Florencia Leonardi

Books

• Galves, A.; Leonardi, F. and Ost, G. Statistical model selection for stochastic systems with applications to Bioinformatics, Linguistics and Neurobiology. Rio de Janeiro: Editora do IMPA, 2021. v. 1. 146p.

Preprints

• Cerqueira, A. and Leonardi, F. Optimal recovery by maximum and integrated conditional likelihood in the general Stochastic Block Model, 2024.
• Boente, G; Leonardi, F.; Rodriguez, D and Sued, M. Threshold detection under a semiparametric regression model, 2023.
• Leonardi, F. and Bühlmann, P. Computationally efficient change point detection for high-dimensional regression, 2016. 

Published articles

• Leonardi, F. and Severino, M.T.F. Model selection for Markov random fields on graphs under a mixing condition. Stochastic Processes and their Applications, February 2025.
• Cerqueira, A.; Gallo, S.; Leonardi, F. and Vera, C. Consistent model selection for the Degree Corrected Stochastic Block Model. Latin American Journal of Probability and Mathematical Statistics, 26, 2024.
• Leonardi, F. Carvalho, R.R.S. and Frondana, I. Structure recovery for partially observed discrete Markov random fields on graphs under not necessarily positive distributions. Scandinavian Journal of Statistics 51(1), 2024.
• Prates, L., Lemes, R.B., Hünemeier, T. and Leonardi, F. Population based change-point detection for the identification of homozygosity islands. Bioinformatics, 39(4), 2023.
• Leonardi, F., Lopez-Rosenfeld, M., Rodriguez, D., Severino, M.T. and Sued, M. Independent block identification in multivariate time series. Journal of Time Series Analysis, 42(1), 2021.
• Cerqueira, A. and Leonardi, F. Estimation of the number of communities in the Stochastic Block Model. IEEE Transactions on Information Theory, 66(10), 2020.
• Cerqueira, A., Garivier, A. and Leonardi, F. A note on perfect simulation for exponential random graph models. ESAIM P & S, vol. 24, pp. 138-147, 2020.
• de Castro, B.M., Lemes, R.B., Cesar, J., Hünemeier, T. and Leonardi, F. A model selection approach for multiple sequence segmentation and dimensionality reduction. Journal of Multivariate Analysis 167, pp. 319-330, 2018.
• Cerqueira, A., Fraiman, D., Vargas, C.D. and Leonardi, F. A test of hypotheses for random graph distributions built from EEG data. IEEE Transactions on Network Science and Engineering 4(2), pp. 75-82, 2017.
• Bühlmann, P. and Leonardi, F. Comments on: A Random Forest guided tour. (Discussion on a paper by G. Biau and E. Scornet). TEST 25:239, 2016.
• Gallo, S. and Leonardi, F. Nonparametric statistical inference for the context tree of a stationary ergodic process. Electronic Journal of Statistics, 9(2), pp. 2076-2098, 2015.
• Armendáriz, I., Ferrari, PA., Groisman, P. and Leonardi, F. Finite cycle Gibbs measures of permutations of Z^d. ArXiv: 1407.6542. Journal of Statistical Physics, 158(6), pp. 1213-1233,  2015. 
• Collet, P. and Leonardi, F. Loss of memory of hidden Markov models and Lyapunov exponents. Annals of Applied Probability, v.24, pp. 422-446, 2013.  
• Galves, A., Galves, C., Garcia, J., Garcia, N. and Leonardi, F. Context tree selection and linguistic rhythm retrieval from written texts. Annals of Applied Statistics 6(1), pp. 186-209, 2012.  
• Garivier, A. and Leonardi, F. Context tree selection: a unifying view. Stochastic processes and their applications 121, pp. 2488-2506, 2011.
• Leonardi, F.G. Some upper bounds for the rate of convergence of penalized likelihood context tree estimators.ArXiv: math/0701810v5. Brazilian Journal of Probability and Statistics 24, pp. 321-336, 2010.
• Busch, J.R., Ferrari, P.A., Flesia, A.G., Fraiman, R., Grynberg, S. and Leonardi, F. Testing statistical hypothesis on random trees and applications to the protein classification problem. ArXiv: math/0603378. Annals of Applied Statistics 3(2), pp. 542-563, 2009.
• Flesia, A.G., Fraiman, R. and Leonardi, F. Pattern recognition on random trees associated to protein functionality families. ArXiv: math/0711.1369. In: 2 BIOMAT, 2008, La Falda. Actas de la Academia Nacional de Ciencias de Córdoba, Argentina, J. Tirao (Ed), 2008.
• Collet, P., Galves, A. and Leonardi, F. Random perturbations of stochastic processes with unbounded variable length memory. ArXiv: math/0707.2796. Electronic Journal of Probability 13, pp. 1345-1361, 2008.
• Galves, A. and Leonardi, F. Exponential inequalities for empirical unbounded context trees. ArXiv: math/0710.5900. In and Out of Equilibrium 2 (Sidoravicius, V.; Vares, M.E., Eds.), Progress in Probability, v. 60, pp. 257-270, 2008.
• Leonardi, F. A generalization of the PST algorithm: modeling the sparse nature of protein sequences. Bioinformatics (22)11, pp. 1302-1307, 2006.
• Barrera, J., Cesar Jr., R.M., Martins Jr., D.C., Merino, E.F., Vêncio, R.Z.N., Leonardi, F., Yamamoto, M.M., Pereira, C.A.B.and del Portillo, H.A. Constructing probabilistic genetic networks of Plasmodium falciparum from dynamical expression signals of the intraerythrocytic development cycle. In: McConnell; Lin and Hurban. (Org.). Methods of Microarray Data Analysis V., Springer, 2006.

Unpublished articles

• Sousa, A.R., Tairone, M. and Leonardi, F. Model selection criteria for regression models with splines and the automatic localization of knots, 2020.
• Bianchi, A.; Giolo, S.; Soler, J.P and Leonardi, F. Finding the basic neighborhood in variable range Markov random fields: application in SNP association studies. ArXiv: 1302.5589, 2013.
• Leonardi, F., Matioli, S.R., Armelin, H.A. and Galves, A. Detecting phylogenetic relations out from sparse context trees. ArXiv: math/0804.4279, 2007.

Extended abstracts

• Leonardi, F. and Galves, A. Sequence motif identification and protein family classification using probabilistic trees. In: Simpósio Brasileiro de Bioinformática, BSB 2005, São Leopoldo, RS, Brasil. Lecture Notes in Computer Science 3594, pp. 190-193, 2005. 

PhD Thesis

• Leonardi, F. Cadeias estocásticas parcimoniosas com aplicações à classificação e filogenia das sequências de proteínas. Universidade de São Paulo, 2007.