190 lines
11 KiB
HTML
190 lines
11 KiB
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<title>Description of set_prior</title>
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<div><a href="../index.html">Home</a> > <a href="index.html">.</a> > set_prior.m</div>
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<!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png"> Master index</a></td>
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<td align="right"><a href="index.html">Index for . <img alt=">" border="0" src="../right.png"></a></td></tr></table>-->
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<h1>set_prior
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</h1>
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<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
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<div class="box"><strong></strong></div>
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<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
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<div class="box"><strong>function [xparam1,estim_params_,bayestopt_,lb,ub]=set_prior(estim_params_) </strong></div>
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<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
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<div class="fragment"><pre class="comment"></pre></div>
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<!-- crossreference -->
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<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
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This function calls:
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<ul style="list-style-image:url(../matlabicon.gif)">
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<li><a href="inverse_gamma_specification.html" class="code" title="function [s,nu] = inverse_gamma_specification(mu,sigma,type)">inverse_gamma_specification</a> </li><li><a href="uniform_specification.html" class="code" title="function [m,s,p1,p2] = uniform_specification(m,s,p3,p4)">uniform_specification</a> Copyright (C) 2004 Michel Juillard</li></ul>
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This function is called by:
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<ul style="list-style-image:url(../matlabicon.gif)">
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<li><a href="dynare_MC.html" class="code" title="function dynare_MC(var_list_)">dynare_MC</a> </li><li><a href="dynare_estimation.html" class="code" title="function dynare_estimation(var_list_)">dynare_estimation</a> </li></ul>
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<!-- crossreference -->
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<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
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<div class="fragment"><pre>0001 <a name="_sub0" href="#_subfunctions" class="code">function [xparam1,estim_params_,bayestopt_,lb,ub]=set_prior(estim_params_)</a>
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0002 <span class="keyword">global</span> M_ options_
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0003
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0004 nvx = size(estim_params_.var_exo,1);
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0005 nvn = size(estim_params_.var_endo,1);
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0006 ncx = size(estim_params_.corrx,1);
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0007 ncn = size(estim_params_.corrn,1);
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0008 np = size(estim_params_.param_vals,1);
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0009
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0010 estim_params_.nvx = nvx;
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0011 estim_params_.nvn = nvn;
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0012 estim_params_.ncx = ncx;
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0013 estim_params_.ncn = ncn;
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0014 estim_params_.np = np;
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0015
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0016 xparam1 = [];
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0017 ub = [];
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0018 lb = [];
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0019 bayestopt_.pshape = [];
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0020 bayestopt_.pmean = [];
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0021 bayestopt_.pstdev = [];
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0022 bayestopt_.p1 = [];
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0023 bayestopt_.p2 = [];
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0024 bayestopt_.p3 = [];
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0025 bayestopt_.p4 = [];
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0026 bayestopt_.jscale = [];
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0027 bayestopt_.name = [];
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0028 <span class="keyword">if</span> nvx
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0029 xparam1 = estim_params_.var_exo(:,2);
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0030 ub = estim_params_.var_exo(:,4);
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0031 lb = estim_params_.var_exo(:,3);
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0032 bayestopt_.pshape = estim_params_.var_exo(:,5);
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0033 bayestopt_.pmean = estim_params_.var_exo(:,6);
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0034 bayestopt_.pstdev = estim_params_.var_exo(:,7);
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0035 bayestopt_.p3 = estim_params_.var_exo(:,8);
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0036 bayestopt_.p4 = estim_params_.var_exo(:,9);
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0037 bayestopt_.jscale = estim_params_.var_exo(:,10);
