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dagHMM
View on CRAN: Click
here
Download and install dagHMM package within the R console
Install from CRAN:
install.packages("dagHMM")
Install from Github:
library("remotes")
install_github("cran/dagHMM")
Install by package version:
library("remotes")
install_version("dagHMM", "0.1.0")
Attach the package and use:
library("dagHMM")
Maintained by
Prajwal Bende
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
First Published: 2023-01-10
Latest Update: 2023-10-20
Description:
Hidden Markov models (HMMs) are a formal foundation for making probabilistic models of linear sequence. They provide a conceptual toolkit for building complex models just by drawing an intuitive picture. They are at the heart of a diverse range of programs, including genefinding, profile searches, multiple sequence alignment and regulatory site identification. HMMs are the Legos of computational sequence analysis. In graph theory, a tree is an undirected graph in which any two vertices are connected by exactly one path, or equivalently a connected acyclic undirected graph. Tree represents the nodes connected by edges. It is a non-linear data structure. A poly-tree is simply a directed acyclic graph whose underlying undirected graph is a tree. The model proposed in this package is the same as an HMM but where the states are linked via a polytree structure rather than a simple path.
How to cite:
Prajwal Bende (2023). dagHMM: Directed Acyclic Graph HMM with TAN Structured Emissions. R package version 0.1.0, https://cran.r-project.org/web/packages/dagHMM. Accessed 28 Mar. 2025.
Previous versions and publish date:
0.1.0 (2023-01-10 19:40)
Other packages that cited dagHMM R package
View dagHMM citation profile
Other R packages that dagHMM depends,
imports, suggests or enhances
Functions, R codes and Examples using
the dagHMM R package
Some associated functions: backward . baumWelch . baumWelchRecursion . bwd_seq_gen . calc_emis . forward . fwd_seq_gen . gen_emis . initHMM . noisy_or .
Some associated R codes: backward.R . baumWelch.R . bwd_seq_gen.R . forward.R . fwd_seq_gen.R . initHMM.R . Full dagHMM package functions and examples
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