647 lines
46 KiB
HTML
647 lines
46 KiB
HTML
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<title>Description of filt_mc_</title>
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<div><a href="../index.html">Home</a> > <a href="index.html">.</a> > filt_mc_.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>filt_mc_
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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>copyright Marco Ratto 2006</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 [rmse_MC, ixx] = filt_mc_(vvarvecm, loadSA, pfilt, alpha, alpha2, OutDir, istart, alphaPC) </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"> copyright Marco Ratto 2006</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="CheckPath.html" class="code" title="function DirectoryName = CheckPath(type)">CheckPath</a> 06-03-2005</li><li><a href="DsgeSmoother.html" class="code" title="function [alphahat,etahat,epsilonhat,ahat,SteadyState,trend_coeff,aK] = DsgeSmoother(xparam1,gend,Y)">DsgeSmoother</a> stephane.adjemian@cepremap.cnrs.fr [09-07-2004]</li><li><a href="cumplot.html" class="code" title="function h = cumplot(x);">cumplot</a> function h =cumplot(x)</li><li><a href="kernel_density_estimate.html" class="code" title="function [abscissa,f] = kernel_density_estimate(data,number_of_grid_points,bandwidth,kernel_function)">kernel_density_estimate</a> % This function aims at estimating a continuous density. A kernel density</li><li><a href="mh_optimal_bandwidth.html" class="code" title="function optimal_bandwidth = mh_optimal_bandwidth(data,n,bandwidth,kernel_function)">mh_optimal_bandwidth</a> % This function gives the optimal bandwidth parameter of a kernel estimator</li><li><a href="priordens.html" class="code" title="function lnprior = priordens(para, pshape, p1, p2, p3, p4)">priordens</a> This procedure computes a prior density for</li><li><a href="set_all_parameters.html" class="code" title="function set_all_parameters(xparam1)">set_all_parameters</a> </li><li><a href="smirnov.html" class="code" title="function [H,prob,d] = smirnov(x1 , x2 , alpha, iflag )">smirnov</a> Smirnov test for 2 distributions</li><li><a href="stab_map_2.html" class="code" title="function stab_map_2(x,alpha2,fnam, dirname)">stab_map_2</a> function stab_map_2(x,alpha2,istab,fnam)</li><li><a href="steady_.html" class="code" title="function steady_()">steady_</a> Copyright (C) 2001 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_sensitivity.html" class="code" title="function x0=dynare_sensitivity()">dynare_sensitivity</a> copyright Marco Ratto 2006</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 [rmse_MC, ixx] = filt_mc_(vvarvecm, loadSA, pfilt, alpha, alpha2, OutDir, istart, alphaPC)</a>
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0002 <span class="comment">% copyright Marco Ratto 2006</span>
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0003 <span class="keyword">global</span> bayestopt_ estim_params_ M_ options_ oo_
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0004
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0005 <span class="keyword">if</span> nargin<1 | isempty(vvarvecm),
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0006 vvarvecm = options_.varobs;
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0007 <span class="keyword">end</span>
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0008 <span class="keyword">if</span> nargin<2,
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0009 loadSA=0;
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0010 <span class="keyword">end</span>
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0011 <span class="keyword">if</span> nargin<3 | isempty(pfilt),
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0012 pfilt=0.1; <span class="comment">% cut the best 10% of runs</span>
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0013 <span class="keyword">end</span>
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0014 <span class="keyword">if</span> nargin<4 | isempty(alpha),
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0015 alpha=0.002;
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0016 <span class="keyword">end</span>
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0017 <span class="keyword">if</span> nargin<5 | isempty(alpha2),
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0018 alpha2=0.5;
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0019 <span class="keyword">end</span>
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0020 <span class="keyword">if</span> nargin<7 | isempty(istart),
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0021 istart=1;
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0022 <span class="keyword">end</span>
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0023 <span class="keyword">if</span> nargin<8,
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0024 alphaPC=0.5;
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0025 <span class="keyword">end</span>
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0026
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0027 fname_ = M_.fname;
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0028 lgy_ = M_.endo_names;
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0029 dr_ = oo_.dr;
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0030
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0031 disp(<span class="string">' '</span>)
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0032 disp(<span class="string">' '</span>)
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0033 disp(<span class="string">'Starting sensitivity analysis'</span>)
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0034 disp(<span class="string">'for the fit of EACH observed series ...'</span>)
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0035 disp(<span class="string">' '</span>)
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0036 disp(<span class="string">'Deleting old SA figures...'</span>)
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0037 a=dir([OutDir,<span class="string">'\*.*'</span>]);
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0038 <span class="keyword">if</span> options_.opt_gsa.ppost,
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0039 tmp=[<span class="string">'_SA_fit_post'</span>];
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0040 <span class="keyword">else</span>
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0041 <span class="keyword">if</span> options_.opt_gsa.pprior
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0042 tmp=[<span class="string">'_SA_fit_prior'</span>];
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0043 <span class="keyword">else</span>
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0044 tmp=[<span class="string">'_SA_fit_mc'</span>];
