2017-12-14 11:21:39 +01:00
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function surgibbs(ds, A, ndraws)
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%function surgibbs(ds, A, ndraws)
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2017-07-12 16:43:12 +02:00
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% Implements Gibbs Samipling for SUR
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%
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% INPUTS
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% ds [dseries] data
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% A [matrix] prior distribution variance
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% ndraws [int] number of draws
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%
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% OUTPUTS
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% none
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%
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% SPECIAL REQUIREMENTS
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% none
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% Copyright (C) 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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global M_ oo_
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%% Check input
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2017-07-17 11:47:08 +02:00
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assert(nargin == 3 || nargin == 5, 'Incorrect number of arguments passed to surgibbs');
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2017-07-12 16:43:12 +02:00
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%% Estimation
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2017-12-14 11:21:39 +01:00
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[nobs, nvars, pnamesall, beta, X, Y, m] = sur(ds);
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2017-07-17 11:47:08 +02:00
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beta0 = beta;
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2017-07-12 16:43:12 +02:00
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oo_.surgibbs.betadraws = zeros(ndraws, nvars);
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for i = 1:ndraws
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% Draw S, given X, Y, Beta
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resid = reshape(Y - X*beta, nobs, m);
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Omega = rand_inverse_wishart(m, nobs, (resid'*resid)/nobs);
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% Draw beta, given X, Y, S
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tmp = kron(inv(Omega), eye(nobs));
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tmp1 = X'*tmp*X;
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Omegabar = inv(tmp1 + A);
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2017-07-13 13:41:40 +02:00
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betabar = Omegabar*(tmp1*(tmp1\X'*tmp*Y)+A\beta0);
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2017-07-12 16:43:12 +02:00
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Sigma_upper_chol = chol(Omegabar, 'upper');
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beta = rand_multivariate_normal(betabar', Sigma_upper_chol, nvars)';
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oo_.surgibbs.betadraws(i, :) = beta';
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2017-07-12 18:12:26 +02:00
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end
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% save parameter values
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oo_.surgibbs.beta = (sum(oo_.surgibbs.betadraws)/ndraws)';
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2017-07-13 13:41:40 +02:00
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2017-07-17 17:47:29 +02:00
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%% Print Output
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dyn_table('Gibbs Sampling on SUR', {}, {}, pnamesall, ...
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{'Parameter Value'}, 4, oo_.surgibbs.beta);
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%% Plot
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2017-07-12 18:12:26 +02:00
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figure
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nrows = 5;
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ncols = floor(nvars/nrows);
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if mod(nvars, nrows) ~= 0
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ncols = ncols + 1;
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end
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for j = 1:length(pnamesall)
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M_.params(strmatch(pnamesall{j}, M_.param_names, 'exact')) = oo_.surgibbs.beta(j);
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subplot(nrows, ncols, j)
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histogram(oo_.surgibbs.betadraws(:, j))
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2017-07-12 18:26:04 +02:00
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hc = histcounts(oo_.surgibbs.betadraws(:, j));
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line([oo_.surgibbs.beta(j) oo_.surgibbs.beta(j)], [min(hc) max(hc)], 'Color', 'red');
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2017-07-12 18:12:26 +02:00
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title(pnamesall{j}, 'Interpreter', 'none')
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end
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2017-07-17 17:47:29 +02:00
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