94 lines
2.8 KiB
Matlab
94 lines
2.8 KiB
Matlab
function ts = hptrend(ts, lambda) % --*-- Unitary tests --*--
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% ts = hptrend(ts, lambda)
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%
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% Extracts the trend component from a dseries object using Hodrick Prescott filter.
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%
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% INPUTS
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% o ts dseries object.
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% o lambda positive scalar, trend smoothness parameter.
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%
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% OUTPUTS
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% o ts dseries object, with time series replaced by the trend component of the original time series.
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% Copyright (C) 2013 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 nargin>1
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if lambda<=0
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error(['dseries::hptrend: Lambda must be a positive integer!'])
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end
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else
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lambda = [];
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end
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for i=1:ts.vobs
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ts.name(i) = {['hptrend(' ts.name{i} ')']};
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ts.tex(i) = {['\text{hptrend}(' ts.tex{i} ')']};
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end
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ts.data = sample_hp_filter(ts.data,lambda);
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%@test:1
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%$ plot_flag = 0;
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%$
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%$ % Create a dataset.
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%$ e = .2*randn(200,1);
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%$ u = randn(200,1);
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%$ stochastic_trend = cumsum(e);
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%$ deterministic_trend = .1*transpose(1:200);
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%$ x = zeros(200,1);
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%$ for i=2:200
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%$ x(i) = .75*x(i-1) + e(i);
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%$ end
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%$ y = x + stochastic_trend + deterministic_trend;
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%$
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%$ % Test the routine.
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%$ try
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%$ ts0 = dseries(y,'1950Q1');
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%$ ts1 = dseries(stochastic_trend+deterministic_trend,'1950Q1');
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%$ ts2 = ts0.hptrend(1600);
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%$ t(1) = 1;
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%$ catch
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%$ t(1) = 0;
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%$ end
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%$
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%$ if t(1)
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%$ t(2) = dyn_assert(ts2.freq,4);
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%$ t(3) = dyn_assert(ts2.init.freq,4);
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%$ t(4) = dyn_assert(ts2.init.time,[1950, 1]);
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%$ t(5) = dyn_assert(ts2.vobs,1);
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%$ t(6) = dyn_assert(ts2.nobs,200);
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%$ end
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%$
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%$ % Show results
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%$ if plot_flag
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%$ plot(ts1.data,'-k'); % Plot of the stationary component.
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%$ hold on
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%$ plot(ts2.data,'--r'); % Plot of the filtered y.
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%$ hold off
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%$ axis tight
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%$ id = get(gca,'XTick');
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%$ set(gca,'XTickLabel',strings(ts1.dates(id)));
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%$ legend({'Nonstationary component of y', 'Estimated trend of y'})
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%$ print('-depsc2','../doc/dynare.plots/HPTrend.eps')
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%$ system('convert -density 300 ../doc/dynare.plots/HPTrend.eps ../doc/dynare.plots/HPTrend.png');
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%$ system('convert -density 300 ../doc/dynare.plots/HPTrend.eps ../doc/dynare.plots/HPTrend.pdf');
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%$ system('convert -density 300 ../doc/dynare.plots/HPTrend.eps ../doc/dynare.plots/HPTrend.jpg');
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%$ end
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%$ T = all(t);
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%@eof:1 |