how do we sample in spatial statistics?

We have developed a spatial sampling library, spsurvey,  that we are
about to submit to cran.  It can sample points, lines, or polygons using
either simple random sampling, unequal probability sampling,
stratification.  Main focus is on spatially balanced sampling - new
approach developed by Stevens and Olsen.  spsurvey currently uses ESRI
shapefiles as main input but when it reads them in it creates an sp
object.  The resulting sample is also an sp object.  A prelliminary
version of the library can be found at http://www.epa.gov/nheerl/arm
under "Software Downloads".  It is called psurvey.design there.
spsurvey should be on cran before end of July.

Tony Olsen




                                                                        
             "Edzer J.                                                  
             Pebesma"                                                   
             <e.pebesma at geo.u                                        To 
             u.nl>                    zhijie zhang <epistat at gmail.com>  
             Sent by:                                                cc 
             r-sig-geo-bounce         r-sig-geo at stat.math.ethz.ch       
             s at stat.math.ethz                                   Subject 
             .ch                      Re: [R-sig-Geo] how do we sample  
                                      in spatial statistics?            
                                                                        
             07/04/2006 01:19                                           
             AM

Dear friends,
  Sorry for sending an empty email because of mismanipulation.
  Do we also use sample() function to do the spatial sampling? I look

for

the sample() and think it's one-dimensional sampling.
In spatial statistics, do we need two-dimentional sampling or some

other

sampling techniques? Which functions could be used in spatial samping

in R?

thanks very much!

spsample in package has a few simple spatial sampling techniques
(basically those described in Ripley, 1981: random, regular,
stratified, nonaligned systematic) on lines, polygons and
grids. More advanced sampling techniques are found in
package spatstat.

--
Edzer

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