v4 matlab: removed useless asamin.m and added an error message for mode_compute=2

git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@1893 ac1d8469-bf42-47a9-8791-bf33cf982152

matlab/asamin.m

@@ -1,160 +0,0 @@
-%  ASAMIN A gateway function to Adaptive Simulated Annealing (ASA)
-%
-%  ASAMIN is a matlab gateway function to Lester Ingber's Adaptive
-%  Simulated Annealing (ASA)
-%
-%  Copyright (c) 1999-2001  Shinichi Sakata. All Rights Reserved. 
-%
-%  $Id: asamin.m,v 1.1.2.1 2004/03/27 14:41:06 michel Exp $
-%
-%  Usage:
-%
-%  asamin ('set')
-%
-%    lists the current value of each option.
-%
-%  asamin ('set', opt_name)
-%
-%    shows the current value of the option given by a character string
-%    opt_name; e.g., 
-%
-%        asamin ('set', 'seed')
-%
-%  asamin ('set', opt_name, opt_value)
-%
-%    set the value opt_value to the option opt_name; e.g.,
-%
-%        asamin ('set', 'seed', 654342)
-%        asamin ('set', 'asa_out_file', 'example.log')
-%
-%  The valid options in these commands are:
-%
-%    rand_seed
-%    test_in_cost_func
-%    use_rejected_cost
-%    asa_out_file
-%    limit_acceptances
-%    limit_generated
-%    limit_invalid
-%    accepted_to_generated_ratio
-%    cost_precision
-%    maximum_cost_repeat
-%    number_cost_samples
-%    temperature_ratio_scale
-%    cost_parameter_scale
-%    temperature_anneal_scale
-%    include_integer_parameters
-%    user_initial_parameters
-%    sequential_parameters
-%    initial_parameter_temperature
-%    acceptance_frequency_modulus
-%    generated_frequency_modulus
-%    reanneal_cost
-%    reanneal_parameters
-%    delta_x
-%
-%    rand_seed is the seed of the random number generation in ASA. 
-%
-%    If test_in_cost_func is set to zero, the cost function should
-%    simply return the value of the objective function. When
-%    test_in_cost_func is set to one, asamin () calls the cost
-%    function with a threshold value as well as the parameter
-%    value. The cost function needs to judge if the value of the cost
-%    function exceeds the threshold as well as compute the value of
-%    the cost function when asamin () requires. (See COST FUNCTION
-%    below for details.)
-%
-%    All other items but use_rejected_cost belong to structure
-%    USER_OPTIONS in ASA. See ASA_README in the ASA package for
-%    details. The default value of use_rejected_cost is zero. If you
-%    set this option to one, ASA uses the current cost value to
-%    compute certain indices, even if the current state is rejected by
-%    the user cost function, provided that the current cost value is
-%    lower than the cost value of the past best state. (See COST
-%    FUNCTION below about the user cost function.)
-%
-%  asamin ('reset')
-%    resets all option values to the hard-coded default values.
-%
-%  [fstar,xstar,grad,hessian,state] = ...
-%     asamin ('minimize', func, xinit, xmin, xmax, xtype,...
-%              parm1, parm2, ...)
-%
-%     minimizes the cost function func (also see COST FUNCTION below).
-%     The argument xinit specifies the initial value of the arguments
-%     of the cost function. Each element of the vectors xmin and xmax
-%     specify the lower and upper bounds of the corresponding
-%     argument.  The vector xtype indicates the types of the
-%     arguments. If xtype(i) is -1 if the i'th argument is real;
-%     xtype(i) is 1 if the i'th argument is integer. If this argument
-%     should be ignored in reannealing, multiply the corresponding
-%     element of xtype by 2 so that the element is 2 or -2. All
-%     parameters following xtype are optional and simply passed to the
-%     cost function each time the cost function is called.
-%
-%     This way of calling asamin returns the following values:
-%
-%     fstar
-%       The value of the objective function at xstar.
-%     xstar
-%       The argument vector at the exit from the ASA routine. If things go
-%       well, xstar should be the minimizer of "func".
-%     grad
-%       The gradient of "func" at xstar.
-%     hessian
-%       The Hessian of "func" at xstar.
-%     state
-%       The vector containing the information on the exit state. 
-%       state(1) is the exit_code, and state(2) is the cost flag. See 
-%       ASA_README for details.
-%
-%
-%     
-%  COST FUNCTION
-%
-%  If test_in_cost_func is set to zero, asamin () calls the "cost
-%  function" (say, cost_func) with one argument, say x (the real cost
-%  function is evaluated at this point). Cost_func is expected to
-%  return the value of the objective function and cost_flag, the
-%  latter of which must be zero if any constraint (if any) is
-%  violated; otherwise one.
-%
-%  When test_in_cost_func is equal to one, asamin () calls the "cost
-%  function" (say, cost_func) with three arguments, say, x (at which
-%  the real cost function is evaluated), critical_cost_value, and
-%  no_test_flag. Asamin expects cost_func to return three scalar
-%  values, say, cost_value, cost_flag, and user_acceptance_flag in the
-%  following manner.
-%   
-%    1. The function cost_func first checks if x satisfies the
-%    constraints of the minimization problem. If any of the
-%    constraints is not satisfied, cost_func sets zero to cost_flag
-%    and return. (user_acceptance_flag and cost_value will not be used
-%    by asamin () in this case.) If all constraints are satisfied, set
-%    one to cost_flag, and proceed to the next step.
-%   
-%    2. If asamin () calls cost_func with no_test_flag==1, cost_func
-%    must compute the value of the cost function, set it to cost_value
-%    and return. When no_test_flag==0, cost_func is expected to judge
-%    if the value of the cost function is greater than
-%    critical_cost_value. If the value of the cost function is found
-%    greater than critical_cost_value, cost_func must set zero to
-%    user_acceptance_flag and return. (asamin () will not use
-%    cost_value in this case.) On the other hand, if the value of the
-%    cost function is found no greater than critical_cost_value,
-%    cost_func must compute the cost function at x, set it to
-%    cost_value, and set one to user_acceptance_flag.
-%   
-%  Remark: To understand the usefulness of test_in_cost_func == 1,
-%  note that it is sometimes easier to check if the value of the cost
-%  function is greater than critical_cost_value than compute the value
-%  of the cost function. For example, suppose that the cost function g
-%  is implicitly defined by an equation f(g(x),x)=0, where f is
-%  strictly increasing in the first argument, and evaluation of g(x)
-%  is computationally expensive (e.g., requiring an iterative method
-%  to find a solution to f(y,x)=0). But we can easily show that
-%  f(critical_cost_value,x) < 0 if and only if g(x) >
-%  critical_cost_value. We can judge if g(x) > critical_cost_value by
-%  computing f(critical_cost_value,x). The value of g(x) is not
-%  necessary.
-%

