[R-sig-Geo] fitting nested structure model variogram using gstat

[Edzer Pebesma]

On 02/25/2014 07:26 PM, Moshood Agba Bakare wrote:
> Dear All,
> I have fitted basic model such as spherical, Gaussian, exponential, and
> linear to empirical variogram using gstat library in R. The models were
> fitted in omnidirectional and different directions to detect if the data
> exhibit anisotropy.
> 
> mpvar<-variogram(yield~1,canmod.sp,cutoff=300,width = 7 , cressie=TRUE)
> plot(empvar, xlab = "Lag distance (m)", ylab = "Semivariance", main =
> "Omnidirectional empirical Variogram for Yield")
> 
> 
> ### directional variogram
> empvar<-variogram(yield ~ 1,canmod.sp,cutoff=300,width =
> 7,alpha=c(0,45,90,135),cressie=TRUE)
> plot(empvar,xlab = "Lag distance (m)", ylab = "Semivariance", main =
> "Directional empirical Variogram
> 
> without defining the lag tolerance in my script, hope this would not have
> negative impact on my result.
> 
> secondly, I intend to fit nested structure model by looking at the linear

Your "firstly" just escaped me.

> combination of those basic model (spherical, gaussian, exponential, and
> linear). Please how do I modify my R script in gstat to model such a
> complex nested structure?

?vgm

> 
> Thirdly, if it is a must to define my lag tolerance, will it be 1.5 times
> whatever I use as my lag distance as specified by width=7?
> 

I don't know what you mean by "lag tolerance" -- does this term come
from the GSLIB literature? gstat::variogram does allow lags to overlap;
if you'd want this you'd need to write your own smoother for variogram
clouds.
-- 
Edzer Pebesma
Institute for Geoinformatics (ifgi), University of Münster
Heisenbergstraße 2, 48149 Münster, Germany. Phone: +49 251
83 33081 http://ifgi.uni-muenster.de GPG key ID 0xAC227795

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