Merge branch 'jscale' into 'master'

Make default jscale depend on number of estimated parameters

See merge request Dynare/dynare!2041

doc/manual/source/the-model-file.rst

@@ -6381,9 +6381,8 @@ block decomposition of the model (see :opt:`block`).
 
     .. option:: mh_jscale = DOUBLE
 
-       The scale parameter of the jumping distribution’s covariance
+       The scale parameter of the jumping distribution's covariance
-       matrix (Metropolis-Hastings or TaRB-algorithm). The default
+       matrix (Metropolis-Hastings or TaRB-algorithm). This option must be tuned to
-       value is rarely satisfactory. This option must be tuned to
        obtain, ideally, an acceptance ratio of 25%-33%. Basically, the
        idea is to increase the variance of the jumping distribution if
        the acceptance ratio is too high, and decrease the same
@@ -6401,7 +6400,7 @@ block decomposition of the model (see :opt:`block`).
        subsequent runs via the ``posterior_sampler_options`` option
        :ref:`scale_file <scale-file>`. Both ``mode_compute=6`` and
        ``scale_file`` will overwrite any value specified in
-       ``estimated_params`` with the tuned value. Default: ``0.2``.
+       ``estimated_params`` with the tuned value. Default: ``2.38/sqrt(n)``.
 
        Note also that for the Random Walk Metropolis Hastings
        algorithm, it is possible to use option :opt:`mh_tune_jscale
@@ -6409,7 +6408,7 @@ block decomposition of the model (see :opt:`block`).
        of ``mh_jscale``. In this case, the ``mh_jscale`` option must
        not be used.
 
-    .. option:: mh_init_scale = DOUBLE
+    .. option:: mh_init_scale = DOUBLE (deprecated)
 
        The scale to be used for drawing the initial value of the
        Metropolis-Hastings chain. Generally, the starting points
@@ -6421,8 +6420,8 @@ block decomposition of the model (see :opt:`block`).
        at the beginning of Dynare execution, i.e. the default will not
        take into account potential changes in ``mh_jscale`` introduced
        by either ``mode_compute=6`` or the
-       ``posterior_sampler_options`` option :ref:`scale_file
+       ``posterior_sampler_options`` option :ref:`scale_file<scale-file>`. 
-       <scale-file>`. If ``mh_init_scale`` is too wide during
+       If ``mh_init_scale`` is too wide during
        initalization of the posterior sampler so that 100 tested draws
        are inadmissible (e.g. Blanchard-Kahn conditions are always
        violated), Dynare will request user input of a new
@@ -6434,6 +6433,26 @@ block decomposition of the model (see :opt:`block`).
        most 10 times, at which point Dynare will abort with an error
        message.
 
+    .. option:: mh_init_scale_factor = DOUBLE
+
+       The multiple of ``mh_jscale`` used for drawing the initial value of the
+       Metropolis-Hastings chain. Generally, the starting points
+       should be overdispersed for the *Brooks and Gelman (1998)*
+       convergence diagnostics to be meaningful. Default:
+       ``2``
+
+       If ``mh_init_scale_factor`` is too wide during
+       initalization of the posterior sampler so that 100 tested draws
+       are inadmissible (e.g. Blanchard-Kahn conditions are always
+       violated), Dynare will request user input of a new
+       ``mh_init_scale_factor`` value with which the next 100 draws will be
+       drawn and tested. If the :opt:`nointeractive` option has been
+       invoked, the program will instead automatically decrease
+       ``mh_init_scale_factor`` by 10 percent after 100 futile draws and try
+       another 100 draws. This iterative procedure will take place at
+       most 10 times, at which point Dynare will abort with an error
+       message.
+
     .. option:: mh_tune_jscale [= DOUBLE]
 
        Automatically tunes the scale parameter of the jumping
@@ -6450,7 +6469,7 @@ block decomposition of the model (see :opt:`block`).
     .. option:: mh_tune_guess = DOUBLE
 
        Specifies the initial value for the :opt:`mh_tune_jscale
-       <mh_tune_jscale [= DOUBLE]>` option. Default: ``0.2``. Must not
+       <mh_tune_jscale [= DOUBLE]>` option. Default: ``2.39/sqrt(n)``. Must not
        be set if :opt:`mh_tune_jscale <mh_tune_jscale [= DOUBLE]>` is
        not used.
 

matlab/calibrate_mh_scale_parameter.m

@@ -55,6 +55,9 @@ n = length(Parameters);
 correction = 1.0;
 
 % Set the initial value of the scale parameter
+if isempty(options.guess)
+    options.guess=2.38/sqrt(length(Parameters));
+end
 Scale = options.guess;
 
 % Transposition of some arrays.

