90 lines
5.6 KiB
HTML
90 lines
5.6 KiB
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<title>Description of posterior_moments</title>
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<div><a href="../index.html">Home</a> > <a href="index.html">.</a> > posterior_moments.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>posterior_moments
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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>stephane.adjemian@ens.fr [09-09-2005]</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 [post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(xx,info) </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"> stephane.adjemian@ens.fr [09-09-2005]
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Computes posterior mean, median, variance, HPD interval, deciles, and density from posterior draws.</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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<li><a href="GetPosteriorParametersStatistics.html" class="code" title="function GetPosteriorParametersStatistics()">GetPosteriorParametersStatistics</a> stephane.adjemian@ens.fr [09-09-2005]</li><li><a href="PosteriorIRF.html" class="code" title="function PosteriorIRF(type)">PosteriorIRF</a> stephane.adjemian@ens.fr [09-25-2005]</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 [post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(xx,info)</a>
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0002 <span class="comment">% stephane.adjemian@ens.fr [09-09-2005]</span>
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0003 <span class="comment">% Computes posterior mean, median, variance, HPD interval, deciles, and density from posterior draws.</span>
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0004 <span class="keyword">global</span> options_
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0005
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0006 xx = xx(:);
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0007 xx = sort(xx);
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0008
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0009
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0010 post_mean = mean(xx);
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0011 post_median = median(xx);
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0012 post_var = var(xx);
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0013
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0014 n = length(xx);
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0015 m = round((1-options_.mh_conf_sig)*n);
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0016 k = zeros(m,1);
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0017 jj = n-m;
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0018 <span class="keyword">for</span> ii = 1:m
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0019 k(ii) = xx(jj)-xx(ii);
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0020 jj = jj + 1;
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0021 <span class="keyword">end</span>
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0022 [kmin,idx] = min(k);
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0023 hpd_interval = [xx(idx) xx(idx)+kmin];
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0024
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0025 post_deciles = xx([round(0.1*n) <span class="keyword">...</span>
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0026 round(0.2*n)<span class="keyword">...</span>
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0027 round(0.3*n)<span class="keyword">...</span>
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0028 round(0.4*n)<span class="keyword">...</span>
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0029 round(0.5*n)<span class="keyword">...</span>
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0030 round(0.6*n)<span class="keyword">...</span>
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0031 round(0.7*n)<span class="keyword">...</span>
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0032 round(0.8*n)<span class="keyword">...</span>
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0033 round(0.9*n)]);
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0034
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0035 <span class="keyword">if</span> ~info
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0036 density = [];
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0037 <span class="keyword">else</span>
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0038 number_of_grid_points = 2^9; <span class="comment">% 2^9 = 512 !... Must be a power of two.</span>
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0039 bandwidth = 0; <span class="comment">% Rule of thumb optimal bandwidth parameter.</span>
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0040 kernel_function = <span class="string">'gaussian'</span>; <span class="comment">% Gaussian kernel for Fast Fourrier Transform approximaton.</span>
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0041 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>(xx,length(xx),bandwidth,kernel_function);
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0042 [density(:,1),density(:,2)] = <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>(xx,number_of_grid_points,optimal_bandwidth,kernel_function);
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0043 <span class="keyword">end</span></pre></div>
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