Spatial and Spatio-Temporal Bayesian Model for Circular Data
Implementation of Bayesian models for spatial and spatio-temporal interpolation of circular data using Gaussian Wrapped and Gaussian Projected distributions.
Currently the following models are implemented: Spatial Wrapped Normal Spatial Projected Normal Spatio-Temporal Wrapped Normal Spatio-Temporal Projected Normal
If you are linux/linux-like users or simply you want to compile from source the best way is to use "devtools"
r
devtools_installed <- require(devtools)
if (!devtools_installed){
install.packages("devtools", dep = TRUE)
library(devtools)
}
install_github("santoroma/CircSpaceTime")
Dependencies: Rcpp, RcppArmadillo, circular, ggplot2, coda Suggested: foreach, parallel, iterators, doParallel, knitr, rmarkdown, gridExtra
### From CRAN The package is in submission on CRAN.
r
install.packages("CircSpaceTime", dep = TRUE)
## Using the package
r
library(CircSpaceTime)
For further information on the package you can read the help or take a look at the vignette
Please help us to improve the package! For any issue/error/"what is this?" report the best way is to visit the issues page and: 1. Find if already exist a similar issue, read it and if the case write a precise comment with reproducible example. 2. If not, open a new one writing a precise comment with reproducible example.
## Thanks
Mario, Gianluca and Giovanna
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.