uls.sim {smerc} | R Documentation |
uls.test
on simulated datauls.sim
efficiently performs
uls.test
on a simulated data set. The
function is meant to be used internally by the
uls.test
function, but is informative for
better understanding the implementation of the test.
uls.sim( nsim = 1, ty, ex, w, pop, ubpop, type = "poisson", check.unique = FALSE, cl = NULL )
nsim |
A positive integer indicating the number of simulations to perform. |
ty |
The total number of cases in the study area. |
ex |
The expected number of cases for each region. The default is calculated under the constant risk hypothesis. |
w |
A binary spatial adjacency matrix for the regions. |
pop |
The population size associated with each region. |
ubpop |
The upperbound of the proportion of the total population to consider for a cluster. |
type |
The type of scan statistic to compute. The
default is |
check.unique |
A logical value indicating whether a
check for unique values should be determined. The
default is |
cl |
A cluster object created by |
A vector with the maximum test statistic for each simulated data set.
data(nydf) data(nyw) coords = with(nydf, cbind(longitude, latitude)) cases = floor(nydf$cases) pop = nydf$pop ty = sum(cases) ex = ty/sum(pop) * pop tsim = uls.sim(1, ty, ex, nyw, pop = pop, ubpop = 0.5)