PACKAGE / R / MIT LICENSE
INLAcircular
Bayesian circular regression and joint circular models using Integrated Nested Laplace Approximation (INLA).
01 / THE PACKAGE
Circular models.
Bayesian computation.
INLAcircular brings together circular distributions, penalized complexity priors, and tools for fitting circular regression and joint circular models.
The distribution and PC-prior functions work without INLA. For model fitting, install INLA separately; the package uses its namespace directly.
02 / GET STARTED
Install from GitHub.
1. Install INLAcircular
Install remotes if needed, then install the development version from the package repository.
install.packages("remotes")
remotes::install_github(
"XiangYEstats/INLAcircular"
)
library(INLAcircular)2. Add INLA for model fitting
Model fitting requires INLA ≥ 25.08.21. It is optional and not installed automatically. Use the stable INLA repository:
install.packages(
"INLA",
repos = c(
getOption("repos"),
INLA = "https://inla.r-inla-download.org/R/stable"
)
)You do not need to attach INLA to use the package. If you attach both packages and want the compatibility inla() function on the search path, load library(INLA) before library(INLAcircular).
03 / DOCUMENTATION
Find the details
when you need them.
The package guide covers circular distributions, PC-prior functions, model specification, direct fitting with INLA::inla(), and inlacc().
help(package = "INLAcircular")
?inlaccIf your installation includes the vignette, open the comprehensive guide with:
vignette(
"INLAcircular-guide",
package = "INLAcircular"
)For a GitHub installation, building the vignette requires build_vignettes = TRUE in the remotes::install_github() call and the guide’s build dependencies. See the remotes installation options and the package repository for the complete setup.