120 lines
7.9 KiB
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120 lines
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<div><a href="../index.html">Home</a> > <a href="index.html">.</a> > stab_map_marginal.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>stab_map_marginal
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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>function stab_map_1(lpmat, ibehaviour, inonbehaviour, aname, ipar, dirname)</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 stab_map_marginal(lpmat, ibehaviour, inonbehaviour, aname, ipar, dirname) </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">function stab_map_1(lpmat, ibehaviour, inonbehaviour, aname, ipar, dirname)
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lpmat = Monte Carlo matrix
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ibehaviour = index of behavioural runs
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inonbehaviour = index of non-behavioural runs
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aname = label of the analysis
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ipar = index array of parameters to plot
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dirname = (OPTIONAL) path of the directory where to save
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(default: current directory)
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Plots: dotted lines for BEHAVIOURAL
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solid lines for NON BEHAVIOURAL
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USES smirnov</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="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></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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</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 stab_map_marginal(lpmat, ibehaviour, inonbehaviour, aname, ipar, dirname)</a>
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0002 <span class="comment">%function stab_map_1(lpmat, ibehaviour, inonbehaviour, aname, ipar, dirname)</span>
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0003 <span class="comment">%</span>
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0004 <span class="comment">% lpmat = Monte Carlo matrix</span>
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0005 <span class="comment">% ibehaviour = index of behavioural runs</span>
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0006 <span class="comment">% inonbehaviour = index of non-behavioural runs</span>
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0007 <span class="comment">% aname = label of the analysis</span>
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0008 <span class="comment">% ipar = index array of parameters to plot</span>
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0009 <span class="comment">% dirname = (OPTIONAL) path of the directory where to save</span>
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0010 <span class="comment">% (default: current directory)</span>
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0011 <span class="comment">%</span>
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0012 <span class="comment">% Plots: dotted lines for BEHAVIOURAL</span>
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0013 <span class="comment">% solid lines for NON BEHAVIOURAL</span>
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0014 <span class="comment">% USES smirnov</span>
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0015
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0016 <span class="keyword">global</span> estim_params_ bayestopt_ M_ options_
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0017
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0018 fname_ = M_.fname;
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0019 <span class="keyword">if</span> nargin<5,
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0020 ipar=[1:npar];
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0021 <span class="keyword">end</span>
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0022 nparplot=length(ipar);
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0023 <span class="keyword">if</span> nargin<6,
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0024 dirname=<span class="string">''</span>;;
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0025 <span class="keyword">end</span>
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0026
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0027 nshock = estim_params_.nvx;
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0028 nshock = nshock + estim_params_.nvn;
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0029 nshock = nshock + estim_params_.ncx;
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0030 nshock = nshock + estim_params_.ncn;
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0031
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0032 npar=size(lpmat,2);
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0033 ishock= npar>estim_params_.np;
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0034
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0035 number_of_grid_points = 2^9; <span class="comment">% 2^9 = 512 !... Must be a power of two.</span>
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0036 bandwidth = 0; <span class="comment">% Rule of thumb optimal bandwidth parameter.</span>
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0037 kernel_function = <span class="string">'gaussian'</span>; <span class="comment">% Gaussian kernel for Fast Fourrier Transform approximaton.</span>
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0038 <span class="comment">%kernel_function = 'uniform'; % Gaussian kernel for Fast Fourrier Transform approximaton.</span>
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0039
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0040 lpmat=lpmat(:,ipar);
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0041 ftit=bayestopt_.name(ipar+nshock*(1-ishock));
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0042
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0043 <span class="keyword">for</span> i=1:ceil(npar/12),
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0044 figure(<span class="string">'name'</span>,aname),
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0045 <span class="keyword">for</span> j=1+12*(i-1):min(npar,12*i),
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0046 subplot(3,4,j-12*(i-1))
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0047 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>(lpmat(ibehaviour,j),length(ibehaviour),bandwidth,kernel_function);
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0048 [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>(lpmat(ibehaviour,j),number_of_grid_points,<span class="keyword">...</span>
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0049 optimal_bandwidth,kernel_function);
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0050 plot(x1, f1,<span class="string">':k'</span>,<span class="string">'linewidth'</span>,2)
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0051 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>(lpmat(inonbehaviour,j),length(inonbehaviour),bandwidth,kernel_function);
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0052 [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>(lpmat(inonbehaviour,j),number_of_grid_points,<span class="keyword">...</span>
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0053 optimal_bandwidth,kernel_function);
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0054 hold on, plot(x1, f1,<span class="string">'k'</span>,<span class="string">'linewidth'</span>,2)
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0055
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0056 title(ftit{j},<span class="string">'interpreter'</span>,<span class="string">'none'</span>)
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0057 <span class="keyword">end</span>
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0058 saveas(gcf,[dirname,<span class="string">'/'</span>,fname_,<span class="string">'_'</span>,aname,<span class="string">'_'</span>,int2str(i)])
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0059 eval([<span class="string">'print -depsc2 '</span> dirname <span class="string">'\'</span> fname_ <span class="string">'_'</span> aname <span class="string">'_'</span> int2str(i)]);
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0060 eval([<span class="string">'print -dpdf '</span> dirname <span class="string">'\'</span> fname_ <span class="string">'_'</span> aname <span class="string">'_'</span> int2str(i)]);
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0061 <span class="keyword">if</span> options_.nograph, close(gcf), <span class="keyword">end</span>
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0062 <span class="keyword">end</span></pre></div>
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<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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