Hi? I want to use the the correlation setting with corSpher in nlme to account for potential spatial autocorrelation in my data. My data include observations from across the globe with locations in latitude and longitude (decimal degrees). From the R help for corSpher, the example syntax would be something like: fm1Wheat2 <- gls(yield ~ variety - 1, corr =corSpher(c(28, 0.2), form = ~ latitude + longitude, nugget = TRUE)) My question is whether the latitude and longitude provided should be projected into a spatial projection that preserves distances or areas or whether providing decimal degrees is appropriate? Many thanks!
Using corSpher to correct for spatial autocorrelation
2 messages · Julie Lee-Yaw, Thierry Onkelinx
Dear Julie, corSpher() is a spherical variogram / correlogram model. It defines a specific shape of the variogram, not the kind of data. All variogram models in nlme assume Euclidean distances, so you will need projected data. But that opens another can of worm when your data spans a considerable part of the globe. This paper might be relevant for you: https://www.math.ntnu.no/inla/r-inla.org/papers/jss/lindgren.pdf 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 thierry.onkelinx at inbo.be 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 /////////////////////////////////////////////////////////////////////////////////////////// 2018-06-22 2:12 GMT+02:00 Julie Lee-Yaw via R-sig-mixed-models <r-sig-mixed-models at r-project.org>:
Hi
I want to use the the correlation setting with corSpher in nlme to account for potential spatial autocorrelation in my data. My data include observations from across the globe with locations in latitude and longitude (decimal degrees). From the R help for corSpher, the example syntax would be something like:
fm1Wheat2 <- gls(yield ~ variety - 1, corr =corSpher(c(28, 0.2), form = ~ latitude + longitude, nugget = TRUE))
My question is whether the latitude and longitude provided should be projected into a spatial projection that preserves distances or areas or whether providing decimal degrees is appropriate?
Many thanks!
[[alternative HTML version deleted]]
_______________________________________________ R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models