title: Is there an R function to find P-values and standard deviation for finite mixture modeling
body: <p>I have a question about finding P-values and standard deviations in R for finite mixture modeling. I have used the mixtools package (logisregmixEM) for a research. From there I got corresponding components with their coefficients, shown below:</p>
  
  <pre><code>dput(head(out.3.1$beta))
  </code></pre>
  
  <pre><code>-113.554228089564, 85.8568239333594, 69.529811815757, 2.04122936030937, 
  -0.224133734059534, 0.187941094390128, 0.341071906324811, -0.3432506594164, 
  -0.00731884252474948, 0.878493908098931, 0.0337483330433497, 
  0.423255572216283, -0.022725911109589, -0.169046203073331, -0.00796170326778525
  ), .Dim = c(6L, 3L), .Dimnames = list(c("beta.0", "beta.1", "beta.2", 
  "beta.3", "beta.4", "beta.5"), c("comp.1", "comp.2", "comp.3"
  )))
  </code></pre>
  
  <p>Is there any way to find out if the beta's I got are significant, and is there a way to find out the standard deviations, both for each component. In the mixtools package, they don't speak about any standard deviation or significance/p-values. Hope you can help me out!</p>