[R-sig-Geo] Learning Resources Spatial Regression Models from the ground up

[Roger Bivand]

Renato, friends,

This repo: https://github.com/rsbivand/kk_spatial_book has updated code for Katarzyna Kopczwska's book to work after rgdal etc. were retired. I used it in a talk last November which explains what is going on - please contact me if you'd like a copy of the slides.

Roger

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

________________________________________
From: R-sig-Geo <r-sig-geo-bounces using r-project.org> on behalf of Renato Assunção <assuncaoest using gmail.com>
Sent: 24 April 2024 18:50
To: Josiah Parry
Cc: r-sig-geo using r-project.org
Subject: Re: [R-sig-Geo]  Learning Resources Spatial Regression Models from the ground up

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

Hi Josiah,
this book may be useful:

@book{kopczewska2020applied,
  title={Applied spatial statistics and econometrics: data analysis in R},
  author={Kopczewska, Katarzyna},
  year={2020},
  publisher={Routledge}
}

https://tinyurl.com/3v6k5y2h
Renato Assunção


Em qua., 24 de abr. de 2024 às 13:25, Roger Bivand <Roger.Bivand using nhh.no>
escreveu:

> 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.Bivand using nhh.no
>
> ________________________________________
> From: R-sig-Geo <r-sig-geo-bounces using r-project.org> on behalf of Josiah
> Parry <josiah.parry using gmail.com>
> Sent: 24 April 2024 17:58
> To: Christopher W. Ryan
> Cc: r-sig-geo using 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.parry using 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 <cryan using 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]]
> > >
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> > >
> >
>
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