title: Logistic Regression in R with the nlstools package or with a glm?
body: <p>I had a statistic class where a Logistic Regression was set up on some ecotoxicological data (dose-response curve) and the nlstools package was used for this purpose. So far when I came across the Logistic Regression I only used the glm and I am not sure what is the difference between these two approaches. When applying both approaches on the same data there was a clear difference between the fitted curves. </p>
  
  <p>I already tried to look for answers but what I've read so far is that the nlstools package is used for nonlinear Regressions. From what I've read the Logistic Regression is not really a nonlinear Regression but a gerneralized linear model. Why can you use the nlstools package then? And I am a little bit confused how I should classify the Logistic Regression. Thanks for your help! </p>