Nothing
library(Umpire)
set.seed(97531)
ce <- ClinicalEngine(666, 4, FALSE)
N <- nrow(ce)
dset <- rand(ce, 300)
cnm <- ClinicalNoiseModel(N) # default shape and scale
noisy <- blur(cnm, dset$data)
# next line used to throw a subtle rounding error
dt <- makeDataTypes(dset$data, 1/3, 1/3, 1/3, 0.3,
range = c(3, 9), exact = FALSE)
testfun <- function(NF, exact) {
ce <- ClinicalEngine(NF, 4, FALSE)
N <- nrow(ce)
dset <- rand(ce, 300)
cnm <- ClinicalNoiseModel(N) # default shape and scale
noisy <- blur(cnm, dset$data)
dt <- makeDataTypes(dset$data, 1/3, 1/3, 1/3, 0.3,
range = c(3, 9), exact = exact)
invisible(dt)
}
dt <- testfun(27, exact = FALSE)
dim(dt$binned)
table( sapply(dt$cutpoints, function(x) x$Type) )
dt <- testfun(27, exact = TRUE)
dim(dt$binned)
table( sapply(dt$cutpoints, function(x) x$Type) )
dt <- testfun(81, exact = TRUE)
dim(dt$binned)
table( sapply(dt$cutpoints, function(x) x$Type) )
dt <- testfun(28, exact = TRUE)
dim(dt$binned)
table( sapply(dt$cutpoints, function(x) x$Type) )
dt <- testfun(29, exact = TRUE) # can only get 28 since all blocks are equal size
dim(dt$binned)
table( sapply(dt$cutpoints, function(x) x$Type) )
dt <- testfun(500, exact = FALSE)
dim(dt$binned)
table( sapply(dt$cutpoints, function(x) x$Type) )
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