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0045 <span class="keyword">end</span>
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0046 <span class="keyword">end</span>
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0047 <span class="keyword">for</span> j=1:length(a),
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0048 <span class="keyword">if</span> strmatch([fname_,tmp],a(j).name),
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0049 disp(a(j).name)
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0050 delete([OutDir,<span class="string">'\'</span>,a(j).name])
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0051 <span class="keyword">end</span>,
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0052 <span class="keyword">end</span>
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0053 disp(<span class="string">'done !'</span>)
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0054
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0055
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0056 nshock=estim_params_.nvx + estim_params_.nvn + estim_params_.ncx + estim_params_.ncn;
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0057 npar=estim_params_.np;
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0058 <span class="keyword">for</span> j=1:npar+nshock,
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0059 <span class="keyword">if</span> j>nshock
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0060 <span class="keyword">if</span> isfield(oo_,<span class="string">'posterior_mode'</span>),
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0061 xparam1(j)=oo_.posterior_mode.parameters.(bayestopt_.name{j});
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0062 <span class="keyword">end</span>
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0063 <span class="keyword">if</span> isfield(oo_,<span class="string">'posterior_mean'</span>),
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0064 xparam1_mean(j)=oo_.posterior_mean.parameters.(bayestopt_.name{j});
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0065 <span class="keyword">end</span>
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0066 <span class="keyword">else</span>
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0067 <span class="keyword">if</span> isfield(oo_,<span class="string">'posterior_mode'</span>),
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0068 xparam1(j)=oo_.posterior_mode.shocks_std.(bayestopt_.name{j});
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0069 <span class="keyword">end</span>
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0070 <span class="keyword">if</span> isfield(oo_,<span class="string">'posterior_mean'</span>),
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0071 xparam1_mean(j)=oo_.posterior_mean.shocks_std.(bayestopt_.name{j});
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0072 <span class="keyword">end</span>
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0073 <span class="keyword">end</span>
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0074 <span class="keyword">end</span>
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0075
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0076 <span class="keyword">if</span> options_.opt_gsa.ppost,
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0077 fnamtmp=[fname_,<span class="string">'_post'</span>];
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0078 DirectoryName = <a href="CheckPath.html" class="code" title="function DirectoryName = CheckPath(type)">CheckPath</a>(<span class="string">'metropolis'</span>);
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0079 <span class="keyword">else</span>
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0080 <span class="keyword">if</span> options_.opt_gsa.pprior
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0081 fnamtmp=[fname_,<span class="string">'_prior'</span>];
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0082 <span class="keyword">else</span>
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0083 fnamtmp=[fname_,<span class="string">'_mc'</span>];
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0084 <span class="keyword">end</span>
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0085 <span class="keyword">end</span>
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0086 <span class="keyword">if</span> ~loadSA,
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0087 <span class="keyword">if</span> exist(<span class="string">'xparam1'</span>,<span class="string">'var'</span>)
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0088 <a href="set_all_parameters.html" class="code" title="function set_all_parameters(xparam1)">set_all_parameters</a>(xparam1);
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0089 <a href="steady_.html" class="code" title="function steady_()">steady_</a>;
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0090 ys_mode=oo_.steady_state;
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0091 <span class="keyword">end</span>
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0092 <span class="keyword">if</span> exist(<span class="string">'xparam1_mean'</span>,<span class="string">'var'</span>)
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0093 <a href="set_all_parameters.html" class="code" title="function set_all_parameters(xparam1)">set_all_parameters</a>(xparam1_mean);
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0094 <a href="steady_.html" class="code" title="function steady_()">steady_</a>;
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0095 ys_mean=oo_.steady_state;
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0096 <span class="keyword">end</span>
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0097 eval(options_.datafile)
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0098 <span class="keyword">if</span> ~options_.opt_gsa.ppost
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0099 load([OutDir,<span class="string">'\'</span>,fnamtmp]);
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0100 <span class="keyword">else</span>
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0101 load([DirectoryName <span class="string">'/'</span> M_.fname <span class="string">'_data.mat'</span>]);
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0102 filfilt = dir([DirectoryName <span class="string">'/'</span> M_.fname <span class="string">'_filter*.mat'</span>]);
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0103 filparam = dir([DirectoryName <span class="string">'/'</span> M_.fname <span class="string">'_param*.mat'</span>]);
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0104 x=[];
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0105 logpo2=[];
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0106 sto_ys=[];
