logncdf
              "upper")"upper")Log-normal cumulative distribution function (CDF).
For each element of x, compute the cumulative distribution function (CDF) of the log-normal distribution with mean parameter mu and standard deviation parameter sigma, each corresponding to the associated normal distribution. The size of p is the common size of x, mu, and sigma. A scalar input functions as a constant matrix of the same size as the other inputs.
If a random variable follows this distribution, its logarithm is normally distributed with mean mu and standard deviation sigma.
 Default parameter values are mu = 0 and
 sigma = 1.  Both parameters must be reals and
 sigma > 0.  For sigma <= 0, NaN is
 returned.
 When called with three output arguments, i.e. [p, plo,
 pup], logncdf computes the confidence bounds for p when
 the input parameters mu and sigma are estimates.  In such case,
 pcov, a  matrix containing the covariance matrix of the
 estimated parameters, is necessary.  Optionally, alpha, which has a
 default value of 0.05, specifies the 100 * (1 - alpha) percent
 confidence bounds.  plo and pup are arrays of the same size as
 p containing the lower and upper confidence bounds.
 […] = logncdf (…, "upper") computes the upper tail
 probability of the log-normal distribution with parameters mu and
 sigma, at the values in x.
Further information about the log-normal distribution can be found at https://en.wikipedia.org/wiki/Log-normal_distribution
See also: logninv, lognpdf, lognrnd, lognfit, lognlike, lognstat
Source Code: logncdf
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 ## Plot various CDFs from the log-normal distribution
 x = 0:0.01:3;
 p1 = logncdf (x, 0, 1);
 p2 = logncdf (x, 0, 0.5);
 p3 = logncdf (x, 0, 0.25);
 plot (x, p1, "-b", x, p2, "-g", x, p3, "-r")
 grid on
 legend ({"μ = 0, σ = 1", "μ = 0, σ = 0.5", "μ = 0, σ = 0.25"}, ...
         "location", "southeast")
 title ("Log-normal CDF")
 xlabel ("values in x")
 ylabel ("probability")
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