A Dirichlet Autoregressive Model for the Analysis of Microbiota Time-Series Data

Autor: A. Moya, I. Creus-Martí, F. J. Santonja
Přispěvatelé: Ministerio de Economía y Competitividad (España), Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), Instituto de Salud Carlos III, Generalitat Valenciana, Asociación Española Contra el Cáncer, European Commission
Rok vydání: 2021
Předmět:
Zdroj: Digital.CSIC. Repositorio Institucional del CSIC
instname
Complexity, Vol 2021 (2021)
Complexity
r-FISABIO. Repositorio Institucional de Producción Científica
ISSN: 1099-0526
1076-2787
Popis: Growing interest in understanding microbiota dynamics has motivated the development of different strategies to model microbiota time series data. However, all of them must tackle the fact that the available data are high-dimensional, posing strong statistical and computational challenges. In order to address this challenge, we propose a Dirichlet autoregressive model with time-varying parameters, which can be directly adapted to explain the effect of groups of taxa, thus reducing the number of parameters estimated by maximum likelihood. A strategy has been implemented which speeds up this estimation. The usefulness of the proposed model is illustrated by application to a case study.
This work was supported by grants from the Spanish Ministry of Economy and Competitiveness (projects MTM2017-83850-P, SAF2012-31187, SAF2013-49788-EXP, and SAF2015-65878-R), Carlos III Institute of Health (projects PIE14/00045 and AC15/00022), Generalitat Valenciana (projects PrometeoII/2014/065 and Prometeo/2018/A/133), and Asociación Española Contra el Cancer (project AECC 2017–1485) and cofinanced by the European Regional Development Fund (ERDF).
Databáze: OpenAIRE
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