124 lines
4.1 KiB
Matlab
124 lines
4.1 KiB
Matlab
function [theta, fxsim, neval] = slice_sampler(objective_function,theta,thetaprior,sampler_options,varargin)
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% function [theta, fxsim, neval] = slice_sampler(objective_function,theta,thetaprior,sampler_options,varargin)
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% ----------------------------------------------------------
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% UNIVARIATE SLICE SAMPLER - stepping out (Neal, 2003)
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% W: optimal value in the range (3,10)*std(x)
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% - see C.Planas and A.Rossi (2014)
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% objective_function(theta,varargin): -log of any unnormalized pdf
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% with varargin (optional) a vector of auxiliaty parameters
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% to be passed to f( ).
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% ----------------------------------------------------------
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%
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% INPUTS
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% objective_function: objective function (expressed as minus the log of a density)
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% theta: last value of theta
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% thetaprior: bounds of the theta space
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% sampler_options: posterior sampler options
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% varargin: optional input arguments to objective function
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%
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% OUTPUTS
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% theta: new theta sample
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% fxsim: value of the objective function for the new sample
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% neval: number of function evaluations
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%
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% SPECIAL REQUIREMENTS
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% none
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% Copyright (C) 2015-2017 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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if sampler_options.rotated %&& ~isempty(sampler_options.V1),
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[theta, fxsim, neval] = rotated_slice_sampler(objective_function,theta,thetaprior,sampler_options,varargin{:});
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if isempty(sampler_options.mode) % jumping
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return
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else
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nevalR=sum(neval);
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end
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end
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theta=theta(:);
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npar = length(theta);
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W1 = sampler_options.W1;
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neval = zeros(npar,1);
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for it=1:npar
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neval(it) = 0;
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W = W1(it);
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xold = theta(it);
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% XLB = thetaprior(3);
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% XUB = thetaprior(4);
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XLB = thetaprior(it,1);
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XUB = thetaprior(it,2);
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% -------------------------------------------------------
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% 1. DRAW Z = ln[f(X0)] - EXP(1) where EXP(1)=-ln(U(0,1))
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% THIS DEFINES THE SLICE S={x: z < ln(f(x))}
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% -------------------------------------------------------
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fxold = -feval(objective_function,theta,varargin{:});
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neval(it) = neval(it) + 1;
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Z = fxold + log(rand(1,1));
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% -------------------------------------------------------------
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% 2. FIND I=(L,R) AROUND X0 THAT CONTAINS S AS MUCH AS POSSIBLE
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% STEPPING-OUT PROCEDURE
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% -------------------------------------------------------------
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u = rand(1,1);
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L = max(XLB,xold-W*u);
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R = min(XUB,L+W);
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while(L > XLB)
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xsim = L;
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theta(it) = xsim;
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fxl = -feval(objective_function,theta,varargin{:});
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neval(it) = neval(it) + 1;
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if (fxl <= Z)
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break
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end
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L = max(XLB,L-W);
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end
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while(R < XUB)
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xsim = R;
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theta(it) = xsim;
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fxr = -feval(objective_function,theta,varargin{:});
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neval(it) = neval(it) + 1;
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if (fxr <= Z)
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break
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end
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R = min(XUB,R+W);
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end
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% ------------------------------------------------------
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% 3. SAMPLING FROM THE SET A = (I INTERSECT S) = (LA,RA)
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% ------------------------------------------------------
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fxsim = Z-1;
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while (fxsim < Z)
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u = rand(1,1);
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xsim = L + u*(R - L);
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theta(it) = xsim;
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fxsim = -feval(objective_function,theta,varargin{:});
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neval(it) = neval(it) + 1;
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if (xsim > xold)
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R = xsim;
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else
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L = xsim;
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end
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end
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end
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if sampler_options.rotated && ~isempty(sampler_options.mode) % jumping
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neval=sum(neval)+nevalR;
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end
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