title: Fitting non-linear Langmuir Isotherm in R
body: <p>I want to fit Isotherm models for the following data in R. The simplest isotherm model is Langmuir model given  here <a href="http://www.alfisol.com/IFS/IFS-003/LMMpro-Langmuir.php" rel="nofollow noreferrer">model is given in the bottom of the page</a>. My MWE is given below which throw the error. I wonder if there is any R package for Isotherm models.</p>
  
  <pre><code>X &lt;- c(10, 30, 50, 70, 100, 125)
  Y &lt;- c(155, 250, 270, 330, 320, 323)
  Data &lt;- data.frame(X, Y)
  LangIMfm2 &lt;- nls(formula = Y ~ Q*b*X/(1+b*X),  data = Data, start = list(Q = 1, b = 0.5), algorith = "port")
  
  Error in nls(formula = Y ~ Q * b * X/(1 + b * X), data = Data, start = list(Q = 1,  : 
    Convergence failure: singular convergence (7)
  </code></pre>
  
  <p><strong>Edited</strong></p>
  
  <p>Some nonlinear models can be transform to linear models. My understanding is that there might be one-to-one relationship between the estimates of nonlinear model and its linear model form but their corresponding standard errors are not related to each other. Is this assertion true? Are there any pitfalls in fitting Nonlinear Models by transforming to linearity?</p>