[R-sig-Geo] Impute missing values along a spatial network

[Tobias Ruttenauer]

Thank you very much for the hint, Roger! Completely right, a Gaussian process actually does not make too much sense in this case. I'll have a look into INLA and see if I can work with that.

For now, I don't have any covariates in this. This is mainly because I'm specifically interested in the annual variation of traffic counts, but available covariates are all time-constant.

Thanks again and best wishes
Tobias


-----Original Message-----
From: Roger Bivand <Roger.Bivand using nhh.no> 
Sent: 24 March 2021 14:18
To: Tobias Ruttenauer <tobias.ruttenauer using nuffield.ox.ac.uk>
Cc: r-sig-geo using r-project.org
Subject: Re: [R-sig-Geo] Impute missing values along a spatial network

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