> - krigging in package fields, which also requires irregular spaced data
That kriging requires irregularly spaced data sounds new to me ;) It cannot be, you misread something (I feel free to say that even if I never used that package). It can be tricky doing kriging, though, if you're not comfortable with a little bit of geostatistics. You have to infer a variogram model for each data set; you possibly run into non-stationarity or anisotropy, which are indeed very well treated (maybe at best) by kriging in one of its forms, but ... it takes more than this list to help you then; basically kriging requires modelling, so it is often very difficult to set up an automatic procedure. I can reccomend kriging if the spatial variability of your data (compared to grid refinement) is quite important. In other simple cases, a wheighted mean using the (squared) inverse of the distance as wheight and a spherical neighbourhood could be the simpliest way to perform the interpolation. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
