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


From source

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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CircSpaceTime documentation built on June 6, 2019, 5:06 p.m.