rtnorm90ci generates truncated normal random numbers based on the 90% confidence interval
calculating the distribution parameter numerically from the 90%-confidence interval or via a
fit on the 90%-confidence interval. The fit might include the median or not.
rposnorm90ci generates positive normal random numbers based on the 90% confidence interval.
It is a wrapper function for rtnorm90ci.
rtnorm_0_1_90ci generates normal random numbers truncated to \([0,1]\) based on the
90% confidence interval. It is a wrapper function for rtnorm90ci.
rtnorm90ci(
n,
ci,
median = mean(ci),
lowerTrunc = -Inf,
upperTrunc = Inf,
method = "numeric",
relativeTolerance = 0.05,
...
)rposnorm90ci(
n,
lower,
median = mean(c(lower, upper)),
upper,
method = "numeric",
relativeTolerance = 0.05,
...
)
rtnorm_0_1_90ci(
n,
lower,
median = mean(c(lower, upper)),
upper,
method = "numeric",
relativeTolerance = 0.05,
...
)
Number of generated observations.
numeric 2-dimensional vector; lower, i.e ci[[1]], and upper bound, i.e
ci[[2]], of the 90%-confidence interval.
if NULL: truncated normal is fitted only to lower and upper value of the
confidence interval; if numeric: truncated normal is fitted on the confidence interval
and the median simultaneously. For details cf. below. This option is only relevant if
method="fit".
numeric; lower truncation point of the distribution (>= -Inf).
numeric; upper truncation point of the distribution (<= Inf).
method used to determine the parameters of the truncated normal; possible methods
are "numeric" (the default) and "fit".
numeric; the relative tolerance level of deviation of the
generated confidence interval from the specified interval. If this deviation is greater than
relativeTolerance a warning is given.
further parameters to be passed to paramtnormci_numeric or
paramtnormci_fit, respectively.
numeric; lower bound of the 90% confidence interval.
numeric; upper bound of the 90% confidence interval.
method="numeric" is implemented by paramtnormci_numeric and
method="fit" by paramtnormci_fit.
Positive normal random number generation: a positive normal distribution
is a truncated normal distribution with lower truncation point equal to zero and upper truncation
is infinity. rposnorm90ci implements this as a wrapper function for
rtnorm90ci(n, c(lower,upper), median, lowerTrunc=0, upperTrunc=Inf, method, relativeTolerance,...).
0-1-(truncated) normal random number generation: a 0-1-normal distribution
is a truncated normal distribution with lower truncation point equal to zero and upper truncation
equal to 1. rtnorm_0_1_90ci implements this as a wrapper function for
rtnorm90ci(n, c(lower,upper), median, lowerTrunc=0, upperTrunc=1, method, relativeTolerance,...).
For the implementation of method="numeric": paramtnormci_numeric;
for the implementation of method="fit": paramtnormci_fit.