R package citation, R package reverse dependencies, R package scholars, install an r package from GitHub hy is package acceptance pending why is package undeliverable amazon why is package on hold dhl tour packages why in r package r and r package full form why is r free why r is bad which r package to install which r package has which r package which r package version which r package readxl which r package ggplot which r package fread which r package license where is package.json where is package-lock.json where is package.swift where is package explorer in eclipse where is package where is package manager unity where is package installer android where is package manager console in visual studio who r package which r package to install which r package version who is package who is package deal who is package design r and r package full form r and r package meaning what r package has what package r what is package in java what is package what is package-lock.json what is package in python what is package.json what is package installer do r package can't install r packages r can't find package r can't load package can't load xlsx package r can't install psych package r can't install sf package r Write if else in NONMEM pk pd
mHMMbayes
View on CRAN: Click
here
Download and install mHMMbayes package within the R console
Install from CRAN:
install.packages("mHMMbayes")
Install from Github:
library("remotes")
install_github("cran/mHMMbayes")
Install by package version:
library("remotes")
install_version("mHMMbayes", "1.1.0")
Attach the package and use:
library("mHMMbayes")
Maintained by
Emmeke Aarts
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-10-25
Latest Update: 2023-10-02
Description:
An implementation of the multilevel (also known as mixed or random
effects) hidden Markov model using Bayesian estimation in R. The multilevel
hidden Markov model (HMM) is a generalization of the well-known hidden
Markov model, for the latter see Rabiner (1989) . The
multilevel HMM is tailored to accommodate (intense) longitudinal data of
multiple individuals simultaneously, see e.g., de Haan-Rietdijk et al.
. Using a multilevel framework, we allow
for heterogeneity in the model parameters (transition probability matrix and
conditional distribution), while estimating one overall HMM. The model can
be fitted on multivariate data with either a categorical, normal, or Poisson
distribution, and include individual level covariates (allowing for e.g.,
group comparisons on model parameters). Parameters are estimated using
Bayesian estimation utilizing the forward-backward recursion within a hybrid
Metropolis within Gibbs sampler. Missing data (NA) in the dependent
variables is accommodated assuming MAR. The package also includes various
visualization options, a function to simulate data, and a function to obtain
the most likely hidden state sequence for each individual using the Viterbi
algorithm.
How to cite:
Emmeke Aarts (2019). mHMMbayes: Multilevel Hidden Markov Models Using Bayesian Estimation. R package version 1.1.0, https://cran.r-project.org/web/packages/mHMMbayes. Accessed 22 Dec. 2024.
Previous versions and publish date:
Other packages that cited mHMMbayes R package
View mHMMbayes citation profile
Other R packages that mHMMbayes depends,
imports, suggests or enhances
Complete documentation for mHMMbayes
Functions, R codes and Examples using
the mHMMbayes R package
Some associated functions: int_to_prob . mHMM . mHMMbayes-package . nonverbal . nonverbal_cov . obtain_emiss . obtain_gamma . pd_RW_emiss_cat . pd_RW_gamma . plot.mHMM . plot.mHMM_gamma . prior_emiss_cat . prior_emiss_cont . prior_gamma . prob_to_int . sim_mHMM . vit_mHMM .
Some associated R codes: RcppExports.R . data.R . forward_prob.R . forward_prob_cpp.R . int_to_prob.R . logl_mnl.R . mHMM.R . mHMMbayes-package.R . mnl_RW_once.R . mnl_hess.R . obtain_emiss.R . obtain_gamma.R . pd_RW_emiss_cat.R . pd_RW_gamma.R . plot.mHMM.R . plot.mHMM_gamma.R . print.mHMM.R . print.mHMM_.R . prior_emiss_cat.R . prior_emiss_cont.R . prior_gamma.R . sim_mHMM.R . summary.mHMM.R . utility_func_mHMM.R . vit_mHMM.R . Full mHMMbayes package functions and examples
Downloads during the last 30 days
Get rewarded with contribution points by
helping add
Reviews / comments / questions /suggestions ↴↴↴
Today's Hot Picks in Authors and Packages
quickcode
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Obinna Obianom (view profile)
tropAlgebra
It includes functions like tropical addition, tropical multiplication for vectors and matrices. In t ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Muhammad Kashif Hanif (view profile)
dmlalg
Implementation of double machine learning (DML) algorithms in R,
based on Emmenegger and Buehlmann ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Corinne Emmenegger (view profile)
composits
A compositional multivariate and univariate time series outlier ensemble.It uses the four R packages ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Sevvandi Kandanaarachchi (view profile)
elect
Functions to compute state-specific and marginal life expectancies. The computation is based on a fi ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Ardo van den Hout (view profile)
LOGANTree
Enables researchers to model log-file data from computer-based assessments using machine-learning te ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Qi Qin (view profile)