norminvp | R Documentation |
Computes with tail-precision the quantile function
of the standard normal distribution at 0\le p\le 1
,
and truncated to the interval [l,u]
.
Infinite values for vectors l
and u
are accepted.
norminvp(p, l, u)
p |
quantile at |
l |
lower truncation limit |
u |
upper truncation limit |
Suppose we wish to simulate a random variable Z
drawn from N(\mu,\sigma^2)
and
conditional on l<Z<u
using the inverse transform method.
To achieve this, first compute
X=norminvp(runif(1),(l-mu)/sig,(u-mu)/sig)
and then set
Z=mu+sig*X
quantile value of the truncated normal distribution.
If you wish to simulate truncated normal variables fast, use trandn
.
Using norminvp
is advisable only when needed, for example,
in quasi-Monte Carlo or antithetic sampling, where the inverse transform method
is unavoidable.
Zdravko I. Botev
Z. I. Botev (2017), The Normal Law Under Linear Restrictions: Simulation and Estimation via Minimax Tilting, Journal of the Royal Statistical Society, Series B, 79 (1), pp. 1–24.
trandn
d <- 150 # simulate via inverse transform method
norminvp(runif(d),l = 1:d, u = rep(Inf, d))
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