DIRECT
Bayesian Clustering of Multivariate Data Under the Dirichlet-Process Prior
A Bayesian clustering method for replicated time series or replicated measurements from multiple experimental conditions, e.g., time-course gene expression data. It estimates the number of clusters directly from the data using a Dirichlet-process prior. See Fu, A. Q., Russell, S., Bray, S. and Tavare, S. (2013) Bayesian clustering of replicated time-course gene expression data with weak signals. The Annals of Applied Statistics. 7(3) 1334-1361. doi:10.1214/13-AOAS650.
- Version1.1.0
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release09/07/2023
Documentation
Team
Audrey Qiuyan Fu
Show author detailsRolesAuthorSteven Russell
Show author detailsRolesAuthorSarah J. Bray
Show author detailsRolesAuthorSimon Tavare
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 224 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 3,620 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Apr 17, 2024 with 34 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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