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Wesley Bertoli
Researcher at Federal University of Technology - Paraná
Publications - 15
Citations - 213
Wesley Bertoli is an academic researcher from Federal University of Technology - Paraná. The author has contributed to research in topics: Count data & Poisson distribution. The author has an hindex of 3, co-authored 11 publications receiving 132 citations. Previous affiliations of Wesley Bertoli include University of São Paulo.
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Bayesian Model Averaging: A Systematic Review and Conceptual Classification
TL;DR: Bayesian model averaging (BMA) provides a coherent and systematic mechanism for accounting for model uncertainty as discussed by the authors, which can be regarded as an direct application of Bayesian inference to the problem of model selection, combined estimation and prediction.
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Whole transcriptomic network analysis using Co-expression Differential Network Analysis (CoDiNA)
Deisy Morselli Gysi,Tiago de Miranda Fragoso,Fatemeh Zebardast,Wesley Bertoli,Volker Busskamp,Volker Busskamp,Eivind Almaas,Katja Nowick +7 more
TL;DR: CoDiNA detects links and nodes that are common, specific or different among the networks, resulting in a comprehensive network analysis method, more sophisticated than simply comparing the presence or absence of network nodes.
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A new class of bivariate Lindley distributions based on stress and shock models and some of their reliability properties
TL;DR: In this article, a new class of bivariate Lindley distribution of the Marshall-Olkin type was introduced to evaluate a 2-component series system's reliability function, and the proposed methodology is based on introducing a latent variable following an Exponential or a Lindley Distribution.
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A discrete analog of Gumbel distribution: properties, parameter estimation and applications
TL;DR: In this article, a discrete version of the Gumbel distribution (Type-I Extreme Value distribution) has been derived by using the general approach of discretization of a continuous distribution.
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A Bayesian approach for some zero-modified Poisson mixture models:
TL;DR: In this paper, a class of zero modified Poisson mixture models is proposed as an alternative to model overdispersed count data exhibiting inflation or deflation of zeros, which is a relevant feature of our model.