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0038 bayestopt_.name = cellstr(M_.exo_names(estim_params_.var_exo(:,1),:));
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0039 <span class="keyword">end</span>
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0040 <span class="keyword">if</span> nvn
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0041 <span class="keyword">for</span> i=1:nvn
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0042 estim_params_.var_endo(i,1) = strmatch(deblank(M_.endo_names(estim_params_.var_endo(i,1),:)),deblank(options_.varobs),<span class="string">'exact'</span>);
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0043 <span class="keyword">end</span>
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0044 xparam1 = [xparam1; estim_params_.var_endo(:,2)];
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0045 ub = [ub; estim_params_.var_endo(:,4)];
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0046 lb = [lb; estim_params_.var_endo(:,3)];
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0047 bayestopt_.pshape = [ bayestopt_.pshape; estim_params_.var_endo(:,5)];
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0048 bayestopt_.pmean = [ bayestopt_.pmean; estim_params_.var_endo(:,6)];
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0049 bayestopt_.pstdev = [ bayestopt_.pstdev; estim_params_.var_endo(:,7)];
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0050 bayestopt_.p3 = [ bayestopt_.p3; estim_params_.var_endo(:,8)];
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0051 bayestopt_.p4 = [ bayestopt_.p4; estim_params_.var_endo(:,9)];
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0052 bayestopt_.jscale = [ bayestopt_.jscale; estim_params_.var_endo(:,10)];
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0053 bayestopt_.name = cellstr(strvcat(char(bayestopt_.name),<span class="keyword">...</span>
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0054 M_.endo_names(estim_params_.var_endo(:,1),:)));
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0055 <span class="keyword">end</span>
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0056 <span class="keyword">if</span> ncx
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0057 xparam1 = [xparam1; estim_params_.corrx(:,3)];
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0058 ub = [ub; max(min(estim_params_.corrx(:,5),1),-1)];
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0059 lb = [lb; max(min(estim_params_.corrx(:,4),1),-1)];
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0060 bayestopt_.pshape = [ bayestopt_.pshape; estim_params_.corrx(:,6)];
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0061 bayestopt_.pmean = [ bayestopt_.pmean; estim_params_.corrx(:,7)];
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0062 bayestopt_.pstdev = [ bayestopt_.pstdev; estim_params_.corrx(:,8)];
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0063 bayestopt_.p3 = [ bayestopt_.p3; estim_params_.corrx(:,9)];
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0064 bayestopt_.p4 = [ bayestopt_.p4; estim_params_.corrx(:,10)];
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0065 bayestopt_.jscale = [ bayestopt_.jscale; estim_params_.corrx(:,11)];
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0066 bayestopt_.name = cellstr(strvcat(char(bayestopt_.name),<span class="keyword">...</span>
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0067 char(strcat(cellstr(M_.exo_names(estim_params_.corrx(:,1),:)),<span class="keyword">...</span>
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0068 <span class="string">','</span>,<span class="keyword">...</span>
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0069 cellstr(M_.exo_names(estim_params_.corrx(:,2),:))))));
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0070 <span class="keyword">end</span>
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0071 <span class="keyword">if</span> ncn
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0072 xparam1 = [xparam1; estim_params_.corrn(:,3)];
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0073 ub = [ub; max(min(estim_params_.corrn(:,5),1),-1)];
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0074 lb = [lb; max(min(estim_params_.corrn(:,4),1),-1)];
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0075 bayestopt_.pshape = [ bayestopt_.pshape; estim_params_.corrn(:,6)];
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0076 bayestopt_.pmean = [ bayestopt_.pmean; estim_params_.corrn(:,7)];
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0077 bayestopt_.pstdev = [ bayestopt_.pstdev; estim_params_.corrn(:,8)];
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0078 bayestopt_.p3 = [ bayestopt_.p3; estim_params_.corrn(:,9)];
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0079 bayestopt_.p4 = [ bayestopt_.p4; estim_params_.corrn(:,10)];
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0080 bayestopt_.jscale = [ bayestopt_.jscale; estim_params_.corrn(:,11)];
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0081 bayestopt_.name = cellstr(strvcat(char(bayestopt_.name),<span class="keyword">...</span>
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0082 char(strcat(cellstr(M_.endo_names(estim_params_.corrn(:,1),:)),<span class="keyword">...</span>
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0083 <span class="string">','</span>,<span class="keyword">...</span>
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0084 cellstr(M_.endo_names(estim_params_.corrn(:,2),:))))));
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0085 <span class="keyword">end</span>
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0086 <span class="keyword">if</span> np
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0087 xparam1 = [xparam1; estim_params_.param_vals(:,2)];
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0088 ub = [ub; estim_params_.param_vals(:,4)];
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0089 lb = [lb; estim_params_.param_vals(:,3)];
