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diff --git a/octave_packages/m/statistics/distributions/logncdf.m b/octave_packages/m/statistics/distributions/logncdf.m
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+## Copyright (C) 2012 Rik Wehbring
+## Copyright (C) 1995-2012 Kurt Hornik
+##
+## This file is part of Octave.
+##
+## Octave is free software; you can redistribute it and/or modify it
+## under the terms of the GNU General Public License as published by
+## the Free Software Foundation; either version 3 of the License, or (at
+## your option) any later version.
+##
+## Octave is distributed in the hope that it will be useful, but
+## WITHOUT ANY WARRANTY; without even the implied warranty of
+## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with Octave; see the file COPYING.  If not, see
+## <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn  {Function File} {} logncdf (@var{x})
+## @deftypefnx {Function File} {} logncdf (@var{x}, @var{mu}, @var{sigma})
+## For each element of @var{x}, compute the cumulative distribution
+## function (CDF) at @var{x} of the lognormal distribution with
+## parameters @var{mu} and @var{sigma}.  If a random variable follows this
+## distribution, its logarithm is normally distributed with mean
+## @var{mu} and standard deviation @var{sigma}.
+##
+## Default values are @var{mu} = 1, @var{sigma} = 1.
+## @end deftypefn
+
+## Author: KH <Kurt.Hornik@wu-wien.ac.at>
+## Description: CDF of the log normal distribution
+
+function cdf = logncdf (x, mu = 0, sigma = 1)
+
+  if (nargin != 1 && nargin != 3)
+    print_usage ();
+  endif
+
+  if (!isscalar (mu) || !isscalar (sigma))
+    [retval, x, mu, sigma] = common_size (x, mu, sigma);
+    if (retval > 0)
+      error ("logncdf: X, MU, and SIGMA must be of common size or scalars");
+    endif
+  endif
+
+  if (iscomplex (x) || iscomplex (mu) || iscomplex (sigma))
+    error ("logncdf: X, MU, and SIGMA must not be complex");
+  endif
+
+  if (isa (x, "single") || isa (mu, "single") || isa (sigma, "single"))
+    cdf = zeros (size (x), "single");
+  else
+    cdf = zeros (size (x));
+  endif
+
+  k = isnan (x) | !(sigma > 0) | !(sigma < Inf);
+  cdf(k) = NaN;
+
+  k = (x == Inf) & (sigma > 0) & (sigma < Inf);
+  cdf(k) = 1;
+
+  k = (x > 0) & (x < Inf) & (sigma > 0) & (sigma < Inf);
+  if (isscalar (mu) && isscalar (sigma))
+    cdf(k) = stdnormal_cdf ((log (x(k)) - mu) / sigma);
+  else
+    cdf(k) = stdnormal_cdf ((log (x(k)) - mu(k)) ./ sigma(k));
+  endif
+
+endfunction
+
+
+%!shared x,y
+%! x = [-1 0 1 e Inf];
+%! y = [0, 0, 0.5, 1/2+1/2*erf(1/2), 1];
+%!assert(logncdf (x, zeros(1,5), sqrt(2)*ones(1,5)), y);
+%!assert(logncdf (x, 0, sqrt(2)*ones(1,5)), y);
+%!assert(logncdf (x, zeros(1,5), sqrt(2)), y);
+%!assert(logncdf (x, [0 1 NaN 0 1], sqrt(2)), [0 0 NaN y(4:5)]);
+%!assert(logncdf (x, 0, sqrt(2)*[0 NaN Inf 1 1]), [NaN NaN NaN y(4:5)]);
+%!assert(logncdf ([x(1:3) NaN x(5)], 0, sqrt(2)), [y(1:3) NaN y(5)]);
+
+%% Test class of input preserved
+%!assert(logncdf ([x, NaN], 0, sqrt(2)), [y, NaN]);
+%!assert(logncdf (single([x, NaN]), 0, sqrt(2)), single([y, NaN]), eps("single"));
+%!assert(logncdf ([x, NaN], single(0), sqrt(2)), single([y, NaN]), eps("single"));
+%!assert(logncdf ([x, NaN], 0, single(sqrt(2))), single([y, NaN]), eps("single"));
+
+%% Test input validation
+%!error logncdf ()
+%!error logncdf (1,2)
+%!error logncdf (1,2,3,4)
+%!error logncdf (ones(3),ones(2),ones(2))
+%!error logncdf (ones(2),ones(3),ones(2))
+%!error logncdf (ones(2),ones(2),ones(3))
+%!error logncdf (i, 2, 2)
+%!error logncdf (2, i, 2)
+%!error logncdf (2, 2, i)
+