CircSpaceTime: an R package for spatial and spatio-temporal modelling of circular data

DOI10.1080/00949655.2020.1725008OpenAlexW3005420815WikidataQ117304402 ScholiaQ117304402MaRDI QIDQ5107778

Gianluca Mastrantonio, Mario Santoro, Giovanna Jona Lasinio

Publication date: 28 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2001.00405

zbMATH Keywords

Rcppcircular dataspatial modelspatio-temporal modelsoftware development

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15)

Related Items

Goodness-of-fit tests for multiple regression with circular response, Recent advances in directional statistics, A non-stationary model for spatially dependent circular response data based on wrapped Gaussian processes

Uses Software

• R
• AMCMC
• foreach
• CircNNTSR
• Rcpp
• RcppArmadillo
• spBayes
• RcppEigen
• CircStats
• circular
• doParallel
• isocir
• Directional
• CircSiZer
• CircSpaceTime
• bpnreg
• rWind
• CircOutlier
• Wrapped

Cites Work

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• A Bayesian model for longitudinal circular data based on the projected normal distribution
• Spatial analysis of wave direction data using wrapped Gaussian processes
• Spatio-temporal circular models with non-separable covariance structure
• A multivariate hidden Markov model for the identification of sea regimes from incomplete skewed and circular time series
• AMCMC: an R interface for adaptive MCMC
• RcppArmadillo: accelerating R with high-performance C++ linear algebra
• Bayesian estimation and hypothesis tests for a circular generalized linear model
• Inference from iterative simulation using multiple sequences
• Directional data analysis under the general projected normal distribution
• Topics in Circular Statistics
• Handbook of Spatial Statistics
• Circular interpretation of regression coefficients
• Applied Directional Statistics
• Detection of outliers in simple circular regression models using the mean circular error statistic
• Modeling Space and Space-Time Directional Data Using Projected Gaussian Processes
• Model-based clustering of multivariate skew data with circular components and missing values
• Estimation of Parameters Subject to Order Restrictions on a Circle With Application to Estimation of Phase Angles of Cell Cycle Genes