dynare/matlab/estimation/calibrate_mh_scale_parameter.m

138 lines
5.0 KiB
Matlab

function Scale = calibrate_mh_scale_parameter(ObjectiveFunction, CovarianceMatrix, Parameters, MhBounds, options, varargin)
% function Scale = calibrate_mh_scale_parameter(ObjectiveFunction, CovarianceMatrix, Parameters, MhBounds, options, varargin)
% Tune the MH scale parameter so that the overall acceptance ratio is close to AcceptanceTarget.
%
% INPUTS
% - ObjectiveFunction [fhandle] Function (posterior kernel).
% - CovarianceMatrix [double] n*n matrix, covariance matrix of the jumping distribution.
% - Parameters [double] n*1 vector, parameter values.
% - MhBounds [double] n*2 matrix, bounds on the possible values for the parameters.
% - options [structure] content of options_.tune_mh_jscale.
% - varargin [cell] Additional arguments to be passed to ObjectiveFunction.
%
% OUTPUTS
% - Scale [double] scalar, optimal scale parameter for the jumping distribution.
%
% Note: program terminates if c3 consecutive runs of stepsize draws occured where
% i) the overall acceptance rate was less than c1 from target and
% ii) less than c2 over the last stepsize=2000 draws.
% Adjustment between steps takes place using a weighted average with the exponent being rho
% Copyright © 2020-2023 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/>.
% Fire up the wait bar
hh_fig = dyn_waitbar(0,'Tuning of the scale parameter...');
set(hh_fig,'Name','Tuning of the scale parameter.');
% Intilialize various counters.
j = 1; jj = 1; isux = 0; jsux = 0; i = 0;
% Evaluate the objective function.
logpo0 = - feval(ObjectiveFunction, Parameters, varargin{:});
logpo1 = logpo0;
% Get the dimension of the problem.
n = length(Parameters);
% Initialize the correction on the scale factor.
correction = 1.0;
% Set the initial value of the scale parameter
if isempty(options.guess)
options.guess=2.38/sqrt(length(Parameters));
end
Scale = options.guess;
% Transposition of some arrays.
MhBounds = MhBounds';
Parameters = Parameters';
% Compute the Cholesky of the covariance matrix, return an error if the
% matrix is not positive definite.
try
dd = chol(CovarianceMatrix);
catch
error('The covariance matrix has to be a symmetric positive definite matrix!')
end
% Set parameters related to the proposal distribution
if options.rwmh.proposal_distribution=='rand_multivariate_normal'
nu = n;
elseif options.rwmh.proposal_distribution=='rand_multivariate_student'
nu = options.rwmh.student_degrees_of_freedom;
end
% Random Walk Metropolis Hastings iterations...
while j<=options.maxiter
% Obtain a proposal (jump)
proposal = feval(options.rwmh.proposal_distribution, Parameters, Scale*dd, nu);
% If out of boundaries set the posterior kernel equal to minus infinity
% so that the proposal will be rejected with probability one.
if all(proposal > MhBounds(1,:)) && all(proposal < MhBounds(2,:))
logpo0 = -feval(ObjectiveFunction, proposal(:), varargin{:});
else
logpo0 = -inf;
end
% Move if the proposal is enough likely...
if logpo0>-inf && log(rand)<logpo0-logpo1
Parameters = proposal;
logpo1 = logpo0;
isux = isux + 1;
jsux = jsux + 1;
end% ... otherwise I don't move.
prtfrc = j/options.maxiter;
% Update the waitbar
if ~mod(j, 10)
dyn_waitbar(prtfrc, hh_fig, sprintf('Acceptance ratio [during last %u]: %f [%f]', options.stepsize, isux/j, jsux/jj));
end
% Adjust the value of the scale parameter.
if ~mod(j, options.stepsize)
r1 = jsux/jj; % Local acceptance ratio
r2 = isux/j; % Overall acceptance ratio
% Set correction for the scale factor
c1 = r1/options.target;
if abs(c1-1)>.05
correction = correction^options.rho*c1^(1-options.rho);
else
correction = c1;
end
% Apply correction
if c1>0
Scale = Scale*correction;
else
Scale = Scale/10;
end
% Update some counters.
jsux = 0; jj = 0;
if abs(r2-options.target)<options.c2 && abs(r1-options.target)<options.c1
i = i+1;
else
i = 0;
end
% Test convergence.
if i>options.c3
break
end
end
j = j+1;
jj = jj + 1;
end
dyn_waitbar_close(hh_fig);