14 citations · 40 across the 13 of their papers we have counts for
15 papers
Sparse Markov Models for High-dimensional Inference
Guilherme Ost, Daniel Takahashi
Finite order Markov models are theoretically well-studied models for dependent discrete data. Despite their generality, application in empirical work when the order is large is rar…
Self-Switching Markov Chains: emerging dominance phenomena
S. Gallo, G. Iacobelli, G. Ost +1
In many dynamical systems in nature, the law of the dynamics changes along with the temporal evolution of the system. These changes are often associated with the occurrence of cert…
Mixing rates for potentials of non-summable variations
Christophe Gallesco, Daniel Y. Takahashi
Mixing rates and decay of correlations for dynamics defined by potentials with summable variations are well understood, but little is known for non-summable variations. In this pap…
Correlation between graphs with an application to brain networks analysis
André Fujita, Daniel Yasumasa Takahashi, Joana Bisol Balardin +1
The global functional brain network (graph) is more suitable for characterizing brain states than local analysis of the connectivity of brain regions. Therefore, graph-theoretic ap…
Consolidating a Link Centered Neural Connectivity Framework with Directed Transfer Function Asymptotics
Luiz A. Baccalá, Daniel Y. Takahashi, Koichi Sameshima
We present a unified mathematical derivation of the asymptotic behaviour of three of the main forms of \textit{directed transfer function} (DTF) complementing recent partial direct…
Characterization of the stability of chains associated with -measures
Christophe Gallesco, Sandro Gallo, Daniel Yasumasa Takahashi
In this paper we introduce a notion of asymptotic stability of a probability kernel, which we call dynamic uniqueness. We say that a kernel exhibits dynamic uniqueness if all the s…
A statistical test to identify differences in clustering structures
André Fujita, Daniel Y. Takahashi, Alexandre G. Patriota +1
Statistical inference on functional magnetic resonance imaging (fMRI) data is an important task in brain imaging. One major hypothesis is that the presence or not of a psychiatric…
Explicit estimates in the Bramson-Kalikow model
Christophe Gallesco, Sandro Gallo, Daniel Yasumasa Takahashi
The aim of the present article is to explicitly compute parameters for which the Bramson-Kalikow model exhibits phase-transition. The main ingredient of the proof is a simple new c…
Discriminating different classes of biological networks by analyzing the graphs spectra distribution
Daniel Yasumasa Takahashi, João Ricardo Sato, Carlos Eduardo Ferreira +1
The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such…
Attractive regular stochastic chains: perfect simulation and phase transition
Sandro Gallo, Daniel Yasumasa Takahashi
We prove that uniqueness of the stationary chain, or equivalently, of the -measure, compatible with an attractive regular probability kernel is equivalent to either one of the f…
Markov Approximations of chains of infinite order in the -metric
Sandro Gallo, Matthieu Lerasle, Daniel Yasumasa Takahashi
We derive explicit upper bounds for the -distance between a chain of infinite order and its canonical -steps Markov approximation. Our proof is entirely constructive an…
Sharp oracle inequalities and slope heuristic for specification probabilities estimation in discrete random fields
Matthieu Lerasle, Daniel Y. Takahashi
We study the problem of estimating the one-point specification probabilities in non-necessary finite discrete random fields from partially observed independent samples. Our procedu…
Information theoretic interpretation of frequency domain connectivity measures
Daniel Yasumasa Takahashi, Luiz Antonio Baccalá, Koichi Sameshima
To provide adequate multivariate measures of information flow between neural structures, modified expressions of Partial Directed Coherence (PDC) and Directed Transfer Function (DT…
An Oracle Approach for Interaction Neighborhood Estimation in Random Fields
Matthieu Lerasle, Daniel Yasumasa Takahashi
We consider the problem of interaction neighborhood estimation from the partial observation of a finite number of realizations of a random field. We introduce a model selection rul…
Identifying interacting pairs of sites in Ising models on a countable set
Antonio Galves, Enza Orlandi, Daniel Yasumasa Takahashi
This paper address the problem of identifying pairs of interacting sites from a finite sample of independent realizations of the Ising model. We consider Ising models in a infinite…