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mkinfit objects are given as arguments, it is checked if they have been
fitted to the same data. It is the responsibility of the user to make sure
that the models are nested, i.e. one of them has less degrees of freedom
and can be expressed by fixing the parameters of the other." />


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    <h1>Likelihood ratio test for mkinfit models</h1>
    <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/lrtest.mkinfit.R'><code>R/lrtest.mkinfit.R</code></a></small>
    <div class="hidden name"><code>lrtest.mkinfit.Rd</code></div>
    </div>

    <div class="ref-description">
    <p>Compare two mkinfit models based on their likelihood. If two fitted
mkinfit objects are given as arguments, it is checked if they have been
fitted to the same data. It is the responsibility of the user to make sure
that the models are nested, i.e. one of them has less degrees of freedom
and can be expressed by fixing the parameters of the other.</p>
    </div>

    <pre class="usage"><span class='co'># S3 method for mkinfit</span>
<span class='fu'><a href='https://rdrr.io/pkg/lmtest/man/lrtest.html'>lrtest</a></span><span class='op'>(</span><span class='va'>object</span>, object_2 <span class='op'>=</span> <span class='cn'>NULL</span>, <span class='va'>...</span><span class='op'>)</span>

<span class='co'># S3 method for mmkin</span>
<span class='fu'><a href='https://rdrr.io/pkg/lmtest/man/lrtest.html'>lrtest</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 <code><a href='mkinfit.html'>mkinfit</a></code> object, or an <code><a href='mmkin.html'>mmkin</a></code> column
object containing two fits to the same data.</p></td>
    </tr>
    <tr>
      <th>object_2</th>
      <td><p>Optionally, another mkinfit object fitted to the same data.</p></td>
    </tr>
    <tr>
      <th>...</th>
      <td><p>Argument to <code><a href='mkinfit.html'>mkinfit</a></code>, passed to
<code><a href='update.mkinfit.html'>update.mkinfit</a></code> for creating the alternative fitted object.</p></td>
    </tr>
    </table>

    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>

    <p>Alternatively, an argument to mkinfit can be given which is then passed
to <code><a href='update.mkinfit.html'>update.mkinfit</a></code> to obtain the alternative model.</p>
<p>The comparison is then made by the <code><a href='https://rdrr.io/pkg/lmtest/man/lrtest.html'>lrtest.default</a></code>
method from the lmtest package. The model with the higher number of fitted
parameters (alternative hypothesis) is listed first, then the model with the
lower number of fitted parameters (null hypothesis).</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'>test_data</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>synthetic_data_for_UBA_2014</span><span class='op'>[[</span><span class='fl'>12</span><span class='op'>]</span><span class='op'>]</span><span class='op'>$</span><span class='va'>data</span>, <span class='va'>name</span> <span class='op'>==</span> <span class='st'>"parent"</span><span class='op'>)</span>
<span class='va'>sfo_fit</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='va'>test_data</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
<span class='va'>dfop_fit</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='st'>"DFOP"</span>, <span class='va'>test_data</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
<span class='fu'><a href='https://rdrr.io/pkg/lmtest/man/lrtest.html'>lrtest</a></span><span class='op'>(</span><span class='va'>dfop_fit</span>, <span class='va'>sfo_fit</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Likelihood ratio test
#&gt; 
#&gt; Model 1: DFOP with error model const
#&gt; Model 2: SFO with error model const
#&gt;   #Df  LogLik Df  Chisq Pr(&gt;Chisq)    
#&gt; 1   5 -42.453                         
#&gt; 2   3 -63.954 -2 43.002  4.594e-10 ***
#&gt; ---
#&gt; Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/lmtest/man/lrtest.html'>lrtest</a></span><span class='op'>(</span><span class='va'>sfo_fit</span>, <span class='va'>dfop_fit</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Likelihood ratio test
#&gt; 
#&gt; Model 1: DFOP with error model const
#&gt; Model 2: SFO with error model const
#&gt;   #Df  LogLik Df  Chisq Pr(&gt;Chisq)    
#&gt; 1   5 -42.453                         
#&gt; 2   3 -63.954 -2 43.002  4.594e-10 ***
#&gt; ---
#&gt; Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1</div><div class='input'>
<span class='co'># The following two examples are commented out as they fail during</span>
<span class='co'># generation of the static help pages by pkgdown</span>
<span class='co'>#lrtest(dfop_fit, error_model = "tc")</span>
<span class='co'>#lrtest(dfop_fit, fixed_parms = c(k2 = 0))</span>

<span class='co'># However, this equivalent syntax also works for static help pages</span>
<span class='fu'><a href='https://rdrr.io/pkg/lmtest/man/lrtest.html'>lrtest</a></span><span class='op'>(</span><span class='va'>dfop_fit</span>, <span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span><span class='op'>(</span><span class='va'>dfop_fit</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Likelihood ratio test
#&gt; 
#&gt; Model 1: DFOP with error model tc
#&gt; Model 2: DFOP with error model const
#&gt;   #Df  LogLik Df  Chisq Pr(&gt;Chisq)    
#&gt; 1   6 -34.587                         
#&gt; 2   5 -42.453 -1 15.731  7.302e-05 ***
#&gt; ---
#&gt; Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/lmtest/man/lrtest.html'>lrtest</a></span><span class='op'>(</span><span class='va'>dfop_fit</span>, <span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span><span class='op'>(</span><span class='va'>dfop_fit</span>, fixed_parms <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>k2 <span class='op'>=</span> <span class='fl'>0</span><span class='op'>)</span><span class='op'>)</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Likelihood ratio test
#&gt; 
#&gt; Model 1: DFOP with error model const
#&gt; Model 2: DFOP with error model const and fixed parameter(s) k2
#&gt;   #Df  LogLik Df  Chisq Pr(&gt;Chisq)    
#&gt; 1   5 -42.453                         
#&gt; 2   4 -57.340 -1 29.776  4.851e-08 ***
#&gt; ---
#&gt; Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1</div><div class='input'><span class='co'># }</span>
</div></pre>
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