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<meta property="og:description" content="This function returns the product of the likelihood densities of each
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dnorm, i.e. assuming normal distribution, and with the means
predicted by the degradation model, and the standard deviations predicted by
the error model." />
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<h1>Calculated the log-likelihood of a fitted mkinfit object</h1>
<small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/logLik.mkinfit.R'><code>R/logLik.mkinfit.R</code></a></small>
<div class="hidden name"><code>logLik.mkinfit.Rd</code></div>
</div>
<div class="ref-description">
<p>This function returns the product of the likelihood densities of each
observed value, as calculated as part of the fitting procedure using
<code><a href='https://rdrr.io/r/stats/Normal.html'>dnorm</a></code>, i.e. assuming normal distribution, and with the means
predicted by the degradation model, and the standard deviations predicted by
the error model.</p>
</div>
<pre class="usage"><span class='co'># S3 method for mkinfit</span>
<span class='fu'><a href='https://rdrr.io/r/stats/logLik.html'>logLik</a></span><span class='op'>(</span><span class='va'>object</span>, <span class='va'>...</span><span class='op'>)</span></pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>object</th>
<td><p>An object of class <code><a href='mkinfit.html'>mkinfit</a></code>.</p></td>
</tr>
<tr>
<th>...</th>
<td><p>For compatibility with the generic method</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>An object of class <code><a href='https://rdrr.io/r/stats/logLik.html'>logLik</a></code> with the number of estimated
parameters (degradation model parameters plus variance model parameters)
as attribute.</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>The total number of estimated parameters returned with the value of the
likelihood is calculated as the sum of fitted degradation model parameters
and the fitted error model parameters.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p>Compare the AIC of columns of <code><a href='mmkin.html'>mmkin</a></code> objects using
<code><a href='AIC.mmkin.html'>AIC.mmkin</a></code>.</p></div>
<h2 class="hasAnchor" id="author"><a class="anchor" href="#author"></a>Author</h2>
<p>Johannes Ranke</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'>
<span class='co'># \dontrun{</span>
<span class='va'>sfo_sfo</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>
parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, to <span class='op'>=</span> <span class='st'>"m1"</span><span class='op'>)</span>,
m1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span>
<span class='op'>)</span>
</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'> <span class='va'>d_t</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>FOCUS_2006_D</span>, <span class='va'>value</span> <span class='op'>!=</span> <span class='fl'>0</span><span class='op'>)</span>
<span class='va'>f_nw</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>sfo_sfo</span>, <span class='va'>d_t</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> <span class='co'># no weighting (weights are unity)</span>
<span class='va'>f_obs</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span><span class='op'>(</span><span class='va'>f_nw</span>, error_model <span class='op'>=</span> <span class='st'>"obs"</span><span class='op'>)</span>
<span class='va'>f_tc</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span><span class='op'>(</span><span class='va'>f_nw</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span>
<span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span><span class='va'>f_nw</span>, <span class='va'>f_obs</span>, <span class='va'>f_tc</span><span class='op'>)</span>
</div><div class='output co'>#> df AIC
#> f_nw 5 204.4486
#> f_obs 6 205.8727
#> f_tc 6 141.9656</div><div class='input'> <span class='co'># }</span>
</div></pre>
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