nth_even = compose(@(x) x - 1, @(x) x * 2)
    nth_even(1) % => 0
    nth_even(2) % => 2
    nth_even(3) % => 4

    adder = @(x, y) x + y;
    tot = partial(@reduce, adder);
    sumargs = @(varargin) sum(varargin);

    sumargs(1, 2, 3, 4) % => 10
    apply(sumargs, [1, 2, 3, 4]) % => 10

    % partial
    a = 1;
    b = ones(2, 1) / 2;
    movingavg2 = functools.partial(@filter, b, a);
    movingavg2(1:4) % => [0.5, 1.5, 2.5, 3.5]

    % rpartial
    isodate = rpartial(@datestr, 'yyyy-mm-dd HH:MM:SS');
    isodate(datenum(2010, 1, 1)) % => '2010-01-01 00:00:00'

    % Annoying
    cellfun(@(x) x + 2, {-1, 0, 1, 2}, 'UniformOutput', false) % => {1, 2, 3, 4}

    % Awesome
    map_ = rpartial(@cellfun, 'UniformOutput', false)
    map_(@(x) x + 2, {-1, 0, 1, 2}) % => {1, 2, 3, 4}

    % Unfortunately, function application in MATLAB is even slower than its slow for loops.
    % So, you probably shouldn't use this for math, although you can.
    map(@(x) x * 2, {1, 2, 3}) % => {2, 4, 6}

    % Better to use this as a utility function
    pwd % => /some/directory
    filepaths = map(partial(@fullfile, pwd), {'1.txt', '2.txt', '3.txt', '4.txt'});
    filepaths{2} % => '/some/directory/2.txt'

    reduce(@(x, y) x + y, [1 2 3 4]) % => 10
    reduce(@(x, y) x + y, [1 2 3 4], 10) % => 20

    % Something cleverer
    join = @(sep, args) ...
        reduce(@(x, y) [x sep y], ...
            map(@num2str, args));
    join(', ', [1 2 3 4]) % => '1, 2, 3, 4')

    functools.if_(true, @() 'Hello') % => 'Hello'
    functools.if_(false, @() 'Hello') % => []
    functools.if_(false, @() 'Hello', @() 'Goodbye') % => 'Goodbye'
    functools.if_(true, @(msg) msg, @(msg) msg, {'Hello'}) % => 'Hello'
    functools.if_(false, @(msg) msg, @(msg) msg, {'Goodbye'}) % => 'Goodbye'
    functools.if_(false, @(msg) msg, {'Hello'}, @(msg) msg, {'Goodbye'}) % => 'Goodbye'

    % Wrap functions that refuse to return a value with partial(nth, 0)
    apply(@disp, {'Disp will choke on this'}) % => ERROR
    apply(partial(@nth, 0, @disp), {'Disp will actually display this'}) % => [] (But the text is displayed)

    % 2nd output of sort is the former indices of the newly-sorted elements
    nth(1, @sort, [100, 400, 200, 300]) % => [100 200 300 400]
    nth(2, @sort, [100, 400, 200, 300]) % => [1   3   4   2]

    fact = Y( ...
        @(self) ... % Accepts a function...
            @(n) ... % that returns a function ...
                if_(n <= 1, ...
                    @() 1, ...
                    @() n * self(n-1))); % ... that uses self recursively.
    fact(4) % => 24
    fact(6) % => 720

    fib = functools.Y(...
        @(self)...
            @(n) ...
                if_(n <= 1,...
                    @() 1, ...
                    @() self(n - 1) + self(n - 2)));

    functools.map(fib, 0:9) % => {1 1 2 3 5 8 13 21 34 55}

    tail = @(lst) lst(2:end);
    head = @(lst) lst(1);
    qs = Y(...
        @(self) ...
            @(lst) ...
                if_(isempty(lst), ...
                    @() [], ... Is empty
                    @() [ ...
                        self(tail(lst(lst <= head(lst)))), ...
                        head(lst), ...
                        self(lst(lst > head(lst)))]));

    quicksort([8,2,45,0,4,1,2,3]) % => [0, 1, 2, 2, 3, 4, 8, 45]

    biglist = randn(1, 1000);
    tic
    x1 = qs(biglist);
    fprintf('\nAnonymous Quicksort: '); toc
    % => Anonymous Quicksort: Elapsed time is 0.929396 seconds.

    tic
    x2 = sort(biglist);
    fprintf('Built-in sort: '); toc
    % => Built-in sort: Elapsed time is 0.000062 seconds.