Installation
About
Random univariate and multivariate finite mixture model generation, estimation, clustering, latent class analysis and classification. Variables can be continuous, discrete, independent or dependent and may follow normal, lognormal, Weibull, gamma, Gumbel, binomial, Poisson, Dirac, uniform or circular von Mises parametric families.
Citation | rebmix citation info |
Key Metrics
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Maintainer
Maintainer | Marko Nagode |
Depends
R | ≥ 3.1.0 |
Imports
methods | |
stats | |
utils | |
graphics | |
grDevices |