Spatial and Spatio-Temporal Bayesian Model for Circular Data
Average Prediction Error for circular Variables.
CircSpaceTime: implementation of Bayesian models, for spatial and spat...
Testing Convergence of mcmc using package coda
The Continuous Ranked Probability Score for Circular Variables.
Kriging using projected normal model.
#' Spatio temporal interpolation using projected spatial temporal norm...
Samples from the Projected Normal spatial model
Samples from the posterior distribution of the Projected Normal spatia...
Rose diagram in ggplot2 inspired from rose.diag in package circular.
Spatial interpolation using wrapped normal model.
Prediction using wrapped normal spatio-temporal model.
Samples from the Wrapped Normal spatial model
Samples from the posterior distribution of the Wrapped Normal spatial ...
Implementation of Bayesian models for spatial and spatio-temporal interpolation of circular data using Gaussian Wrapped and Gaussian Projected distributions. We developed the methods described in Jona Lasinio G. et al. (2012) <doi: 10.1214/12-aoas576>, Wang F. et al. (2014) <doi: 10.1080/01621459.2014.934454> and Mastrantonio G. et al. (2016) <doi: 10.1007/s11749-015-0458-y>.