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• W3186476570 abstract "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." @default.
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• W3186476570 date "2021-07-17" @default.
• W3186476570 modified "2023-10-16" @default.
• W3186476570 title "A Dirichlet Autoregressive Model for the Analysis of Microbiota Time-Series Data" @default.
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• W3186476570 doi "https://doi.org/10.1155/2021/9951817" @default.
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