Title: Microbe-Metabolite Interactions-Based Metabolic Profiles
person(given = "Guangchuang", family = "Yu",
Implements a computational framework to predict microbial community-based
metabolic profiles with 'O2PLS' model. It provides procedures of model
training and prediction. Paired microbiome and metabolome data are needed
for modeling, and the trained model can be applied to predict metabolites
of analogous environments using new microbial feature abundances.
Imports: magrittr (>= 2.0.1), OmicsPLS (>= 2.0.2), utils, stats
Suggests: rmarkdown, knitr, prettydoc, testthat (>= 3.0.0)
Author: Wenli Tang [aut, cre] (<https://orcid.org/0000-0002-6141-5854>),
Guangchuang Yu [aut, ths] (<https://orcid.org/0000-0002-6485-8781>)

Description: Implement different types of model mixing and model
selection methods for linear or logistic models.

Title: Model selection uncertainty and model mixing

Packaged: 2012-06-18 09:11:23 UTC; Administrateur

Title: Fitting Markov-Modulated Linear Regression Models
person("Nadezda", "Spiridovska", email = "Spiridovska.N@tsi.lv", role = c("aut", "cre")),
person("Diana", "Santalova", role = "ctb"))
Description: A set of tools for fitting Markov-modulated linear regression, where responses Y(t) are time-additive, and model operates in the external environment, which is described as a continuous time Markov chain with finite state space.
Model is proposed by Alexander Andronov (2012) <arXiv:1901.09600v1> and algorithm of parameters estimation is based on eigenvalues and eigenvectors decomposition.
Also, package will provide a set of data simulation tools for Markov-modulated linear regression (for academical/research purposes).
Packaged: 2019-01-29 14:25:08 UTC; Nadezda Spiridovska

Markov-switching regression models have the same idea of varying the regression parameters randomly in accordance with external environment. The difference is that for Markov-modulated linear regression model the external environment is described as a continuous-time homogeneous irreducible Markov chain with known parameters while switching models consider Markov chain as unobserved and estimation procedure involves estimation of transition matrix.
These models have significant differences in terms of the analytical approach.
Also, package provides a set of data simulation tools for Markov-modulated linear regression (for academical/research purposes).
Packaged: 2020-01-08 09:11:00 UTC; Nadezda Spiridovska