title: Regression with Heteroskedasticity Corrected Standard Errors
body: <p>I would like to find the R implementation that most closely resembles Stata output for fitting a Least Squares Regression function with Heteroskedastic Corrected Standard Errors.  Specifically I would like the corrected standard errors to be in the "summary" and not have to do additional calculations for my initial round of hypothesis testing.  I am looking for a solution that is as "clean" as what Eviews and Stata provide.</p>
  
  <p>So far, using the "lmtest" package the best I can come up with is:</p>
  
  <pre><code>model &lt;- lm(...)
  coeftest(model, vcov = hccm) 
  </code></pre>
  
  <p>This gives me the output that I want, but it does not seem to be using  "coeftest" for its stated purpose. I would also have to use the summary with the incorrect standard errors to read off the R^2 and F stat, etc.  I feel that there should exist a "one line" solution to this problem given how dynamic R is. </p>
  
  <p>Thanks</p>