Hi all,
  In classical statistics, we always need to generate a theoretical model
such as y=a+b1*x1+b2*x2+e to study some new estimation content. I am
wondering how to generate the similar spatial dataset for a theoretical
model.
Say y is response variable, x1 and x2 are explanatory variables.
1. If y is a continous variable, how should we generate the dataset for a
theoretical spatial point process model in R?
2. If y is a continous variable, how should we generate the dataset for a
theoretical spatial lattice data model in R?
3. If y is 0/1 binary variable, how should we generate the dataset for a
theoretical spatial point process model in R?
4. If y is 0/1 binary variable, how should we generate the dataset for a
ttheoretical spatial lattice data in R?
  spatstat and other packages allow us to generate a dataset of a specified
point process and other models, but it seems that they donot allow us to
include possible explanatory variables into a theoretical model. Maybe i
missed some ideas in them.
  Anybody can express some ideas or point out some useful resources on the
above four different situations? Small examples in R are preferred.
  Thanks a lot.

-- 
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Jane Chang
Queen's

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