Florencia Graciela Leonardi
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Universidade de São Paulo (USP). Instituto de Matemática e Estatística (IME) (Institutional affiliation for the last research proposal) Birthplace: Argentina
Florencia Graciela Leonardi in research grants and scholarships supported by FAPESP.
- Model selection in high dimensions: theoretical properties and applications, AP.ESCIENCE.R
Abstract
The main goal of this research project is to study model selection methods for high-dimensional data analysis. The data will be composed by different types and structures, such as graphs and random networks, large vectors or temporal space data. The focus of this project is related to predictive models and the objective is to select models with adequate size in order to minimize the pre...
- XV Latin American Congress of probability and mathematical statistics, AR.EXT
- Structure selection for stochastic processes in high dimensions, AP.R
Abstract
The main goal of this research project is to study methods of statistical inference to identify different structural aspects in stochastic processes in high dimensions. We will consider principally the estimation of the graph of interaction in Markov random fields, also known in the statistical literature as graphical models, and the identification of change points for stochastic proce...
- Consistent estimation of stochastic processes with variable length memory: applications to the modeling of biological sequences, AP.R
Abstract
The main goal of this project is to study the properties of stochastic processes with variable length memory and its estimation. We also propose to apply the tools of data analysis based on this type of processes to two important problems of Biology: the genetic mapping of complex diseases and the characterization of the secondary structure in proteins. From the theoretical point of vi...
(Only some records are available in English at this moment)
- High dimensional statistical inference for stochastic processes with application in neuroscience, BP.PD
Abstract
Over the past years, with the computational advances, statistics have undergone drastic changes, especially with regard to the increasing capacity of data storage. For each individual, more and more features have been collected, then the number of parameters to be estimated have becomes much larger than the number of observations. It is the case, for example, of areas as biology or appl...
- Perfect simulation of probabilistic networks, BP.DR
Abstract
The main goal of this research project is the construction and study of perfect simulation algorithms for probabilistic networks. We will consider the problem of perfect simulation of Markov random fields taking values on a finite alphabet, both in the case of a fixed underlying graph as well as in the case of a random underlying graph. For the latter we will consider principally the ex...
- Perfect simulation of Markov Random Fields on graphs, BE.EP.DR
Abstract
The main goal of this research project is the development of perfect simulation algorithms for Markov random fields defined on graphs, taking values on a finite alphabet. In order to achieve these goals, we will adapt some techniques from the literature and we will study the theoretical properties of the algorithms proposed. In particular we will focus our attention on the Coupling fo...
- Statistical inference for models of brain activity, BE.PQ
Abstract
In this project we will be concerned with the statistical inference of graphical models exhibiting an evolution in time. In particular, we will focus on the following research lines:- The development of new probabilistic models for the description of brain activity, taking into account variable range dependence in time and space. - The use of penalized maximum likelihood and convex prog...
| 1 / 1 | Ongoing research grants |
| 4 / 4 | Completed research grants |
| 4 / 2 | Completed scholarships in Brazil |
| 2 / 2 | Completed scholarships abroad |
| 11 / 9 | All research grants and scholarships |
| Associated processes | |
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
| Publications | 5 |
| Citations | 46 |
| Cit./Article | 9.2 |
| Data from Web of Science | |
GARIVIER, A.; LEONARDI, F.. Context tree selection: A unifying view. Stochastic Processes and their Applications, v. 121, n. 11, p. 2488-2506, NOV 2011. Web of Science Citations: 9.
COLLET, PIERRE; GALVES, ANTONIO; LEONARDI, FLORENCIA. Random perturbations of stochastic processes with unbounded variable length memory. ELECTRONIC JOURNAL OF PROBABILITY, v. 13, p. 1345-1361, AUG 25 2008. Web of Science Citations: 6.
CASTRO, BRUNO M.; LEMES, RENAN B.; CESAR, JONATAS; HUNEMEIER, TABITA; LEONARDI, FLORENCIA. A model selection approach for multiple sequence segmentation and dimensionality reduction. JOURNAL OF MULTIVARIATE ANALYSIS, v. 167, p. 319-330, SEP 2018. Web of Science Citations: 0.
BUSCH, JORGE R.; FERRARI, PABLO A.; FLESIA, ANA GEORGINA; FRAIMAN, RICARDO; GRYNBERG, SEBASTIAN P.; LEONARDI, FLORENCIA. TESTING STATISTICAL HYPOTHESIS ON RANDOM TREES AND APPLICATIONS TO THE PROTEIN CLASSIFICATION PROBLEM. Annals of Applied Statistics, v. 3, n. 2, p. 542-563, JUN 2009. Web of Science Citations: 11.
GALVES, ANTONIO; GALVES, CHARLOTTE; GARCIA, JESUS E.; GARCIA, NANCY L.; LEONARDI, FLORENCIA. CONTEXT TREE SELECTION AND LINGUISTIC RHYTHM RETRIEVAL FROM WRITTEN TEXTS. Annals of Applied Statistics, v. 6, n. 1, p. 186-209, MAR 2012. Web of Science Citations: 20.
(References retrieved automatically from State of São Paulo Research Institutions)
CERQUEIRA, Andressa. Inferência estatística para grafos aleatórios e redes. 2018. Tese (Doutorado) – Instituto de Matemática e Estatística. Universidade de São Paulo (USP). São Paulo.