fast.sim | R Documentation |
fast.test
on simulated datafast.sim
efficiently performs
fast.test
on a simulated data set. The
function is meant to be used internally by the
fast.test
function, but is informative for
better understanding the implementation of the test.
fast.sim(nsim = 1, ty, ex, pop, ubpop, type = "poisson", 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. |
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 |
cl |
A cluster object created by |
A vector with the maximum test statistic for each simulated data set.
data(nydf)
coords <- with(nydf, cbind(longitude, latitude))
cases <- floor(nydf$cases)
pop <- nydf$pop
ty <- sum(cases)
ex <- ty / sum(pop) * pop
tsim <- fast.sim(1, ty, ex, pop = pop, ubpop = 0.5)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.