title: "non-finite value supplied by optim" error when using betareg
body: <p>I'm working with <a href="/questions/tagged/betareg" class="post-tag" title="show questions tagged &#39;betareg&#39;" rel="tag">betareg</a> package for beta regression but receive the below error:</p>
  
  <blockquote>
    <p>Error in optim(par = start, fn = loglikfun, gr = gradfun, method = method,  : 
    non-finite value supplied by optim</p>
  </blockquote>
  
  <p>I can trace this error to creating the initial values for <code>optim</code>. Specifically, these lines of <a href="https://github.com/rforge/betareg/blob/master/pkg/R/betareg.R#L288-L290" rel="nofollow noreferrer"><code>betareg.fit</code></a>, which uses <code>lm.wfit</code> to generate starting values. </p>
  
  <p>It turns out that one of the starting values is returned as <code>NA</code> for my dataset. I'm unsure why this is the case, since there are no missing values in the data / input to <code>lm.wfit</code>.</p>
  
  <h3>Reproducible example to see NA</h3>
  
  <pre><code>## data -- a sample of 100 obs from my actual data
  nobs &lt;- 100L
  w &lt;- rep(1, nobs)
  offset &lt;- rep(0, nobs)
  y &lt;- stats::rbeta(nobs, 0.75, 1.658)
  x &lt;- structure(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
  1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
  1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
  1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
  1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.0165928242550604, 
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  0.0722387772757858, 0.0272373540856031, 0.0538907902524382, 0.0295235311312482, 
  0.0318257956448911, 0.231788079470199, 0.0674772036474164, 0.14846108458939, 
  0.0969908238068386, 0.0441553321506012, 0.154121863799283, 0, 
  0.110460389247421, 0.0292207792207792, 0.0522853185595568, 0.205288796102992, 
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  0.0751429349305745, 0.217853751187085, 0.0510314875135722, 0.108407709439207, 
  0.04, 0.0638009815535624, 0.128329297820823, 0.0398115958281933, 
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  0.0158054711246201, 0.152565574210159, 0.123442866663249, 0.0672186083185492, 
  0.129032258064516, 0, 0.104565780781544, 0.0551948051948052, 
  0.03601108033241, 0.160055671537926, 0.02201309207499, 0.0668891510112489, 
  0.0421455938697318, 0.0632911392405063, 0.234027661399237, 0.0206896551724138, 
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  0.088748974363268, 0.0422641509433962, 0.0467084108986292, 0.0920096852300242, 
  0.0401480318492767, 0.05103760198652, 0.0208333333333333, 0.0470016207455429, 
  0.0887666928515318, 0.075451647183847, 0.0310601719197708, 0.0928685551212356, 
  0.148991255923013, 0.0204541959296663, 0.0689569784090949, 0.0356901206750445, 
  0.0680173661360347, 0.0508956145768993, 0.0320699343321964, 0.0293185419968304, 
  0.0659340659340659, 0.00284090909090909, 0.0402373780415312, 
  0, 0.0230103440996411, 0.0629090909090909, 0.0229802513464991, 
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  0.0443828016643551, 0.0975012248897599, 0.00964630225080386, 
  0, 0, 0.0678391959798995, 0.05, 0.167973405256225, 0.0427812745869394, 
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  0.235552733134678, 0.0947352232531912, 0.154476512637182, 0.137157008940595, 
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  0.10678391959799, 0.0583333333333333, 0.233080348742395, 0.127753737214791, 
  0.233930088412044, 0.13375941339675, 0.13934317947634, 0.338085539714868, 
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  0.227009113504557, 0.254081770341384, 0.155103348822304, 0.161162856336438, 
  0.124957303134607, 0.155363748458693, 0.214043708410037, 0.111702127659574, 
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  0.352371916508539, 0.384971413013885, 0.245204178537512, 0.314060803474484, 
  0.177397478189521, 0.128301886792453, 0.418175664240988, 0.0532687651331719, 
  0.263429404508243, 0.351343561546648, 0.520833333333333, 0.160453808752026, 
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  0.302720922280299, 0.464089813912954, 0.325967367919772, 0.509502256498519, 
  0.357452966714906, 0.387770228536133, 0.389464763566684, 0.401743264659271, 
  0.450549450549451, 0.0741477272727273, 0.371069078965643, 0.0344827586206897, 
  0.351488283723876, 0.394836363636364, 0.10394973070018, 0.0164705882352941, 
  0.0661846496106785, 0.247721658259119, 0.271552795031056, 0.375866851595007, 
  0.326800587947085, 0.090032154340836, 0.302631578947368, 0, 0.293969849246231, 
  0.0916666666666667, 0.262623094775136, 0.37765538945712, 0.437246326652613, 
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  0.306166509243017, 0.536532606954014, 0.426756985605419, 0.214233164297538, 
  0.515413070283601, 0.401348069939186, 0.23936170212766, 0.406859205776173, 
  0.301968017675986, 0.46031385697156, 0.417500510516643, 0.280645161290323, 
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  1, 1, 0), .Dim = c(100L, 35L), .Dimnames = list(c("2801", "2316", 
  "382", "8062", "2687", "2731", "8019", "5652", "8429", "3479", 
  "7753", "9001", "2188", "8121", "8478", "5817", "1528", "2460", 
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  "341", "228", "1543", "553", "9709", "9493", "881", "7647", "6039", 
  "2925"), c("(Intercept)", "x 1", "x 2", "x 3", "x 4", "x 5", 
  "x 6", "x 7", "x 8", "x 9", "x 10", "x 11", "x 12", "x 13", "x 14", 
  "x 15", "x 16", "x 17", "x 18", "x 19", "x 20", "x 21", "x 22", 
  "x 23", "x 24", "x 25", "x 26", "x 27", "x 28", "x 29", "x 30", 
  "x 31", "x 32", "x 33", "x 34")))
  </code></pre>
  
  <h2>Inside <code>betareg</code>: the NA that causes the problem</h2>
  
  <pre><code>linkfun &lt;- function(mu) {.Call(stats:::C_logit_link, mu)}
  auxreg_test &lt;- lm.wfit(x, linkfun(y), w, offset)
  # problem:
  (beta &lt;- auxreg_test$coefficients)
  is.na(beta['x 8'])
  
  &gt; beta['x 8']
  x 8 
   NA 
  </code></pre>
  
  <p>I originally thought this might be related to using the CRAN version of <code>betareg</code> (3.1-0). But I updated to the <code>rforge</code> version (3.2-0) via <code>devtools::install_github("rforge/betareg/pkg")</code> and still have the same problem.</p>
  
  <p>If I remove the offending predictor from my formula, <code>betareg</code> runs fine; however, the predictor is a necessary one.</p>