Commit 99da257e authored by Sébastien Villemot's avatar Sébastien Villemot
Browse files

Merge remote-tracking branch 'houtanb/master'

parents 2b37eae3 4c1fe625
......@@ -66,17 +66,15 @@ case ${MATLAB_ARCH} in
MACOSX_DEPLOYMENT_TARGET='10.6'
if test "${MATLAB_ARCH}" = "maci"; then
ARCHS='i386'
MATLAB_FFLAGS=''
else
ARCHS='x86_64'
MATLAB_FFLAGS='-m64'
fi
MATLAB_DEFS="$MATLAB_DEFS -DNDEBUG"
MATLAB_CFLAGS="-fno-common -no-cpp-precomp -arch $ARCHS -isysroot $SDKROOT -mmacosx-version-min=$MACOSX_DEPLOYMENT_TARGET -fexceptions -O2"
MATLAB_LDFLAGS="-L$MATLAB/bin/${MATLAB_ARCH} -Wl,-twolevel_namespace -undefined error -arch $ARCHS -Wl,-syslibroot,$SDKROOT -mmacosx-version-min=$MACOSX_DEPLOYMENT_TARGET -bundle -Wl,-exported_symbols_list,\$(top_srcdir)/mexFunction-MacOSX.map"
MATLAB_LIBS="-lmx -lmex -lmat -lstdc++ -lmwlapack"
MATLAB_CXXFLAGS="-fno-common -no-cpp-precomp -fexceptions -arch $ARCHS -isysroot $SDKROOT -mmacosx-version-min=$MACOSX_DEPLOYMENT_TARGET -O2"
MATLAB_FFLAGS="-fexceptions $MATLAB_FFLAGS -fbackslash"
MATLAB_FFLAGS="-fexceptions -fbackslash -arch $ARCHS"
# Starting from MATLAB 7.5, BLAS and LAPACK are in distinct libraries
AX_COMPARE_VERSION([$MATLAB_VERSION], [ge], [7.5], [MATLAB_LIBS="${MATLAB_LIBS} -lmwblas"])
ax_mexopts_ok="yes"
......
function clean_files_for_second_type_of_mex(M_, options_, type)
%function clean_files_for_second_type_of_mex()
% function clean_files_for_second_type_of_mex(M_, options_, type)
% clean the files for the appropriate file tag and mex function
%
% INPUTS
......
function clean_ms_estimation_files(file_tag)
% function clean_ms_estimation_files()
% function clean_ms_estimation_files(file_tag)
% removes MS estimation files
%
% INPUTS
......
function clean_ms_forecast_files(file_tag)
% function clean_ms_forecast_files()
% function clean_ms_forecast_files(file_tag)
% removes MS forecast files
%
% INPUTS
......
function clean_ms_init_files(file_tag)
% function clean_ms_init_files()
% function clean_ms_init_files(file_tag)
% removes MS initialization files
%
% INPUTS
......
function clean_ms_irf_files(file_tag)
% function clean_ms_irf_files()
% function clean_ms_irf_files(file_tag)
% removes MS irf files
%
% INPUTS
......
function clean_ms_mdd_files(file_tag, pt)
% function clean_ms_mdd_files()
% function clean_ms_mdd_files(file_tag, pt)
% removes MS mdd files
%
% INPUTS
......
function clean_ms_probabilities_files(file_tag)
% function clean_ms_probabilities_files()
% function clean_ms_probabilities_files(file_tag)
% removes MS probabilities files
%
% INPUTS
......
function clean_ms_simulation_files(file_tag)
% function clean_ms_simulation_files()
% function clean_ms_simulation_files(file_tag)
% removes MS simulation files
%
% INPUTS
......
function clean_ms_variance_decomposition_files(file_tag)
% function clean_ms_variance_decomposition_files()
% function clean_ms_variance_decomposition_files(file_tag)
% removes MS variance decomposition files
%
% INPUTS
......
function clean_sbvar_files()
%function clean_sbvar_files()
% function clean_sbvar_files()
% Remove files created by sbvar
%
% INPUTS
......
function create_dir(dirname)
% function create_dir()
% function create_dir(dirname)
% creates directory if it doesn't exist
%
% INPUTS
......
function delete_dir_if_exists(dirname)
% function delete_dir_if_exists()
% function delete_dir_if_exists(dirname)
% removes directory if it exists
%
% INPUTS
......
function delete_if_exists(fname)
% function delete_if_exists()
% function delete_if_exists(fname)
% removes MS intermediary files
%
% INPUTS
......
function dyn_save_graph(dirname,graph_name,graph_formats,TeX,names,texnames,caption)
% function dyn_graph_save(graph_name,graph_formats,TeX)
% function dyn_save_graph(dirname,graph_name,graph_formats,TeX,names,texnames,caption)
% saves Dynare graphs
%
% INPUTS
......
function options_=initialize_ms_sbvar_options(M_, options_)
%function initialize_ms_sbvar_options()
% function options_=initialize_ms_sbvar_options(M_, options_)
% sets ms sbvar options back to their default values
%
% INPUTS
......
function [options_, oo_]=ms_compute_mdd(M_, options_, oo_)
%function ms_compute_mdd()
% MS Sbvar Compute Marginal Data Density
% function [options_, oo_]=ms_compute_mdd(M_, options_, oo_)
% Markov-switching SBVAR: Compute Marginal Data Density
%
% INPUTS
% M_: (struct) model structure
......
function [options_, oo_]=ms_compute_probabilities(M_, options_, oo_)
%function ms_simulation()
% MS Sbvar Compute Posterior Mode Regime Probabilities
% function [options_, oo_]=ms_compute_probabilities(M_, options_, oo_)
% Markov-switching SBVAR: Compute Posterior Mode Regime Probabilities
%
% INPUTS
% M_: (struct) model structure
......
function [options_, oo_]=ms_estimation(M_, options_, oo_)
%function ms_estimation()
% MS Sbvar Estimation
% function [options_, oo_]=ms_estimation(M_, options_, oo_)
% Markov-switching SBVAR: Estimation
%
% INPUTS
% M_: (struct) model structure
......
function [options_, oo_]=ms_forecast(M_, options_, oo_)
%function ms_forecast()
% MS-SBVAR Forecast
% function [options_, oo_]=ms_forecast(M_, options_, oo_)
% Markov-switching SBVAR: Forecast
%
% INPUTS
% M_: (struct) model structure
......
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