matlab/dynare_estimation.m

@@ -318,13 +318,14 @@ if options_.mode_compute > 0 & options_.posterior_mode_estimation
     end
   elseif options_.mode_compute == 2
     % asamin('set','maximum_cost_repeat',0);
-    if ~options_.bvar_dsge
-      [fval,xparam1,grad,hessian_asamin,exitflag] = ...
-          asamin('minimize','DsgeLikelihood',xparam1,lb,ub,-ones(size(xparam1)),gend,data);   
-    else
-      [fval,xparam1,grad,hessian_asamin,exitflag] = ...
-          asamin('minimize','DsgeVarLikelihood',xparam1,lb,ub,-ones(size(xparam1)),gend);   
-    end       
+% $$$     if ~options_.bvar_dsge
+% $$$       [fval,xparam1,grad,hessian_asamin,exitflag] = ...
+% $$$           asamin('minimize','DsgeLikelihood',xparam1,lb,ub,-ones(size(xparam1)),gend,data);   
+% $$$     else
+% $$$       [fval,xparam1,grad,hessian_asamin,exitflag] = ...
+% $$$           asamin('minimize','DsgeVarLikelihood',xparam1,lb,ub,-ones(size(xparam1)),gend);   
+% $$$     end       
+    error('ESTIMATION: mode_compute=2 option (Lester Ingber''s Adaptive Simulated Annealing) is no longer available')
   elseif options_.mode_compute == 3
     optim_options = optimset('display','iter','MaxFunEvals',100000,'TolFun',1e-8,'TolX',1e-6);
     if isfield(options_,'optim_opt')