Lognormal inverse cumulative distribution function
X = logninv(P,mu,sigma)
[X,XLO,XUP] = logninv(P,mu,sigma,pcov,alpha)
X = logninv(P,mu,sigma) returns
P of the inverse lognormal cdf with distribution
the mean and standard deviation, respectively, of the associated normal
be vectors, matrices, or multidimensional arrays that all have the
same size, which is also the size of
A scalar input for
expanded to a constant array with the same dimensions as the other
[X,XLO,XUP] = logninv(P,mu,sigma,pcov,alpha) returns
confidence bounds for
X when the input parameters
pcov is the covariance matrix of the
alpha specifies 100(1 -
bounds. The default value of
alpha is 0.05.
arrays of the same size as
X containing the lower
and upper confidence bounds.
logninv computes confidence bounds for
a normal approximation to the distribution of the estimate
where q is the
from a normal distribution with mean 0 and standard deviation 1. The
computed bounds give approximately the desired confidence level when
large samples, but in smaller samples other methods of computing the
confidence bounds might be more accurate.
The lognormal inverse function is defined in terms of the lognormal cdf as
 Evans, M., N. Hastings, and B. Peacock. Statistical Distributions. Hoboken, NJ: Wiley-Interscience, 2000. pp. 102–105.