received a Bachelor´s degree in Statistics from Universidade Estadual de Campinas (1985), MsSci in Mathematics from Associação Instituto Nacional de Matemática Pura e Aplicada (1988) and Phd. in Statistics from University of Wisconsin - Madison (1993). She has expertise in Probability and Statistics, focusing on Special Stochastic Processes, acting on the following subjects: invariant measure, perfect simulation, percolation, spatial point processes and loss networks. (Source: Lattes Curriculum)
| News published in Agência FAPESP Newsletter about the researcher |
| More itemsLess items |
| TITULO |
| Articles published in other media outlets ( ): |
| More itemsLess items |
| VEICULO: TITULO (DATA) |
| VEICULO: TITULO (DATA) |
The Thematic Project proposed here brings together a significant portion of theProbability and Stochastic Processes research group in the state of São Paulo. This group iswell-established in the Departments of Statistics and Mathematics at USP, Unicamp, UFSCar,and UFABC and has gained international visibility and recognition due to several factors: (i) itsconsistent and noteworthy publica…
A mathematical center is proposed to integrate mathematical modeling with basic and applied lines of research at the frontier of neuroscience. The proposal is a response to the increasing importance of mathematical structures in theoretical neuroscience. One of the underlying reasons is the huge mass of data generated by recent experimental capabilities of research, whose analysis require…
Markov Chains with variable length have been widely explored in the literature of probability andstatistics. However, little is known when the transition probabilities depend on exogenous variables. Wepropose novel context algorithms and search for the conditions and asymptotic behavior of the estimatedcontext trees. (AU)
(Only some records are available in English at this moment)
We will study and characterize the phase-transition for the contact process with non-exponential recovery times, in particular, the case when the recovery times are deterministic. Moreover, we will study non-Markovian rumor spreading models on non-complete graphs, in order to obtain limit theorems. (AU)
Variable Length Markov Chains have been used in many fields for temporal stochastic processes in finite state space. Recently, exogenous information has been incorporated into these models in order to better predict the transition probability. On the other hand, when several sources are used, it is not yet known how to incorporate the spatial dependence between the chains.
The data to be analyzed comes from a clinical trial to control/treat the effect of sertraline. The data set consists of 96 patients subject to severe depression, randomized between sertraline and placebo. For each individual, several scalar covariates are measured, as well as resting EEG signals on a total of 14 electrodes. The response for each individual is the difference in the Hamilto…
Markov random fields are often used when analyzing image data. In some applications, these analyses become difficult due to the presence of textures in images, which hinders the use of spatial models with simple interaction neighborhoods because they induce very sophisticated correlation structures. The main goals of the project are (i) to study and develop probabilistic methods for ident…
The objective of this project is to study a spatial network model with set of vertices given by a locally finite set of R^d. Our goal is the construction of an infinite volume Gibbs measure for which the probability of observing a graph is based on the graph's statistics (triangles, stars, vertices degree) and it penalizes edges between nodes that are very far apart.
Poisson processes are one of the most popular point process models for count data. Many natural phenomena can be described with this process, and estimation of parameters is usually easy. The basic assumption for a spatial Poisson process is independence between disjoint sets. However, data from many applications show interaction between points, either by clustering or repulsion. In this …
(Only some records are available in English at this moment)
In this research project we aim to study new statistical inference approaches for networks' analysis. In particular we focus on networks that exhibit community structure, that is, the nodes are organized into groups with similar connection patterns. We are interested in developing new statistical approaches applied to the study of a single network as well as for random samples of networks.
n many areas of science one aims to study latent sub-population based only on observations of aggregated population observation. In this work, aggregated curves will mean linear combination of functional data that cannot be observed individually. We assume that several aggregated curves with linearly independent coefficients are available and each aggregated curve is an independent partia…
| 2 / 2 | Ongoing grants |
| 13 / 11 | Completed research grants |
| 3 / 3 | Ongoing scholarships in Brazil |
| 11 / 7 | Completed scholarships in Brazil |
| 3 / 2 | Completed scholarships abroad |
| 32 / 25 | All research grants and scholarships |
| Associated processes | |
CV Lattes
ORCID