[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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