t2norm | R Documentation |
Functions which deliver TRUE
or FALSE
if any approximation if possible.
The approximation parameter c
can be set directly, or it can be given via getOption
. The approximation functions deliver TRUE
in the following scenarios:
t2norm
: n>c
with c=30
binom2norm
: if the type
is "single"
(default) then it checks size × prob (1-prob)>c
, or else it checks size × prob>c
and size × (1-prob)>c
with c=9
clt2norm
: n>c
with c=30
. Note that the existence of the expectation and variance, which are required by the Central Limit Theorem, cannot be checked.
“
t2norm(n, c = getOption("distribution.t2norm", 30))
binom2norm(
size,
prob,
c = getOption("distribution.binom2norm", 9),
type = c("single", "double")
)
clt2norm(n, c = getOption("distribution.clt2norm", 30))
approx_binom2norm(
size,
prob,
c = getOption("distribution.binom2norm", 9),
type = c("single", "double")
)
approx_clt2norm(n, c = getOption("distribution.clt2norm", 30))
approx_t2norm(n, c = getOption("distribution.t2norm", 30))
n |
integer: number of observations |
c |
numeric: approximation parameter (default: |
size |
integer: number of observations |
prob |
numeric: probability of success on each trial |
type |
character: approximation condition used |
logical if the approximation would be possible
# check for 5 observations
t2norm(n=c(5,50))
binom2norm(size=c(5,50), prob=0.5)
binom2norm(size=c(5,50), prob=0.5, type="double")
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