Bayesian mixture models of univariate Gaussian distributions using JAGS

Bayesian mixture models of univariate Gaussian
distributions using JAGS

c(person("Bettina", "Gruen", role = c("aut", "cre"),
email = "Bettina.Gruen@jku.at"),
person("Martyn", "Plummer", role = "ctb"))
Bettina Gruen [aut, cre],
Martyn Plummer [ctb]

graphics, stats, methods, rjags (>= 2.1.0), coda (>= 0.13)
The fitting of finite mixture models of univariate
Gaussian distributions using JAGS within a Bayesian
framework is provided.

c(person("Bettina", "Gruen", role = c("aut", "cre"),
email = "Bettina.Gruen@R-project.org",
comment = c(ORCID = "0000-0001-7265-4773")),
person("Martyn", "Plummer", role = "ctb",
comment = c(ORCID = "0000-0001-5130-6497")))
Fits finite mixture models of univariate Gaussian distributions using JAGS within a Bayesian framework.

The 'Tidymodels' Extension for Bayesian Models
c(
person("Alberto", "Almuiña", email = "albertogonzalezalmuinha@gmail.com", role = c("aut", "cre"))
)
Bayesian framework for use with the 'tidymodels' ecosystem. Includes the following models: Sarima, Garch,
Random walk (naive), Additive Linear State Space Models, Stochastic Volatily Models from 'bayesforecast' package,
Adaptive Splines Surfaces from 'BASS' package and ETS from 'Rlgt' package.
R (>= 4.0.0), parsnip, bayesforecast, bsts
rlang (>= 0.1.2), brms, BASS, StanHeaders, Rlgt, rstan,
magrittr, purrr, dplyr, stringr, tibble, tidyr, dials, rsample,
workflows, modeltime, timetk
tidymodels, tidyverse, lubridate, knitr, rmarkdown, roxygen2,
testthat (>= 3.0.0), covr

Bayesian framework for use with the 'tidymodels' ecosystem. Includes the following models: Sarima, Garch,
Random walk (naive), Additive Linear State Space Models, Stochastic Volatility Models from 'bayesforecast' package,
Adaptive Splines Surfaces from 'BASS' package and ETS from 'Rlgt' package.
rlang (>= 0.1.2), brms, BASS, Rlgt, rstan, magrittr, purrr,
dplyr, tibble, dials, workflows, modeltime, timetk, cli,
crayon, rstudioapi

Non-Parametric Bayesian Analyses of Animal Movement
c(person(given = "Joshua",
family = "Cullen",
role = c("aut", "cre", "cph"),
email = "joshcullen10@gmail.com",
comment = c(ORCID = "0000-0002-6935-9340")),
person(given = "Denis",
family = "Valle",
role = c("aut", "cph")))
Methods for assessing animal movement from telemetry and biologging
data using non-parametric Bayesian methods. This includes features for pre-
processing and analysis of data, as well as the visualization of results
from the models. This framework does not rely on standard parametric density
functions, which provides flexibility during model fitting.
covr, testthat, spelling, knitr, rmarkdown, ggforce,
RcppArmadillo
Joshua Cullen [aut, cre, cph] (<https://orcid.org/0000-0002-6935-9340>),
Denis Valle [aut, cph]