Description of min

DESCRIPTION

@info:
! @deftypefn {Function File} {@var{c} =} min (@var{a},@var{b})
! @anchor{@dynDate/gt}
! @sp 1
! Overloads the min function for the Dynare dates class (@ref{dynDate}).
! @sp 2
! @strong{Inputs}
! @sp 1
! @table @ @var
! @item a
! Dynare date object instantiated by @ref{dynDate}.
! @item b
! Dynare date object instantiated by @ref{dynDate}.
! @end table
! @sp 1
! @strong{Outputs}
! @sp 1
! @table @ @var
! @item c
! Dynare date object instantiated by @ref{dynDate}. @var{c} is a copy of @var{a} if @var{a}<=@var{b}, a copy of @var{b} otherwise.
! @end table
! @sp 2
! @strong{This function is called by:}
! @sp 2
! @strong{This function calls:}
!
! @end deftypefn
@eod:

CROSS-REFERENCE INFORMATION

SPAmalg [b,rts,ia,nexact,nnumeric,lgroots,aimcode] = ...

PlotPosteriorDistributions function PlotPosteriorDistributions()

PosteriorFilterSmootherAndForecast function PosteriorFilterSmootherAndForecast(Y,gend, type)

PosteriorIRF Builds posterior IRFs after the MH algorithm.

PosteriorIRF_core1 PARALLEL CONTEXT

PosteriorIRF_core2 PARALLEL CONTEXT

bvar_irf builds IRFs for a bvar model

cmaes

csminwel1 [fhat,xhat,ghat,Hhat,itct,fcount,retcodehat] = csminwel1(fcn,x0,H0,grad,crit,nit,method,epsilon,varargin)

dr_block function [dr,info,M_,options_,oo_] = dr_block(dr,task,M_,options_,oo_)

dyn_ramsey_static function [steady_state,params,check] = dyn_ramsey_static_(x)

dynare_estimation function dynare_estimation(var_list)

dynare_estimation_1 function dynare_estimation_1(var_list_,dname)

dynare_estimation_init function dynare_estimation_init(var_list_, gsa_flag)

dynare_graph_init function dynare_graph_init(figure_name,colors)

dynare_identification function [pdraws, TAU, GAM, LRE, gp, H, JJ] = dynare_identification(options_ident, pdraws0)

gcompare GCOMPARE : GCOMPARE ( [ 'file1' ; 'file2' ] , [ 'var1' ; 'var2' ...] )

graph_decomp function []=graph_decomp(z,varlist,initial_period,freq)

filt_mc_ function [rmse_MC, ixx] = filt_mc_(OutDir)

myboxplot sout = myboxplot (data,notched,symbol,vertical,maxwhisker)

prior_draw_gsa Draws from the prior distributions

redform_map function redform_map(dirname)

redform_screen function redform_map(dirname)

smirnov Smirnov test for 2 distributions

stab_map_

stab_map_1 function [proba, dproba] = stab_map_1(lpmat, ibehaviour, inonbehaviour, aname, iplot, ipar, dirname, pcrit)

tcrit function t_crit = tcrit(n,pval0)

teff [yt, j0, ir, ic]=teff(T,Nsam,istable)

homotopy3 function homotopy3(values, step_nbr)

identification_analysis function [ide_hess, ide_moments, ide_model, ide_lre, derivatives_info, info] = identification_analysis(params,indx,indexo,options_ident,data_info, prior_exist, name_tex, init)

identification_checks function [condJ, ind0, indnoJ, ixnoJ, McoJ, PcoJ, jweak, jweak_pair] = identification_checks(JJ, hess_flag)

independent_metropolis_hastings Independent Metropolis-Hastings algorithm.

independent_metropolis_hastings_core PARALLEL CONTEXT

kernel_density_estimate Estimates a continuous density.

mode_check Checks the estimated ML mode or Posterior mode.

mr_gstep function [f0, x, ig] = mr_gstep(h1,x,func0,htol0,varargin)

mr_hessian [hessian_mat, gg, htol1, ihh, hh_mat0, hh1] = mr_hessian(init,x,func,hflag,htol0,varargin)

ms_sbvar_setup function ms_sbvar_setup(options_)

msstart2 function msstart2(options_)

plot_ms_variance_decomposition function plot_ms_variance_decomposition(M_, options_, vd, figure_name, varargin)

myboxplot sout = myboxplot (data,notched,symbol,vertical,maxwhisker)

newrat [xparam1, hh, gg, fval, igg] = newrat(func0, x, hh, gg, igg, ftol0, nit, flagg, varargin)

osr_obj objective function for optimal simple rules (OSR)

distributeJobs PARALLEL CONTEXT

masterParallel PARALLEL CONTEXT

plot_icforecast Build plots for the conditional forecasts.

plot_identification function plot_identification(params,idemoments,idehess,idemodel, idelre, advanced, tittxt, name, IdentifDirectoryName)

plot_priors function plot_priors

posterior_moments Computes posterior mean, median, variance, HPD interval, deciles, and density from posterior draws.

