Static documentation rebuilt by pkgdown

1 files changed, 30 insertions, 2 deletions

diff --git a/docs/reference/logLik.mkinfit.html b/docs/reference/logLik.mkinfit.html
index 250bc1d8..5fd6c6d7 100644
--- a/docs/reference/logLik.mkinfit.html
+++ b/docs/reference/logLik.mkinfit.html
@@ -33,7 +33,21 @@
 <meta property="og:title" content="Calculated the log-likelihood of a fitted mkinfit object — logLik.mkinfit" />
 
 <meta property="og:description" content="This function simply calculates the product of the likelihood densities
-  calc" />
+  calculated using dnorm, i.e. assuming normal distribution.
+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.
+For the case of unweighted least squares fitting, we calculate one
+  constant standard deviation from the residuals using sd
+  and add one to the number of fitted degradation model parameters.
+For the case of manual weighting, we use the weight given for each
+  observation as standard deviation in calculating its likelihood.
+In the case of iterative reweighting, the variances obtained by this
+  procedure are used in the likelihood calculations, and the number of
+  estimated parameters is obtained by the number of degradation model
+  parameters plus the number of variance model parameters, i.e. the number of
+  observed variables if the reweighting method is &quot;obs&quot;, and two if the
+  reweighting method is &quot;tc&quot;." />
 <meta name="twitter:card" content="summary" />
 
 
@@ -125,7 +139,21 @@
     <div class="ref-description">
     
     <p>This function simply calculates the product of the likelihood densities
-  calc</p>
+  calculated using <code>dnorm</code>, i.e. assuming normal distribution.</p>
+<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>
+<p>For the case of unweighted least squares fitting, we calculate one
+  constant standard deviation from the residuals using <code>sd</code>
+  and add one to the number of fitted degradation model parameters.</p>
+<p>For the case of manual weighting, we use the weight given for each
+  observation as standard deviation in calculating its likelihood.</p>
+<p>In the case of iterative reweighting, the variances obtained by this
+  procedure are used in the likelihood calculations, and the number of
+  estimated parameters is obtained by the number of degradation model
+  parameters plus the number of variance model parameters, i.e. the number of
+  observed variables if the reweighting method is "obs", and two if the
+  reweighting method is "tc".</p>
     
     </div>