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0107 <span class="keyword">for</span> j=1:length(filparam),
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0108 <span class="comment">%load([DirectoryName '/' M_.fname '_param',int2str(j),'.mat']);</span>
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0109 <span class="keyword">if</span> isempty(strmatch([M_.fname <span class="string">'_param_irf'</span>],filparam(j).name))
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0110 load([DirectoryName <span class="string">'/'</span> filparam(j).name]);
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0111 x=[x; stock];
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0112 logpo2=[logpo2; stock_logpo];
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0113 sto_ys=[sto_ys; stock_ys];
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0114 clear stock stock_logpo stock_ys;
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0115 <span class="keyword">end</span>
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0116 <span class="keyword">end</span>
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0117 logpo2=-logpo2;
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0118 <span class="keyword">end</span>
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0119 nruns=size(x,1);
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0120 nfilt=floor(pfilt*nruns);
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0121 disp(<span class="string">' '</span>)
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0122 disp(<span class="string">'Computing RMSE''s...'</span>)
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0123 fobs = options_.first_obs;
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0124 nobs=options_.nobs;
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0125 <span class="keyword">for</span> i=1:size(vvarvecm,1),
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0126 vj=deblank(vvarvecm(i,:));
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0127 <span class="keyword">if</span> options_.prefilter == 1
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0128 eval([vj,<span class="string">'='</span>,vj,<span class="string">'-bayestopt_.mean_varobs(i);'</span>])
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0129 <span class="keyword">end</span>
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0130
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0131 jxj = strmatch(vj,lgy_(dr_.order_var,:),<span class="string">'exact'</span>);
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0132 js = strmatch(vj,lgy_,<span class="string">'exact'</span>);
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0133 <span class="keyword">if</span> exist(<span class="string">'xparam1'</span>,<span class="string">'var'</span>)
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0134 eval([<span class="string">'rmse_mode(i) = sqrt(mean(('</span>,vj,<span class="string">'(fobs-1+istart:fobs-1+nobs)-oo_.steady_state(js)-oo_.FilteredVariables.'</span>,vj,<span class="string">'(istart:end-1)).^2));'</span>])
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0135 <span class="keyword">end</span>
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0136 y0=zeros(nobs+1,nruns);
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0137 <span class="keyword">if</span> options_.opt_gsa.ppost
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0138 nbb=0;
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0139 <span class="keyword">for</span> j=1:length(filfilt),
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0140 load([DirectoryName <span class="string">'/'</span> M_.fname <span class="string">'_filter'</span>,num2str(j),<span class="string">'.mat'</span>]);
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0141 nb = size(stock,4);
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0142 y0(:,nbb+1:nbb+nb)=squeeze(stock(1,jxj,:,:)); + <span class="keyword">...</span>
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0143 kron(sto_ys(nbb+1:nbb+nb,js)',ones(size(stock,3),1));
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0144 <span class="comment">%y0(:,:,size(y0,3):size(y0,3)+size(stock,3))=stock;</span>
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0145 nbb=nbb+nb;
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0146 clear stock;
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0147 <span class="keyword">end</span>
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0148 <span class="keyword">else</span>
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0149 y0 = squeeze(stock_filter(:,jxj,:)) + <span class="keyword">...</span>
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0150 kron(stock_ys(js,:),ones(size(stock_filter,1),1));
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0151 <span class="keyword">end</span>
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0152 y0M=mean(y0,2);
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0153 <span class="keyword">for</span> j=1:nruns,
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0154 eval([<span class="string">'rmse_MC(j,i) = sqrt(mean(('</span>,vj,<span class="string">'(fobs-1+istart:fobs-1+nobs)-y0(istart:end-1,j)).^2));'</span>])
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0155 <span class="keyword">end</span>
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0156 <span class="keyword">if</span> exist(<span class="string">'xparam1_mean'</span>,<span class="string">'var'</span>)
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0157 <span class="comment">%eval(['rmse_pmean(i) = sqrt(mean((',vj,'(fobs-1+istart:fobs-1+nobs)-y0M(istart:end-1)).^2));'])</span>
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0158 [alphahat,etahat,epsilonhat,ahat,SteadyState,trend_coeff,aK] = <a href="DsgeSmoother.html" class="code" title="function [alphahat,etahat,epsilonhat,ahat,SteadyState,trend_coeff,aK] = DsgeSmoother(xparam1,gend,Y)">DsgeSmoother</a>(xparam1_mean,stock_gend,stock_data);
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0159 y0 = ahat(jxj,:)' + <span class="keyword">...</span>
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0160 kron(ys_mean(js,:),ones(size(ahat,2),1));
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0161 eval([<span class="string">'rmse_pmean(i) = sqrt(mean(('</span>,vj,<span class="string">'(fobs-1+istart:fobs-1+nobs)-y0(istart:end-1)).^2));'</span>])
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0162 <span class="keyword">end</span>
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0163 <span class="keyword">end</span>
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0164 clear stock_filter;
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0165 <span class="keyword">for</span> j=1:nruns,
