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
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