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Added option resampling_threshold (estimation command, non linear filters).

time-shift
Stéphane Adjemian (Scylla) 2014-08-29 12:56:05 +02:00
parent a6009908e4
commit 08c74b8f41
7 changed files with 12 additions and 7 deletions
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5
doc/dynare.texi
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@ -5317,10 +5317,13 @@ No resampling.
Resampling at each iteration, this is the default value.
@item generic
Resampling if and only if the effective sample size is below a certain level defined by @code{resampling_threshold*number_of_particles}.
Resampling if and only if the effective sample size is below a certain level defined by @ref{resampling_threshold}*@ref{number_of_particles}.
@end table
@item resampling_threshold = @var{DOUBLE}
@anchor{resampling_threshold}
A real number between zero and one. The resampling step is triggered as soon as the effective number of particles is less than this number times the total number of particles (as set by @ref{number_of_particles}). This option is effective if and only if option @ref{resampling} has value @code{generic}.
@end table

3
matlab/global_initialization.m
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@ -239,8 +239,7 @@ particle.unscented.kappa = 0;
particle.resampling.status.systematic = 1;
particle.resampling.status.none = 0;
particle.resampling.status.generic = 0;
particle.resampling.neff_threshold = .5;
particle.resampling.threshold = .5;
% Choice of the resampling method
particle.resampling.method1 = 'traditional' ;
particle.resampling.method2 = 'kitagawa';

2
matlab/particle/conditional_particle_filter.m
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@ -113,7 +113,7 @@ for t=1:sample_size
SumSampleWeights = sum(SampleWeights) ;
lik(t) = log(SumSampleWeights) ;
SampleWeights = SampleWeights./SumSampleWeights ;
if (DynareOptions.particle.resampling.status.generic && neff(SampleWeights)<DynareOptions.particle.resampling.neff_threshold*sample_size) || DynareOptions.particle.resampling.status.systematic
if (DynareOptions.particle.resampling.status.generic && neff(SampleWeights)<DynareOptions.particle.resampling.threshold*sample_size) || DynareOptions.particle.resampling.status.systematic
ks = ks + 1 ;
StateParticles = resample(StateParticles',SampleWeights',DynareOptions)';
SampleWeights = ones(1,number_of_particles)/number_of_particles ;

2
matlab/particle/online_auxiliary_filter.m
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@ -206,7 +206,7 @@ for t=1:sample_size
wtilde = lnw./wtilde ;
% normalization
weights = wtilde/sum(wtilde);
if (variance_update==1) && (neff(weights)<DynareOptions.particle.resampling.neff_threshold*sample_size)
if (variance_update==1) && (neff(weights)<DynareOptions.particle.resampling.threshold*sample_size)
variance_update = 0 ;
end
% final resampling (advised)

2
matlab/particle/sequential_importance_particle_filter.m
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@ -158,7 +158,7 @@ for t=1:sample_size
wtilde = weights.*exp(lnw-dfac);
lik(t) = log(sum(wtilde))+dfac;
weights = wtilde/sum(wtilde);
if (DynareOptions.particle.resampling.status.generic && neff(weights)<DynareOptions.particle.resampling.neff_threshold*sample_size) || DynareOptions.particle.resampling.status.systematic
if (DynareOptions.particle.resampling.status.generic && neff(weights)<DynareOptions.particle.resampling.threshold*sample_size) || DynareOptions.particle.resampling.status.systematic
if pruning
temp = resample([tmp(mf0,:)' tmp_(mf0,:)'],weights',DynareOptions);
StateVectors = temp(:,1:number_of_state_variables)';

4
preprocessor/DynareBison.yy
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@ -107,7 +107,7 @@ class ParsingDriver;
%token MFS MH_CONF_SIG MH_DROP MH_INIT_SCALE MH_JSCALE MH_MODE MH_NBLOCKS MH_REPLIC MH_RECOVER POSTERIOR_MAX_SUBSAMPLE_DRAWS MIN MINIMAL_SOLVING_PERIODS
%token MODE_CHECK MODE_CHECK_NEIGHBOURHOOD_SIZE MODE_CHECK_SYMMETRIC_PLOTS MODE_CHECK_NUMBER_OF_POINTS MODE_COMPUTE MODE_FILE MODEL MODEL_COMPARISON MODEL_INFO MSHOCKS ABS SIGN
%token MODEL_DIAGNOSTICS MODIFIEDHARMONICMEAN MOMENTS_VARENDO DIFFUSE_FILTER SUB_DRAWS TAPER_STEPS GEWEKE_INTERVAL MCMC_JUMPING_COVARIANCE MOMENT_CALIBRATION
%token NUMBER_OF_PARTICLES RESAMPLING SYSTEMATIC GENERIC
%token NUMBER_OF_PARTICLES RESAMPLING SYSTEMATIC GENERIC RESAMPLING_THRESHOLD
%token <string_val> NAME
%token NAN_CONSTANT NO_STATIC NOBS NOCONSTANT NODISPLAY NOCORR NODIAGNOSTIC NOFUNCTIONS NO_HOMOTOPY
%token NOGRAPH NOMOMENTS NOPRINT NORMAL_PDF SAVE_DRAWS
@ -1679,6 +1679,7 @@ estimation_options : o_datafile
| o_consider_only_observed
| o_number_of_particles
| o_resampling
| o_resampling_threshold
;
list_optim_option : QUOTED_STRING COMMA QUOTED_STRING
@ -2645,6 +2646,7 @@ o_number_of_particles : NUMBER_OF_PARTICLES EQUAL INT_NUMBER { driver.option_num
o_resampling : RESAMPLING EQUAL SYSTEMATIC
| RESAMPLING EQUAL NONE {driver.option_num("particle.resampling.status.systematic", "0"); driver.option_num("particle.resampling.status.none", "1"); }
| RESAMPLING EQUAL GENERIC {driver.option_num("particle.resampling.status.systematic", "0"); driver.option_num("particle.resampling.status.generic", "1"); };
o_resampling_threshold : RESAMPLING_THRESHOLD EQUAL non_negative_number { driver.option_num("particle.resampling.threshold", $3); };
o_gsa_identification : IDENTIFICATION EQUAL INT_NUMBER { driver.option_num("identification", $3); }; /*not in doc */
o_gsa_morris : MORRIS EQUAL INT_NUMBER { driver.option_num("morris", $3); };

1
preprocessor/DynareFlex.ll
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@ -358,6 +358,7 @@ DATE -?[0-9]+([YyAa]|[Mm]([1-9]|1[0-2])|[Qq][1-4]|[Ww]([1-9]{1}|[1-4][0-9]|5[0-2
<DYNARE_STATEMENT>systematic {return token::SYSTEMATIC;}
<DYNARE_STATEMENT>none {return token::NONE;}
<DYNARE_STATEMENT>generic {return token::GENERIC;}
<DYNARE_STATEMENT>resampling_threshold {return token::RESAMPLING_THRESHOLD;}
<DYNARE_STATEMENT>alpha {
yylval->string_val = new string(yytext);