title: Extrapolation in R
body: <p>I have a reference data set, <code>p</code>, </p>
  
  <pre><code>p=structure(list(v = 0:26, t = c(Inf, 1.016, 0.568, 0.418666666666667, 
  0.344, 0.2992, 0.269333333333333, 0.248, 0.232, 0.219555555555556, 
  0.2096, 0.201454545454545, 0.194666666666667, 0.188923076923077, 
  0.184, 0.179733333333333, 0.176, 0.172705882352941, 0.169777777777778, 
  0.167157894736842, 0.1648, 0.162666666666667, 0.160727272727273, 
  0.15895652173913, 0.157333333333333, 0.15584, 0.154461538461538
  )), .Names = c("v", "t"), row.names = c(NA, -27L), class = "data.frame")
  </code></pre>
  
  <p>Which <code>p$v</code> and <code>p$t</code> have the following relation :</p>
  
  <pre><code>t=(0.16*(0.75*v + 5.6))/v
  </code></pre>
  
  <p>my second data set is measured data ,<code>w</code>, contains the same variable like :</p>
  
  <pre><code>w=structure(list(v = c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 
  13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26), t = c(0.235291176470588, 
  0.354020375722543, 0.310974343434343, 0.25272725498699, 0.20351968240702, 
  0.163155804025208, 0.132330740162655, 0.108593108108108, 0.0859813015873016, 
  0.0655131899302683, 0.0492580103144236, 0.0368029846567365, 0.030538003253355, 
  0.0300744415648525, 0.0347586421891237, 0.0451097744360902, NA, 
  NA, NA, NA, NA, NA, NA, NA, NA, NA, NA)), .Names = c("v", "t"
  ), row.names = c(NA, -27L), class = "data.frame")
  </code></pre>
  
  <p>My reference data <code>p</code>, follows a power law, I would like to do a prediction based on power law fit on the data to replace the <code>NA</code> on my measured data.  How could I do this in R ?</p>