sig-geo@stat.math.ethz.ch
Subject: [R-sig-Geo] Regression Kriging
Hello Sir/Madam
This is Pritam Chand, working as Technical Associate in Forest Survey of
India, Dehrdaun. I have some doubts regarding regression kriging. Actually I
am trying to make final regression kriging predicted map and using R
Hello Sir/Madam
This is Pritam Chand, working as Technical Associate in Forest Survey of
India, Dehrdaun. I have some doubts regarding regression kriging. Actually I
am trying to make final regression kriging predicted map and using R and
ILWIS software. I am able to reach steps upto variogram an
Alisa, those references are certainly *very* relevant!
Thanks!
Facundo.-
Alisa Coffin escribió:
> Don & Facundo,
>
> This is something that I'm interested in as well for coastal marine
> applications.
>
> The only solution I've found so far is a cumbersome "barrier" function
> available i
Hi Don, sorry about de delay,
Don MacQueen escribió:
> Facundo,
>
> I am interested in essentially the same thing, though my application
> is inside buildings. I am wondering what technique(s), software, etc.
> you would be using to calculate your distances.
well, in fact i didn't face the prob
The soap package that accompanies mgcv may be of interest:
http://www.maths.bath.ac.uk/~sw283/simon/software.html
Cheers, Mike.
Alisa Coffin wrote:
> Don & Facundo,
>
> This is something that I'm interested in as well for coastal marine
> applications.
>
> The only solution I've found so far is
Don & Facundo,
This is something that I'm interested in as well for coastal marine
applications.
The only solution I've found so far is a cumbersome "barrier" function
available in the kriging operation of ArcGIS. I would be interested in
seeing an (better) implementation of the idea in R.
I was
Facundo,
I am interested in essentially the same thing,
though my application is inside buildings. I am
wondering what technique(s), software, etc. you
would be using to calculate your distances.
I asked about this about a month ago, here on
r-sig-geo, and received some helpful replies. The
Hello All,
I'm performing regression kriging (using both gstat and geoR) in an
urban environment. Thus, i have discontinuities (buildings) in the
prediction space which make distances to be non-euclidean.
I need to estimate variogram and make predictions using distances
calculated by myself
Dear Edzer,
I've "medidated" on the answer you gave to Jose. Two considerations have raise:
1 - when you say that the approach of GLM is a way to consider
spatial dependence. I'm not sure about this. GLM are a way to account
for link functions between the dependent variables and covariates (ex.
P
Jose, is your model linear, or are you using a generalized linear model?
The questions is not so much: model parameters before or after kriging
residuals, but rather: model parameters under the assumption of
independent observations (the usual regression approach), or model
parameters under the as
Hi,
I have used regression kriging to model abundance of an invasive
species. After performing a stepwise regression of the model, I fitted
a theoretical variogram to a empirical variogram of the residuals. My
question is how to obtain the parameter estimate of the model after
kriging the residual
egression line.
>
>
> see also:
> FITTING DISTRIBUTIONS WITH R (by Vito Ricci)
> http://cran.r-project.org/doc/contrib/Ricci-distributions-en.pdf
>
>
> Tom Hengl
> http://spatial-analyst.net
>
>
> -----Original Message-
> From: [EMAIL PROTECTED] [mailto:
o Ricci)
http://cran.r-project.org/doc/contrib/Ricci-distributions-en.pdf
Tom Hengl
http://spatial-analyst.net
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of
G. Allegri
Sent: dinsdag 15 januari 2008 15:28
To: r-sig-geo@stat.math.ethz.ch
Subject:
I'm trying to realize e regression kriging with gstat package on my
soil samples data. The response variable (ECe measuere) and covariates
appear positvely skewed.
As Tomislav Hengl suggests in its "framework for RK" [1], a logistic
transformation is proposed as a generic way to reduce the skewenes
14 matches
Mail list logo
