telescope
Bayesian Mixtures with an Unknown Number of Components
Fits Bayesian finite mixtures with an unknown number of components using the telescoping sampler and different component distributions. For more details see Frühwirth-Schnatter et al. (2021) doi:10.1214/21-BA1294.
- Version0.2-0
- R versionR (≥ 4.0.0)
- LicenseGPL-2
- Needs compilation?No
- telescope citation info
- Last release01/23/2025
Documentation
- VignetteBayesian Latent Class Analysis Models with the Telescoping Sampler
- VignetteBayesian Mixture of Latent Class Analysis Models with the Telescoping Sampler
- VignetteBayesian Poisson Mixtures with the Telescoping Sampler
- VignetteBayesian Multivariate Gaussian Mixtures with the Telescoping Sampler
- VignetteBayesian Univariate Gaussian Mixtures with the Telescoping Sampler
- MaterialNEWS
Team
Gertraud Malsiner-Walli
MaintainerShow author detailsBettina Grün
Sylvia Frühwirth-Schnatter
Insights
Last 30 days
This package has been downloaded 160 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 2 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 1,808 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 Jun 16, 2024 with 47 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.
Data provided by CRAN
Binaries
Dependencies
- Imports6 packages
- Suggests6 packages