logncdf.m

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## Copyright (C) 1995, 1996, 1997, 2005, 2006, 2007 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}, @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 distributionfunction cdf = logncdf (x, mu, sigma)  if (! ((nargin == 1) || (nargin == 3)))    print_usage ();  endif  if (nargin == 1)    mu = 0;    sigma = 1;  endif  ## The following "straightforward" implementation unfortunately does  ## not work (because exp (Inf) -> NaN etc):  ## cdf = normal_cdf (log (x), log (mu), sigma);  ## Hence ...  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  cdf = zeros (size (x));  k = find (isnan (x) | !(sigma > 0) | !(sigma < Inf));  if (any (k))    cdf(k) = NaN;  endif  k = find ((x == Inf) & (sigma > 0) & (sigma < Inf));  if (any (k))    cdf(k) = 1;  endif  k = find ((x > 0) & (x < Inf) & (sigma > 0) & (sigma < Inf));  if (any (k))    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  endifendfunction

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