## Copyright (C) 2012 Rik Wehbring
## Copyright (C) 1995-2016 Kurt Hornik
## Copyright (C) 2023 Andreas Bertsatos <abertsatos@biol.uoa.gr>
##
## This file is part of the statistics package for GNU Octave.
##
## This program 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.
##
## This program 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
## this program; if not, see <http://www.gnu.org/licenses/>.

## -*- texinfo -*-
## @deftypefn  {statistics} {@var{y} =} exppdf (@var{x})
## @deftypefnx {statistics} {@var{y} =} exppdf (@var{x}, @var{mu})
##
## Exponential probability density function (PDF).
##
## For each element of @var{x}, compute the probability density function (PDF)
##  of the exponential distribution with mean parameter @var{mu}.  The size of
## @var{y} is the common size of @var{x} and @var{mu}.  A scalar input functions
## as a constant matrix of the same size as the other inputs.
##
## Default value for @var{mu} = 1.
##
## A common alternative parameterization of the exponential distribution is to
## use the parameter @math{λ} defined as the mean number of events in an
## interval as opposed to the parameter @math{μ}, which is the mean wait time
## for an event to occur. @math{λ} and @math{μ} are reciprocals,
## i.e. @math{μ = 1 / λ}.
##
## Further information about the exponential distribution can be found at
## @url{https://en.wikipedia.org/wiki/Exponential_distribution}
##
## Input arguments must be @qcode{double} or @qcode{single}; integer, logical,
## and character arrays are rejected.  MATLAB accepts a character array and
## evaluates it at the character codes, which Octave deliberately does not,
## since a character array is an integer type and integers are refused too.
##
## @seealso{expcdf, expinv, exprnd, expfit, explike, expstat}
## @end deftypefn

function y = exppdf (x, mu)

  ## Check for valid number of input arguments
  if (nargin < 1)
    error ("exppdf: function called with too few input arguments.");
  endif

  ## Add defaults (if missing input arguments)
  if (nargin < 2)
    mu = 0;
  endif

  ## Check for common size of X and MU
  if (! isscalar (x) || ! isscalar (mu))
    [retval, x, mu] = common_size (x, mu);
    if (retval > 0)
      error ("exppdf: X and MU must be of common size or scalars.");
    endif
  endif

  ## Check for X and MU being double or single
  if (! (isfloat (x) && isfloat (mu)))
    error ("exppdf: X and MU must be double or single.");
  endif

  ## Check for X and MU being reals
  if (iscomplex (x) || iscomplex (mu))
    error ("exppdf: X and MU must not be complex.");
  endif

  ## Check for appropriate class
  if (isa (x, 'single') || isa (mu, 'single'))
    y = zeros (size (x), 'single');
  else
    y = zeros (size (x));
  endif

  k = isnan (x) | ! (mu > 0);
  y(k) = NaN;

  k = (x >= 0) & (x < Inf) & (mu > 0);
  if (isscalar (mu))
    y(k) = exp (-x(k) / mu) / mu;
  else
    y(k) = exp (-x(k) ./ mu(k)) ./ mu(k);
  endif

endfunction

%!demo
%! ## Plot various PDFs from the exponential distribution
%! x = 0:0.01:5;
%! y1 = exppdf (x, 2/3);
%! y2 = exppdf (x, 1.0);
%! y3 = exppdf (x, 2.0);
%! plot (x, y1, '-b', x, y2, '-g', x, y3, '-r')
%! grid on
%! ylim ([0, 1.5])
%! legend ({'μ = 2/3', 'μ = 1', 'μ = 2'}, 'location', 'northeast')
%! title ('Exponential PDF')
%! xlabel ('values in x')
%! ylabel ('density')

## Test output
%!shared x,y
%! x = [-1 0 0.5 1 Inf];
%! y = gampdf (x, 1, 2);
%!assert_equal (exppdf (x, 2*ones (1,5)), y)
%!assert_equal (exppdf (x, 2*[1 0 NaN 1 1]), [y(1) NaN NaN y(4:5)])
%!assert_equal (exppdf ([x, NaN], 2), [y, NaN])

## Test class of input preserved
%!assert_equal (exppdf (single ([x, NaN]), 2), single ([y, NaN]))
%!assert_equal (exppdf ([x, NaN], single (2)), single ([y, NaN]))

## Test input validation
%!error<exppdf: function called with too few input arguments.> exppdf ()
%!error<exppdf: function called with too many inputs> exppdf (1,2,3)
%!error<exppdf: X and MU must be of common size or scalars.> ...
%! exppdf (ones (3), ones (2))
%!error<exppdf: X and MU must be of common size or scalars.> ...
%! exppdf (ones (2), ones (3))
%!error<exppdf: X and MU must be double or single.> exppdf (int32 (2), 2)
%!error<exppdf: X and MU must be double or single.> exppdf (true, 2)
%!error<exppdf: X and MU must be double or single.> exppdf ('a', 2)
%!error<exppdf: X and MU must not be complex.> exppdf (i, 2)
%!error<exppdf: X and MU must not be complex.> exppdf (2, i)
