17 citations · 29 across the 22 of their papers we have counts for
5 papers · 1 filter
Bayesian Markov-Switching Partial Reduced-Rank Regression
Maria F. Pintado, Matteo Iacopini, Luca Rossini +1
Reduced-Rank (RR) regression is a powerful dimensionality reduction technique but it overlooks any possible group configuration among the responses by assuming a low-rank structure…
Bayesian Partial Reduced-Rank Regression
Maria F. Pintado, Matteo Iacopini, Luca Rossini +1
Reduced-rank (RR) regression may be interpreted as a dimensionality reduction technique able to reveal complex relationships among the data parsimoniously. However, RR regression m…
Bayesian Analysis of High Dimensional Vector Error Correction Model
Parley R Yang, Alexander Y Shestopaloff
Vector Error Correction Model (VECM) is a classic method to analyse cointegration relationships amongst multivariate non-stationary time series. In this paper, we focus on high dim…
Uncertainty Quantification in Bayesian Reduced-Rank Sparse Regressions
Maria F. Pintado, Matteo Iacopini, Luca Rossini +1
Reduced-rank regression recognises the possibility of a rank-deficient matrix of coefficients. We propose a novel Bayesian model for estimating the rank of the coefficient matrix,…
New reconstruction and data processing methods for regression and interpolation analysis of multidimensional big data
Yuri K. Shestopaloff, Alexander Y. Shestopaloff
The problems of computational data processing involving regression, interpolation, reconstruction and imputation for multidimensional big datasets are becoming more important these…