9 citations · 11 across the 3 of their papers we have counts for
4 papers
Learning Measurement Models for Unobserved Variables
Ricardo Silva, Richard Scheines, Clark Glymour +1
Observed associations in a database may be due in whole or part to variations in unrecorded (latent) variables. Identifying such variables and their causal relationships with one a…
Latent Composite Likelihood Learning for the Structured Canonical Correlation Model
Ricardo Silva
Latent variable models are used to estimate variables of interest quantities which are observable only up to some measurement error. In many studies, such variables are known but n…
Bayesian Inference for Gaussian Mixed Graph Models
Ricardo Silva, Zoubin Ghahramani
We introduce priors and algorithms to perform Bayesian inference in Gaussian models defined by acyclic directed mixed graphs. Such a class of graphs, composed of directed and bi-di…
On estimating covariances between many assets with histories of highly variable length
Robert B. Gramacy, Joo Hee Lee, Ricardo Silva
Quantitative portfolio allocation requires the accurate and tractable estimation of covariances between a large number of assets, whose histories can greatly vary in length. Such d…