title: Calibration (inverse prediction) from LOESS object in R
body: <p>I have fit a LOESS local regression to some data and I want to be able to find the X value associated with a given Y value.  </p>
  
  <pre><code>plot(cars, main = "Stopping Distance versus Speed")
  car_loess &lt;- loess(cars$dist~cars$speed,span=.5)
  lines(1:50, predict(car_loess,data.frame(speed=1:50)))
  </code></pre>
  
  <p>I was hoping that I could use teh inverse.predict function from the chemCal package, but that does not work for LOESS objects.</p>
  
  <p>Does anyone have any idea how I might be able to do this calibrationa in a better way than predicticting Y values from a long vector of X values and looking through the resulting fitted Y for the Y value of interest and taking its corresponding X value?  </p>
  
  <p>Practically speaking in the above example, let's say I wanted to find the speed at which the stopping distance is 15.</p>
  
  <p>Thanks!</p>