104 citations · 107 across the 5 of their papers we have counts for
6 papers
Sufficient reductions in regression with mixed predictors
Efstathia Bura, Liliana Forzani, Rodrigo García Arancibia +2
Most data sets comprise of measurements on continuous and categorical variables. In regression and classification Statistics literature, modeling high-dimensional mixed predictors…
Envelopes for multivariate linear regression with linearly constrained coefficients
Dennis Cook, Liliana Forzani, Lan Liu
A constrained multivariate linear model is a multivariate linear model with the columns of its coefficient matrix constrained to lie in a known subspace. This class of models inclu…
Fundamentals of path analysis in the social sciences
R. Dennis Cook, Liliana Forzani
Motivated by a recent series of diametrically opposed articles on the relative value of statistical methods for the analysis of path diagrams in the social sciences, we discuss fro…
Asymptotic theory for maximum likelihood estimates in reduced-rank multivariate generalised linear models
Efstathia Bura, Sabrina Duarte, Liliana Forzani +2
Reduced-rank regression is a dimensionality reduction method with many applications. The asymptotic theory for reduced rank estimators of parameter matrices in multivariate linear…
Principal Fitted Components for Dimension Reduction in Regression
R. Dennis Cook, Liliana Forzani
We provide a remedy for two concerns that have dogged the use of principal components in regression: (i) principal components are computed from the predictors alone and do not make…
On the maximal function for the generalized Ornstein-Uhlenbeck semigroup
Jorge Betancor, Liliana Forzani, Roberto Scotto +1
In this note we consider the maximal function for the generalized Ornstein-Uhlenbeck semigroup in $\RR$ associated with the generalized Hermite polynomials and prove th…