activity
20092015
most citedVector Autoregressive Models With Measurement Errors for Testing Ganger Causality

9 citations · 23 across the 5 of their papers we have counts for

collaborators

5 papers

stat.ME2015★ 5 cited

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…

stat.ME2013★ 2 cited

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…

stat.ME2012★ 4 cited

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…

stat.ME2009★ 9 cited

Vector Autoregressive Models With Measurement Errors for Testing Ganger Causality

Alexandre G. Patriota, Joao R. Sato, Betsabe G. Blas

This paper develops a method for estimating parameters of a vector autoregression (VAR) observed in white noise. The estimation method assumes the noise variance matrix is known an…

stat.ME2009★ 3 cited

Identification and quantification of Granger causality between gene sets

Andre Fujita, Joao Ricardo Sato, Kaname Kojima +4

Wiener and Granger have introduced an intuitive concept of causality between two variables which is based on the idea that an effect never occurs before its cause. Later, Geweke ha…