R package spTimer: Spatio-Temporal Bayesian Modelling. Fits, spatially predicts and temporally forecasts large amounts of space-time data using [1] Bayesian Gaussian Process (GP) Models, [2] Bayesian Auto-Regressive (AR) Models, and [3] Bayesian Gaussian Predictive Processes (GPP) based AR Models for spatio-temporal big-n problems. Bakar and Sahu (2015) <doi:10.18637/jss.v063.i15>.

References in zbMATH (referenced in 20 articles , 1 standard article )

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  1. Sahu, Sujit K.: Bayesian modeling of spatio-temporal data with R (2022)
  2. Mahdi, Esam; Alshamari, Sana; Khashabi, Maryam; Alkorbi, Alya: Hierarchical Bayesian spatio-temporal modeling for (\mathrmPM_10) prediction (2021)
  3. Bakar, K. Shuvo: Interpolation of daily rainfall data using censored Bayesian spatially varying model (2020)
  4. Bakar, K. Shuvo; Jin, Huidong: Areal prediction of survey data using Bayesian spatial generalised linear models (2020)
  5. Gilani, Owais; Urbanek, Simon; Kane, Michael J.: Distributions of human exposure to ozone during commuting hours in Connecticut using the cellular device network (2020)
  6. Waleed Almutiry, Vineetha Warriyar K V, Rob Deardon: Continuous Time Individual-Level Models of Infectious Disease: a Package EpiILMCT (2020) arXiv
  7. Araki, Takamitsu; Akaho, Shotaro: Spatially multi-scale dynamic factor modeling via sparse estimation (2019)
  8. Bass, Mark R.; Sahu, Sujit K.: Dynamically updated spatially varying parameterizations of hierarchical Bayesian models for spatial data (2019)
  9. Ickowicz, Adrien; Ford, Jessica; Hayes, Keith: A mixture model approach for compositional data: inferring land-use influence on point-referenced water quality measurements (2019)
  10. Mukhopadhyay, Sabyasachi; Ogutu, Joseph O.; Bartzke, Gundula; Dublin, Holly T.; Piepho, Hans-Peter: Modelling spatio-temporal variation in sparse rainfall data using a hierarchical Bayesian regression model (2019)
  11. Duncan Lee; Alastair Rushworth; Gary Napier: Spatio-Temporal Areal Unit Modeling in R with Conditional Autoregressive Priors Using the CARBayesST Package (2018) not zbMATH
  12. Bakar, K. Shuvo; Kokic, Philip; Jin, Huidong: Hierarchical spatially varying coefficient and temporal dynamic process models using \textttspTDyn (2016)
  13. Del Sarto, Simone; Ranalli, Maria Giovanna; Cappelletti, David; Moroni, Beatrice; Crocchianti, Stefano; Castellini, Silvia: Modelling spatio-temporal air pollution data from a mobile monitoring station (2016)
  14. Andrew Finley; Sudipto Banerjee; Alan Gelfand: spBayes for Large Univariate and Multivariate Point-Referenced Spatio-Temporal Data Models (2015) not zbMATH
  15. Edzer Pebesma; Roger Bivand; Paulo Ribeiro: Software for Spatial Statistics (2015) not zbMATH
  16. Fabio Sigrist; Hans Künsch; Werner Stahel: spate: An R Package for Spatio-Temporal Modeling with a Stochastic Advection-Diffusion Process (2015) not zbMATH
  17. Khandoker Bakar; Sujit Sahu: spTimer: Spatio-Temporal Bayesian Modeling Using R (2015) not zbMATH
  18. Martin Schlather; Alexander Malinowski; Peter Menck; Marco Oesting; Kirstin Strokorb: Analysis, Simulation and Prediction of Multivariate Random Fields with Package RandomFields (2015) not zbMATH
  19. Francesco Finazzi; Alessandro Fassò: D-STEM: A Software for the Analysis and Mapping of Environmental Space-Time Variables (2014) not zbMATH
  20. Duncan Lee: CARBayes: An R Package for Bayesian Spatial Modeling with Conditional Autoregressive Priors (2013) not zbMATH