We are looking for a worked out example of spatiotemporal interpolation (using spatiotemporal kriging / regression-kriging or universal kriging) of daily precipitation in R. Daily precipitation is a zero-inflated variable so using some model based geostatistical solution (https://www.jstatsoft.org/article/view/v063i12/v63i12.pdf) is probably not an option? We would like to compare geostatistical interpolation with the spacetime RF: https://github.com/thengl/GeoMLA#prediction-of-spatio-temporal-variable thank you, T. Hengl https://orcid.org/0000-0002-9921-5129 _______________________________________________ R-sig-Geo mailing list [hidden email] https://stat.ethz.ch/mailman/listinfo/r-sig-geo |
Dear Tomislav,
Blangiardo and Cameletti (2015) Spatial and Spatio-temporal Bayesian Models with R - INLA models the Parana state rainfall data (chapter 8). See https://sites.google.com/a/r-inla.org/stbook/ Not kriging but maybe useful for you. Best regards, ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance [hidden email] Havenlaan 88 bus 73, 1000 Brussel www.inbo.be /////////////////////////////////////////////////////////////////////////////////////////// To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey /////////////////////////////////////////////////////////////////////////////////////////// 2018-04-10 22:26 GMT+02:00 Tomislav Hengl <[hidden email]>: > > We are looking for a worked out example of spatiotemporal interpolation > (using spatiotemporal kriging / regression-kriging or universal kriging) of > daily precipitation in R. Daily precipitation is a zero-inflated variable so > using some model based geostatistical solution > (https://www.jstatsoft.org/article/view/v063i12/v63i12.pdf) is probably not > an option? > > We would like to compare geostatistical interpolation with the spacetime RF: > > https://github.com/thengl/GeoMLA#prediction-of-spatio-temporal-variable > > thank you, > > T. Hengl > https://orcid.org/0000-0002-9921-5129 > > _______________________________________________ > R-sig-Geo mailing list > [hidden email] > https://stat.ethz.ch/mailman/listinfo/r-sig-geo _______________________________________________ R-sig-Geo mailing list [hidden email] https://stat.ethz.ch/mailman/listinfo/r-sig-geo |
Hi,
> Blangiardo and Cameletti (2015) Spatial and Spatio-temporal Bayesian > Models with R - INLA models the Parana state rainfall data (chapter > 8). See https://sites.google.com/a/r-inla.org/stbook/ Not kriging but > maybe useful for you. > This is also modeled in the SPDE tutorial http://www.r-inla.org/examples/tutorials/spde-tutorial . Also, I have fitted a space-time model using INLA for the Ireland wind data described in the spacetime vignette. Not really what you want, but you can change the likelihood to a zero-inflated one (INLA provides several of them) if that is what you want… Best, Virgilio _______________________________________________ R-sig-Geo mailing list [hidden email] https://stat.ethz.ch/mailman/listinfo/r-sig-geo |
Free forum by Nabble | Edit this page |