dagHMM: Directed Acyclic Graph HMM with TAN Structured Emissions

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.

Getting started

Package details

AuthorPrajwal Bende [aut, cre], Russ Greiner [ths], Pouria Ramazi [ths]
MaintainerPrajwal Bende <prajwal.bende@gmail.com>
LicenseGPL (>= 2.0.0)
Version0.1.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("dagHMM")

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dagHMM documentation built on Jan. 11, 2023, 1:13 a.m.