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+## Copyright (C) 2025 Jayant Chauhan <0001jayant@gmail.com>
+##
+## 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{D} =} dummyvar (@var{g})
+##
+## Create dummy variables (one-hot encoding) from a grouping variable.
+##
+## The input @var{g} must be a numeric vector of group indices or a
+## @code{categorical} array.  The output @var{D} is a numeric matrix whose
+## columns correspond to the distinct groups and whose rows correspond to the
+## elements of @var{g}.
+##
+## For numeric inputs, the number of columns in @var{D} is equal to
+## @code{max (@var{g})}, and column @math{k} corresponds to group @math{k}.
+##
+## For @code{categorical} inputs, the number and order of columns in @var{D}
+## correspond to the categories returned by @code{categories (@var{g})}.
+## Categories that are defined but not present in @var{g} produce columns of
+## zeros.
+##
+## Elements of @var{g} that are @code{<undefined>} result in rows of
+## @code{NaN} values in @var{D}.
+##
+## If @var{g} is a single-column table, the grouping variable is taken from that
+## column.  For example:
+##
+## @example
+## D = dummyvar (T.Group)
+## @end example
+##
+## @seealso{tabulate, grpstats}
+## @end deftypefn
+
+function D = dummyvar (g)
+
+  if (nargin ~= 1)
+    error ("Invalid call to dummyvar.  Correct usage is:\n\n  D = dummyvar (g)");
+  end
+
+  ## Table single-column extraction
+  if (isa (g, "table"))
+    if (size (g, 2) ~= 1)
+      error ("dummyvar on a table expects a single-column input");
+    end
+    try
+      g = g{:,1};
+    catch
+      ## table class exists but indexing failed — let later checks handle it
+    end
+  end
+
+
+  ## --- CATEGORICAL branch ---
+  if (exist ("categorical", "class") && isa (g, "categorical"))
+
+    if (! isvector (g) || size (g,2) ~= 1)
+      error ("Categorical grouping variable must have one column.");
+    end
+
+    cats = cellstr (categories (g));
+    K = numel (cats);
+    n = rows (g);
+
+    if (n == 0)
+      error ("Categorical grouping variable must have one column.");
+    end
+
+    g_str = cellstr (g(:));
+    D = zeros (n, K);
+
+    for i = 1:n
+      if (isundefined (g(i)))
+        D(i,:) = NaN;
+      else
+        for k = 1:K
+          if (strcmp (g_str{i}, cats{k}))
+            D(i,k) = 1;
+            break;
+          end
+        endfor
+      end
+    endfor
+
+    D = double (D);
+    return;
+  end
+
+  ## --- NUMERIC branch ---
+  if (isnumeric (g) && isvector (g))
+
+    g = g(:);
+    if (isempty (g))
+      D = zeros (0, 0);
+      return;
+    end
+
+    K = max (g);
+    if (! isreal (K) || K < 0)
+      error ("dummyvar:InvalidInput", ...
+             "Numeric grouping must produce a positive integer number of groups.");
+    end
+
+    n = numel (g);
+    D = zeros (n, K);
+    idx = round (g);
+
+    for i = 1:n
+      if (! isnan (idx(i)) && idx(i) >= 1 && idx(i) <= K)
+        D(i, idx(i)) = 1;
+      end
+    endfor
+
+    D = double (D);
+    return;
+  end
+
+  error ("dummyvar:UnsupportedType", ...
+         "dummyvar requires a numeric vector or a categorical array.");
+end
+
+## Test dummyvar behavior 
+
+%!test
+%! ## numeric grouping vector
+%! g = [1;2;1;3;2];
+%! D = dummyvar(g);
+%! assert(isequal(D, [1 0 0; 0 1 0; 1 0 0; 0 0 1; 0 1 0]));
+
+%!test
+%! g = categorical({'a';'b';'a'}, {'a','b','c'});
+%! D = dummyvar(g);
+%! cats = categories(g);
+%! g_str = cellstr(g);
+%!
+%! for k = 1:numel(cats)
+%!   mask = strcmp(g_str, cats{k});
+%!   assert(all(D(mask, k) == 1));
+%!   assert(all(D(!mask, k) == 0));
+%! endfor
+
+
+%!test
+%! g = categorical({'a'; ''; 'b'}, {'a','b','c'});
+%! D = dummyvar(g);
+%! assert(all(isnan(D(2,:))));
+%! assert(sum(D(1,:) == 1) == 1);
+%! assert(sum(D(3,:) == 1) == 1);
+
+%!test
+%! G = categorical({'a'; 'b'; 'a'}, {'a','b','c'});
+%! T = table(G, [10;20;30], 'VariableNames', {'G','Val'});
+%! D = dummyvar(T.G);
+%! assert(size(D,2) == numel(categories(G)));
+
+%!test
+%! ## table column input
+%! G = categorical({'a'; 'b'; 'a'}, {'a','b','c'});
+%! T = table(G, [10;20;30], 'VariableNames', {'G','Val'});
+%! D = dummyvar(T.G);
+%! assert(size(D,2) == numel(categories(G)));
+
+## Test input validation
+
+%!error<Invalid call to dummyvar.  Correct usage is> dummyvar
+%!error<function called with too many inputs> dummyvar (1, 2)
+
+%!error<Categorical grouping variable must have one column> ...
+%! dummyvar (categorical ([], {'a','b'}))
+
+%!error<Categorical grouping variable must have one column> ...
+%! dummyvar (categorical ({'a','b'}, {'a','b'}))   ## row categorical
+
+%!error<dummyvar on a table expects a single-column input> ...
+%! dummyvar (table ([1;2], [3;4]))
+
+%!error<dummyvar requires a numeric vector or a categorical array> ...
+%! dummyvar (struct ("a", 1))