[R-sig-Geo] Impute missing values along a spatial network
Roger Bivand
Roger@B|v@nd @end|ng |rom nhh@no
Wed Mar 24 15:18:16 CET 2021
On Wed, 24 Mar 2021, Tobias Ruttenauer wrote:
> Dear list members,
>
> I am trying to construct a road network with traffic estimates for each
> road segment. I have count data of the traffic for a subset of the
> segments and I have the road network as spatial lines data. For those
> segments without count data, I would like to perform something like
> linear imputation or some sort of interpolation / kriging along the road
> network instead of using pure geographical distance. For instance, if I
> have 7 road segments A-B-C-D-E and F-G (F and G are unconnected to the
> rest), and I have data for A and D, how can I impute data for B, C (and
> E) by only using A and D, while ignoring F and G even though they might
> be geographically close?
Are there any relevant covariates associated with the road segments? I
think that this is more of a Markov than a Gaussian random field, so a
Poisson spatial regression with a neighbour matrix representing contiguous
segments might be possible. Covariates, or an offset by an expected volume
might help. INLA with a Besag model - INLA fits missing responses, or
mgcv::gam() with an "mrf" smooth or hglm() then predict?
Any other suggestions?
Roger
>
> This seems fairly intuitive to me but I couldn't find a package doing
> that. stplanr would do something related but it seems it needs
> origin-destination data (which I don't have). I'd be grateful if someone
> could nudge me into the right direction. I guess I'm using the wrong
> terminology.
>
> Thanks a lot and best wishes
> Tobias
>
> Tobias Rüttenauer
> Nuffield College
> University of Oxford
> Oxford, OX1 1NF
>
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--
Roger Bivand
Department of Economics, Norwegian School of Economics,
Postboks 3490 Ytre Sandviken, 5045 Bergen, Norway.
e-mail: Roger.Bivand using nhh.no
https://orcid.org/0000-0003-2392-6140
https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
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