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diff --git a/octave_packages/m/statistics/distributions/fpdf.m b/octave_packages/m/statistics/distributions/fpdf.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} {} fpdf (@var{x}, @var{m}, @var{n})
+## For each element of @var{x}, compute the probability density function
+## (PDF) at @var{x} of the F distribution with @var{m} and @var{n}
+## degrees of freedom.
+## @end deftypefn
+
+## Author: KH <Kurt.Hornik@wu-wien.ac.at>
+## Description: PDF of the F distribution
+
+function pdf = fpdf (x, m, n)
+
+  if (nargin != 3)
+    print_usage ();
+  endif
+
+  if (!isscalar (m) || !isscalar (n))
+    [retval, x, m, n] = common_size (x, m, n);
+    if (retval > 0)
+      error ("fpdf: X, M, and N must be of common size or scalars");
+    endif
+  endif
+
+  if (iscomplex (x) || iscomplex (m) || iscomplex (n))
+    error ("fpdf: X, M, and N must not be complex");
+  endif
+
+  if (isa (x, "single") || isa (m, "single") || isa (n, "single"))
+    pdf = zeros (size (x), "single");
+  else
+    pdf = zeros (size (x));
+  endif
+
+  k = isnan (x) | !(m > 0) | !(m < Inf) | !(n > 0) | !(n < Inf);
+  pdf(k) = NaN;
+
+  k = (x > 0) & (x < Inf) & (m > 0) & (m < Inf) & (n > 0) & (n < Inf);
+  if (isscalar (m) && isscalar (n))
+    tmp = m / n * x(k);
+    pdf(k) = (exp ((m/2 - 1) * log (tmp)
+                   - ((m + n) / 2) * log (1 + tmp))
+              * (m / n) ./ beta (m/2, n/2));
+  else
+    tmp = m(k) .* x(k) ./ n(k);
+    pdf(k) = (exp ((m(k)/2 - 1) .* log (tmp)
+                   - ((m(k) + n(k)) / 2) .* log (1 + tmp))
+              .* (m(k) ./ n(k)) ./ beta (m(k)/2, n(k)/2));
+  endif
+
+endfunction
+
+
+%% F (x, 1, m) == T distribution (sqrt (x), m) / sqrt (x)
+%!test
+%! x = rand (10,1);
+%! x = x(x > 0.1 & x < 0.9);
+%! y = tpdf (sqrt (x), 2) ./ sqrt (x);
+%! assert(fpdf (x, 1, 2), y, 5*eps);
+
+%!shared x,y
+%! x = [-1 0 0.5 1 2];
+%! y = [0 0 4/9 1/4 1/9];
+%!assert(fpdf (x, 2*ones(1,5), 2*ones(1,5)), y, eps);
+%!assert(fpdf (x, 2, 2*ones(1,5)), y, eps);
+%!assert(fpdf (x, 2*ones(1,5), 2), y, eps);
+%!assert(fpdf (x, [0 NaN Inf 2 2], 2), [NaN NaN NaN y(4:5)], eps);
+%!assert(fpdf (x, 2, [0 NaN Inf 2 2]), [NaN NaN NaN y(4:5)], eps);
+%!assert(fpdf ([x, NaN], 2, 2), [y, NaN], eps);
+
+%% Test class of input preserved
+%!assert(fpdf (single([x, NaN]), 2, 2), single([y, NaN]), eps("single"));
+%!assert(fpdf ([x, NaN], single(2), 2), single([y, NaN]), eps("single"));
+%!assert(fpdf ([x, NaN], 2, single(2)), single([y, NaN]), eps("single"));
+
+%% Test input validation
+%!error fpdf ()
+%!error fpdf (1)
+%!error fpdf (1,2)
+%!error fpdf (1,2,3,4)
+%!error fpdf (ones(3),ones(2),ones(2))
+%!error fpdf (ones(2),ones(3),ones(2))
+%!error fpdf (ones(2),ones(2),ones(3))
+%!error fpdf (i, 2, 2)
+%!error fpdf (2, i, 2)
+%!error fpdf (2, 2, i)
+