A Dirichlet Autoregressive Model for the Analysis of Microbiota Time-Series Data
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 t...
Saved in:
| Main Authors: | I. Creus-Martí, A. Moya, F. J. Santonja |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/9951817 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Bayesian Hierarchical Compositional Models for Analysing Longitudinal Abundance Data from Microbiome Studies
by: I. Creus Martí, et al.
Published: (2022-01-01) -
THE AUTOREGRESSION MODEL WITH DRIFTING COEFFICIENTS FOR THEPREDICTION OF SHORT TIME SERIES
by: Gemma Manvelovna Markarian, et al.
Published: (2022-10-01) -
Modification of ARL for detecting changes on the double EWMA chart in time series data with the autoregressive model
by: Kotchaporn Karoon, et al.
Published: (2023-12-01) -
On close-to-pseudoconvex Dirichlet series
by: O. M. Mulyava, et al.
Published: (2024-06-01) -
THE PROMINENCE OF VECTOR AUTOREGRESSIVE MODEL IN MULTIVARIATE TIME SERIES FORECASTING MODELS WITH STATIONARY PROBLEMS
by: Embay Rohaeti, et al.
Published: (2022-12-01)