69 citations · 186 across the 20 of their papers we have counts for
6 papers · 1 filter
Population based change-point detection for the identification of homozygosity islands
Lucas Prates, Renan B Lemes, Tábita Hünemeier +1
In this paper, we propose a new method for offline change-point detection on some parameters of the distribution of a random vector. We introduce a penalized maximum likelihood app…
Model selection criteria for regression models with splines and the automatic localization of knots
Alex Rodrigo dos S. Sousa, Magno T. F. Severino, Florencia G. Leonardi
In this paper we propose a model selection approach to fit a regression model using splines with a variable number of knots. We introduce a penalized criterion to estimate the numb…
Structure recovery for partially observed discrete Markov random fields on graphs under not necessarily positive distributions
Florencia Leonardi, Rodrigo R. S. Carvalho
We propose a penalized pseudo-likelihood criterion to estimate the graph of conditional dependencies in a discrete Markov random field that can be partially observed. We prove the…
Computationally efficient change point detection for high-dimensional regression
Florencia Leonardi, Peter Bühlmann
Large-scale sequential data is often exposed to some degree of inhomogeneity in the form of sudden changes in the parameters of the data-generating process. We consider the problem…
A model selection approach for multiple sequence segmentation and dimensionality reduction
Bruno M. de Castro, Florencia Leonardi
In this paper we consider the problem of segmenting aligned random sequences of equal length , into a finite number of independent blocks. We propose to use a penalized maxi…
Finding the basic neighborhood in variable range Markov random fields: application in SNP association studies
André J. Bianchi, Suely R. Giolo, Júlia P. Soler +1
The SNPs (Single Nucleotide Polymorphisms) genotyping platforms are of great value for gene mapping of complex diseases. Nowadays, the high-density of these molecular markers enabl…