## S3 method for class 'quadrattest':
pool(..., df=NULL, df.est=NULL, nsim=1999, Xname=NULL)"quadrattest").df.est.df."quadrattest".pool is generic. This is the method for the
class "quadrattest". An object of class "quadrattest" represents a
$\chi^2$ test or Monte Carlo test
of goodness-of-fit for a point process model, based on quadrat counts.
Such objects are created by the command quadrat.test.
Each of the arguments ... must be an object of class
"quadrattest". They must all be the same type of test
(chi-squared test or Monte Carlo test, conditional or unconditional)
and must all have the same type of alternative hypothesis.
The test statistic of the pooled test is the Pearson $X^2$ statistic taken over all cells (quadrats) of all tests. The $p$ value of the pooled test is then computed using either a Monte Carlo test or a $\chi^2$ test.
For a pooled $\chi^2$ test, the number of degrees of freedom of
the combined test is computed by adding the degrees of freedom
of all the tests (equivalent to assuming the tests are independent)
unless it is determined by the arguments df or df.est.
The resulting $p$ value is computed to obtain the
pooled test.
For a pooled Monte Carlo test, new simulations are performed to determine the pooled Monte Carlo $p$ value.
pool,
quadrat.testY <- split(humberside)
test1 <- quadrat.test(Y[[1]])
test2 <- quadrat.test(Y[[2]])
pool(test1, test2, Xname="Humberside")Run the code above in your browser using DataLab