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0166 lnprior(j,1) = <a href="priordens.html" class="code" title="function lnprior = priordens(para, pshape, p1, p2, p3, p4)">priordens</a>(x(j,:),bayestopt_.pshape,bayestopt_.p1,bayestopt_.p2,bayestopt_.p3,bayestopt_.p4);
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0167 <span class="keyword">end</span>
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0168 likelihood=logpo2(:)+lnprior(:);
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0169 disp(<span class="string">'... done!'</span>)
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0170
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0171 <span class="keyword">if</span> options_.opt_gsa.ppost
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0172 save([OutDir,<span class="string">'\'</span>,fnamtmp], <span class="string">'x'</span>, <span class="string">'logpo2'</span>, <span class="string">'likelihood'</span>, <span class="string">'rmse_MC'</span>, <span class="string">'rmse_mode'</span>,<span class="string">'rmse_pmean'</span>)
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0173 <span class="keyword">else</span>
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0174 save([OutDir,<span class="string">'\'</span>,fnamtmp], <span class="string">'likelihood'</span>, <span class="string">'rmse_MC'</span>, <span class="string">'rmse_mode'</span>,<span class="string">'rmse_pmean'</span>,<span class="string">'-append'</span>)
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0175 <span class="keyword">end</span>
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0176 <span class="keyword">else</span>
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0177 load([OutDir,<span class="string">'\'</span>,fnamtmp],<span class="string">'x'</span>,<span class="string">'logpo2'</span>,<span class="string">'likelihood'</span>,<span class="string">'rmse_MC'</span>,<span class="string">'rmse_mode'</span>,<span class="string">'rmse_pmean'</span>);
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0178 lnprior=likelihood(:)-logpo2(:);
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0179 nruns=size(x,1);
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0180 nfilt=floor(pfilt*nruns);
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0181 <span class="keyword">end</span>
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0182 <span class="comment">% smirnov tests</span>
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0183 nfilt0=nfilt*ones(size(vvarvecm,1),1);
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0184 logpo2=logpo2(:);
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0185 <span class="keyword">if</span> ~options_.opt_gsa.ppost
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0186 [dum, ipost]=sort(logpo2);
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0187 <span class="keyword">end</span>
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0188 <span class="keyword">for</span> i=1:size(vvarvecm,1),
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0189 [dum, ixx(:,i)]=sort(rmse_MC(:,i));
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0190 <span class="keyword">if</span> options_.opt_gsa.ppost,
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0191 <span class="comment">%nfilt0(i)=length(find(rmse_MC(:,i)<rmse_pmean(i)));</span>
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0192 rmse_txt=rmse_pmean;
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0193 <span class="keyword">else</span>
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0194 <span class="keyword">if</span> options_.opt_gsa.pprior,
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0195 rmse_txt=rmse_mode;
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0196 <span class="keyword">else</span>
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0197 <span class="comment">%nfilt0(i)=length(find(rmse_MC(:,i)<rmse_pmean(i)));</span>
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0198 rmse_txt=rmse_pmean;
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0199 <span class="keyword">end</span>
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0200 <span class="keyword">end</span>
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0201 <span class="keyword">for</span> j=1:npar+nshock,
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0202 [H,P,KSSTAT] = <a href="smirnov.html" class="code" title="function [H,prob,d] = smirnov(x1 , x2 , alpha, iflag )">smirnov</a>(x(ixx(nfilt0(i)+1:<span class="keyword">end</span>,i),j),x(ixx(1:nfilt0(i),i),j), alpha);
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0203 [H1,P1,KSSTAT1] = <a href="smirnov.html" class="code" title="function [H,prob,d] = smirnov(x1 , x2 , alpha, iflag )">smirnov</a>(x(ixx(nfilt0(i)+1:<span class="keyword">end</span>,i),j),x(ixx(1:nfilt0(i),i),j),alpha,1);
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0204 [H2,P2,KSSTAT2] = <a href="smirnov.html" class="code" title="function [H,prob,d] = smirnov(x1 , x2 , alpha, iflag )">smirnov</a>(x(ixx(nfilt0(i)+1:<span class="keyword">end</span>,i),j),x(ixx(1:nfilt0(i),i),j),alpha,-1);
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0205 <span class="keyword">if</span> H1 & H2==0,
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0206 SS(j,i)=1;
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0207 <span class="keyword">elseif</span> H1==0,
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0208 SS(j,i)=-1;
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0209 <span class="keyword">else</span>
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0210 SS(j,i)=0;
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0211 <span class="keyword">end</span>
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0212 PP(j,i)=P;
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0213 <span class="keyword">end</span>
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0214 <span class="keyword">end</span>
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0215 figure(<span class="string">'name'</span>,<span class="string">'prior'</span>)
|
|
0216 <span class="keyword">for</span> i=1:size(vvarvecm,1),
|
|
0217 subplot(3,3,i)
|
|
0218 h=<a href="cumplot.html" class="code" title="function h = cumplot(x);">cumplot</a>(lnprior(ixx(1:nfilt0(i),i)));
|
|
0219 set(h,<span class="string">'color'</span>,<span class="string">'red'</span>)
|
|
0220 hold on, <a href="cumplot.html" class="code" title="function h = cumplot(x);">cumplot</a>(lnprior)
|
|
0221 h=<a href="cumplot.html" class="code" title="function h = cumplot(x);">cumplot</a>(lnprior(ixx(nfilt0(i)+1:<span class="keyword">end</span>,i)));
|
|
0222 set(h,<span class="string">'color'</span>,<span class="string">'green'</span>)
|
|
0223 title(vvarvecm(i,:))
|
|
0224 <span class="keyword">end</span>
|
|
0225 <span class="keyword">if</span> options_.opt_gsa.ppost
