PhD student in Statistics at the University of Campinas (Unicamp), studying about Variable Length Markov Chains and their applications in predicting Dengue cases. Undertook a scientific initiation in the area of Unfolding Models of Item Response Theory (TRI), with a project financed by the Fundação de Amparo à pesquisa do Estado de São Paulo (FAPESP). Worked as an independent researcher for the International Policy Center for Inclusive Growth (IPC-IG) and as a research fellow for the National School of Public Administration (ENAP) and for the Brazilian Agricultural Research Corporation (EMBRAPA). (Source: Lattes Curriculum)
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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 present project aims to study the main one-dimensional and parametric Item Response Theory (IRT) unfolding models, providing an appropriate methodological review, discussing aspects such as interpretation, applicability and estimation and implementing them in the computational environment R, through frequentist/Bayesian marginal-profiled methods. As far as we are concerned, there are …
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