5 papers
Bayesian Controlled FDR Variable Selection via Parameter-Expanded Latent Knockoffs
Lorenzo Focardi-Olmi, Anna Gottard, Michele Guindani +1
In many research fields, researchers aim to identify significant associations between a set of explanatory variables and a response while controlling the FDR. The Knockoff filter h…
Bayesian Multi-Group Functional Factor Models with Parameter-Expanded Cumulative Shrinkage Priors
Xuanye Dai, Anna Gottard, Michele Guindani +1
Functional data consist of trajectories observed over a continuous domain, such as time, space, or wavelength. Here we consider curves observed on different groups of subjects and…
Copula-based models for spatially dependent cylindrical data
Francesca Labanca, Anna Gottard, Nadja Klein
Cylindrical data frequently arise across various scientific disciplines, including meteorology (e.g., wind direction and speed), oceanography (e.g., marine current direction and sp…
A Bayesian Approach for Inference on Mixed Graphical Models
Mauro Florez, Anna Gottard, Carrie McAdams +2
Mixed data refers to a type of data in which variables can be of multiple types, such as continuous, discrete, or categorical. This data is routinely collected in various fields, i…
Uncertainty-Aware Fairness-Adaptive Classification Trees
Anna Gottard, Vanessa Verrina, Sabrina Giordano
In an era where artificial intelligence and machine learning algorithms increasingly impact human life, it is crucial to develop models that account for potential discrimination in…