famuvie / georcb Goto Github PK

While package gdistance works well enough for most purposes, for really large datasets it may be more efficient to wrap up the geodesic C++ library by Danil Kirsanov.
It implements a geodesic (shortest path) algorithm for a triangular mesh (triangulated surface).

Doing so would also require to implement methods for constructing and manipulating the meshes.
We could borrow that functionality from r-inla.

I am in the process of doing this in my fork of this repo.

...of the covariance matrix for the observations.

• Possibly adding an automatic correction (?)

Hi,

I am using your very useful code, and thank you for it !

Nevertheless, when I am using the krige.conv method, I have some problem of divergence that I don't observe using the standard krige.conv method of GeoR with the same parameters.

Adding the distance matrices give me very diverging results when the geodata set increase. For one or two points to krige on my network I don't have any problem, but when there are more than 500 points to "merge", very extreme values appear.

Did you already observe this phenomenon ? Do you have any idea about which parameters could be badly given in my function ?

krige.conv(geodata= Obs,
locations = PT_gd$coords,
krige=krige.control(cov.model="spherical",cov.pars=c(30,500), nugget=0),
dd.dists.mat=distances, dl.dists.mat=distances_to_obs )

Thank you.

Kind regards,

Pierre

P.S. I checked my distance matrices and they seems to be ok.