title: The errors on lmfit parameters are not always shown
body: <p>I am trying to fit a curve to some data points using lmfit and I need the errors on the parameters. After I call: <code>out = model.fit(y, pars, x, weights = 1/error)</code> I do: <code>print(out.fit_report())</code>. Sometimes the output is like this (part of hit posted here):</p>
  
  <pre><code># fitting method   = leastsq
      # function evals   = 490
      # data points      = 380
      # variables        = 14
      chi-square         = 1035.65572
      reduced chi-square = 2.82966043
      Akaike info crit   = 408.995142
      Bayesian info crit = 464.157539
  [[Variables]]
      line1_c:        49.2699229 +/- 0.17590656 (0.36%) (init = 60.38407)
      sv1_skew:      -6.04992639 +/- 0.50325827 (8.32%) (init = 0)
      sv1_center:     13284.8621 +/- 0.01423913 (0.00%) (init = 13284)
      sv1_sigma:      1.32758560 +/- 0.02864233 (2.16%) (init = 1)
      sv1_amplitude:  240.685241 +/- 3.80236837 (1.58%) (init = 1)
      sv1_gamma:      1.32758560 +/- 0.02864233 (2.16%) == 'sv1_sigma'
  </code></pre>
  
  <p>which is what I need (i.e. the parameters have errors associated with them). However other times it is like this:</p>
  
  <pre><code>    # fitting method   = leastsq
      # function evals   = 9509
      # data points      = 64
      # variables        = 14
      chi-square         = 3023.19802
      reduced chi-square = 60.4639605
      Akaike info crit   = 274.731995
      Bayesian info crit = 304.956358
  ##  Warning: uncertainties could not be estimated:
      sv3_center:     at initial value
      sv4_amplitude:  at boundary
  [[Variables]]
      line1_c:        49.6633100 (init = 60.35763)
      sv1_skew:      -19.2947984 (init = 0)
      sv1_amplitude:  269.063100 (init = 1)
      sv1_center:     13285.0635 (init = 13284)
      sv1_sigma:      1.66532381 (init = 1)
      sv1_gamma:      1.66532381 == 'sv1_sigma'
  </code></pre>
  
  <p>Why can't the uncertainties be estimated in the second case. Also, for the exactly same fit and data, sometimes I get the errors on parameters, sometimes I don't i.e. I just run <code>python code.py</code> twice in a row, without any modification, and sometimes I get the estimates of the error sometimes I don't. However in both cases the fit looks really good by eye. Can someone help me understand what is going on? Thank you!</p>