|
|
0226 saveas(gcf,[OutDir,<span class="string">'\'</span>,fname_,<span class="string">'_SA_fit_post_lnprior'</span>])
|
|
0227 eval([<span class="string">'print -depsc2 '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_post_lnprior'</span>]);
|
|
0228 eval([<span class="string">'print -dpdf '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_post_lnprior'</span>]);
|
|
0229 <span class="keyword">else</span>
|
|
0230 <span class="keyword">if</span> options_.opt_gsa.pprior
|
|
0231 saveas(gcf,[OutDir,<span class="string">'\'</span>,fname_,<span class="string">'_SA_fit_prior_lnprior'</span>])
|
|
0232 eval([<span class="string">'print -depsc2 '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_prior_lnprior'</span>]);
|
|
0233 eval([<span class="string">'print -dpdf '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_prior_lnprior'</span>]);
|
|
0234 <span class="keyword">else</span>
|
|
0235 saveas(gcf,[OutDir,<span class="string">'\'</span>,fname_,<span class="string">'_SA_fit_mc_lnprior'</span>])
|
|
0236 eval([<span class="string">'print -depsc2 '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_mc_lnprior'</span>]);
|
|
0237 eval([<span class="string">'print -dpdf '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_mc_lnprior'</span>]);
|
|
0238 <span class="keyword">end</span>
|
|
0239 <span class="keyword">end</span>
|
|
0240 close(gcf)
|
|
0241 figure(<span class="string">'name'</span>,<span class="string">'likelihood'</span>)
|
|
0242 <span class="keyword">for</span> i=1:size(vvarvecm,1),
|
|
0243 subplot(3,3,i)
|
|
0244 h=<a href="cumplot.html" class="code" title="function h = cumplot(x);">cumplot</a>(likelihood(ixx(1:nfilt0(i),i)));
|
|
0245 set(h,<span class="string">'color'</span>,<span class="string">'red'</span>)
|
|
0246 hold on, h=<a href="cumplot.html" class="code" title="function h = cumplot(x);">cumplot</a>(likelihood);
|
|
0247 h=<a href="cumplot.html" class="code" title="function h = cumplot(x);">cumplot</a>(likelihood(ixx(nfilt0(i)+1:<span class="keyword">end</span>,i)));
|
|
0248 set(h,<span class="string">'color'</span>,<span class="string">'green'</span>)
|
|
0249 title(vvarvecm(i,:))
|
|
0250 <span class="keyword">end</span>
|
|
0251 <span class="keyword">if</span> options_.opt_gsa.ppost
|
|
0252 saveas(gcf,[OutDir,<span class="string">'\'</span>,fname_,<span class="string">'_SA_fit_post_lnlik'</span>])
|
|
0253 eval([<span class="string">'print -depsc2 '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_post_lnlik'</span>]);
|
|
0254 eval([<span class="string">'print -dpdf '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_post_lnlik'</span>]);
|
|
0255 <span class="keyword">else</span>
|
|
0256 <span class="keyword">if</span> options_.opt_gsa.pprior
|
|
0257 saveas(gcf,[OutDir,<span class="string">'\'</span>,fname_,<span class="string">'_SA_fit_prior_lnlik'</span>])
|
|
0258 eval([<span class="string">'print -depsc2 '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_prior_lnlik'</span>]);
|
|
0259 eval([<span class="string">'print -dpdf '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_prior_lnlik'</span>]);
|
|
0260 <span class="keyword">else</span>
|
|
0261 saveas(gcf,[OutDir,<span class="string">'\'</span>,fname_,<span class="string">'_SA_fit_mc_lnlik'</span>])
|
|
0262 eval([<span class="string">'print -depsc2 '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_mc_lnlik'</span>]);
|
|
0263 eval([<span class="string">'print -dpdf '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_mc_lnlik'</span>]);
|
|
0264 <span class="keyword">end</span>
|
|
0265 <span class="keyword">end</span>
|
|
0266 close(gcf)
|
|
0267 figure(<span class="string">'name'</span>,<span class="string">'posterior'</span>)
|
|
0268 <span class="keyword">for</span> i=1:size(vvarvecm,1),
|
|
0269 subplot(3,3,i)
|
|
0270 h=<a href="cumplot.html" class="code" title="function h = cumplot(x);">cumplot</a>(logpo2(ixx(1:nfilt0(i),i)));
|
|
0271 set(h,<span class="string">'color'</span>,<span class="string">'red'</span>)
|
|
0272 hold on, h=<a href="cumplot.html" class="code" title="function h = cumplot(x);">cumplot</a>(logpo2);
|
|
0273 h=<a href="cumplot.html" class="code" title="function h = cumplot(x);">cumplot</a>(logpo2(ixx(nfilt0(i)+1:<span class="keyword">end</span>,i)));
|
|
0274 set(h,<span class="string">'color'</span>,<span class="string">'green'</span>)
|
|
0275 title(vvarvecm(i,:))
|
|
0276 <span class="keyword">end</span>
|
|
0277 <span class="keyword">if</span> options_.opt_gsa.ppost
|
|
0278 saveas(gcf,[OutDir,<span class="string">'\'</span>,fname_,<span class="string">'_SA_fit_post_lnpost'</span>])
|
|
0279 eval([<span class="string">'print -depsc2 '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_post_lnpost'</span>]);
|
|
0280 eval([<span class="string">'print -dpdf '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_post_lnpost'</span>]);
|
|
0281 <span class="keyword">else</span>
|
|
0282 <span class="keyword">if</span> options_.opt_gsa.pprior
|
|
0283 saveas(gcf,[OutDir,<span class="string">'\'</span>,fname_,<span class="string">'_SA_fit_prior_lnpost'</span>])
|
|
0284 eval([<span class="string">'print -depsc2 '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_prior_lnpost'</span>]);
|
|
0285 eval([<span class="string">'print -dpdf '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_prior_lnpost'</span>]);
|
|
0286 <span class="keyword">else</span>
|
|
0287 saveas(gcf,[OutDir,<span class="string">'\'</span>,fname_,<span class="string">'_SA_fit_mc_lnpost'</span>])
|
|
0288 eval([<span class="string">'print -depsc2 '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_mc_lnpost'</span>]);
|
|
0289 eval([<span class="string">'print -dpdf '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_mc_lnpost'</span>]);
|
|
0290 <span class="keyword">end</span>
|
|
0291 <span class="keyword">end</span>
|
|
0292 close(gcf)
|
|
0293
|
|
0294 param_names=<span class="string">''</span>;
|
|
0295 <span class="keyword">for</span> j=1:npar+nshock,
|
|
0296 param_names=str2mat(param_names, bayestopt_.name{j});
|
|
0297 <span class="keyword">end</span>
|
|
0298 param_names=param_names(2:<span class="keyword">end</span>,:);
|
|
0299
|
|
0300 disp(<span class="string">' '</span>)
|
|
0301 disp(<span class="string">'RMSE over the MC sample:'</span>)
|
|
0302 disp(<span class="string">' min yr RMSE max yr RMSE'</span>)
|
|
0303 <span class="keyword">for</span> j=1:size(vvarvecm,1),
|
|
0304 disp([vvarvecm(j,:), sprintf(<span class="string">'%15.5g'</span>,[(min(rmse_MC(:,j))) [(max(rmse_MC(:,j)))]])])
|
|
0305 <span class="keyword">end</span>
|
|
0306 invar = find( std(rmse_MC)./mean(rmse_MC)<=0.0001 );
|
|
0307 <span class="keyword">if</span> ~isempty(invar)
|
|
0308 disp(<span class="string">' '</span>)
|
|
0309 disp(<span class="string">' '</span>)
|
|
