Include fixed parameters in model names in lrtest

3 files changed, 37 insertions, 18 deletions

diff --git a/docs/news/index.html b/docs/news/index.html
index baddfc96..5aef06f9 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -134,12 +134,13 @@
 <a href="#mkin-0-9-49-8-unreleased" class="anchor"></a>mkin 0.9.49.8 (unreleased)<small> Unreleased </small>
 </h1>
 <ul>
-<li>‘confint.mkinfit’: Make the quadratic approximation the default, as the likelihood profiling takes too much time for any with more than three parameters</li>
+<li><p>‘lrtest.mkinfit’: Improve naming of the compared fits in the case of fixed parameters</p></li>
+<li><p>‘confint.mkinfit’: Make the quadratic approximation the default, as the likelihood profiling takes a lot of time, especially if the fit has more than three parameters</p></li>
 </ul>
 </div>
     <div id="mkin-0-9-49-7-2019-11-01" class="section level1">
 <h1 class="page-header">
-<a href="#mkin-0-9-49-7-2019-11-01" class="anchor"></a>mkin 0.9.49.7 (2019-11-01)<small> Unreleased </small>
+<a href="#mkin-0-9-49-7-2019-11-01" class="anchor"></a>mkin 0.9.49.7 (2019-11-01)<small> 2019-11-02 </small>
 </h1>
 <ul>
 <li><p>Fix a bug introduced in 0.9.49.6 that occurred if the direct optimisation yielded a higher likelihood than the three-step optimisation in the d_3 algorithm, which caused the fitted parameters of the three-step optimisation to be returned instead of the parameters of the direct optimisation</p></li>
diff --git a/docs/reference/confint.mkinfit.html b/docs/reference/confint.mkinfit.html
index 13662adf..ea69c3bb 100644
--- a/docs/reference/confint.mkinfit.html
+++ b/docs/reference/confint.mkinfit.html
@@ -40,10 +40,10 @@
 the curvature of the likelihood function at the maximum likelihood parameter
 estimates.
 The alternative method 'profile' is based on the profile likelihood for each
-parameter. The method uses two nested optimisations and can take a very long
-time, even if parallelized by specifying 'cores' on unixoid platforms. The
-speed of the method could likely be improved by using the method of Venzon
-and Moolgavkar (1988)." />
+parameter. The 'profile' method uses two nested optimisations and can take a
+very long time, even if parallelized by specifying 'cores' on unixoid
+platforms. The speed of the method could likely be improved by using the
+method of Venzon and Moolgavkar (1988)." />
 <meta name="twitter:card" content="summary" />
 
 
@@ -144,10 +144,10 @@ and Moolgavkar (1988)." />
 the curvature of the likelihood function at the maximum likelihood parameter
 estimates.
 The alternative method 'profile' is based on the profile likelihood for each
-parameter. The method uses two nested optimisations and can take a very long
-time, even if parallelized by specifying 'cores' on unixoid platforms. The
-speed of the method could likely be improved by using the method of Venzon
-and Moolgavkar (1988).</p>
+parameter. The 'profile' method uses two nested optimisations and can take a
+very long time, even if parallelized by specifying 'cores' on unixoid
+platforms. The speed of the method could likely be improved by using the
+method of Venzon and Moolgavkar (1988).</p>
     </div>
 
     <pre class="usage"><span class='co'># S3 method for mkinfit</span>
@@ -254,13 +254,13 @@ On Windows machines, cores &gt; 1 is currently not supported.</p></td>
   <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"max"</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
 <span class='no'>f_d_1</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>SFO_SFO</span>, <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span>(<span class='no'>FOCUS_2006_D</span>, <span class='no'>value</span> <span class='kw'>!=</span> <span class='fl'>0</span>), <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
 <span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span>(<span class='no'>ci_profile</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span>(<span class='no'>f_d_1</span>, <span class='kw'>method</span> <span class='kw'>=</span> <span class='st'>"profile"</span>, <span class='kw'>cores</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>))</div><div class='output co'>#&gt;        User      System verstrichen 
-#&gt;      51.341       0.000      51.370 </div><div class='input'><span class='co'># Using more cores does not save much time here, as parent_0 takes up most of the time</span>
+#&gt;      51.058       0.000      51.088 </div><div class='input'><span class='co'># Using more cores does not save much time here, as parent_0 takes up most of the time</span>
 <span class='co'># If we additionally exclude parent_0 (the confidence of which is often of</span>
 <span class='co'># minor interest), we get a nice performance improvement from about 50</span>
 <span class='co'># seconds to about 12 seconds if we use at least four cores</span>
 <span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span>(<span class='no'>ci_profile_no_parent_0</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span>(<span class='no'>f_d_1</span>, <span class='kw'>method</span> <span class='kw'>=</span> <span class='st'>"profile"</span>,
   <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"k_parent_sink"</span>, <span class='st'>"k_parent_m1"</span>, <span class='st'>"k_m1_sink"</span>, <span class='st'>"sigma"</span>), <span class='kw'>cores</span> <span class='kw'>=</span> <span class='no'>n_cores</span>))</div><div class='output co'>#&gt; <span class='message'>Profiling the likelihood</span></div><div class='output co'>#&gt;        User      System verstrichen 
-#&gt;       0.001       0.007      11.432 </div><div class='input'><span class='no'>ci_profile</span></div><div class='output co'>#&gt;                       2.5%        97.5%
+#&gt;       0.005       0.004      11.349 </div><div class='input'><span class='no'>ci_profile</span></div><div class='output co'>#&gt;                       2.5%        97.5%
 #&gt; parent_0      96.456003650 1.027703e+02
 #&gt; k_parent_sink  0.040762501 5.549764e-02
 #&gt; k_parent_m1    0.046786482 5.500879e-02
diff --git a/docs/reference/lrtest.mkinfit.html b/docs/reference/lrtest.mkinfit.html
index fae471fc..1d82eb74 100644
--- a/docs/reference/lrtest.mkinfit.html
+++ b/docs/reference/lrtest.mkinfit.html
@@ -73,7 +73,7 @@ and can be expressed by fixing the parameters of the other." />
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">mkin</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.9.49.6</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.9.49.8</span>
       </span>
     </div>
 
@@ -196,11 +196,29 @@ lower number of fitted parameters (null hypothesis).</p>
 #&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'>
-# The following two examples are commented out as they fail during
-# generation of the static help pages by pkgdown
-# lrtest(dfop_fit, error_model = "tc")
-# lrtest(dfop_fit, fixed_parms = c(k2 = 0))
-# }
+<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 works for static help pages</span>
+<span class='fu'><a href='https://rdrr.io/pkg/lmtest/man/lrtest.html'>lrtest</a></span>(<span class='no'>dfop_fit</span>, <span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span>(<span class='no'>dfop_fit</span>, <span class='kw'>error_model</span> <span class='kw'>=</span> <span class='st'>"tc"</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='no'>dfop_fit</span>, <span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span>(<span class='no'>dfop_fit</span>, <span class='kw'>fixed_parms</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>k2</span> <span class='kw'>=</span> <span class='fl'>0</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'># }
 </div></pre>
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