Ultimixt
Bayesian Analysis of Location-Scale Mixture Models using a Weakly Informative Prior
A generic reference Bayesian analysis of unidimensional mixture distributions obtained by a location-scale parameterisation of the model is implemented. The including functions simulate and summarize posterior samples for location-scale mixture models using a weakly informative prior. There is no need to define priors for scale-location parameters except two hyperparameters in which are associated with a Dirichlet prior for weights and a simplex.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.1 |
rolling linux/jammy R-4.5 | Ultimixt_2.1.tar.gz |
152.5 KiB |
2.1 |
rolling linux/noble R-4.5 | Ultimixt_2.1.tar.gz |
152.5 KiB |
2.1 |
rolling source/ R- | Ultimixt_2.1.tar.gz |
22.7 KiB |
2.1 |
latest linux/jammy R-4.5 | Ultimixt_2.1.tar.gz |
152.5 KiB |
2.1 |
latest linux/noble R-4.5 | Ultimixt_2.1.tar.gz |
152.5 KiB |
2.1 |
latest source/ R- | Ultimixt_2.1.tar.gz |
22.7 KiB |
2.1 |
2026-04-26 source/ R- | Ultimixt_2.1.tar.gz |
22.7 KiB |
2.1 |
2026-04-23 source/ R- | Ultimixt_2.1.tar.gz |
22.7 KiB |
2.1 |
2026-04-09 windows/windows R-4.5 | Ultimixt_2.1.zip |
155.0 KiB |
2.1 |
2025-04-20 source/ R- | Ultimixt_2.1.tar.gz |
22.7 KiB |