[size=1.2em]Normal inverse cumulative distribution function

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X = norminv(P,mu,sigma)
[X,XLO,XUP] = norminv(P,mu,sigma,pcov,alpha)

X = norminv(P,mu,sigma) computes the inverse of the normal cdf using the corresponding mean mu and standard deviation sigma at the corresponding probabilities in P. P, mu, and sigma can be vectors, matrices, or multidimensional arrays that all have the same size. A scalar input is expanded to a constant array with the same dimensions as the other inputs. The parameters in sigma must be positive, and the values in P must lie in the interval [0 1].

[X,XLO,XUP] = norminv(P,mu,sigma,pcov,alpha) produces confidence bounds for X when the input parameters mu and sigma are estimates.pcov is the covariance matrix of the estimated parameters. alpha specifies 100(1 - alpha)% confidence bounds. The default value of alpha is 0.05.XLO and XUP are arrays of the same size as X containing the lower and upper confidence bounds.