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

2024-04-25 Thread Banerjee, Rudy 
https://a.co/d/1gF4NTE Bayesian Analysis for the Social Sciences by Simon 
Jackman m. He deep dives into the philosophy behind both probability axioms of 
finite (Kolgomorov) and countable (de Finetti) perspectives. His take on Bayes 
vs frequentist is a gem! He also clarifies the most severe shortcoming on the 
frequentist approach: that mixed modal priors cannot produce mixed modal 
posteriors … Regards, Rudy Banerjee

On Apr 24, 2024, at 8:53 AM, Christopher W. Ryan via R-sig-Geo 
 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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Re: [R-sig-Geo] Learning Resources Spatial Regression Models from the ground up

2024-04-24 Thread Renato Assunção 
Thank you so much for sharing!
Renato

Em qua., 24 de abr. de 2024 às 13:58, Roger Bivand 
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.biv...@nhh.no
>
> 
> From: R-sig-Geo  on behalf of Renato
> Assunção 
> Sent: 24 April 2024 18:50
> To: Josiah Parry
> 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 assuncao...@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 
> 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.biv...@nhh.no
> >
> > 
> > From: R-sig-Geo  on behalf of Josiah
> > Parry 
> > 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

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

2024-04-24 Thread 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.biv...@nhh.no


From: R-sig-Geo  on behalf of Renato Assunção 

Sent: 24 April 2024 18:50
To: Josiah Parry
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 assuncao...@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 
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.biv...@nhh.no
>
> 
> From: R-sig-Geo  on behalf of Josiah
> Parry 
> 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  >
> 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
> > > no

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

2024-04-24 Thread Roger Bivand 
This is short and well-written: 
https://us.sagepub.com/en-us/nam/spatial-regression-models/book262155,  Spatial 
Regression Models, Second Edition,  Michael D. Ward - Duke University, USA, 
Kristian Skrede Gleditsch - University of Essex, UK.

Roger

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


From: Josiah Parry 
Sent: 24 April 2024 18:35
To: Roger Bivand
Cc: Christopher W. Ryan; r-sig-geo@r-project.org
Subject: Re: [R-sig-Geo] Learning Resources Spatial Regression Models from the 
ground up

Thank you, Roger!

On Wed, Apr 24, 2024 at 12:25 PM Roger Bivand 
mailto:roger.biv...@nhh.no>> wrote:
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/<https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Frsbivand.github.io%2FPG_AGII_2sem%2F&data=05%7C02%7CRoger.Bivand%40nhh.no%7C479829832beb4d92138808dc647c9587%7C33a15b2f849941998d56f20b5aa91af2%7C0%7C0%7C638495733461093640%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=d88qeVfPDYgBhrdwhx0RZtQSXX5SELGjYXex3tUA6Js%3D&reserved=0>.
 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<mailto:roger.biv...@nhh.no>


From: R-sig-Geo 
mailto:r-sig-geo-boun...@r-project.org>> on 
behalf of Josiah Parry mailto:josiah.pa...@gmail.com>>
Sent: 24 April 2024 17:58
To: Christopher W. Ryan
Cc: r-sig-geo@r-project.org<mailto: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<mailto: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 
mailto: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<https://eur02.safelinks.protection.outlook.com/?ur

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

2024-04-24 Thread Renato Assunção 
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 
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.biv...@nhh.no
>
> 
> From: R-sig-Geo  on behalf of Josiah
> Parry 
> 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  >
> 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
> > >
> >
>
> [[alternative HTML version deleted]]
>
> ___
> R-sig-Geo mailing list
> R-sig-Geo@r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> ___
> R-sig-Geo mailing list
> R-sig-Geo@r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>

[[alternative HTML version deleted]]

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

2024-04-24 Thread Josiah Parry 
Thank you, Roger!

On Wed, Apr 24, 2024 at 12:25 PM Roger Bivand  wrote:

> 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  on behalf of Josiah
> Parry 
> 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  >
> 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
> > >
> >
>
> [[alternative HTML version deleted]]
>
> ___
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> R-sig-Geo@r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>

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

2024-04-24 Thread Roger Bivand 
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  on behalf of Josiah Parry 

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

2024-04-24 Thread Dexter Locke 
in GeoDA  Luc Anselin and Sergio J. Rey. (2014). Modern Spatial
Econometrics in Practice: A Guide to GeoDa, GeoDaSpace and PySAL. [link to
book]


Exploring Spatial Data with GeoDa: A Workbook (2005; 244 pp.,5.1Mb)
https://geodacenter.github.io/docs/geodaworkbook.pdfhttps://geodacenter.github.io/docs/geodaworkbook.pdf
Chapters
17, 18, 21, 22 - 25.

More conceptually advanced, at least look at figure 1: Golgher, A. B., &
Voss, P. R. (2016). How to Interpret the Coefficients of Spatial Models:
Spillovers, Direct and Indirect Effects. Spatial Demography, 4(3), 175–205.
https://doi.org/10.1007/s40980-015-0016-y

-Dexter


On Wed, Apr 24, 2024 at 12:03 PM Josiah Parry 
wrote:

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

2024-04-24 Thread Josiah Parry 
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 
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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Re: [R-sig-Geo] Learning Resources Spatial Regression Models from the ground up

2024-04-24 Thread Christopher W. Ryan via R-sig-Geo 
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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