7 citations · 14 across the 8 of their papers we have counts for
10 papers
Mean-Tilted Intervals: Regression and Dynamic Models
Antonio De Leon, Raquel Prado, Bruno Sansó
Mean-tilted intervals (MTIs) provide a fixed-content family of interval targets indexed by retained-mean balance. This paper develops generalized-Bayes computation for using those…
Bayesian Quantile Deep Echo State Networks for Nonlinear Time Series
Antonio De Leon, Raquel Prado, Bruno Sansó
Conditional quantiles are central to asymmetric decision losses, tail-risk assessment, and interval forecasts, but Bayesian quantile regression for nonlinear time series can be dif…
Mean-Tilted Intervals: Short Tolerance Intervals
Antonio De Leon, Raquel Prado, Bruno Sansó
Intervals with the same probability content can have different endpoint placements and widths. This matters for tolerance inference, where a reported interval must also satisfy a r…
Bayesian Quantile-Based Correction and Synthesis of Hydrologic Products
Antonio De Leon, Raquel Prado, Bruno Sansó
River-flow forecasting requires predictive distributions that remain informative in both routine and extreme conditions. We develop a Bayesian quantile-based correction-and-synthes…
exdqlm: An R Package for Estimation and Analysis of Flexible Dynamic Quantile Linear Models
Antonio De Leon, Raquel Barata, Raquel Prado +1
We present the R package exdqlm for Bayesian quantile regression, with primary emphasis on dynamic state-space quantile models for time series. The package is built around extended…
Bayesian Nonparametric Multivariate Mixture of Autoregressive Processes: With Application to Brain Signals
Guillermo Granados-Garcia, Raquel Prado, Hernando Ombao
One of the goals of neuroscience is to study interactions between different brain regions during rest and while performing specific cognitive tasks. The Multivariate Bayesian Autor…
Bayesian tensor regression using the Tucker decomposition for sparse spatial modeling
Daniel Spencer, Rajarshi Guhaniyogi, Russell Shinohara +1
Modeling with multidimensional arrays, or tensors, often presents a problem due to high dimensionality. In addition, these structures typically exhibit inherent sparsity, requiring…
Efficient Bayesian PARCOR Approaches for Dynamic Modeling of Multivariate Time Series
Wenjie Zhao, Raquel Prado
A Bayesian lattice filtering and smoothing approach is proposed for fast and accurate modeling and inference in multivariate non-stationary time series. This approach offers comput…
Bayesian Mixed Effect Sparse Tensor Response Regression Model with Joint Estimation of Activation and Connectivity
Daniel Spencer, Rajarshi Guhaniyogi, Raquel Prado
Brain activation and connectivity analyses in task-based functional magnetic resonance imaging (fMRI) experiments with multiple subjects are currently at the forefront of data-driv…
The 2004 Venezuelan Presidential Recall Referendum: Discrepancies Between Two Exit Polls and Official Results
Raquel Prado, Bruno Sansó
We present a simulation-based study in which the results of two major exit polls conducted during the recall referendum that took place in Venezuela on August 15, 2004, are compare…