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<title>Description of kalman_filter</title>
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<h1>kalman_filter
&nbsp;&nbsp;<img src="../{MEXTYPE}.png" alt="Linux x86" border="0" title="Linux x86"></h1>
<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
<div class="box"><strong>SYNOPSIS</strong></div>
<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
<div class="box"><strong>function [loglik, per, d] = kalman_filter(varargin) </strong></div>
<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
<div class="fragment"><pre class="comment">
SYNOPSIS
[loglik,per,d] = kalman_filter(Z,H,T,R,Q,Y,a,P)
[loglik,per,d] = kalman_filter(Z,H,T,R,Q,Y,a,P,flag)
[loglik,per,d] = kalman_filter(Z,H,T,R,Q,Y,a,Pstar,Pinf)
[loglik,per,d] = kalman_filter(Z,H,T,R,Q,Y,a,Pstar,Pinf,flag)
SEMANTICS
The first two commands run a Kalman filter for non-diffuse
initial conditions, the other two for diffuse initial conditions.
Input:
Z,H,T,R,Q gives a state space form
Y observed data (columns correspond to periods)
a mean of initial state
P covariance of initial non-diffuse state
Pstar finite part of covariance of initial diffuse state
Pinf infinite part of covariance of initial diffuse state
flag string starting with 'u', or 'U' runs a univariate
form of the filter; if omitted, a multivariate version
is run by default
Output:
loglik data log likelihood
per number of succesfully filtered periods; if no error
then per equals to the number of columns of Y
d number of initial periods for which the state is
still diffuse (d is always 0 for non-diffuse case)
Copyright 2005, Ondra Kamenik</pre></div>
<!-- crossreference -->
<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
This function calls:
<ul style="list-style-image:url(../matlabicon.gif)">
</ul>
This function is called by:
<ul style="list-style-image:url(../matlabicon.gif)">
<li><a href="DsgeLikelihood.html" class="code" title="function [fval,cost_flag,ys,trend_coeff,info] = DsgeLikelihood(xparam1,gend,data)">DsgeLikelihood</a> stephane.adjemian@cepremap.cnrs.fr [09-07-2004]</li></ul>
<!-- crossreference -->
<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
<div class="fragment"><pre>0001 <span class="comment">%</span>
0002 <span class="comment">% SYNOPSIS</span>
0003 <span class="comment">%</span>
0004 <span class="comment">% [loglik,per,d] = kalman_filter(Z,H,T,R,Q,Y,a,P)</span>
0005 <span class="comment">% [loglik,per,d] = kalman_filter(Z,H,T,R,Q,Y,a,P,flag)</span>
0006 <span class="comment">% [loglik,per,d] = kalman_filter(Z,H,T,R,Q,Y,a,Pstar,Pinf)</span>
0007 <span class="comment">% [loglik,per,d] = kalman_filter(Z,H,T,R,Q,Y,a,Pstar,Pinf,flag)</span>
0008 <span class="comment">%</span>
0009 <span class="comment">% SEMANTICS</span>
0010 <span class="comment">%</span>
0011 <span class="comment">% The first two commands run a Kalman filter for non-diffuse</span>
0012 <span class="comment">% initial conditions, the other two for diffuse initial conditions.</span>
0013 <span class="comment">%</span>
0014 <span class="comment">% Input:</span>
0015 <span class="comment">% Z,H,T,R,Q gives a state space form</span>
0016 <span class="comment">% Y observed data (columns correspond to periods)</span>
0017 <span class="comment">% a mean of initial state</span>
0018 <span class="comment">% P covariance of initial non-diffuse state</span>
0019 <span class="comment">% Pstar finite part of covariance of initial diffuse state</span>
0020 <span class="comment">% Pinf infinite part of covariance of initial diffuse state</span>
0021 <span class="comment">% flag string starting with 'u', or 'U' runs a univariate</span>
0022 <span class="comment">% form of the filter; if omitted, a multivariate version</span>
0023 <span class="comment">% is run by default</span>
0024 <span class="comment">%</span>
0025 <span class="comment">% Output:</span>
0026 <span class="comment">% loglik data log likelihood</span>
0027 <span class="comment">% per number of succesfully filtered periods; if no error</span>
0028 <span class="comment">% then per equals to the number of columns of Y</span>
0029 <span class="comment">% d number of initial periods for which the state is</span>
0030 <span class="comment">% still diffuse (d is always 0 for non-diffuse case)</span>
0031 <span class="comment">%</span>
0032 <span class="comment">% Copyright 2005, Ondra Kamenik</span>
0033 <span class="comment">%</span>
0034
0035 <a name="_sub0" href="#_subfunctions" class="code">function [loglik, per, d] = kalman_filter(varargin)</a>
0036
0037 [loglik, per, d] = kalman_filter_(varargin{:});</pre></div>
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