0310 disp(<span class="string">'RMSE is not varying significantly over the MC sample for the following variables:'</span>)
|
|
0311 disp(vvarvecm(invar,:))
|
|
0312 disp(<span class="string">'These variables are excluded from SA'</span>)
|
|
0313 disp(<span class="string">'[Unless you treat these series as exogenous, there is something wrong in your estimation !]'</span>)
|
|
0314 <span class="keyword">end</span>
|
|
0315 ivar = find( std(rmse_MC)./mean(rmse_MC)>0.0001 );
|
|
0316 vvarvecm=vvarvecm(ivar,:);
|
|
0317 rmse_MC=rmse_MC(:,ivar);
|
|
0318
|
|
0319 disp(<span class="string">' '</span>)
|
|
0320 <span class="keyword">if</span> options_.opt_gsa.ppost==0 & options_.opt_gsa.pprior,
|
|
0321 disp([<span class="string">'Sample filtered the '</span>,num2str(pfilt*100),<span class="string">'% best RMSE''s for each observed series ...'</span> ])
|
|
0322 <span class="keyword">else</span>
|
|
0323 disp([<span class="string">'Sample filtered the best RMSE''s smaller than RMSE at the posterior mean ...'</span> ])
|
|
0324 <span class="keyword">end</span>
|
|
0325 <span class="comment">% figure, boxplot(rmse_MC)</span>
|
|
0326 <span class="comment">% set(gca,'xticklabel',vvarvecm)</span>
|
|
0327 <span class="comment">% saveas(gcf,[fname_,'_SA_RMSE'])</span>
|
|
0328
|
|
0329 disp(<span class="string">' '</span>)
|
|
0330 disp(<span class="string">' '</span>)
|
|
0331 disp(<span class="string">'RMSE ranges after filtering:'</span>)
|
|
0332 <span class="keyword">if</span> options_.opt_gsa.ppost==0 & options_.opt_gsa.pprior,
|
|
0333 disp([<span class="string">' best '</span>,num2str(pfilt*100),<span class="string">'% filtered remaining 90%'</span>])
|
|
0334 disp([<span class="string">' min max min max posterior mode'</span>])
|
|
0335 <span class="keyword">else</span>
|
|
0336 disp([<span class="string">' best filtered remaining '</span>])
|
|
0337 disp([<span class="string">' min max min max posterior mean'</span>])
|
|
0338 <span class="keyword">end</span>
|
|
0339 <span class="keyword">for</span> j=1:size(vvarvecm,1),
|
|
0340 disp([vvarvecm(j,:), sprintf(<span class="string">'%15.5g'</span>,[min(rmse_MC(ixx(1:nfilt0(j),j),j)) <span class="keyword">...</span>
|
|
0341 max(rmse_MC(ixx(1:nfilt0(j),j),j)) <span class="keyword">...</span>
|
|
0342 min(rmse_MC(ixx(nfilt0(j)+1:<span class="keyword">end</span>,j),j)) <span class="keyword">...</span>
|
|
0343 max(rmse_MC(ixx(nfilt0(j)+1:<span class="keyword">end</span>,j),j)) <span class="keyword">...</span>
|
|
0344 rmse_txt(j)])])
|
|
0345 <span class="comment">% disp([vvarvecm(j,:), sprintf('%15.5g',[min(logpo2(ixx(1:nfilt,j))) ...</span>
|
|
0346 <span class="comment">% max(logpo2(ixx(1:nfilt,j))) ...</span>
|
|
0347 <span class="comment">% min(logpo2(ixx(nfilt+1:end,j))) ...</span>
|
|
0348 <span class="comment">% max(logpo2(ixx(nfilt+1:end,j)))])])</span>
|
|
0349 <span class="keyword">end</span>
|
|
0350
|
|
0351 <span class="comment">%stab_map_1(x, ipost(1:nfilt), ipost(nfilt+1:end), 'SA_post', 1);</span>
|
|
0352 <span class="comment">%stab_map_2(x(ipost(1:nfilt),:),alpha2,'SA_post', 1);</span>
|
|
0353 <span class="comment">% for i=1:size(vvarvecm,1),</span>
|
|
0354 <span class="comment">% aname=['SA_fit_ALL_',deblank(vvarvecm(i,:))];</span>
|
|
0355 <span class="comment">% stab_map_1(x, ixx(1:nfilt,i), ixx(nfilt+1:end,i), aname, 1);</span>
|
|
0356 <span class="comment">% close all</span>
|
|
0357 <span class="comment">% end</span>
|
|
0358
|
|
0359 SP=zeros(npar+nshock,size(vvarvecm,1));
|
|
0360 <span class="keyword">for</span> j=1:size(vvarvecm,1),
|
|
0361 ns=find(PP(:,j)<alpha);
|
|
0362 SP(ns,j)=ones(size(ns));
|
|
0363 SS(:,j)=SS(:,j).*SP(:,j);
|
|
0364 <span class="keyword">end</span>
|
|
0365
|
|
0366 <span class="keyword">for</span> j=1:npar+nshock, <span class="comment">%estim_params_.np,</span>
|
|
0367 nsp(j)=length(find(SP(j,:)));
|
|
0368 <span class="keyword">end</span>
|
|
0369 snam0=param_names(find(nsp==0),:);
|
|
0370 snam1=param_names(find(nsp==1),:);
|
|
0371 snam2=param_names(find(nsp>1),:);
|
|
0372 snam=param_names(find(nsp>0),:);
|
|
0373 <span class="comment">% snam0=bayestopt_.name(find(nsp==0));</span>
|
|
0374 <span class="comment">% snam1=bayestopt_.name(find(nsp==1));</span>
|
|
0375 <span class="comment">% snam2=bayestopt_.name(find(nsp>1));</span>
|
|
0376 <span class="comment">% snam=bayestopt_.name(find(nsp>0));</span>
|
|
0377 nsnam=(find(nsp>1));
|
|
0378
|
|
0379 disp(<span class="string">' '</span>)
|
|
0380 disp(<span class="string">' '</span>)
|
|
0381 disp(<span class="string">'These parameters do not affect significantly the fit of ANY observed series:'</span>)
|
|
0382 disp(snam0)
|
|
0383 disp(<span class="string">' '</span>)
|
|
0384 disp(<span class="string">'These parameters affect ONE single observed series:'</span>)
|
|
0385 disp(snam1)
|
|
0386 disp(<span class="string">' '</span>)
|
|
0387 disp(<span class="string">'These parameters affect MORE THAN ONE observed series: trade off exists!'</span>)
|
|
0388 disp(snam2)
|
|
0389
|
|
0390
|
|
0391 <span class="comment">%pnam=bayestopt_.name(end-estim_params_.np+1:end);</span>
|
|
0392 pnam=bayestopt_.name;
|
|
0393
|
|
0394 <span class="comment">% plot trade-offs</span>
|
|
0395 a00=jet(size(vvarvecm,1));
|
|
0396 <span class="keyword">for</span> ix=1:ceil(length(nsnam)/6),
|
|
0397 figure,
|
|
0398 <span class="keyword">for</span> j=1+6*(ix-1):min(size(snam2,1),6*ix),
|
|
0399 subplot(2,3,j-6*(ix-1))
|
|
0400 <span class="comment">%h0=cumplot(x(:,nsnam(j)+nshock));</span>
|
|
0401 h0=<a href="cumplot.html" class="code" title="function h = cumplot(x);">cumplot</a>(x(:,nsnam(j)));
|
|
0402 <span class="comment">%set(h0,'color',[1 1 1])</span>
|
|
0403 hold on,
|
|
0404 np=find(SP(nsnam(j),:));
|
|
0405 <span class="comment">%a0=jet(nsp(nsnam(j)));</span>
|
|
0406 a0=a00(np,:);
|
|
0407 <span class="keyword">for</span> i=1:nsp(nsnam(j)), <span class="comment">%size(vvarvecm,1),</span>
|
|
0408 <span class="comment">%h0=cumplot(x(ixx(1:nfilt,np(i)),nsnam(j)+nshock));</span>
|
|
0409 h0=<a href="cumplot.html" class="code" title="function h = cumplot(x);">cumplot</a>(x(ixx(1:nfilt0(np(i)),np(i)),nsnam(j)));
|
|
0410 set(h0,<span class="string">'color'</span>,a0(i,:))
|
|
0411 <span class="keyword">end</span>
|
|
0412 ydum=get(gca,<span class="string">'ylim'</span>);
|
|
0413 <span class="comment">%xdum=xparam1(nshock+nsnam(j));</span>
|
|
0414 xdum=xparam1(nsnam(j));
|
|
0415 h1=plot([xdum xdum],ydum);
|
|
0416 set(h1,<span class="string">'color'</span>,[0.85 0.85 0.85],<span class="string">'linewidth'</span>,2)
|
|
0417 h0=legend(str2mat(<span class="string">'base'</span>,vvarvecm(np,:)),0);
|
|
0418 set(h0,<span class="string">'fontsize'</span>,6)
|
|
0419 <span class="comment">%h0=legend({'base',vnam{np}}',0);</span>
|
|
0420 xlabel(<span class="string">''</span>)
|
|
