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.
Learning Resources Spatial Regression Models from the ground up
11 messages · Josiah Parry, Christopher W. Ryan, Dexter Locke +3 more
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 at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
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.
[[alternative HTML version deleted]]
_______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
in GeoDA Luc Anselin and Sergio J. Rey. (2014). Modern Spatial Econometrics in Practice: A Guide to GeoDa, GeoDaSpace and PySAL. [link to book] <https://www.amazon.com/Modern-Spatial-Econometrics-Practice-GeoDaSpace/dp/0986342106?ie=UTF8&keywords=anselin%20spatial%20econometrics&qid=1421531753&ref_=sr_1_1&sr=8-1> 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 <josiah.parry at gmail.com> 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 <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.
[[alternative HTML version deleted]]
_______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
[[alternative HTML version deleted]]
_______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
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
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
[You don't often get email from josiah.parry at 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 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. > > > > [[alternative HTML version deleted]] > > > > _______________________________________________ > > R-sig-Geo mailing list > > R-sig-Geo at r-project.org > > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > > > [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
Thank you, Roger!
On Wed, Apr 24, 2024 at 12:25?PM Roger Bivand <Roger.Bivand at 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/. 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 [You don't often get email from josiah.parry at 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 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. [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
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 [You don't often get email from josiah.parry at 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 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. [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo _______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
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.Bivand at nhh.no
From: Josiah Parry <josiah.parry at gmail.com>
Sent: 24 April 2024 18:35
To: Roger Bivand
Cc: Christopher W. Ryan; r-sig-geo at r-project.org
Subject: Re: [R-sig-Geo] Learning Resources Spatial Regression Models from the ground up
Sent: 24 April 2024 18:35
To: Roger Bivand
Cc: Christopher W. Ryan; r-sig-geo at 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 <Roger.Bivand at nhh.no<mailto:Roger.Bivand at 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.Bivand at nhh.no<mailto:Roger.Bivand at nhh.no>
________________________________________
From: R-sig-Geo <r-sig-geo-bounces at r-project.org<mailto:r-sig-geo-bounces at r-project.org>> on behalf of Josiah Parry <josiah.parry at gmail.com<mailto:josiah.parry at gmail.com>>
Sent: 24 April 2024 17:58
To: Christopher W. Ryan
Cc: r-sig-geo at r-project.org<mailto:r-sig-geo at 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 at gmail.com<mailto:josiah.parry at 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 at binghamton.edu<mailto: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<https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fr-spatial.org%2Fbook%2F16-SpatialRegression.html&data=05%7C02%7CRoger.Bivand%40nhh.no%7C479829832beb4d92138808dc647c9587%7C33a15b2f849941998d56f20b5aa91af2%7C0%7C0%7C638495733461105290%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=3A0FGWazHD8Y2ZkGipNU1kmdHUZXcFac7teNY3%2FaryI%3D&reserved=0>) is good but with
> less
> > handholding than I might need.
> >
> > [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > R-sig-Geo mailing list
> > R-sig-Geo at r-project.org<mailto:R-sig-Geo at r-project.org>
> > https://stat.ethz.ch/mailman/listinfo/r-sig-geo<https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fstat.ethz.ch%2Fmailman%2Flistinfo%2Fr-sig-geo&data=05%7C02%7CRoger.Bivand%40nhh.no%7C479829832beb4d92138808dc647c9587%7C33a15b2f849941998d56f20b5aa91af2%7C0%7C0%7C638495733461113282%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=k1vLJpymp1g8%2FtFxC5tBK5X5WcQcU0tNtdvTnDpaO7M%3D&reserved=0>
> >
>
[[alternative HTML version deleted]]
_______________________________________________
R-sig-Geo mailing list
R-sig-Geo at r-project.org<mailto:R-sig-Geo at r-project.org>
https://stat.ethz.ch/mailman/listinfo/r-sig-geo<https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fstat.ethz.ch%2Fmailman%2Flistinfo%2Fr-sig-geo&data=05%7C02%7CRoger.Bivand%40nhh.no%7C479829832beb4d92138808dc647c9587%7C33a15b2f849941998d56f20b5aa91af2%7C0%7C0%7C638495733461119640%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=kTJAc3SAyqIII97slv9fhrllhyq7Fw%2FSlKQ1Rbaw3AI%3D&reserved=0>
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
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
[You don't often get email from assuncaoest at 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 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 > > [You don't often get email from josiah.parry at 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 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. > > > > > > [[alternative HTML version deleted]] > > > > > > _______________________________________________ > > > R-sig-Geo mailing list > > > R-sig-Geo at r-project.org > > > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > > > > > > > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-Geo mailing list > R-sig-Geo at r-project.org > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > _______________________________________________ > R-sig-Geo mailing list > R-sig-Geo at r-project.org > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
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 [You don't often get email from assuncaoest at 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 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 [You don't often get email from josiah.parry at 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 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. [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo _______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
1 day later
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 <r-sig-geo at r-project.org> 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. _______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo _______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo