title: Fixing variance values in lme4
body: <p>I am using the <code>lme4</code> R package to create a linear mixed model using the <code>lmer()</code> function. In this model I have four random effects and one fixed effect (intercept). My question is about the estimated variances of the random effects. Is it possible to specify initial values for the covariance parameters in a similar way as it can be done in <code>SAS</code> with the <code>PARMS</code> argument.</p>
  
  <p>In the following example, the estimated variances are:</p>
  
  <pre><code>c(0.00000, 0.03716, 0.00000, 0.02306)
  </code></pre>
  
  <p>I would like to <em>fix</em> these to (for example) </p>
  
  <pre><code>c(0.09902947, 0.02460464, 0.05848691, 0.06093686)
  </code></pre>
  
  <p>so there are not estimated.</p>
  
  <pre><code>    &gt; summary(mod1)
      Linear mixed model fit by maximum likelihood  ['lmerMod']
      Formula: log_cumcover_mod ~ (1 | kildestationsnavn) + (1 | year) + (1 |  
          kildestationsnavn:year) + (1 | proevetager)
         Data: res
  
           AIC      BIC   logLik deviance df.resid 
         109.9    122.9    -48.9     97.9       59 
  
      Scaled residuals: 
          Min      1Q  Median      3Q     Max 
      -2.1056 -0.6831  0.2094  0.8204  1.7574 
  
      Random effects:
       Groups                 Name        Variance Std.Dev.
       kildestationsnavn:year (Intercept) 0.00000  0.0000  
       kildestationsnavn      (Intercept) 0.03716  0.1928  
       proevetager            (Intercept) 0.00000  0.0000  
       year                   (Intercept) 0.02306  0.1518  
       Residual                           0.23975  0.4896  
      Number of obs: 65, groups:  
      kildestationsnavn:year, 6; kildestationsnavn, 3; proevetager, 2; year, 2
  
      Fixed effects:
                  Estimate Std. Error t value
      (Intercept)   4.9379     0.1672   29.54
  </code></pre>