Allow non-integer values for hp_filter parameter
parent
ef26fe0034
commit
1b4dcdd7f1
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@ -2828,8 +2828,8 @@ Order of autocorrelation coefficients to compute and to print. Default: @code{5}
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Number of points dropped at the beginning of simulation before
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computing the summary statistics. Default: @code{100}.
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@item hp_filter = @var{INTEGER}
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Uses HP filter with @math{\lambda} = @var{INTEGER} before computing
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@item hp_filter = @var{DOUBLE}
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Uses HP filter with @math{\lambda} = @var{DOUBLE} before computing
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moments. Default: no filter.
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@item hp_ngrid = @var{INTEGER}
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@ -60,7 +60,7 @@ if options_.nomoments == 0
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title='MOMENTS OF SIMULATED VARIABLES';
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if options_.hp_filter
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title = [title ' (HP filter, lambda = ' ...
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int2str(options_.hp_filter) ')'];
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num2str(options_.hp_filter) ')'];
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end
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headers=char('VARIABLE','MEAN','STD. DEV.','VARIANCE','SKEWNESS', ...
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'KURTOSIS');
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@ -73,7 +73,7 @@ if options_.nocorr == 0
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title = 'CORRELATION OF SIMULATED VARIABLES';
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if options_.hp_filter
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title = [title ' (HP filter, lambda = ' ...
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int2str(options_.hp_filter) ')'];
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num2str(options_.hp_filter) ')'];
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end
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headers = char('VARIABLE',M_.endo_names(ivar,:));
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dyntable(title,headers,labels,corr,size(labels,2)+2,8,4);
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@ -93,7 +93,7 @@ if ar > 0
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title = 'AUTOCORRELATION OF SIMULATED VARIABLES';
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if options_.hp_filter
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title = [title ' (HP filter, lambda = ' ...
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int2str(options_.hp_filter) ')'];
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num2str(options_.hp_filter) ')'];
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end
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headers = char('VARIABLE',int2str([1:ar]'));
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dyntable(title,headers,labels,autocorr,size(labels,2)+2,8,4);
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@ -53,7 +53,7 @@ oo_.var = oo_.gamma_y{1};
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if ~options_.noprint %options_.nomoments == 0
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title='THEORETICAL MOMENTS';
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if options_.hp_filter
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title = [title ' (HP filter, lambda = ' int2str(options_.hp_filter) ')'];
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title = [title ' (HP filter, lambda = ' num2str(options_.hp_filter) ')'];
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end
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headers=char('VARIABLE','MEAN','STD. DEV.','VARIANCE');
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labels = deblank(M_.endo_names(ivar,:));
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@ -64,7 +64,7 @@ if ~options_.noprint %options_.nomoments == 0
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title='VARIANCE DECOMPOSITION (in percent)';
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if options_.hp_filter
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title = [title ' (HP filter, lambda = ' ...
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int2str(options_.hp_filter) ')'];
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num2str(options_.hp_filter) ')'];
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end
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headers = M_.exo_names;
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headers(M_.exo_names_orig_ord,:) = headers;
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@ -95,7 +95,7 @@ if options_.nocorr == 0 && size(stationary_vars, 1) > 0
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disp(' ')
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title='MATRIX OF CORRELATIONS';
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if options_.hp_filter
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title = [title ' (HP filter, lambda = ' int2str(options_.hp_filter) ')'];
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title = [title ' (HP filter, lambda = ' num2str(options_.hp_filter) ')'];
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end
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labels = deblank(M_.endo_names(ivar(i1),:));
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headers = char('Variables',labels);
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@ -113,7 +113,7 @@ if options_.ar > 0 && size(stationary_vars, 1) > 0
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disp(' ')
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title='COEFFICIENTS OF AUTOCORRELATION';
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if options_.hp_filter
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title = [title ' (HP filter, lambda = ' int2str(options_.hp_filter) ')'];
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title = [title ' (HP filter, lambda = ' num2str(options_.hp_filter) ')'];
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end
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labels = deblank(M_.endo_names(ivar(i1),:));
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headers = char('Order ',int2str([1:options_.ar]'));
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@ -3,7 +3,7 @@ function [hptrend,hpcycle] = sample_hp_filter(y,s)
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%
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% INPUTS
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% y [double] T*n matrix of data (n is the number of variables)
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% s [integer] scalar, smoothing parameter.
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% s [double] scalar, smoothing parameter.
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%
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% OUTPUTS
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% hptrend [double] T*n matrix, trend component of y.
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@ -1833,7 +1833,7 @@ o_nofunctions : NOFUNCTIONS { driver.option_num("nofunctions", "1"); };
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o_nomoments : NOMOMENTS { driver.option_num("nomoments", "1"); };
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o_irf : IRF EQUAL INT_NUMBER { driver.option_num("irf", $3); };
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o_irf_shocks : IRF_SHOCKS EQUAL '(' symbol_list ')' { driver.option_symbol_list("irf_shocks"); };
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o_hp_filter : HP_FILTER EQUAL INT_NUMBER { driver.option_num("hp_filter", $3); };
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o_hp_filter : HP_FILTER EQUAL non_negative_number { driver.option_num("hp_filter", $3); };
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o_hp_ngrid : HP_NGRID EQUAL INT_NUMBER { driver.option_num("hp_ngrid", $3); };
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o_periods : PERIODS EQUAL INT_NUMBER { driver.option_num("periods", $3); };
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o_cutoff : CUTOFF EQUAL non_negative_number { driver.cutoff($3); }
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