Modeling
Statistical models for representing complex structures and relationships in data.
UFPE · CCEN · Department of Statistics
Modeling the
complexity
of data.
MultLab is the Multidisciplinary Laboratory for Statistical Modeling, dedicated to statistical methodology and its applications to complex scientific problems.
scroll to explore
01 · The laboratory
Statistics for
real-world data.
MultLab is part of the Department of Statistics at the Center for Exact and Natural Sciences of the Federal University of Pernambuco.
The laboratory was authorized by UFPE in 2023 as the Multidisciplinary Laboratory for Statistical Modeling, linked to CCEN. Its work connects methodological development, statistical computing and applications across scientific fields.
The research areas presented on this website are an editorial synthesis based on the public research, projects and scientific output of the coordinators and collaborators — not a normative list of official laboratory research lines.
Institutional source
UFPE ↗
Inference
Frequentist and Bayesian approaches to estimation, diagnosis and prediction.
Applications
Scientific problems in health, social sciences, nutrition, finance and other fields.
Collaboration
Research with national and international partners and student training.
02 · Research
Where MultLab
asks questions of data.
A map of research areas that appear prominently in the public work and projects associated with the coordinators.
A01
Regression models
Linear and generalized models, inference, diagnostics and structures for censored or non-standard responses.
A02
Time series
Discrete and continuous processes, estimation, diagnostics and forecasting under different approaches.
A03
Bayesian inference
Bayesian modeling, estimation and prediction for complex data and dependent processes.
A04
Econometrics & complex data
Methods for longitudinal structures, functional data, missing data and applications in social and health sciences.
A05
Applied modeling
Turning scientific problems into interpretable statistical models, with attention to uncertainty and prediction.
From theory to application.
Research combines methodological development, simulation, statistical computing and applications to real data.
View publications →03 · Coordination
Two perspectives,
one laboratory.
AW
MultLab · Coordinator
Aldo William
Medina Garay
Professor at the Department of Statistics at UFPE. His public academic profile highlights generalized linear models, censored models and regression theory.
PhD USP · 2014
Area Statistical modeling
FM
MultLab · Coordinator
Francyelle de
Lima Medina
Professor at the Department of Statistics at UFPE. Her public academic profile highlights time series and econometrics, including discrete processes, estimation and forecasting.
PhD USP · 2014
Area Time series
04 · Publications
Research that
keeps moving.
Selected recent works from the public scientific output of Aldo William Medina Garay, included to contextualize the laboratory's activity.
Generalized Poisson regression model: Properties, residual analysis, and machine learning.
Edwin M. Ortega; Aldo M. Garay; Gabriela M. Rodrigues; Roberto Vila; Gauss M. Cordeiro · Quality & Quantity, 60, 5969–5990.
Likelihood-based inference for interval censored regression models under heavy-tailed distributions.
Yessenia A. Gil; Aldo M. Garay; Victor H. Lachos · Statistical Methods & Applications, 34, 519–544.
Mixed-effects models for censored data with autoregressive errors using the multivariate Student’s t-distribution.
Zhong, K.; Olivari, R.C.; Garay, A.M.; Lachos, V.H. · The New England Journal of Statistics in Data Science, 3, 119–134.
Bayesian analysis of censored/missing regression models with autoregressive errors and symmetrical distributions.
Garay, A.M.; Medina, F.; Torres, F.S.; Lachos, V.H. · Statistical Papers, 65, 5649–5690.
05 · Contact
Let's talk
about research?
MultLab is open to collaborations, projects, supervision and discussions about statistical modeling.
Coordination · Aldoagaray@de.ufpe.br ↗
Coordination · Francyellefrancy@de.ufpe.br ↗
Institutional reference
Department of Statistics · CCEN/UFPE
Av. Jorn. Aníbal Fernandes, 497–629 · Cidade Universitária · Recife–PE