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FVDDPpkg
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Download and install FVDDPpkg package within the R console
Install from CRAN:
install.packages("FVDDPpkg")
Install from Github:
library("remotes")
install_github("cran/FVDDPpkg")
Install by package version:
library("remotes")
install_version("FVDDPpkg", "0.1.2")
Attach the package and use:
library("FVDDPpkg")
Maintained by
Stefano Damato
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.FVDDPpkg . FVDDPpkg results . FVDDPpkg.pdf . FVDDPpkg . FVDDPpkg_0.1.2.tar.gz . FVDDPpkg_0.1.2.zip . FVDDPpkg_0.1.2.zip . FVDDPpkg_0.1.2.zip . FVDDPpkg_0.1.2.tgz . FVDDPpkg_0.1.2.tgz . FVDDPpkg_0.1.2.tgz . FVDDPpkg_0.1.2.tgz . FVDDPpkg_0.1.2.tgz . FVDDPpkg_0.1.2.tgz . https://CRAN.R-project.org/package=FVDDPpkg .
First Published: 2024-07-09
Latest Update: 2024-07-09
Description:
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.
How to cite:
Stefano Damato (2024). FVDDPpkg: Implement Fleming-Viot-Dependent Dirichlet Processes. R package version 0.1.2, https://cran.r-project.org/web/packages/FVDDPpkg. Accessed 21 Feb. 2025.
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