations are not independent. Using a noninformative prior, a unconditional test based on the highest posterior density credible set is determined. From a Gibbs sampler simulation study the effect of correlation on the performance of the Bayesian significance test derived under the assumption of no correlation is examined. This paper is a generalization of earlier studies by KIM (1991) to not independent observations.

A cooperative sensor network : optimal deployment and functioning

Alfonso Farina, Antonio Graziano, Francesca Mariani, Francesco Zirilli (2010)

RAIRO - Operations Research - Recherche Opérationnelle

A network of mobile cooperative sensors is considered. The following problems are studied: (1) the “optimal“deployment of the sensors on a given territory; (2) the detection of local anomalies in the noisy data measured by the sensors. In absence of an information fusion center in the network, from “local” interactions between sensors “global“solutions of these problems are found.

A Cooperative Sensor Network: Optimal Deployment and Functioning

Alfonso Farina, Antonio Graziano, Francesca Mariani, Francesco Zirilli (2011)

RAIRO - Operations Research

A network of mobile cooperative sensors is considered. The following problems are studied: (1) the “optimal" deployment of the sensors on a given territory; (2) the detection of local anomalies in the noisy data measured by the sensors. In absence of an information fusion center in the network, from “local" interactions between sensors “global" solutions of these problems are found.

A weighted version of Gamma distribution

Kanchan Jain, Neetu Singla, Rameshwar D. Gupta (2014)

Discussiones Mathematicae Probability and Statistics

Weighted Gamma (WG), a weighted version of Gamma distribution, is introduced. The hazard function is increasing or upside-down bathtub depending upon the values of the parameters. This distribution can be obtained as a hidden upper truncation model. The expressions for the moment generating function and the moments are given. The non-linear equations for finding maximum likelihood estimators (MLEs) of parameters are provided and MLEs have been computed through simulations and also for a real data...

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