function p = wblcdf(x, scale, shape)

% Cumulative distribution function for the Weibull distribution.
%
% INPUTS
% - x     [double] Positive real scalar or vector.
% - scale [double] Positive hyperparameter (scalar).
% - shape [double] Positive hyperparameter (scalar).
%
% OUTPUTS
% - p     [double] Probability value(s) in [0,1], same size as x.

% Copyright © 2015-2026 Dynare Team
%
% This file is part of Dynare.
%
% Dynare 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.
%
% Dynare 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 Dynare.  If not, see <https://www.gnu.org/licenses/>.


% Check input arguments.

if nargin<3
    error('Three input arguments required!')
end

if ~isnumeric(x) || ~isreal(x)
    error('First input argument must be real!')
end

if ~isnumeric(scale) || ~isreal(scale) || any(scale(:)<=0)
    error('Second input argument must be real and positive (scale parameter of the Weibull distribution)!')
end

if ~isnumeric(shape) || ~isreal(shape) || any(shape(:)<=0)
    error('Third input argument must be real and positive (shape parameter of the Weibull distribution)!')
end

if ~isscalar(scale) || ~isscalar(shape)
    [retval, x, scale, shape] = common_size(x, scale, shape);
    if retval > 0
        error('x, scale and shape must be of common size or scalars');
    end
end

% Vectorized evaluation of the CDF.
p = zeros(size(x));
p(isinf(x) & x>0) = 1;
k = x > 0 & ~isinf(x);
if any(k(:))
    if isscalar(scale) && isscalar(shape)
        p(k) = 1 - exp(-(x(k)./scale).^shape);
    else
        p(k) = 1 - exp(-(x(k)./scale(k)).^shape(k));
    end
end

return;

%@test:1
try
    p = wblcdf(-1, .5, .1);
    t(1) = true;
catch
    t(1) = false;
end

% Check the results
if t(1)
    t(2) = isequal(p, 0);
end
T = all(t);
%@eof:1

%@test:2
try
    p = wblcdf(Inf, .5, .1);
    t(1) = true;
catch
    t(1) = false;
end

% Check the results
if t(1)
    t(2) = isequal(p, 1);
end
T = all(t);
%@eof:2

%@test:3
% Set the hyperparameters of a Weibull definition.
scale = .5;
shape = 1.5;

% Compute the median of the weibull distribution.
m = scale*log(2)^(1/shape);

try
    p = wblcdf(m, scale, shape);
    t(1) = true;
catch
    t(1) = false;
end

% Check the results
if t(1)
    t(2) = abs(p-.5)<1e-12;
end
T = all(t);
%@eof:3

%@test:4
% Consistency check between wblinv and wblcdf.

% Set the hyperparameters of a Weibull definition.
scale = .5;
shape = 1.5;

% Compute quatiles of the weibull distribution.
q = 0:.05:1;
m = zeros(size(q));
p = zeros(size(q));
for i=1:length(q)
    m(i) = wblinv(q(i), scale, shape);
end

try
    for i=1:length(q)
        p(i) = wblcdf(m(i), scale, shape);
    end
    t(1) = true;
catch
    t(1) = false;
end

% Check the results
if t(1)
    for i=1:length(q)
        t(i+1) = abs(p(i)-q(i))<1e-12;
    end
end
T = all(t);
%@eof:4

%@test:5
% Test with vector-valued x input.

% Set the hyperparameters of a Weibull distribution.
scale = .5;
shape = 1.5;

% Build a vector of x values including boundary cases.
x = [-1, 0, scale*log(2)^(1/shape), 1, Inf];

try
    p = wblcdf(x, scale, shape);
    t(1) = true;
catch
    t(1) = false;
end

% Check the results.
if t(1)
    t(2) = isequal(size(p), size(x));
    t(3) = isequal(p(1), 0);    % x < 0 → p = 0
    t(4) = isequal(p(2), 0);    % x = 0 → p = 0
    t(5) = abs(p(3) - 0.5) < 1e-12;  % x = median → p = 0.5
    t(6) = p(4) > 0 && p(4) < 1;     % interior point
    t(7) = isequal(p(5), 1);    % x = Inf → p = 1
end
T = all(t);
%@eof:5