prior_posterior_statistics function prior_posterior_statistics(type,dataset)

random_walk_metropolis_hastings function record=random_walk_metropolis_hastings(TargetFun,ProposalFun,xparam1,vv,mh_bounds,varargin)

random_walk_metropolis_hastings_core PARALLEL CONTEXT

set_prior function [xparam1,estim_params_,bayestopt_,lb,ub]=set_prior(estim_params_)

shock_decomposition function z = shock_decomposition(M_,oo_,options_,varlist)

simplex_optimization_routine Nelder-Mead like optimization routine.

simultxdet function [y_,int_width]=simultxdet(y0,ex,ex_det, iorder,var_list,M_,oo_,options_)

stoch_simul_sparse This file is a modified version of stoch_simul.m: common parts should be factorized!

variance_decomposition_mc_analysis This function analyses the (posterior or prior) distribution of the

vnorm VNORM - Return the vector norm along specified dimension of A

SOURCE CODE

0001 function c = min(a,b)
0002 
0003 %@info:
0004 %! @deftypefn {Function File} {@var{c} =} min (@var{a},@var{b})
0005 %! @anchor{@dynDate/gt}
0006 %! @sp 1
0007 %! Overloads the min function for the Dynare dates class (@ref{dynDate}).
0008 %! @sp 2
0009 %! @strong{Inputs}
0010 %! @sp 1
0011 %! @table @ @var
0012 %! @item a
0013 %! Dynare date object instantiated by @ref{dynDate}.
0014 %! @item b
0015 %! Dynare date object instantiated by @ref{dynDate}.
0016 %! @end table
0017 %! @sp 1
0018 %! @strong{Outputs}
0019 %! @sp 1
0020 %! @table @ @var
0021 %! @item c
0022 %! Dynare date object instantiated by @ref{dynDate}. @var{c} is a copy of @var{a} if @var{a}<=@var{b}, a copy of @var{b} otherwise.
0023 %! @end table
0024 %! @sp 2
0025 %! @strong{This function is called by:}
0026 %! @sp 2
0027 %! @strong{This function calls:}
0028 %!
0029 %! @end deftypefn
0030 %@eod:
0031 
0032 % Copyright (C) 2011 Dynare Team
0033 % stephane DOT adjemian AT univ DASH lemans DOT fr
0034 %
0035 % This file is part of Dynare.
0036 %
0037 % Dynare is free software: you can redistribute it and/or modify
0038 % it under the terms of the GNU General Public License as published by
0039 % the Free Software Foundation, either version 3 of the License, or
0040 % (at your option) any later version.
0041 %
0042 % Dynare is distributed in the hope that it will be useful,
0043 % but WITHOUT ANY WARRANTY; without even the implied warranty of
0044 % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
0045 % GNU General Public License for more details.
0046 %
0047 % You should have received a copy of the GNU General Public License
0048 % along with Dynare.  If not, see <http://www.gnu.org/licenses/>.
0049 
0050 verbose = 0;
0051 
0052 if nargin~=2
0053     error('dynDate::min: I need exactly two input arguments!')
0054 end
0055 
0056 if ~( isa(a,'dynDate') && isa(b,'dynDate'))
0057     error(['dynDate::min: Input arguments ' inputname(1) 'and ' inputname(2) ' have to be a dynDate objects!'])
0058 end
0059 
0060 if verbose && a.freq~=b.freq
0061     error(['dynDate::min: Input arguments ' inputname(1) 'and ' inputname(2) ' have no common frequencies!'])
0062 end
0063 
0064 if a<=b
0065     c = a;
0066 else
0067     c = b;
0068 end
0069 
0070 %@test:1
0071 %$ addpath ../matlab
0072 %$
0073 %$ % Define some dates
0074 %$ date_1 = 1950;
0075 %$ date_2 = 2000;
0076 %$ date_3 = '1950Q2';
0077 %$ date_4 = '1950Q3';
0078 %$ date_5 = '1950M1';
0079 %$ date_6 = '1948M6';
0080 %$
0081 %$ % Call the tested routine.
0082 %$ d1 = dynDate(date_1);
0083 %$ d2 = dynDate(date_2);
0084 %$ d3 = dynDate(date_3);
0085 %$ d4 = dynDate(date_4);
0086 %$ d5 = dynDate(date_5);
0087 %$ d6 = dynDate(date_6);
0088 %$ m1 = min(d1,d2);
0089 %$ i1 = (m1==d1);
0090 %$ m2 = min(d3,d4);
0091 %$ i2 = (m2==d3);
0092 %$ m3 = min(d5,d6);
0093 %$ i3 = (m3==d6);
0094 %$
0095 %$ % Check the results.
0096 %$ t(1) = dyn_assert(i1,1);
0097 %$ t(2) = dyn_assert(i2,1);
0098 %$ t(3) = dyn_assert(i3,1);
0099 %$ T = all(t);
0100 %@eof:1

min

PURPOSE

SYNOPSIS

DESCRIPTION

CROSS-REFERENCE INFORMATION

SOURCE CODE