8 citations · 15 across the 7 of their papers we have counts for
7 papers
Model-based Clustering of Multi-Dimensional Zero-Inflated Counts via the EM Algorithm
Zahra AghahosseinaliShirazi, Pedro A. Rangel, Camila P. E. de Souza
Zero-inflated count data arise in various fields, including health, biology, economics, and the social sciences. These data are often modelled using probabilistic distributions suc…
BayesCPclust: A Bayesian Approach for Clustering Constant-Wise Change-Point Data
Ana Carolina da Cruz, Camila P. E. de Souza
Change-point models deal with ordered data sequences. Their primary goal is to infer the locations where an aspect of the data sequence changes. In this paper, we propose and imple…
Bayesian Adaptive Selection of Basis Functions for Functional Data Representation
Pedro Henrique T. O. Sousa, Camila P. E. de Souza, Ronaldo Dias
Considering the context of functional data analysis, we developed and applied a new Bayesian approach via Gibbs sampler to select basis functions for a finite representation of fun…
Clustering Functional Data via Variational Inference
Chengqian Xian, Camila de Souza, John Jewell +1
Functional data analysis deals with data recorded densely over time (or any other continuum) with one or more observed curves per subject. Conceptually, functional data are continu…
Aggregated functional data model applied on clustering and disaggregation of UK electrical load profiles
Gabriel Franco, Camila P. E. de Souza, Nancy L. Garcia
Understanding electrical energy demand at the consumer level plays an important role in planning the distribution of electrical networks and offering of off-peak tariffs, but obser…
Switching nonparametric regression models for multi-curve data
Camila P. E. de Souza, Nancy E. Heckman, Helena Xu
We develop and apply an approach for analyzing multi-curve data where each curve is driven by a latent state process. The state at any particular point determines a smooth function…
Switching Nonparametric Regression Models and the Motorcycle Data revisited
Camila P. E. de Souza, Nancy E. Heckman
We propose a methodology to analyze data arising from a curve that, over its domain, switches among J states. We consider a sequence of response variables, where each response y de…