0421 set(findobj(get(h0,<span class="string">'children'</span>),<span class="string">'type'</span>,<span class="string">'text'</span>),<span class="string">'interpreter'</span>,<span class="string">'none'</span>)
|
|
0422 title([pnam{nsnam(j)}],<span class="string">'interpreter'</span>,<span class="string">'none'</span>)
|
|
0423 <span class="keyword">if</span> options_.opt_gsa.ppost
|
|
0424 saveas(gcf,[OutDir,<span class="string">'\'</span>,fname_,<span class="string">'_SA_fit_post_'</span>,num2str(ix)])
|
|
0425 eval([<span class="string">'print -depsc2 '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_post_'</span> int2str(ix)]);
|
|
0426 eval([<span class="string">'print -dpdf '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_post_'</span> int2str(ix)]);
|
|
0427 <span class="keyword">else</span>
|
|
0428 <span class="keyword">if</span> options_.opt_gsa.pprior
|
|
0429 saveas(gcf,[OutDir,<span class="string">'\'</span>,fname_,<span class="string">'_SA_fit_prior_'</span>,num2str(ix)])
|
|
0430 eval([<span class="string">'print -depsc2 '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_prior_'</span> int2str(ix)]);
|
|
0431 eval([<span class="string">'print -dpdf '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_prior_'</span> int2str(ix)]);
|
|
0432 <span class="keyword">else</span>
|
|
0433 saveas(gcf,[OutDir,<span class="string">'\'</span>,fname_,<span class="string">'_SA_fit_mc_'</span>,num2str(ix)])
|
|
0434 eval([<span class="string">'print -depsc2 '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_mc_'</span> int2str(ix)]);
|
|
0435 eval([<span class="string">'print -dpdf '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_mc_'</span> int2str(ix)]);
|
|
0436 <span class="keyword">end</span>
|
|
0437 <span class="keyword">end</span>
|
|
0438 <span class="keyword">end</span>
|
|
0439 <span class="keyword">end</span>
|
|
0440 close all
|
|
0441
|
|
0442 <span class="keyword">for</span> j=1:size(SP,2),
|
|
0443 nsx(j)=length(find(SP(:,j)));
|
|
0444 <span class="keyword">end</span>
|
|
0445
|
|
0446 number_of_grid_points = 2^9; <span class="comment">% 2^9 = 512 !... Must be a power of two.</span>
|
|
0447 bandwidth = 0; <span class="comment">% Rule of thumb optimal bandwidth parameter.</span>
|
|
0448 kernel_function = <span class="string">'gaussian'</span>; <span class="comment">% Gaussian kernel for Fast Fourrier Transform approximaton.</span>
|
|
0449 <span class="comment">%kernel_function = 'uniform'; % Gaussian kernel for Fast Fourrier Transform approximaton.</span>
|
|
0450
|
|
0451 <span class="keyword">for</span> ix=1:ceil(length(nsnam)/6),
|
|
0452 figure,
|
|
0453 <span class="keyword">for</span> j=1+6*(ix-1):min(size(snam2,1),6*ix),
|
|
0454 subplot(2,3,j-6*(ix-1))
|
|
0455 optimal_bandwidth = <a href="mh_optimal_bandwidth.html" class="code" title="function optimal_bandwidth = mh_optimal_bandwidth(data,n,bandwidth,kernel_function)">mh_optimal_bandwidth</a>(x(:,nsnam(j)),size(x,1),bandwidth,kernel_function);
|
|
0456 [x1,f1] = <a href="kernel_density_estimate.html" class="code" title="function [abscissa,f] = kernel_density_estimate(data,number_of_grid_points,bandwidth,kernel_function)">kernel_density_estimate</a>(x(:,nsnam(j)),number_of_grid_points,<span class="keyword">...</span>
|
|
0457 optimal_bandwidth,kernel_function);
|
|
0458 h0 = plot(x1, f1);
|
|
0459 hold on,
|
|
0460 np=find(SP(nsnam(j),:));
|
|
0461 <span class="comment">%a0=jet(nsp(nsnam(j)));</span>
|
|
0462 a0=a00(np,:);
|
|
0463 <span class="keyword">for</span> i=1:nsp(nsnam(j)), <span class="comment">%size(vvarvecm,1),</span>
|
|
0464 optimal_bandwidth = <a href="mh_optimal_bandwidth.html" class="code" title="function optimal_bandwidth = mh_optimal_bandwidth(data,n,bandwidth,kernel_function)">mh_optimal_bandwidth</a>(x(ixx(1:nfilt0(np(i)),np(i)),nsnam(j)),nfilt,bandwidth,kernel_function);
|
|
0465 [x1,f1] = <a href="kernel_density_estimate.html" class="code" title="function [abscissa,f] = kernel_density_estimate(data,number_of_grid_points,bandwidth,kernel_function)">kernel_density_estimate</a>(x(ixx(1:nfilt0(np(i)),np(i)),nsnam(j)),number_of_grid_points,<span class="keyword">...</span>
|
|
0466 optimal_bandwidth,kernel_function);
|
|
0467 h0 = plot(x1, f1);
|
|
0468 set(h0,<span class="string">'color'</span>,a0(i,:))
|
|
0469 <span class="keyword">end</span>
|
|
0470 ydum=get(gca,<span class="string">'ylim'</span>);
|
|
0471 set(gca,<span class="string">'ylim'</span>,[0 ydum(2)]);
|
|
0472 <span class="comment">%xdum=xparam1(nshock+nsnam(j));</span>
|
|
0473 xdum=xparam1(nsnam(j));
|
|
0474 h1=plot([xdum xdum],[0 ydum(2)]);
|
|
0475 set(h1,<span class="string">'color'</span>,[0.85 0.85 0.85],<span class="string">'linewidth'</span>,2)
|
|
0476 h0=legend(str2mat(<span class="string">'base'</span>,vvarvecm(np,:)),0);
|
|
0477 set(h0,<span class="string">'fontsize'</span>,6)
|
|
0478 <span class="comment">%h0=legend({'base',vnam{np}}',0);</span>
|
|
0479 xlabel(<span class="string">''</span>)
|
|
0480 set(findobj(get(h0,<span class="string">'children'</span>),<span class="string">'type'</span>,<span class="string">'text'</span>),<span class="string">'interpreter'</span>,<span class="string">'none'</span>)
|
|
0481 title([pnam{nsnam(j)}],<span class="string">'interpreter'</span>,<span class="string">'none'</span>)
|
|
0482 <span class="keyword">if</span> options_.opt_gsa.ppost
|
|
0483 saveas(gcf,[OutDir,<span class="string">'\'</span>,fname_,<span class="string">'_SA_fit_post_dens_'</span>,num2str(ix)])
|
|
0484 eval([<span class="string">'print -depsc2 '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_post_dens_'</span> int2str(ix)]);
|
|
0485 eval([<span class="string">'print -dpdf '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_post_dens_'</span> int2str(ix)]);
|
|
0486 <span class="keyword">else</span>
|
|
0487 <span class="keyword">if</span> options_.opt_gsa.pprior
|
|
0488 saveas(gcf,[OutDir,<span class="string">'\'</span>,fname_,<span class="string">'_SA_fit_prior_dens_'</span>,num2str(ix)])
|
|
0489 eval([<span class="string">'print -depsc2 '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_prior_dens_'</span> int2str(ix)]);
|
|
0490 eval([<span class="string">'print -dpdf '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_prior_dens_'</span> int2str(ix)]);
|
|
0491 <span class="keyword">else</span>
|
|
0492 saveas(gcf,[OutDir,<span class="string">'\'</span>,fname_,<span class="string">'_SA_fit_mc_dens_'</span>,num2str(ix)])
|
|
0493 eval([<span class="string">'print -depsc2 '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_mc_dens_'</span> int2str(ix)]);
|
|
0494 eval([<span class="string">'print -dpdf '</span> OutDir <span class="string">'\'</span> fname_ <span class="string">'_SA_fit_mc_dens_'</span> int2str(ix)]);
|
|
0495 <span class="keyword">end</span>
|
|
0496 <span class="keyword">end</span>
|
|
0497 <span class="keyword">end</span>
|
|
0498 <span class="keyword">end</span>
|
|
0499 close all
|
|
0500
|
|
