Learning Resources Spatial Regression Models from the ground up

Thank you so much for sharing!
Renato

Em qua., 24 de abr. de 2024 ?s 13:58, Roger Bivand <Roger.Bivand at nhh.no>
escreveu:
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 at nhh.no

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

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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 Assun??o

Em qua., 24 de abr. de 2024 ?s 13:25, Roger Bivand <Roger.Bivand at 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 at nhh.no

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

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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 at 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.

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Learning Resources Spatial Regression Models from the ground up

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