## 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} =} invgpdf (@var{x}, @var{mu}, @var{lambda})
##
## Inverse Gaussian probability density function (PDF).
##
## For each element of @var{x}, compute the probability density function (PDF)
## of the inverse Gaussian distribution with scale parameter @var{mu} and shape
## parameter @var{lambda}.  The size of @var{y} is the common size of @var{x},
## @var{mu}, and @var{lambda}.  A scalar input functions as a constant matrix of
## the same size as the other inputs.
##
## The inverse Gaussian CDF is only defined for @qcode{@var{mu} > 0} and
## @qcode{@var{lambda} > 0}.
##
## Further information about the inverse Gaussian distribution can be found at
## @url{https://en.wikipedia.org/wiki/Inverse_Gaussian_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{invgcdf, invginv, invgrnd, invgfit, invglike, invgstat}
## @end deftypefn

function y = invgpdf (x, mu, lambda)

  ## Check for valid number of input arguments
  if (nargin < 3)
    error ("invgpdf: function called with too few input arguments.");
  endif

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

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

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

  ## Check for class type
  if (isa (x, 'single') || isa (mu, 'single') || isa (lambda, 'single'));
    is_class = 'single';
  else
    is_class = 'double';
  endif

  ## Return NaNs for out of range values of MU and LAMBDA parameters
  mu(mu <= 0) = NaN;
  lambda(lambda <= 0) = NaN;

  ## Check for valid support of X
  is_zero = (x <= 0);
  x(is_zero) = realmin;

  ## Compute inverse Gaussian PDF
  y = sqrt (lambda ./ (2 .* pi .* x .^ 3)) .* ...
      exp (-0.5 .* lambda .* (x ./ mu - 2 + mu ./ x) ./ mu);

  ## Force zero for unsupported X but valid parameters
  k0 = is_zero & mu > 0 & lambda > 0;
  y(k0) = 0;

  ## Cast to appropriate class
  y = cast (y, is_class);

endfunction

%!demo
%! ## Plot various PDFs from the inverse Gaussian distribution
%! x = 0:0.001:3;
%! y1 = invgpdf (x, 1, 0.2);
%! y2 = invgpdf (x, 1, 1);
%! y3 = invgpdf (x, 1, 3);
%! y4 = invgpdf (x, 3, 0.2);
%! y5 = invgpdf (x, 3, 1);
%! plot (x, y1, '-b', x, y2, '-g', x, y3, '-r', x, y4, '-c', x, y5, '-y')
%! grid on
%! xlim ([0, 3])
%! ylim ([0, 3])
%! legend ({'μ = 1, σ = 0.2', 'μ = 1, σ = 1', 'μ = 1, σ = 3', ...
%!          'μ = 3, σ = 0.2', 'μ = 3, σ = 1'}, 'location', 'northeast')
%! title ('Inverse Gaussian PDF')
%! xlabel ('values in x')
%! ylabel ('density')

## Test output
%!shared x, y
%! x = [-Inf, -1, 0, 1/2, 1, Inf];
%! y = [0, 0, 0, 0.8788, 0.3989, 0];
%!assert_equal (invgpdf ([x, NaN], 1, 1), [y, NaN], 1e-4)
%!assert_equal (invgpdf (x, 1, [-2, -1, 0, 1, 1, 1]), [nan(1,3), y([4:6])], 1e-4)

## Test class of input preserved
%!assert_equal (class (hncdf (single ([x, NaN]), 1, 1)), "single")
%!assert_equal (class (hncdf ([x, NaN], 1, single (1))), "single")
%!assert_equal (class (hncdf ([x, NaN], single (1), 1)), "single")

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