Imputation of missing spatial areal data

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Imputation of missing spatial areal data

AMITHA PURANIK
Hello everyone,

I would like to know whether it is possible to use the spatial
autoregressive model to impute missing values in aggregate data? If the OLS
model is replaced with SAR model in regression imputation, would it lead to
better estimates for missing values in a spatial data?
Any opinion/ suggestion is appreciated.

Thanks in advance.

Amitha Puranik.

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Re: Imputation of missing spatial areal data

Roger Bivand
Administrator
On Mon, 28 Oct 2019, Amitha Puranik wrote:

> Hello everyone,
>
> I would like to know whether it is possible to use the spatial
> autoregressive model to impute missing values in aggregate data? If the
> OLS model is replaced with SAR model in regression imputation, would it
> lead to better estimates for missing values in a spatial data? Any
> opinion/ suggestion is appreciated.

Please see the article referenced in the help page for
spatialreg::predict.sarlm():

Michel Goulard, Thibault Laurent & Christine Thomas-Agnan, 2017 About
predictions in spatial autoregressive models: optimal and almost optimal
strategies, Spatial Economic Analysis Volume 12, Issue 2-3, 304-325

The differences in the spatial error model would be through any
differences in covariate coefficient values, but if the differences are
large, the Hausman test for misspecification would fail. Your post nudged
me to raise an issue on spatialreg about SLX prediction, which very likely
also makes sense, and to check predictions where Durbin=TRUE more
generally.

Roger

>
> Thanks in advance.
>
> Amitha Puranik.
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-Geo mailing list
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> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>

--
Roger Bivand
Department of Economics, Norwegian School of Economics,
Helleveien 30, N-5045 Bergen, Norway.
voice: +47 55 95 93 55; e-mail: [hidden email]
https://orcid.org/0000-0003-2392-6140
https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en

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Roger Bivand
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N-5045 Bergen, Norway
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Re: Imputation of missing spatial areal data

AMITHA PURANIK
Dear Roger,

Thank you for the quick response. I shall refer the article that you
recommended.

Kind regards,
Amitha Puranik.


On Mon, Oct 28, 2019 at 3:39 PM Roger Bivand <[hidden email]> wrote:

> On Mon, 28 Oct 2019, Amitha Puranik wrote:
>
> > Hello everyone,
> >
> > I would like to know whether it is possible to use the spatial
> > autoregressive model to impute missing values in aggregate data? If the
> > OLS model is replaced with SAR model in regression imputation, would it
> > lead to better estimates for missing values in a spatial data? Any
> > opinion/ suggestion is appreciated.
>
> Please see the article referenced in the help page for
> spatialreg::predict.sarlm():
>
> Michel Goulard, Thibault Laurent & Christine Thomas-Agnan, 2017 About
> predictions in spatial autoregressive models: optimal and almost optimal
> strategies, Spatial Economic Analysis Volume 12, Issue 2-3, 304-325
>
> The differences in the spatial error model would be through any
> differences in covariate coefficient values, but if the differences are
> large, the Hausman test for misspecification would fail. Your post nudged
> me to raise an issue on spatialreg about SLX prediction, which very likely
> also makes sense, and to check predictions where Durbin=TRUE more
> generally.
>
> Roger
>
> >
> > Thanks in advance.
> >
> > Amitha Puranik.
> >
> >       [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > R-sig-Geo mailing list
> > [hidden email]
> > https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> >
>
> --
> Roger Bivand
> Department of Economics, Norwegian School of Economics,
> Helleveien 30, N-5045 Bergen, Norway.
> voice: +47 55 95 93 55; e-mail: [hidden email]
> https://orcid.org/0000-0003-2392-6140
> https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
>

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