Wind power generation is essential to reduce the use of fossil resources and, consequently, the emission of greenhouse gases (GHG). Currently, the National Interconnected System (SIN) has about 9971 wind turbines in operation, the sixth largest network in the world ranking, and 80% of Brazilian...

Modeling real estate prices in the context of hedonic models often involves fitting a Generalized Additive Model, where only the mean of a (lognormal) distribution is regressed on a set of variables without taking other parameters of the distribution into account. Thus far, the application of...

This work presents a Bayesian approach for inferring the capacity factor of an offshore wind farm. The application of the proposed methodology is illustrated through a case study of a wind power offshore project located on the northern coast of the Rio de Janeiro State.

Models with structured additive predictor provide a very broad and rich framework for complex regression modeling. They can deal simultaneously with nonlinear covariate effects and time trends, unit- or cluster-specific heterogeneity, spatial heterogeneity and complex interactions between...

We propose a multicountry quantile factor augmeneted vector autoregression (QFAVAR) to model heterogeneities both across countries and across characteristics of the distributions of macroeconomic time series. The presence of quantile factors allows for summarizing these two heterogeneities in a...

In this paper we present a nonparametric Bayesian approach for fitting unsmooth or highly oscillating functions in regression models with binary responses. The approach extends previous work by Lang et al. (2002) for Gaussian responses. Nonlinear functions are modelled by first or second order...