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A Bayesian Nonparametric model for the study of time-evolving frequencies, which has become renowned in the study of population genetics. The model consists of a Hidden Markov Model (HMM) in which the latent signal is a distribution-valued stochastic process that takes the form of a finite mixture of Dirichlet Processes, indexed by vectors that count how many times each value is observed in the population. The package implements methodologies presented in Ascolani, Lijoi and Ruggiero (2021) <doi:10.1214/20-BA1206> and Ascolani, Lijoi and Ruggiero (2023) <doi:10.3150/22-BEJ1504> that make it possible to study the process at the time of data collection or to predict its evolution in future or in the past.
Version: | 0.1.2 |
Imports: | Rcpp, Rdpack |
LinkingTo: | Rcpp |
Suggests: | rmarkdown, knitr |
Published: | 2024-07-09 |
DOI: | 10.32614/CRAN.package.FVDDPpkg |
Author: | Stefano Damato [aut, cre] |
Maintainer: | Stefano Damato <stefano.damato at idsia.ch> |
License: | LGPL (≥ 3) |
NeedsCompilation: | yes |
Materials: | README |
CRAN checks: | FVDDPpkg results |
Reference manual: | FVDDPpkg.pdf |
Vignettes: |
FVDDPpkg |
Package source: | FVDDPpkg_0.1.2.tar.gz |
Windows binaries: | r-devel: FVDDPpkg_0.1.2.zip, r-release: FVDDPpkg_0.1.2.zip, r-oldrel: FVDDPpkg_0.1.2.zip |
macOS binaries: | r-release (arm64): FVDDPpkg_0.1.2.tgz, r-oldrel (arm64): FVDDPpkg_0.1.2.tgz, r-release (x86_64): FVDDPpkg_0.1.2.tgz, r-oldrel (x86_64): FVDDPpkg_0.1.2.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.