title: Avoiding underflow for joint probabilities using NumPy
body: <p>I face a problem of estimating a joint probability for independent variables in a simple setup. Currently I have an array of 100 random variables and I would like to obtain their joint probability without failing into the underflow problem. Any ideas how to achieve this goal in numpy? If possible? </p>
  
  <p>If not could someone please explain me further the role of NumPy routine (logaddexp) as I thought it might be a help for me in such situation.</p>