t2norm {exams.forge}

Approximations

Description

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. “

Usage

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))

Arguments

n

integer: number of observations

c

numeric: approximation parameter (default: ⁠getOption("distribution.APPROXFUN)⁠ or a default value)

size

integer: number of observations

prob

numeric: probability of success on each trial

type

character: approximation condition used

Value

logical if the approximation would be possible

Examples

# 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")