title: F-test with HAC estimate
body: <p>I am calculating a multi-variate OLS regression in R, and I know the residual are autocorrelated. I know I can use Newey-West correction when performing the t-test to check whether one of the coefficient is zero. I can do that using:</p>
  
  <pre><code>require(sandwich)
  model &lt;- lm(y ~ x1 + x2)
  coeftest(model, vcov=NeweyWest(model))
  </code></pre>
  
  <p>where y was the variable to regress and x1 and x2 the predictor. This seems a good approach since my sample size is large.
  But what if I want to run an F-test to test whether the coefficient of x1 is 1 and the coefficient of x2 is zero simultaneously? I cannot find a way to do that in R, if I want to account for the autocorrelation of the residuals. For instance, if I use the function <code>linearHypothesis</code> in R, it seems that Newey-West cannot be used as an argument of <code>vcov</code>. Any suggestion? An alternative would be to do bootstrapping to estimate a confidence ellipse for my point (1,0), but I was hoping to use an F-test if possible. Thank you!</p>