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0090 bayestopt_.pshape = [ bayestopt_.pshape; estim_params_.param_vals(:,5)];
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0091 bayestopt_.pmean = [ bayestopt_.pmean; estim_params_.param_vals(:,6)];
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0092 bayestopt_.pstdev = [ bayestopt_.pstdev; estim_params_.param_vals(:,7)];
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0093 bayestopt_.p3 = [ bayestopt_.p3; estim_params_.param_vals(:,8)];
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0094 bayestopt_.p4 = [ bayestopt_.p4; estim_params_.param_vals(:,9)];
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0095 bayestopt_.jscale = [ bayestopt_.jscale; estim_params_.param_vals(:, <span class="keyword">...</span>
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0096 10)];
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0097 bayestopt_.name = cellstr(strvcat(char(bayestopt_.name),M_.param_names(estim_params_.param_vals(:,1),:)));
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0098 <span class="keyword">end</span>
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0099
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0100 bayestopt_.ub = ub;
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0101 bayestopt_.lb = lb;
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0102
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0103 bayestopt_.p1 = bayestopt_.pmean;
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0104 bayestopt_.p2 = bayestopt_.pstdev;
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0105
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0106 <span class="comment">% generalized location parameters by default for beta distribution</span>
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0107 k = find(bayestopt_.pshape == 1);
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0108 k1 = find(isnan(bayestopt_.p3(k)));
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0109 bayestopt_.p3(k(k1)) = zeros(length(k1),1);
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0110 k1 = find(isnan(bayestopt_.p4(k)));
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0111 bayestopt_.p4(k(k1)) = ones(length(k1),1);
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0112
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0113 <span class="comment">% generalized location parameter by default for gamma distribution</span>
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0114 k = find(bayestopt_.pshape == 2);
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0115 k1 = find(isnan(bayestopt_.p3(k)));
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0116 bayestopt_.p3(k(k1)) = zeros(length(k1),1);
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0117
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0118 <span class="comment">% truncation parameters by default for normal distribution</span>
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0119 k = find(bayestopt_.pshape == 3);
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0120 k1 = find(isnan(bayestopt_.p3(k)));
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0121 bayestopt_.p3(k(k1)) = -Inf*ones(length(k1),1);
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0122 k1 = find(isnan(bayestopt_.p4(k)));
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0123 bayestopt_.p4(k(k1)) = Inf*ones(length(k1),1);
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0124
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0125 k = find(bayestopt_.pshape == 4);
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0126 <span class="keyword">for</span> i=1:length(k)
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0127 [bayestopt_.p1(k(i)),bayestopt_.p2(k(i))] = <span class="keyword">...</span>
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0128 <a href="inverse_gamma_specification.html" class="code" title="function [s,nu] = inverse_gamma_specification(mu,sigma,type)">inverse_gamma_specification</a>(bayestopt_.pmean(k(i)),bayestopt_.pstdev(k(i)),1);
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0129 <span class="keyword">end</span>
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0130
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0131 k = find(bayestopt_.pshape == 5);
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0132 <span class="keyword">for</span> i=1:length(k)
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0133 [bayestopt_.pmean(k(i)),bayestopt_.pstdev(k(i)),bayestopt_.p1(k(i)),bayestopt_.p2(k(i))] = <span class="keyword">...</span>
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0134 <a href="uniform_specification.html" class="code" title="function [m,s,p1,p2] = uniform_specification(m,s,p3,p4)">uniform_specification</a>(bayestopt_.pmean(k(i)),bayestopt_.pstdev(k(i)),bayestopt_.p3(k(i)),bayestopt_.p4(k(i)));
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0135 <span class="keyword">end</span>
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0136
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0137 k = find(bayestopt_.pshape == 6);
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0138 <span class="keyword">for</span> i=1:length(k)
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0139 [bayestopt_.p1(k(i)),bayestopt_.p2(k(i))] = <span class="keyword">...</span>
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0140 <a href="inverse_gamma_specification.html" class="code" title="function [s,nu] = inverse_gamma_specification(mu,sigma,type)">inverse_gamma_specification</a>(bayestopt_.pmean(k(i)),bayestopt_.pstdev(k(i)),2);
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0141 <span class="keyword">end</span>
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0142
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0143 k = find(isnan(xparam1));
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0144 xparam1(k) = bayestopt_.pmean(k);</pre></div>
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