The dataset contains a simulated georeferenced population of dimension \(N=1000\). The coordinates are generated in the range \([0,1]\) as a simulated realization of a particular random point pattern: the Neyman-Scott process with Cauchy cluster kernel. The nine values for each unit are generated according to the outcome of a Gaussian stochastic process, with an intensity dependence parameter \(\rho=0.1\) (that means high dependence) and with a spatial trend \(x_{1}+x_{2}+\epsilon\).
simul3A data frame with 1000 rows and 11 variables:
coordinate x
coordinate y
first value of the unit
second value of the unit
third value of the unit
fourth value of the unit
fifth value of the unit
sixth value of the unit
seventh value of the unit
eighth value of the unit
ninth value of the unit