Please also consider:

@book{lesage+pace:09,
   author={James P. {LeSage} and R. Kelley Pace},
   title={Introduction to Spatial Econometrics},
   year={2009},
   publisher={Chapman and Hall/CRC},
   address={Boca Raton FL}
}

which provides the underpinnings to Golgher & Voss just suggested by Dexter. A 
good deal has been going on recently, both about spillovers, and very recent 
work by Bera & Koley on Rao score tests (aka Lagrange multiplier tests). I have 
some notes but no recording from recent lectures, so the notes are skeletal at 
best: https://rsbivand.github.io/PG_AGII_2sem/. In SDSr, my focus was on 
pointing up the topics areas where spatial econometrics could very well benefit 
from the much larger community in disease mapping and in ecology. In both of 
these broad communities, the dependent variable is often discrete, and both of 
these draw lots of maps. I haven't yet got Modelling Spatial and 
Spatial-Temporal Data: A Bayesian Approach by Haining & Li, and expect it to be 
useful.

Hope this helps,

Roger

--
Roger Bivand
Emeritus Professor
Norwegian School of Economics
Postboks 3490 Ytre Sandviken, 5045 Bergen, Norway
roger.biv...@nhh.no

________________________________________
From: R-sig-Geo <r-sig-geo-boun...@r-project.org> on behalf of Josiah Parry 
<josiah.pa...@gmail.com>
Sent: 24 April 2024 17:58
To: Christopher W. Ryan
Cc: r-sig-geo@r-project.org
Subject: Re: [R-sig-Geo]  Learning Resources Spatial Regression Models from the 
ground up

[You don't often get email from josiah.pa...@gmail.com. Learn why this is 
important at https://aka.ms/LearnAboutSenderIdentification ]

Thank you, Chris! I can take a look at the first resource. At the moment my
interest is specifically in spatial econometric models and less so about
point patterns (for the time being).

On Wed, Apr 24, 2024 at 11:51 AM Christopher W. Ryan <cr...@binghamton.edu>
wrote:

> Josiah--
>
> I've found the following very helpful over the years:
>
> Geographic Information Analysis, by David O'Sullivan and David Unwin
>
> Spatial Point Patterns, by Adrian Baddeley, Ege Rubak, and Rolf Turner
>
> Applied Spatial Data Analysis with R, by Roger Bivand, Edzer Pebesma,
> and Virgilio Gomez-Rubio
>
> Statistical Analysis of Spatial and Spatio-Temporal Point Patterns
>
> The last 3 are, as the titles imply, focused specifically on spatial
> point patterns. The first is a bit more general, including methods for
> areal data.
>
> I listed them in increasing order (in my opinion) of mathemtical
> complexity.
>
> --Chris Ryan
>
> In
> Josiah Parry wrote:
> > Hey folks,
> >
> > I'm hoping to build up my knowledge around spatial regression techniques
> > from the ground up—e.g. I'm not interested in R-INLA or other
> exceptionally
> > complex techniques.
> >
> > I'm hoping this listserv has some recommendations for what readings /
> > models I should prioritize learning about in, possibly, an opinionated
> > order.
> >
> > At the moment I've purchased "Modern Spatial Econometrics in Practice" by
> > Luc Anselin and Sergio Rey and will try to work through that. But if
> there
> > are additional resources that folks recommend that are friendly for the
> > not-so-math-inclined, I'd love to have a look at them!
> >
> > The Spatial Regression section of the R-spatial book (
> > https://r-spatial.org/book/16-SpatialRegression.html) is good but with
> less
> > handholding than I might need.
> >
> >       [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > R-sig-Geo mailing list
> > R-sig-Geo@r-project.org
> > https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> >
>

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