IMIFA
Infinite Mixtures of Infinite Factor Analysers and Related Models
Provides flexible Bayesian estimation of Infinite Mixtures of Infinite Factor Analysers and related models, for nonparametrically clustering high-dimensional data, introduced by Murphy et al. (2020) <doi:10.1214/19-BA1179>. The IMIFA model conducts Bayesian nonparametric model-based clustering with factor analytic covariance structures without recourse to model selection criteria to choose the number of clusters or cluster-specific latent factors, mostly via efficient Gibbs updates. Model-specific diagnostic tools are also provided, as well as many options for plotting results, conducting posterior inference on parameters of interest, posterior predictive checking, and quantifying uncertainty.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.2.0 |
rolling source/ R- | IMIFA_2.2.0.tar.gz |
2.4 MiB |
2.2.0 |
rolling linux/jammy R-4.5 | IMIFA_2.2.0.tar.gz |
3.5 MiB |
2.2.0 |
rolling linux/noble R-4.5 | IMIFA_2.2.0.tar.gz |
3.5 MiB |
2.2.0 |
latest source/ R- | IMIFA_2.2.0.tar.gz |
2.4 MiB |
2.2.0 |
latest linux/jammy R-4.5 | IMIFA_2.2.0.tar.gz |
3.5 MiB |
2.2.0 |
latest linux/noble R-4.5 | IMIFA_2.2.0.tar.gz |
3.5 MiB |
2.2.0 |
2026-04-26 source/ R- | IMIFA_2.2.0.tar.gz |
2.4 MiB |
2.2.0 |
2026-04-23 source/ R- | IMIFA_2.2.0.tar.gz |
2.4 MiB |
2.2.0 |
2026-04-09 windows/windows R-4.5 | IMIFA_2.2.0.zip |
3.5 MiB |
2.2.0 |
2025-04-20 source/ R- | IMIFA_2.2.0.tar.gz |
2.4 MiB |