Hi, 

I'm trying to predict the distribution of timber over an area, I have point 
location data- so it would make sense to use a krigging to interpolate the data 
over the whole map. Unfortunately the krigging predictions are pretty bad. 

I have now got environmental data for my study site and have used the r package 
'quantreg' to make a model that I can predict the volume from 
R code:
fit <- rqss(sum_vol~qss(env.factor1,lambda=1)+ qss(env.factor2,lambda=1), tau = 
0.9)
predi<-predict(fit, new, interval = "none", level = 0.9)

unfortunately this is not working either (a problem with the predict function). 
I have also tried linear modelling, Gams and inverse interpolations. 

Does anyone have any ideas on how I could get a spatial map of volume 
distribution from the point data?

Any help is appreciated, 
thank you
sadz

ps- if anything is unclear I would be happy to clarify



      
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