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Variational Approximations for Generalized Linear Latent Variable Models
Hui, Francis K. C.; Warton, David I.; Ormerod, John T.; Haapaniemi, Viivi; Taskinen, Sara (American Statistical Association, 2017)Generalized linear latent variable models (GLLVMs) are a powerful class of models for understanding the relationships among multiple, correlated responses. Estimation, however, presents a major challenge, as the marginal ... -
Fast and universal estimation of latent variable models using extended variational approximations
Korhonen, Pekka; Hui, Francis K. C.; Niku, Jenni; Taskinen, Sara (Springer, 2023)Generalized linear latent variable models (GLLVMs) are a class of methods for analyzing multi-response data which has gained considerable popularity in recent years, e.g., in the analysis of multivariate abundance data in ... -
Efficient estimation of generalized linear latent variable models
Niku, Jenni; Brooks, Wesley; Herliansyah, Riki; Hui, Francis K. C.; Taskinen, Sara; Warton, David I. (Public Library of Science, 2019)Generalized linear latent variable models (GLLVM) are popular tools for modeling multivariate, correlated responses. Such data are often encountered, for instance, in ecological studies, where presence-absences, counts, ... -
Model nuclear energy density functionals derived from ab initio calculations
Salvioni, G.; Dobaczewski, J.; Barbieri, C.; Carlsson, G.; Idini, A.; Pastore, A. (Institute of Physics, 2020)We present the first application of a new approach, proposed in (2016J.Phys.G:Nucl.Part.Phys.4304LT01) to derive coupling constants of the Skyrme energy density functional (EDF) fromab initioHamiltonian. By perturbing theab ... -
On modeling multivariate abundance data with generalized linear latent variable models
Niku, Jenni (Jyväskylän yliopisto, 2020)The multivariate abundance data consist typically of multiple, correlated species encountered at a set of sites, together with records of additional covariates. When analysing such data, model-based approaches have been ...