matlab/default_option_values.m

@@ -396,9 +396,9 @@ options_.logged_steady_state = 0;
 options_.mh_conf_sig = 0.90;
 options_.prior_interval = 0.90;
 options_.mh_drop = 0.5;
-options_.mh_jscale = 0.2;
+options_.mh_jscale = [];
 options_.mh_tune_jscale.status = false;
-options_.mh_tune_jscale.guess = .2;
+options_.mh_tune_jscale.guess = [];
 options_.mh_tune_jscale.target = .33;
 options_.mh_tune_jscale.maxiter = 200000;
 options_.mh_tune_jscale.rho = .7;
@@ -406,7 +406,7 @@ options_.mh_tune_jscale.stepsize = 1000;
 options_.mh_tune_jscale.c1 = .02;
 options_.mh_tune_jscale.c2 = .05;
 options_.mh_tune_jscale.c3 = 4;
-options_.mh_init_scale = 2*options_.mh_jscale;
+options_.mh_init_scale_factor = 2;
 options_.mh_initialize_from_previous_mcmc.status = false;
 options_.mh_initialize_from_previous_mcmc.directory = '';
 options_.mh_initialize_from_previous_mcmc.record = '';

matlab/dynare_estimation_init.m

@@ -534,8 +534,11 @@ if options_.analytic_derivation
     end
 end
 
-% If jscale isn't specified for an estimated parameter, use global option options_.jscale, set to 0.2, by default.
+% If jscale isn't specified for an estimated parameter, use global option options_.jscale, set to optimal value for a normal distribution by default.
 % Note that check_posterior_sampler_options and mode_compute=6 may overwrite the setting
+if isempty(options_.mh_jscale)
+    options_.mh_jscale=2.38/sqrt(length(xparam1));
+end
 k = find(isnan(bayestopt_.jscale));
 bayestopt_.jscale(k) = options_.mh_jscale;
 

matlab/posterior_sampler_initialization.m

@@ -197,7 +197,14 @@ if ~options_.load_mh_file && ~options_.mh_recover
                 if isempty(d)
                     candidate = prior_draw();
                 else
-                    candidate = rand_multivariate_normal( transpose(xparam1), d * options_.mh_init_scale, npar);
+                    if isfield(options_,'mh_init_scale')
+                        if trial==1
+                            fprintf('\nposterior_sampler_initialization: the mh_init_scale-option is deprecated. You should use the mh_init_scale_factor-option instead.\n')
+                        end
+                        candidate = rand_multivariate_normal( transpose(xparam1), d * options_.mh_init_scale, npar);
+                    else
+                        candidate = rand_multivariate_normal( transpose(xparam1), d * options_.mh_init_scale_factor*options_.mh_jscale, npar);
+                    end
                 end
                 if all(candidate(:) >= mh_bounds.lb) && all(candidate(:) <= mh_bounds.ub)
                     ix2(j,new_estimated_parameters) = candidate(new_estimated_parameters);
@@ -219,13 +226,25 @@ if ~options_.load_mh_file && ~options_.mh_recover
                 if init_iter > 100 && validate == 0
                     disp(['Estimation::mcmc: I couldn''t get a valid initial value in 100 trials.'])
                     if options_.nointeractive
-                        disp(['Estimation::mcmc: I reduce mh_init_scale by 10 percent:'])
+                        disp(['Estimation::mcmc: I reduce mh_init_scale_factor by 10 percent:'])
-                        options_.mh_init_scale = .9*options_.mh_init_scale;
+                        if isfield(options_,'mh_init_scale')
-                        disp(sprintf('Estimation::mcmc: Parameter mh_init_scale is now equal to %f.',options_.mh_init_scale))
+                           options_.mh_init_scale = .9*options_.mh_init_scale; 
+                           fprintf('Estimation::mcmc: Parameter mh_init_scale is now equal to %f.\n',options_.mh_init_scale)
+                        else
+                            options_.mh_init_scale_factor = .9*options_.mh_init_scale_factor;
+                            fprintf('Estimation::mcmc: Parameter mh_init_scale_factor is now equal to %f.\n',options_.mh_init_scale_factor)
+                        end
+                        fprintf('Estimation::mcmc: Parameter mh_init_scale_factor is now equal to %f.\n',options_.mh_init_scale_factor)
                     else
-                        disp(['Estimation::mcmc: You should reduce mh_init_scale...'])
+                        if isfield(options_,'mh_init_scale')
-                        disp(sprintf('Estimation::mcmc: Parameter mh_init_scale is equal to %f.',options_.mh_init_scale))
+                            disp(['Estimation::mcmc: You should reduce mh_init_scale...'])
-                        options_.mh_init_scale = input('Estimation::mcmc: Enter a new value...  ');
+                            fprintf('Estimation::mcmc: Parameter mh_init_scale is equal to %f.\n',options_.mh_init_scale)
+                            options_.mh_init_scale_factor = input('Estimation::mcmc: Enter a new value...  ');
+                        else
+                            disp(['Estimation::mcmc: You should reduce mh_init_scale_factor...'])
+                            fprintf('Estimation::mcmc: Parameter mh_init_scale_factor is equal to %f.\n',options_.mh_init_scale_factor)
+                            options_.mh_init_scale_factor = input('Estimation::mcmc: Enter a new value...  ');
+                        end
                     end
                     trial = trial+1;
                 end

preprocessor

@@ -1 +1 @@
-Subproject commit c48248fc0d65ed70fb13dd508ed0254f113cbcb6
+Subproject commit c721718bf621a1c16803216d6a4156931b7cc373