title: How can I output the estimated values of the model coefficients?
body: <p>Sorry if this is a novice question, but I don't understand it. I am fitting a sigmoid curve to my data with <code>glm()</code>. This works, I can plot the output and I see a nice sigmoid curve. </p>
  
  <p>However, how do I get R to return the final values it has fit? As I understand it, R fits the data to <code>logit(y) = b0 + b1x</code>, but when I do <code>&gt; summary(glm.out)</code> I only get</p>
  
  <pre><code>Call:
  glm(formula = e$V2 ~ e$V1, family = binomial(logit), data = e)
  
  Deviance Residuals: 
         1         2         3         4         5         6         7  
  -0.00001  -0.06612  -0.15118  -0.34237   0.20874   0.08724  -0.19557  
  
  Coefficients:
              Estimate Std. Error z value Pr(&gt;|z|)
  (Intercept)  -24.784     20.509  -1.208    0.227
  e$V1           2.073      1.725   1.202    0.229
  
  (Dispersion parameter for binomial family taken to be 1)
  
      Null deviance: 4.60338  on 6  degrees of freedom
  Residual deviance: 0.23388  on 5  degrees of freedom
  AIC: 5.8525
  
  Number of Fisher Scoring iterations: 8
  </code></pre>
  
  <p>How do I get b0 and b1?</p>
  
  <p>A sample dataset:</p>
  
  <p>The Z column can be ignored.</p>
  
  <pre><code>X   Y   Z
  0.0 0.0 6
  6.5 0.0 3
  8.8 0.333333333333  3
  10.5    0.2 10
  11.1    0.0 3
  11.25   0.166666666667  6
  12.0    0.2 5
  12.75   0.5 6
  13.4    0.333333333333  3
  13.5    0.2 5
  14.25   0.5 6
  15.0    0.333333333333  6
  15.7    0.666666666667  3
  15.75   0.666666666667  6
  16.5    0.833333333333  6
  17.25   0.555555555556  9
  18.0    1.0 3
  </code></pre>