0501 <span class="comment">% for j=1:size(SP,2),</span>
|
|
0502 <span class="comment">% nfig=0;</span>
|
|
0503 <span class="comment">% np=find(SP(:,j));</span>
|
|
0504 <span class="comment">% for i=1:nsx(j), %size(vvarvecm,1),</span>
|
|
0505 <span class="comment">% if mod(i,12)==1,</span>
|
|
0506 <span class="comment">% nfig=nfig+1;</span>
|
|
0507 <span class="comment">% %figure('name',['Sensitivity of fit of ',vnam{j}]),</span>
|
|
0508 <span class="comment">% figure('name',['Sensitivity of fit of ',deblank(vvarvecm(j,:)),' ',num2str(nfig)]),</span>
|
|
0509 <span class="comment">% end</span>
|
|
0510 <span class="comment">%</span>
|
|
0511 <span class="comment">% subplot(3,4,i-12*(nfig-1))</span>
|
|
0512 <span class="comment">% optimal_bandwidth = mh_optimal_bandwidth(x(ixx(1:nfilt,j),np(i)),nfilt,bandwidth,kernel_function);</span>
|
|
0513 <span class="comment">% [x1,f1] = kernel_density_estimate(x(ixx(1:nfilt,j),np(i)),number_of_grid_points,...</span>
|
|
0514 <span class="comment">% optimal_bandwidth,kernel_function);</span>
|
|
0515 <span class="comment">% plot(x1, f1,':k','linewidth',2)</span>
|
|
0516 <span class="comment">% optimal_bandwidth = mh_optimal_bandwidth(x(ixx(nfilt+1:end,j),np(i)),nruns-nfilt,bandwidth,kernel_function);</span>
|
|
0517 <span class="comment">% [x1,f1] = kernel_density_estimate(x(ixx(nfilt+1:end,j),np(i)),number_of_grid_points,...</span>
|
|
0518 <span class="comment">% optimal_bandwidth,kernel_function);</span>
|
|
0519 <span class="comment">% hold on, plot(x1, f1,'k','linewidth',2)</span>
|
|
0520 <span class="comment">% ydum=get(gca,'ylim');</span>
|
|
0521 <span class="comment">% %xdum=xparam1(nshock+np(i));</span>
|
|
0522 <span class="comment">% xdum=xparam1(np(i));</span>
|
|
0523 <span class="comment">% h1=plot([xdum xdum],ydum);</span>
|
|
0524 <span class="comment">% set(h1,'color',[0.85 0.85 0.85],'linewidth',2)</span>
|
|
0525 <span class="comment">% %xdum1=mean(x(ixx(1:nfilt,j),np(i)+nshock));</span>
|
|
0526 <span class="comment">% xdum1=mean(x(ixx(1:nfilt,j),np(i)));</span>
|
|
0527 <span class="comment">% h2=plot([xdum1 xdum1],ydum);</span>
|
|
0528 <span class="comment">% set(h2,'color',[0 1 0],'linewidth',2)</span>
|
|
0529 <span class="comment">% % h0=cumplot(x(nfilt+1:end,np(i)+nshock));</span>
|
|
0530 <span class="comment">% % set(h0,'color',[1 1 1])</span>
|
|
0531 <span class="comment">% % hold on,</span>
|
|
0532 <span class="comment">% % h0=cumplot(x(ixx(1:nfilt,j),np(i)+nshock));</span>
|
|
0533 <span class="comment">% % set(h0,'linestyle',':','color',[1 1 1])</span>
|
|
0534 <span class="comment">% %title([pnam{np(i)}])</span>
|
|
0535 <span class="comment">% title([pnam{np(i)},'. K-S prob ', num2str(PP(np(i),j))],'interpreter','none')</span>
|
|
0536 <span class="comment">% xlabel('')</span>
|
|
0537 <span class="comment">% if mod(i,12)==0 | i==nsx(j),</span>
|
|
0538 <span class="comment">% saveas(gcf,[fname_,'_SA_fit_',deblank(vvarvecm(j,:)),'_',int2str(nfig)])</span>
|
|
0539 <span class="comment">% close(gcf)</span>
|
|
0540 <span class="comment">% end</span>
|
|
0541 <span class="comment">% end</span>
|
|
0542 <span class="comment">% end</span>
|
|
0543
|
|
0544
|
|
0545 disp(<span class="string">' '</span>)
|
|
0546 disp(<span class="string">' '</span>)
|
|
0547 disp(<span class="string">'Sensitivity table (significance and direction):'</span>)
|
|
0548 vav=char(zeros(1, size(param_names,2)+3 ));
|
|
0549 ibl = 12-size(vvarvecm,2);
|
|
0550 <span class="keyword">for</span> j=1:size(vvarvecm,1),
|
|
0551 vav = [vav, char(zeros(1,ibl)),vvarvecm(j,:)];
|
|
0552 <span class="keyword">end</span>
|
|
0553 disp(vav)
|
|
0554 <span class="keyword">for</span> j=1:npar+nshock, <span class="comment">%estim_params_.np,</span>
|
|
0555 <span class="comment">%disp([param_names(j,:), sprintf('%8.5g',SP(j,:))])</span>
|
|
0556 disp([param_names(j,:),<span class="string">' '</span>, sprintf(<span class="string">'%12.3g'</span>,PP(j,:))])
|
|
0557 disp([char(zeros(1, size(param_names,2)+3 )),sprintf(<span class="string">' (%6g)'</span>,SS(j,:))])
|
|
0558 <span class="keyword">end</span>
|
|
0559
|
|
0560
|
|
0561 disp(<span class="string">' '</span>)
|
|
0562 disp(<span class="string">' '</span>)
|
|
0563 disp(<span class="string">'Starting bivariate analysis:'</span>)
|
|
0564
|
|
0565 <span class="keyword">for</span> i=1:size(vvarvecm,1)
|
|
0566 <span class="keyword">if</span> options_.opt_gsa.ppost
|
|
0567 fnam = [<span class="string">'SA_fit_post_'</span>,deblank(vvarvecm(i,:))];
|
|
0568 <span class="keyword">else</span>
|
|
0569 <span class="keyword">if</span> options_.opt_gsa.pprior
|
|
0570 fnam = [<span class="string">'SA_fit_prior_'</span>,deblank(vvarvecm(i,:))];
|
|
0571 <span class="keyword">else</span>
|
|
0572 fnam = [<span class="string">'SA_fit_mc_'</span>,deblank(vvarvecm(i,:))];
|
|
0573 <span class="keyword">end</span>
|
|
0574 <span class="keyword">end</span>
|
|
0575 <a href="stab_map_2.html" class="code" title="function stab_map_2(x,alpha2,fnam, dirname)">stab_map_2</a>(x(ixx(1:nfilt0(i),i),:),alpha2,fnam, OutDir);
|
|
0576
|
|
0577 <span class="comment">% [pc,latent,explained] = pcacov(c0);</span>
|
|
0578 <span class="comment">% %figure, bar([explained cumsum(explained)])</span>
|
|
0579 <span class="comment">% ifig=0;</span>
|
|
0580 <span class="comment">% j2=0;</span>
|
|
0581 <span class="comment">% for j=1:npar+nshock,</span>
|
|
0582 <span class="comment">% i2=find(abs(pc(:,j))>alphaPC);</span>
|
|
0583 <span class="comment">% if ~isempty(i2),</span>
|
|
0584 <span class="comment">% j2=j2+1;</span>
|
|
0585 <span class="comment">% if mod(j2,12)==1,</span>
|
|
0586 <span class="comment">% ifig=ifig+1;</span>
|
|
0587 <span class="comment">% figure('name',['PCA of the filtered sample ',deblank(vvarvecm(i,:)),' ',num2str(ifig)]),</span>
|
|
0588 <span class="comment">% end</span>
|
|
0589 <span class="comment">% subplot(3,4,j2-(ifig-1)*12)</span>
|
|
0590 <span class="comment">% bar(pc(i2,j)),</span>
|
|
0591 <span class="comment">% set(gca,'xticklabel',bayestopt_.name(i2)),</span>
|
|
0592 <span class="comment">% set(gca,'xtick',[1:length(i2)])</span>
|
|
0593 <span class="comment">% title(['PC ',num2str(j),'. Explained ',num2str(explained(j)),'%'])</span>
|
|
0594 <span class="comment">% end</span>
|
|
0595 <span class="comment">% if (mod(j2,12)==0 | j==(npar+nshock)) & j2,</span>
|
|
0596 <span class="comment">% saveas(gcf,[fname_,'_SA_PCA_',deblank(vvarvecm(i,:)),'_',int2str(ifig)])</span>
|
|
0597 <span class="comment">% end</span>
|
|
0598 <span class="comment">% end</span>
|
|
0599 <span class="comment">% close all</span>
|
|
0600 <span class="keyword">end</span>
|
|
0601</pre></div>
|
|
<hr><address>Generated on Fri 16-Jun-2006 09:09:06 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/">m2html</a></strong> © 2003</address>
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